Posted on June 27, 2023

In today’s connected world, eCommerce has become an inevitable part of life, transforming the way we shop and interact with brands. With 2.64 billion global digital buyers in 2023, the incredible growth potential of the eCommerce landscape cannot be denied.

In such a competitive landscape, the key to success lies in differentiating your business from the multitude of others vying for ever-diminishing consumer attention.

The single most impactful differentiator? Exceptional customer service and support.

As the online marketplace grows, the demand for prompt and personalized customer service is intensifying. Traditional models of customer service are often unable to meet these demands due to their reactive nature. Enter machine learning (ML), a subfield of artificial intelligence that’s rapidly changing the customer service landscape by offering proactive, personalized, and predictive support.

But how exactly does this all work in the eCommerce industry? What are the key advantages of implementing eCommerce machine learning in your customer service and support systems, and how are these benefits seen in real-life applications? Read along to find answers to these questions.

The Role of Machine Learning in eCommerce Customer Service

In an increasingly digital world, the eCommerce landscape is constantly evolving, and with it, customer expectations. Consumers demand a seamless, personalized, and efficient online shopping experience, which can only be delivered with the help of advanced technologies such as machine learning and deep learning. This paradigm shift has brought machine learning to the forefront of the eCommerce industry, primarily focusing on customer service and support.

Machine learning, an innovative subfield of artificial intelligence, involves the development of complex algorithms that allow computers to learn from and make decisions or predictions based on data. Unlike traditional computer programs, these algorithms don’t need to be explicitly programmed. Instead, they evolve and adapt based on the information they process, which means they become more accurate and efficient over time.

In the context of eCommerce, machine learning can be a genuine game-changer. With the ability to process and analyze vast amounts of data, these algorithms can unearth profound insights that would otherwise remain hidden.

They can:

Track customer behavior
Understand preferences
Predict future actions
Detect and resolve eCommerce errors

The more data these algorithms process, the more accurately they can anticipate and respond to the needs of your existing and potential customers.

Benefits of Machine Learning in eCommerce Customer Service

Embracing machine learning in customer service is not just a trend; it’s a strategic move that offers significant benefits and provides a distinct competitive advantage for eCommerce companies.

Personalization and customer segmentation

By analyzing various data points such as browsing patterns, purchase history, and customer preferences, ML classification algorithms can create detailed customer profiles. These profiles enable online retailers to build personalized recommendation engines, tailor promotional messages, and even predict future purchase behavior.

Moreover, machine learning enables customer segmentation on a granular level. Instead of simply segmenting customers based on broad categories like age or geographical location, ML algorithms can segment customers based on previous customer behaviors and preferences, creating highly-targeted marketing campaigns.

Such precise personalization and customer segmentation can lead to increased customer engagement and higher conversion rates. Ultimately, data is the number one factor to consider if your goal is increased eCommerce sales and business revenue.

Stitch Fix, an online personal styling service, utilizes machine learning algorithms to analyze customer data and preferences, which are then used to provide personalized fashion recommendations. Their algorithms take numerous factors into account, like customer feedback, purchasing history, and current fashion trends, to create recommendation algorithms and deliver a highly tailored service that resonates with their clientele.

Predictive analytics for proactive support

The power of eCommerce machine learning also extends to predictive analytics, which can be a game-changer for customer support. Predictive analytics use machine learning algorithms to identify patterns and trends in user behavior and predict future outcomes.

For instance, if a customer often faces issues while checking out, predictive analytics can proactively identify this and prompt customer service to reach out and assist the customer. This proactive approach not only resolves issues before they escalate but also makes the customer feel valued and taken care of, improving both user experience and customer loyalty.

Harnessing the power of predictive analytics, Delta Air Lines efficiently forecasts customer service needs, considering variables such as flight timetables, historical trends, and exceptional occurrences.

The derived insights enable them to predict the requirement for customer support personnel at any given time. By doing so, Delta ensures optimal staffing, preventing unnecessary manpower during slack periods and guaranteeing adequate customer service representatives during peak times.

Automating routine tasks for improved efficiency

Customer service agents often spend a significant amount of their time handling routine tasks such as answering frequently asked customer questions, updating order statuses, and managing returns. By automating these routine tasks with machine learning for eCommerce, retail businesses can free up their customer service agents to focus on more complex customer inquiries that require human intervention.

Machine learning can automate these tasks around the clock, providing instant support to customers irrespective of time zones or holidays. This constant availability drastically improves the efficiency of customer support and ensures that customers always have access to timely assistance.

Real-time data analysis for quick decision-making

In today’s fast-paced eCommerce environment, being able to make quick decisions based on real-time data is crucial. Machine learning excels at processing vast amounts of data in real-time, providing eCommerce companies with valuable insights that can drive immediate decision-making.

For instance, if an error is detected in the eCommerce platform, machine learning algorithms can identify it quickly, allowing brands to resolve the issue before it impacts a significant number of customers.

Similarly, real-time analysis can reveal sudden changes in customer behavior or market trends, enabling businesses to adapt their strategies swiftly, which can lead to an improved customer experience and give businesses a competitive edge.

Glossier, a direct-to-consumer beauty brand, uses machine learning to monitor and analyze real-time data from various sources, including website traffic, social media interactions, customer feedback, and sales figures.

This real-time data analysis allows Glossier to quickly identify trending products, sudden shifts in consumer preferences, or any spikes in customer complaints about a particular product. These insights enable Glossier to make quick, data-driven decisions such as adjusting their inventory based on trending products, addressing issues with a specific product, or tailoring their marketing campaigns based on the latest consumer trends.

Leveraging Machine Learning for Customer Interactions

The modern consumer expects businesses to be available round-the-clock, offer immediate responses, and understand their unique needs and preferences. Achieving this level of customer interaction might seem challenging, but it becomes significantly more manageable with the application of machine learning.

Chatbots and virtual assistants

A prominent application of eCommerce machine learning in enhancing customer interactions is the development and implementation of chatbots and virtual assistants. These tools have transformed the way businesses communicate with their customers, enabling 24/7 support, immediate responses, and increasingly personalized service.

Chatbots and virtual assistants, powered by machine learning, can interact with customers in a surprisingly human-like manner, answering queries, providing instant replies, relevant product recommendations, virtual customer assistance, and even facilitating transaction processes and business workflows. What sets them apart is their ability to learn from every interaction, constantly improving their communication skills and understanding of customer needs.

Babylon Health’s symptom checker stands as a stellar example of how AI chatbots can revolutionize healthcare. This innovative tool is the brainchild of a collaborative effort between doctors, engineers, and scientists who harnessed the power of machine learning and natural language processing to facilitate organic conversations.

As users input their symptoms, the chatbot intelligently interprets the information provided, identifies potential risk factors and causes, and suggests potential courses of action.

Enhancing Customer Support with Machine Learning

While customer interactions form a key part of eCommerce customer service, the foundation of a robust support system is its ability to handle issues and resolve customer queries effectively and efficiently. Here’s where machine learning comes into play, elevating the support experience by offering predictive and personalized solutions, reducing resolution time, and automating repetitive manual tasks.

An important aspect of customer support is issue detection and resolution. In traditional customer service models, businesses only address issues when customers report them. With machine learning, however, businesses can take a proactive approach.

eCommerce machine learning algorithms can monitor and track eCommerce data to detect anomalies and system errors, or even for the purpose of eCommerce fraud detection. This allows online stores to identify and resolve issues and fraudulent activities before they significantly impact the experience for customers.

Another crucial area where machine learning can enhance customer support is by speeding up response and resolution times. ML algorithms can automatically categorize incoming customer queries based on their urgency and complexity, ensuring that critical issues are prioritized. They can also suggest solutions based on similar past queries, enabling customer support agents to resolve issues faster.

Dealing with a significant volume of customer inquiries daily, software company Freshworks leverages machine learning to analyze and categorize each incoming ticket based on factors like the nature of the issue, the urgency, and the technical skills required to handle it. Once classified, the tickets are automatically routed to the appropriate support agent or team that is best equipped to resolve the issue.

Lastly, machine learning for eCommerce can also aid in providing personalized customer support. By analyzing past interactions and purchase histories, ML algorithms can understand each customer’s unique needs and preferences. This allows customer support agents to provide personalized solutions, enhancing the customer’s experience with the brand.

Use Machine Learning for eCommerce as Your Superpower

As we’ve explored, machine learning and deep learning are powerful allies for eCommerce platforms, enabling them to provide stellar support and service for customers. Through its capabilities of personalization, predictive analytics, automation, and real-time data analysis, ML is setting the stage for a new era of customer service.

Moreover, by monitoring and tracking eCommerce data, machine learning algorithms can identify issues in real-time, allowing swift intervention. This proactive approach minimizes customer churn and frustrations, enhances overall customer satisfaction, and helps eCommerce businesses retain their valuable customer base.

But as we continue to innovate in this field and uncover new ways of harnessing the power of ML, the incorporation of eCommerce machine learning is set to rise exponentially. The eCommerce of the future isn’t just online, it’s intelligent, intuitive, and customer-centric.

As businesses in the eCommerce industry adapt to this new reality, the question isn’t if they should use ML-based solutions, but how well they can implement them to create a superior and personalized shopping experience.

Posted on June 23, 2023

As an eCommerce developer, you may encounter the “The Object Does Not Support the Operation or Argument” JavaScript error while developing web applications. This error means that an object in your code does not support the operation or argument you are trying to perform, resulting in an error message. This guide explains the underlying causes behind this error and provides step-by-step troubleshooting and resolution steps.

Investing the Code for the JavaScript Error

When faced with this error, the first step is to investigate where in your code the error is occurring. To do this, open up your browser’s developer console and look for the error message along with the line number where it occurred. This will give you a starting point for troubleshooting.

Potential Underlying Reasons for this JavaScript Error

There are several underlying reasons behind “The Object Does Not Support the Operation or Argument” JavaScript error. Some of the most common causes are:

Using methods that are not supported on certain objects or elements
Using incompatible data types in your code
Syntax errors in your code
JavaScript library conflicts

How Does this JavaScript Error Occur?

This error can occur while working on any eCommerce project that uses JavaScript. Common scenarios that can lead to this error include:

Attempting to manipulate the DOM with incorrect or unsupported methods
Working with older versions of JavaScript, or using libraries that are incompatible with your code
Using incompatible data types, such as strings instead of integers, in your code

Troubleshooting and Resolving Steps

Now that we understand the possible causes of this error, let’s go through the troubleshooting and resolution steps to fix it.

Step 1: Check the method compatibility

First, check that the method you are using is compatible with the object or element you are trying to manipulate. This error can occur if you try to call an unsupported method on an object. Refer to the browser’s documentation to see what methods are supported.

Code example:

    
      document.getElementById("example").style.visibilty = "hidden";

In the code example above, the “visibility” property is spelled incorrectly. This will throw the error since the method is unsupported.

Step 2: Double-check data types

Make sure you are using the correct data types in your code. Using incompatible data types can cause this error as well. To avoid this, make sure you are using the appropriate data type for each variable and input.

Code example:

    
      let sum = 2 + '2';

This code example concatenates the number 2 and the string “2”. This will result in the error since they are different data types.

Step 3: Look for syntax errors

Syntax errors can also cause this JavaScript error. To ensure that your code is correct, double-check your syntax for any errors.

Code example:

    
      function displayAlert() {
      alert("Hello World!");
      }

This code example is missing parenthesis after the function name. This will cause the error since the syntax is incorrect.

Step 4: Check for library conflicts

If none of the above steps work, it’s time to check for JavaScript library conflicts. Library conflicts occur when two different libraries are used to implement a function or method, causing errors.

Code example:

    
      <script src="jquery.min.js"></script>
      <script src="prototype.min.js"></script>

The above code includes two different JavaScript libraries (jQuery and Prototype) that could conflict with one another.

Best Practices to Avoid this Error

To avoid encountering this error in the future, follow these best practices:

Check documentation and compatibility before using new libraries or frameworks
Regularly review your code for syntax errors
Use data types consistently and correctly throughout your code
Refactor your code periodically to avoid any conflicts

Conclusion

The “The Object Does Not Support the Operation or Argument” JavaScript error can occur during eCommerce development for a variety of reasons. However, by following the troubleshooting and resolution steps outlined in this guide, you can successfully identify and resolve the error. By incorporating the best practices to avoid this error, you can ensure robust and error-free eCommerce web applications.

Posted on June 19, 2023

In the age of the digital revolution, artificial intelligence (AI) stands as one of the most transformative technologies, influencing a myriad of industries in unprecedented ways. From healthcare to transportation, finance to retail, AI is steering a significant shift in how businesses operate.

The eCommerce industry, in particular, is witnessing seismic change thanks to the integration of AI technologies. Analysts predict that by 2030, AI-powered eCommerce solutions will be worth no less than $16.8 billion.

The burgeoning integration of AI within the eCommerce sector can be ascribed to its potential in transforming customer experiences and business operations. By providing personalized shopping experiences, enhancing customer service, streamlining operations, and bolstering sales, AI is evolving the conventional norms of eCommerce.

Yet, this is just the tip of the iceberg. The breadth and depth of AI eCommerce capabilities are far-reaching and profound, and they are explored in this comprehensive guide.

How AI Is Changing the Online Shopping Experience: From Humble Beginnings to Transformative Applications

The journey of AI for eCommerce has been fascinating. From the early adoption in the form of simple recommendation engines to the more sophisticated implementations seen today, AI has consistently pushed the boundaries of what’s possible in online shopping.

The inception of AI eCommerce can be traced back to Amazon’s introduction of product recommendation algorithms, a simple yet effective AI-based system that suggested products based on a user’s browsing and purchasing history. Amazon’s AI venture turned out to be a game-changer, and the approach has since been adopted by virtually every other eCommerce platform.

Fast forward to the early 2000s, with advancements in AI and Machine Learning (ML), businesses started leveraging more advanced and diverse applications of AI. For instance, eBay introduced its AI-powered ShopBot in 2016. ShopBot was a virtual shopping assistant, using natural language processing (NLP) and machine learning to help both existing and potential customers find the items they were looking for.

Another notable example is the launch of Amazon’s virtual assistant, Alexa, which uses AI to interact with users, place orders, track shipments, and provide personalized product recommendations, among other tasks. The integration of voice-assisted shopping marked a significant milestone in the evolution of AI in eCommerce.

In recent years, the use of eCommerce AI has reached new heights:

AI-powered visual search, a feature championed by companies like Pinterest and Google, enables customers to search for products by uploading images. The visual search technology analyzes the image and returns results of identical or similar products.
Another remarkable development is the emergence of AI-powered chatbots, capable of delivering a level of customer service previously achievable only through human agents. Brands like H&M and Sephora use chatbots to provide personalized fashion advice, product recommendations, and instant customer support.
Lastly, the rise of AI in analyzing customer sentiment cannot be understated. Tools that can analyze customer reviews, comments on social media platforms, and other feedback are being used to gain valuable insights into customer behavior and sentiment, allowing online retail businesses to optimize their products and services accordingly.

AI in eCommerce: Diverse Applications Delivering Transformative Results

Artificial intelligence is not just changing the way eCommerce businesses operate but also transforming the very dynamics of online shopping. Let’s delve deeper into how AI is revolutionizing key areas of the online retail industry.

Product recommendations

As we have already mentioned, one of the earliest applications of AI eCommerce is in the form of product recommendation systems. These AI-powered algorithms analyze a user’s past behavior, browsing patterns, and purchase history to suggest products that align with their preferences.

According to a study conducted by McKinsey, 35% of Amazon’s revenue can be attributed to its recommendation engine, underscoring the enormous potential of AI in driving sales. Other eCommerce giants like Alibaba and eBay have also embraced AI-powered recommendation systems to guide users toward product descriptions they may find interesting.

Virtual assistants

AI eCommerce extends beyond screens and pages into our homes and daily lives in the form of virtual assistants. From Amazon’s Alexa to Google’s Assistant and Apple’s Siri, AI has made shopping an effortless task.

Users can now ask their virtual assistants to place orders, track shipments, and even suggest gift ideas. By 2025, it’s estimated that 75% of U.S. households will own a smart speaker, indicating the growing influence of AI-driven virtual assistants in eCommerce.

Customer feedback analysis

The power of AI in deciphering customer sentiment is proving to be a game-changer for online retailers. AI tools can swiftly analyze thousands of customer reviews and feedback across multiple platforms, identifying patterns and trends that might otherwise go unnoticed.

This comprehensive analysis can provide valuable insights into product performance, customer satisfaction, and areas of improvement. For example, sentiment analysis tools powered by AI can monitor and interpret social media mentions and comments to gauge public sentiment about a brand or product, providing real-time feedback to businesses.

Coca-Cola has been at the forefront of leveraging AI for sentiment analysis. The company uses AI to analyze social media comments and feedback to understand customer sentiment about their products. They also use AI to gain insights about their marketing campaigns and use that information to strategize their future marketing efforts.

Personalization

The era of one-size-fits-all marketing is on the wane. In its place, personalization driven by AI is shaping the future of eCommerce. Tailored product recommendations, personalized emails, targeted ads, and customized content based on a user’s behavior, preferences, and previous purchases are redefining the customer journey and experience.

A study shows that a staggering 44% of consumers are likely to become repeat buyers after a personalized experience, emphasizing the potential of AI-driven personalization in boosting customer retention and loyalty.

Fraud detection and prevention

With the exponential increase in online transactions, eCommerce websites are becoming increasingly vulnerable to fraud. Fortunately, AI is stepping in as a robust solution to tackle this growing challenge.

AI systems can analyze thousands of transactions in real time, spotting unusual behavior, identifying suspicious patterns, and flagging potential fraudulent activities. These systems use machine learning algorithms to learn from each transaction, constantly updating their understanding of what constitutes normal behavior and what might be a potential threat.

AI’s role in fraud detection and prevention showcases how the advanced technology is not just enhancing the user experience and optimizing business operations, but also playing a crucial part in securing the eCommerce landscape. As the sophistication of online fraud continues to grow, AI’s role in combating it will become increasingly critical.

Challenges of AI in eCommerce: Navigating the Roadblocks

While AI presents vast opportunities for the eCommerce sector, the path to full-fledged integration is not devoid of challenges. Understanding these potential roadblocks is crucial for businesses aiming to effectively leverage AI in their operations.

Data privacy

One of the most significant concerns with AI eCommerce is ensuring data privacy. As businesses collect and analyze vast amounts of data for AI systems, they must also ensure that this data is securely stored and used.

Breaches can have severe consequences, including hefty fines and a loss of customer trust. With regulations like the General Data Protection Regulation (GDPR) in the EU and the California Consumer Privacy Act (CCPA) in the U.S., businesses must ensure their AI systems comply with these stringent laws.

To tackle this challenge:

Utilize advanced encryption methods, secure access controls, and regular security audits to safeguard customer data and prevent security threats.
Clearly communicate to online customers how their data is being used and stored. This transparency can build trust and ensure compliance with privacy regulations.

Accuracy of AI systems

AI systems are as good as the data they’re trained on. However, even with high-quality data, AI systems aren’t infallible. They can make errors in predictions, provide incorrect recommendations, and may not always interpret customer behavior accurately.

These inaccuracies can lead to customer dissatisfaction and potential loss of business. Continuous refinement and optimization of AI systems, incorporating feedback loops, and rigorous testing are essential to minimize errors.

To tackle this challenge:

Make sure to gather high-quality, diverse, and relevant data. The quality of your input data directly influences the accuracy of AI predictions.
Regularly monitor and adjust AI algorithms to reduce errors and improve accuracy. Regular feedback loops can help identify and rectify inaccuracies quickly.

Complex integration

Integration of AI systems into existing operations can be complex and time-consuming. Businesses need the right infrastructure, skilled personnel, and a clear roadmap for implementation.

It can also be a costly affair, requiring substantial investments in technology and talent. This can be particularly challenging for small and medium-sized enterprises (SMEs) that may not have the necessary resources.

To tackle this challenge:

Instead of implementing AI across all operations at once, consider a phased approach. Begin with one aspect of your business, learn from the implementation, and then expand to other areas.
Consider hiring or consulting with AI experts to assist with integration. This can reduce errors, save time, and ensure the effective deployment of AI systems.

Lack of understanding

Despite the growing influence of AI, there’s still a lack of understanding about the technology among many business leaders. This lack of knowledge can result in unrealistic expectations, improper implementations, and suboptimal utilization of AI capabilities. Hence, educating stakeholders about the potential, limitations, and use cases of AI is crucial.

To tackle this challenge:

Regularly educate your team about AI, its potential, limitations, and impact on your business. This knowledge can help in effective decision-making and the management of AI systems.
It’s crucial to understand that AI isn’t a silver bullet that can solve all problems instantly. Set realistic goals and expectations, and be prepared for a learning curve.

AI Is Here to Stay, so Use It Wisely

In a nutshell, AI for eCommerce is no less than a revolution, decisively reshaping the dynamics of online shopping and business operations. Its profound influence stretches from customer interactions to their expectations and behaviors.

And despite the challenges that arise from data privacy concerns, the accuracy of AI systems, and the complexity and cost of integration, the potential benefits that AI offers are simply too vast to ignore. Companies that successfully incorporate AI technologies into their operations stand a greater chance of staying ahead of the competition, delighting customers with superior experiences, and driving significant growth in an increasingly digital world.

Posted on June 7, 2023

In today’s interconnected world, eCommerce is definitely the high street. The rapid expansion of the internet has brought about a significant shift in consumer behavior, with global eCommerce sales expected to reach $6.9 trillion by 2024.

Nonetheless, in the fiercely competitive environment of eCommerce, businesses must learn to maximize every interaction. The key to turning browsers into buyers and one-time customers into repeat customers lies in the art and science of eCommerce growth funnel optimization.

A growth funnel maps the conversion path of potential customers, from their first interaction with your brand, through the decision-making process, all the way to the point of purchase, and beyond. Understanding how to effectively navigate this journey can mean the difference between the thriving success of your eCommerce business and being left in the dust of your competitors.

How to Build Your eCommerce Growth Funnel

Building an eCommerce growth funnel is akin to constructing a blueprint for your customers’ journey that should ideally culminate in conversion and customer loyalty.

Key metrics and goals for each stage of the funnel

Let’s delve into the essential stages of an eCommerce growth funnel and the key metrics you should be following for each of them.

Awareness stage

In this initial stage, your goal is to attract as many visitors to your site as possible.

The strategies you deploy here are crucial, as they set the tone for all subsequent funnel stages:

Search engine optimization (SEO)
Pay-per-click (PPC) advertising
Social media marketing
Content marketing
Influencer marketing

For instance, the digital fitness platform, Peloton used influencer marketing to build awareness. They partnered with influencers and celebrities in the fitness industry, leveraging their followings to increase brand exposure. The influencers would showcase the Peloton bikes and classes in their social media posts, making their followers aware of the brand.

Key metrics to monitor in this stage:

Website traffic
Social media reach and engagement
Ad click-through rates
Brand mentions

Consideration stage

Once a visitor lands on your site, the next step is to pique their interest in your products or services. This involves high-quality product images, compelling descriptions, customer testimonials and reviews, and FAQs. Video demos or tutorials can also be a useful tool in this stage.

Take Apple, for instance. Their product pages are well-known for their captivating images and detailed product descriptions. They also provide customer reviews and ratings to build trust and pique visitor interest.

Key metrics to track in this stage:

Pageviews
Time spent on the website
Bounce rate
Email open and click-through rates

Conversion stage

This is when your prospective customers actually make purchase decisions. Offering competitive pricing, flexible payment options, free shipping, and a smooth checkout process can all play a significant role in the conversion funnel.

For example, ASOS offers a ‘Buy Now, Pay Later’ option to make it easier for customers to complete their purchase, reducing the financial burden on the customer and making the process easier.

Key metrics to monitor at the purchase stage:

Shopping cart abandonment rate
Conversion rate
Average order value
Cost per acquisition

Loyalty stage

After the sale, your task is to build customer loyalty and encourage repeat purchases. This can be achieved through excellent customer service, loyalty programs, personalized offers, and regular engagement through email newsletters or social media.

For instance, Starbucks’ loyalty program is a prime example of a successful customer retention strategy. They offer points for every purchase, which can be redeemed for free drinks and food, encouraging customers to come back.

Key metrics at this stage include:

Customer lifetime value (CLV)
Retention rate
Repeat purchase rate
Net promoter score (NPS)

Common challenges of eCommerce funnel optimization

While all this may look easy and straightforward, creating eCommerce growth funnels doesn’t come without its challenges:

Driving traffic: While techniques like SEO, PPC, and social media marketing can drive traffic, they require time, effort, and expertise to execute effectively.
Visitor engagement: Keeping visitors on your site long enough to pique their interest can be tricky. High-quality content and blog posts, intuitive navigation, and fast load times can help here.
Conversion: Turning interest into sales is a considerable challenge. Streamlining the checkout process, providing excellent product descriptions, offering competitive pricing, and displaying customer reviews can help improve conversions.
Shopping experience: A single glitch, slow load time, or complicated checkout process can result in cart abandonment, so ensuring a seamless user experience is vital.
Customer loyalty: Acquiring new customers is often more expensive than retaining existing ones, yet building customer loyalty can be difficult. Regular engagement, excellent customer service, and loyalty programs can be effective strategies here.

In each of these areas, it’s essential to continually test, measure, and optimize to ensure you’re meeting your customers’ needs and expectations. Take a look at our guide on eCommerce growth experiments to further improve your knowledge on this topic.

How to Measure Your eCommerce Funnel Performance

It’s great to know all the specific tactics, but how can you measure it all and know how to adjust your strategy over time? This is where the Noibu tool gets to shine.

The Summary Dashboard serves as the central hub, offering a succinct snapshot of your website’s health. It provides insights into the total revenue loss, significant issues, funnel steps affected, and the efforts of your team.

The Quick Stats panel is your starting point on the Summary Dashboard. It gives a quick overview of the annual revenue saved, the outstanding revenue loss, and any new issues identified within the selected time frame.

The Funnel Analysis chart complements the Quick Stats, displaying the Annualized Revenue Loss totals for each step in the marketing funnels during the chosen timeframe. It tracks the customer journey through four critical stages:

When a customer lands on your site.
When a customer adds a product to their cart.
When a customer initiates the checkout process.
When a customer finalizes their order.

The chart helps visualize potential revenue losses at each stage due to errors, aiding you in prioritizing your debugging efforts.

Key features of Noibu

Noibu’s platform offers features that showcase all errors affecting revenue and conversion. It pinpoints the funnel step affected and flags the common steps to reproduce the error.

Session Replay: This feature allows an in-depth replay of the customer journey, negating the need for inbound customer tickets or reliance on insufficient details. It includes video replay and console information, simplifying the error reproduction process.
Developer Tab: The Developer Tab provides vital details needed for confident debugging. It offers stack trace, browser details, last steps, HTTP information, and more, allowing for faster and more effective issue reproduction.
Issue Management: This helps in planning and executing bug resolutions right within Noibu. It allows for ticket triage directly on the platform and syncs with Jira for convenience. With custom tags, organizing and managing issues becomes straightforward, and the sharing capability facilitates cooperation with external partners.

How to Improve Your eCommerce Growth Funnel Optimization

Implementing the mentioned tactics is necessary if your goal is immediate growth, but shaping strategic, long-term plans through a proactive approach will continuously improve your eCommerce growth funnel. Here are some advanced, big-picture tactics to consider.

Leverage data for personalized experiences

Utilize the power of eCommerce data to personalize your user experience at every touchpoint. You can personalize emails, product recommendations, content, offers, and more based on user behavior and preferences.

One example would be to use something similar to “Customers who bought this also bought…” and “Frequently bought together” recommendations to drive additional sales.

Optimize for mobile

With the rise of mCommerce, a mobile-responsive design that loads quickly and provides a seamless browsing and shopping experience across different devices can significantly improve conversion rates.

Apart from providing a mobile-friendly site, consider building an intuitive app and offering features like visual search and social media integration to enhance the mobile shopping experience.

AI and machine learning

AI and machine learning can be leveraged to improve product recommendations, personalize customer experiences, automate customer service via chatbots, and predict future trends. They can help create a more seamless, efficient, and personalized experience for your customers, improving your conversion process and customer retention.

Fashion retailer Stitch Fix uses AI and machine learning to personalize clothing recommendations for customers based on their style, size, and price preferences, creating a unique, tailored shopping experience.

Scaling and Expanding the Funnel

Expanding your eCommerce growth funnel isn’t just about enlarging your customer base, but also about deepening the relationships with your existing customers.

The following are some advanced tactics to help you scale and expand your funnel growth:

Diversify marketing channels: Consider exploring channels such as influencer marketing, podcast advertising, or even offline advertising like print or television, depending on your target audience.
Explore international markets: If your products have potential appeal outside your current geographic market, consider expanding internationally. Fashion retailer Zara is a great example. It operates in over 96 countries, adapting its product offerings and marketing strategies to local trends and cultures.
Enhance product range: This can attract new customer segments and encourage existing customers to make additional purchases. Be sure to conduct thorough market research to understand what new products your customers might be interested in.
Implement new technologies: Whether it’s AR technology to allow customers to ‘try on’ products virtually, AI chatbots to enhance customer service, or personalized video marketing, staying on the cutting edge of technology can provide a significant competitive advantage.
Optimize operations: As your funnel expands, you’ll also need to optimize your operations to handle the increased volume. This might involve enhancing your supply chain management, implementing automation in areas like customer service or inventory management, or improving your website’s hosting and load times to handle increased traffic.

Final Thoughts

While the tactics outlined in this article can provide a solid foundation, remember that no two businesses are exactly alike. The best strategies will always be those that align with your ultimate goals, target audience, and brand identity. Therefore, constant testing, iteration, and flexibility are critical to your sales funnel optimization efforts.

Keep in mind that technology has a significant role to play in this process, with platforms like Noibu providing comprehensive tools for measuring, analyzing, and optimizing your funnel growth and performance.

And finally, remember to maintain a big-picture perspective, focusing not only on immediate tactics but also on long-term strategic planning. Your eCommerce journey is what shapes you and your business, instilling resilience, agility, and an unerring focus on the customer – qualities that are the hallmark of every successful eCommerce venture.

Posted on June 6, 2023

In the fast-paced world of eCommerce, digital shopping carts fill up rapidly with potential purchases. Yet, a significant proportion of these carts never make it to the checkout line. This phenomenon, known as shopping cart abandonment, represents a significant revenue loss for eCommerce stores.

As the eCommerce industry continues to grow, with global retail eCommerce sales expected to reach $6.31 trillion in 2023, so does the potential for revenue loss due to cart abandonment.

Cart abandonment is akin to customers walking into a brick-and-mortar store, filling their shopping baskets with items, reaching the cashier, and then abruptly leaving, never to return. For the business owner, it’s a bewildering and frustrating scenario. This critical juncture, where potential revenue morphs into a lost opportunity, has become a hotbed for analysis, innovation, and strategic planning.

The following article provides a detailed analysis of online shopping cart abandonment, delving into its causes, impact on revenue, and effective strategies for everyone who wants to know how to reduce shopping cart abandonment.

Common Reasons for Cart Abandonment

Seeing these reasons for cart abandonment as serious eCommerce errors will help you identify the pain points in the purchasing journey that dissuade customers from completing their purchases.

Unexpected costs: Hidden costs that customers encounter at the checkout stage can take various forms, such as costs of shipping, taxes, and handling or service fees. If a customer perceives these extra costs as too high or feels blindsided by them, they are likely to abandon their cart.
Mandatory account creation: Mandatory account creation can disrupt the fluidity of the customer experience. A customer’s desire to make a quick purchase can be hampered by the need to spend time creating an account. In fact, research by the Baymard Institute found that 24% of customers abandoned their cart because the site wanted them to create an account.
Complicated checkout process: A checkout process that’s too complicated or time-consuming is a major deterrent. Long forms to fill, unclear navigation, slow load times, or too many steps can frustrate customers and lead to abandonment. The same research suggests that 17% of online customers have abandoned an order during the checkout process because it was too long or complicated.
Security concerns: In an era where data breaches are becoming increasingly common, customers are understandably concerned about the security of their personal and financial information. If your website doesn’t clearly demonstrate that it is secure, customers may abandon eCommerce shopping carts. Trust signals such as SSL certificates, well-known payment gateways, and visible privacy policies can help alleviate these concerns.

Cart abandonment statistics

The impact of cart abandonment on eCommerce can’t be overstated. It represents a major hurdle to optimal conversion rates and has significant implications for lost revenue.

According to the comprehensive report by the Baymard Institute mentioned above, the average cart abandonment rate documented online is approximately 69.99%. In simpler terms, seven out of ten online shoppers leave without completing their purchase, which underscores the extent of the problem and the potential for cart recovery.

Further highlighting the financial impact, data suggests that eCommerce businesses lose approximately $18 billion per year due to abandoned carts. This colossal figure speaks volumes about the magnitude of the problem and the monumental opportunity it presents for revenue recovery.

Optimizing the Checkout Process

A significant portion of your potential customers reaches the checkout process, signaling a strong intent to purchase. However, checkout can be a make-or-break point in the customer journey. Hence, optimizing this process is critical in decreasing your cart abandonment rate, which is one of the main eCommerce KPIs.

Strategies for optimizing the checkout process

Optimizing the checkout process involves making strategic changes that simplify and streamline the process, enhancing user experience, and thereby encouraging customers to complete their purchase.

Simplify the checkout flow: Minimizing the number of form fields and steps required to complete a purchase makes the process more customer-friendly and less likely to cause frustration or impatience.
Offer guest checkout options: This allows users to make a quick purchase without the need for account creation, which can significantly reduce friction and lower abandonment rates.
Provide multiple payment options: By offering a variety of options including debit/credit cards, PayPal, Apple Pay, Google Pay, and others, you cater to a broader audience and increase the likelihood that customers can pay as they prefer.

Etsy offers multiple payment options including credit/debit cards, PayPal, Apple Pay, Google Pay, and even Etsy Gift Cards. This variety ensures that most customers can pay in their preferred way, reducing the likelihood of cart abandonment due to payment-related issues.

Transparent pricing: Be upfront about any additional costs, such as shipping costs or taxes, early in the process. Transparency in pricing helps build trust and reduces the likelihood of customers feeling blindsided at checkout, which could lead to abandonment. Alternatively, provide free shipping if possible.

Warby Parker, an online glasses retailer, provides a commendable example of transparent pricing, with a flat-rate pricing model and no additional shipping charges. Prices on product pages are the final prices that customers pay.

Testing and analyzing the checkout process

Implementing changes is just the beginning. It’s crucial to continuously test and analyze the effectiveness of the checkout process.

A/B testing allows you to experiment with different elements to identify what resonates best with your audience.
Heat mapping can also provide valuable insight into customer behavior during the checkout process.
Tools like UserTesting allow real users to interact with your website while providing feedback.
Different customer segments might behave differently during the checkout process. Analyze behavior based on customer demographics, source of traffic, and type of product to gain deeper insights.
If customers are abandoning their carts, a simple email survey or popup can provide valuable insight into their reasons for not completing a purchase.

Building Trust and Reducing Friction

One significant challenge of eCommerce is the lack of physical interaction, which means building trust with customers becomes more complex. Additionally, any hurdles encountered during the online shopping experience, often referred to as friction points, can easily deter customers.

Building trust

In an age of data breaches and online fraud, customers need assurance that their personal and financial information is secure. Displaying security badges prominently on your website, particularly during the checkout process, can reassure customers. These could include SSL (Secure Sockets Layer) certificates, or badges from well-known internet security companies like Norton, McAfee, or TRUSTe.

Trust can also be built by showcasing social proof like positive customer testimonials, customer reviews, or ratings. According to a consumer review survey by Bizrate Insights, 54.7 percent of customers read at least four product reviews prior to purchasing a product. Highlighting these positive endorsements can reassure potential customers of your product quality and customer service.

Moreover, clear and comprehensive product details, along with high-quality images or videos, can help customers make informed decisions, reducing the chances of post-purchase dissonance and returns, and increasing the likelihood of successful transactions.

Apple provides a stellar example of building trust with its customers. They ensure the entire shopping experience, from browsing products to checkout, is secure. The site uses HTTPS, indicating that all data transferred is encrypted and secure. Additionally, the payment process is streamlined and secure, with Apple Pay as a payment option, reducing the need for customers to enter credit card details.

Apple also extensively showcases customer reviews and ratings for its products. This transparency not only allows potential buyers to make informed decisions but also builds trust in the quality of their products.

Reducing friction

Friction in the eCommerce context refers to anything that hampers the smooth flow of the customer journey, from browsing to purchase. It could be slow website speed, poor navigation, lack of product information, complicated checkout processes, or limited customer support.

Addressing these friction points involves improving website design and functionality, providing detailed product information, simplifying the purchase process, and offering efficient customer support.

A customer-centric return policy can also reduce friction. If digital buyers know they can easily return a product if it doesn’t meet their expectations, they may be more likely to complete the actual purchase.

Zappos, the online shoe and clothing retailer, is a leading example of reducing friction in the eCommerce journey. The website is user-friendly, with intuitive navigation, clear categories, and a robust search function that makes finding products easy.

Moreover, they offer a simplified checkout process with minimal steps, guest checkout option, and multiple payment methods, all contributing to a frictionless user experience. But where Zappos truly shines is in its customer-centric return policy. They offer a 365-day return policy with free shipping both ways, giving customers peace of mind and reducing the perceived risk of purchase.

Recovering Abandoned Carts

While preventive measures to decrease cart abandonment are crucial, it’s equally important to have strategies in place for recovering online carts that do get abandoned.

Strategies for recovering abandoned carts and reclaiming lost revenue

Recovering abandoned carts essentially involves re-engaging with customers who have shown a clear intent to purchase.

Retargeting ads: Retargeting ads allow you to display personalized ads to users who have visited your website but left without making a purchase. These ads, displayed on various platforms such as social media or other websites the user visits, act as reminders of the items left in the cart, prompting customers to return and complete the purchase.
Abandoned cart emails: These are personalized emails sent to customers who abandoned their carts, reminding them of their unfinished purchase. Cart abandonment emails can be simple reminders or offer incentives like a discount code, coupon code, or free shipping options to entice customers to complete their purchase.

Casper, an online mattress retailer, sends out a well-designed cart recovery email. The email is simple, reminding the customer of what they left behind and showcasing the benefits of their product. They also add a bit of humor to keep the tone light and friendly, asking “Did you forget something?”. This kind of personalized email helps reconnect with customers and encourages them to complete their purchase.

Exit-intent popups: These are messages that appear when a user is about to leave your website, offering incentives or assistance to encourage them to stay and complete their purchase.
Live chat support: Offering real-time assistance through live chat can address any questions or concerns that may be causing the customer to abandon their cart. Having questions answered by a live person during an online purchase is one of the most important features a website can offer.

Implementing these strategies can help re-engage customers, address their concerns, and guide them towards completing their purchase, thereby helping you reclaim lost revenue.

Reclaiming Lost Revenue Leads to a Better Bottom Line

Cart abandonment is a persistent and common problem in eCommerce, leading to significant revenue loss. However, with a detailed understanding of its causes and a strategic approach to address them, online businesses can successfully reduce abandonment rates, reclaim lost revenue, and enhance their customer’s shopping experience.

While this article outlines several effective strategies, it’s essential to remember that every eCommerce business is unique. Therefore, make sure to combine data analysis, customer feedback, and constant testing to tailor these strategies to your specific needs and audience.

Remember, the goal is not just to recover lost sales but to create an efficient, customer-friendly shopping process that builds trust and loyalty. The focus should always be on the customer’s journey and eCommerce experience, leading not only to immediate sales recovery but also to long-term business growth through repeat customers.

Posted on June 5, 2023

In today’s highly competitive eCommerce landscape, the ability to drive conversions is crucial for the success and growth of any online business. In that context, conversions, whether they involve purchases, sign-ups, or any other desired action, are the ultimate goal of every eCommerce team.

However, thoroughly understanding the complex journey that customers take from the initial website awareness to the final conversion and why they act how they act in given situations and places can be a daunting task.

Let’s put this into perspective. Despite all the time and hard work that you and your team have spent perfecting your conversion funnel, visitors just flow through your eCommerce site each day but all of the traffic funnels down to just a trickle of sales, signups, and conversions. Sounds familiar? In all likelihood, probably, yes. Is there a way to address this issue? Also, yes.

This is where funnel analytics and website funnel analysis come into play. Funnel analytics help eCommerce teams thoroughly understand how real customers shop online by providing next-level insights into the entire customer journey. This way, eCommerce team leaders and their personnel can identify vital opportunities for optimization and growth by optimizing their conversion funnels to reflect each visitor’s unique customer journey.

In the following sections, we will delve deeper into funnel analytics and explore how the proper utilization of this valuable tool can increase conversions and propel your eCommerce business forward.

Setting Up Funnel Analytics For Your eCommerce Website

To effectively leverage funnel analytics and website funnel analysis, first, CCOs and their dedicated teams need to set up tracking and define their funnel goals and key performance indicators (KPIs).

Defining Your Funnel Goals And KPIs

Defining these will provide a framework for tracking and measuring your funnel and conversion performance. Here are a few steps to follow along the process:

Identify your primary conversion goals. Identify the main actions you want your website visitors to take. For example, it could be purchasing, signing up for a newsletter, or completing a contact form. These goals will serve as the key milestones in your sales funnel.
Break down your funnel into stages. Map out the various stages that customers typically go through before reaching the conversion point. These stages usually include awareness, consideration, and decision-making. For instance, many online shoppers might be visiting the homepage of your eCommerce store, but only a few really see the “thank you” page after purchase. If you break down your funnel conversion path, it would look like this: homepage→category page→product page→cart→checkout→thank you page. Understanding the funnel path will help you track user progression and identify areas for improvement.
Assign KPIs to each funnel stage. Once you have defined your funnel stages, determine the relevant KPIs for each stage. For instance, you might track metrics like website visits, page views, and social media engagement at the awareness stages. At the consideration stage, you could focus on metrics such as product views, cart additions, and wish list interactions. Finally, at the decision-making stage, key metrics may include conversion rate, average order value, and checkout abandonment rate. Assigning specific KPIs will allow you to measure progress and identify areas that need attention.

Set specific and measurable targets. Establish clear targets for each KPI based on your business objectives. These targets should be specific, measurable, attainable, relevant, and time-bound (SMART). For example, you may aim to increase the conversion rate by 8% within the next quarter or reduce cart abandonment by 3% over the next month.

Defining your funnel goals and KPIs lays the foundation for effectively implementing funnel analytics. Now, because this article is focused on using the proper funnel analysis in order to increase conversions and grow the revenue of your eCommerce business, let’s see how your eCommerce team can use the website conversion funnel analysis to monitor funnel performance, diagnose funnel issues, and identify funnel opportunities.

Using Funnel Analytics To Increase Conversions And Grow Your Business

Now that you have set up funnel analytics and defined your goals, it’s time to leverage the power of this data to increase conversions and drive growth for your eCommerce business. Here are two critical strategies for utilizing sales funnel analytics effectively:

How To Use Funnel Reports And Dashboards To Visualize And Monitor Your Funnel Performance?

Funnel reports and dashboards visually represent your funnel performance, allowing you to monitor and assess the effectiveness of your marketing and conversion optimization efforts. Here’s how you can utilize these tools:

Choose the right analytics platform. Select an analytics platform that offers funnel visualization capabilities, such as Noibu or Google Analytics. For instance, Google Analytics 4, or GA4, is the latest Google product that allows for app and web data to be collected separately or in a single continuous property. The latest analytics platform is designed to replace both UA and GA360 by the end of 2023. All these analytics platforms provide users with pre-built reports and customizable dashboards specifically designed to track and analyze the funnel data and use it to their advantage.
Set up funnel visualizations. Configure your analytics platform to generate funnel reports based on the stages you defined earlier. These reports will illustrate the progression of users through your funnel, indicating where they drop off and identifying potential areas for improvement.
Monitor key funnel metrics. Pay attention to key funnel metrics, such as conversion rates at each stage, drop-off points, and overall funnel performance. Regularly review these metrics to track progress toward your goals and identify any anomalies or trends that require attention.
Create customized dashboards. Customize your analytics platform’s dashboard to display your eCommerce business’s most relevant metrics and KPIs. This way, you can have an at-a-glance view of your funnel performance and make informed decisions based on real-time data.

How To Use Funnel Analysis And Insights To Identify And Diagnose Funnel Issues and Opportunities?

Funnel analysis provides not only visualization but also deep insights into your customer journey. Here’s how you can utilize funnel analysis and insights to uncover issues and opportunities within your sales funnel:

Analyze drop-off points. Review your funnel analytics to identify the stages where users drop off the most. By understanding the reasons behind drop-offs, such as confusing checkout processes or lack of information, you can address these issues and optimize the user experience.
Segment your data. Break down your funnel data by different segments, such as traffic sources, demographics, or device types. This segmentation allows you to identify patterns and preferences among different user groups. By tailoring your marketing and optimization strategies to specific segments, you can improve conversions for each group.
Perform A/B testing. Implement A/B testing on different elements of your funnel, such as landing pages, calls-to-action, or checkout processes. You can make data-driven decisions to optimize your funnel for maximum conversions by comparing different versions and analyzing the impact on conversion rates.
Leverage behavioral analytics. Use advanced behavioral analytics tools to gain insights into user interactions, such as mouse movements, click heatmaps, or session recordings. These tools help you understand how users navigate through your website, identify usability issues, and make data-informed improvements.

By leveraging funnel analysis and insights, you can uncover hidden opportunities, diagnose funnel issues, and implement targeted strategies to drive conversions and grow your eCommerce business.

Using Noibu To Track Funnel Statistics And Identify The Issues With Most Revenue Loss To Grow Your eCommerce Business

Noibu is a powerful tool that monitors your eCommerce website and can help you flag errors in real time. One of the many features that Noibu puts on the table for eCommerce teams is that it can also help you track funnel statistics and identify issues that result in revenue loss for your eCommerce business. As a result, by leveraging and harnessing the power of Noibu, you can gain valuable insights into user behavior and address critical issues that hinder conversions.

Funnel Statistics

Noibu’s funnel feature tracks the customer’s buying process across four primary phases:

On-site
Add-to-cart
Checkout started
Order placement.

For each phase, the funnel statistics view summarizes unique sessions and the number of sessions that successfully progressed to the next phase within a specified time frame. For example, you can customize the timeframe for data retrieval, such as the past day, seven days, 14 days, 30 days, or 90 days.

Noibu’s funnel feature also provides insights on sessions lost and transactions lost at each phase. Sessions and transactions lost are distinct only in the on-site and add-to-cart phases. In later stages, transactions lost encompass the natural drop-off attributed to errors encountered in earlier phases.

It is expected to experience some drop-off at each phase of the buying process. By gathering data and computing an average conversion rate, the funnel statistics view determines the number of sessions and transactions lost due to website issues. Furthermore, it estimates the potential revenue loss at each phase if these issues are not addressed.

Issues With Most Revenue Loss

The “issues with most revenue loss” feature is a valuable funnel analysis tool that allows you to prioritize your debugging efforts by pinpointing the issues that have the most significant impact on your revenue. As the funnel statistics view, you can customize the timeframe, such as the past day, seven days, 14 days, 30 days, or 90 days, to gather relevant data.

In the “issues with most revenue loss” view, user-impacting issues verified by your team or Noibu support appear at the top. In contrast, uncategorized problems are ordered by projected revenue loss. Addressing both types of issues is crucial for improving user experience and minimizing revenue loss.

With Noibu’s funnel analysis features, you can filter the table of issues by any column, and you can freely customize which columns appear in the table by opening the menu. The available filters include urgency, assignee, state, label, OS, browser, resolution likeliness, impact, annual revenue loss, leads lost, users impacted, created at, last seen, closed fixed at, error type, error source, page type, and analytics period.

Posted on June 2, 2023

In the dynamic and intensely competitive world of eCommerce, cart abandonment remains a significant challenge. You have probably already employed various strategies to mitigate this issue, but given the persistently high rates of cart abandonment, you may need a more in-depth approach to reduce cart abandonment rates and increase your conversion rate.

Traditional tactics might not cut it in the face of evolving consumer behavior, technological advancements, and a complex competitive landscape. It’s no longer just about having a well-stocked inventory or competitive pricing. Today, the battle is won by those who can strategically leverage data, optimize user experience for a cart owner, and implement smart, adaptive tactics to reduce cart rates.

In this comprehensive guide, we aim to explore eight advanced shopping cart abandonment solutions. First, we’ll delve into the importance of data analysis for understanding customer behavior and cart abandonment, and then we’ll tackle the role of user experience, website design, as well as other tactics you can use to recover abandoned carts.

Analyzing Cart Abandonment Data

The foundation of any effective strategy to reduce cart abandonment lies in a deep understanding of why it happens in the first place. This understanding can only come from a detailed report, which includes rigorous and systematic analysis of cart abandonment data.

Without abandoned cart reports and analytics, you’re navigating the choppy waters of eCommerce based on hunches and assumptions, which is a recipe for wasted resources and disappointing results.

Identifying patterns and trends in cart abandonment

To harness the power of data, you need to become a detective of sorts, seeking patterns and trends in your cart abandonment data. Carefully tracking when and where customers abandon their carts can help you start uncovering the specific factors that contribute to cart abandonment in your store.

By asking these and similar questions, you can start identifying commonalities and trends:

Are there specific products that are more often left in the cart?
Is there a particular stage in the checkout process where customers are most likely to drop off?
Are customers from certain regions more prone to abandoning their carts?
Do abandonment rates fluctuate at different times of the day or week, or during specific seasons?

These insights serve as signposts pointing toward the areas of your store and the aspects of your customer experience that need your attention the most.

Using data to optimize your eCommerce store

Once you’ve gathered valuable insights and data (cart abandonment rate), the next step is to leverage them to optimize your store.

This is where your analysis transforms from a passive exercise into an active, value-adding endeavor:

If certain products consistently have high abandonment rates, it may be time to reevaluate product price points, descriptions, or images.
If customers using mobile phones and devices have a higher tendency to abandon their carts, you might need to improve your mobile shopping experience.
If customers from a particular region are more likely to abandon their carts, perhaps there’s a need to revisit your shipping options, delivery times, or payment methods for that region.

In essence, your cart abandonment data should serve as a roadmap, guiding your optimization efforts. Data-driven optimization allows you to address specific issues that directly contribute to cart abandonment, enhancing the effectiveness and efficiency of your strategies.

Recovering Cart Abandonment: 8 Tactics for Success

The data has been analyzed, patterns have been identified, and you’re armed with a deeper understanding of why customers are abandoning their carts. Now comes the crucial next step – implementing effective tactics for abandoned cart recovery.

Here we delve into a collection of advanced methods that extend beyond common practices, focusing on elevating user experience, optimizing website design, and employing strategic marketing interventions.

1) Importance of user experience

In the realm of eCommerce, user experience (UX) can no longer be an afterthought. Every step of the customer’s journey, from landing on your site to the final step of checkout, needs to be meticulously designed to be smooth, intuitive, and pleasant.

A poorly designed or confusing site can cause frustration, leading customers to abandon their carts and seek a better experience elsewhere.

Prioritize UX to keep customers engaged and reduce the chances of cart abandonment by following these two steps:

Prioritize page load speed because a delay of even a few seconds can lead to higher abandonment rates. Use CDNs, optimize images, minimize HTTP requests, enable browser caching, minify HTML, Javascript, and CSS files, optimize CSS delivery, and prioritize above-the-fold content.
Make sure your checkout process is clear and easy to navigate, with as few checkout fields as possible.

2) Optimize website design

The design of your website is the first thing customers notice, and it can significantly influence their shopping experience. A well-optimized site is easy to navigate, aesthetically pleasing, and intuitively guides customers toward making a purchase.

To reduce cart abandonment, it’s essential to eliminate any hurdles that might make shopping difficult or frustrating:

Make your site easy to navigate with a logical menu structure and clear product categorization.
Provide detailed product descriptions and high-quality images to help customers make informed decisions.
Ensuring your site is responsive and works seamlessly on all devices, especially mobile (fluid grids, flexible images, mobile-first design, hamburger menu, compress images and videos, touch-friendly design, AMP, mobile SEO).
Understand how different colors can elicit different responses from consumers. The chosen color scheme should reflect the brand’s personality and resonate with the target demographic, and the contrast between colors should be such that content is easily legible and calls-to-action stand out.
Set up an exit-intent popup that appears when guest or logged-in users show the intention of leaving your website at the checkout.

3) Effective calls to action

Your call-to-action (CTA) buttons play a critical role in guiding customers through the purchasing process. These buttons should be clear, compelling, and strategically placed to drive customers toward completing a purchase.

This data-driven approach allows you to base your decisions on actual customer behavior, increasing the chances of converting browsers into buyers:

Use clear, compelling language that encourages customers to take action.
Experiment with different colors, sizes, and placements to see what works best.
Use A/B testing to determine the most effective CTAs.

4) Streamline the checkout process

One of the top reasons for cart abandonment and one of the common eCommerce mistakes is a complicated or lengthy checkout process. Streamlining this process, reducing the number of steps, and offering a guest checkout option can significantly reduce cart abandonment.

These steps can make the checkout process quicker and more convenient, encouraging more customers to complete their purchases:

Reduce the number of steps in your checkout process.
Offer a guest checkout option (with cart details included) for guest users who don’t want to create an account/become registered users.
Display all costs, including shipping fees, taxes, and any additional fees upfront to avoid surprising customers at checkout.
Implement the autofill feature for returning customers.
Offer a variety of payment options.

5) Offer incentives

Offering incentives like free shipping, discounts, coupon codes, or gifts can provide the extra nudge some customers need to complete their purchases. However, it’s crucial to ensure these incentives are not only enticing but also effectively communicated.

Consider offering dynamic incentives based on the value of the customer’s cart, which can also encourage customers to add more items to their cart:

Offer free shipping to remove a significant barrier to purchase. This can lead to an increase in conversion rates and average order value, directly influencing the ROI and bottom-line revenue.
Personalized discount codes add an element of exclusivity and personalization to the shopping experience. By increasing conversions, they contribute positively to KPIs like sales revenue, customer acquisition cost, and customer lifetime value.
Free gifts can increase the perceived value of the purchase, making customers feel they’re getting more for their money. This strategy can increase conversion rates and average order value, as customers may be more inclined to spend more to qualify for a free gift.

Finally, make sure to prominently display your incentives and make sure they’re easy for customers to apply, and also test different types of incentives to see what is most effective.

In a recession, customer retention becomes crucial. These strategies can enhance customer satisfaction and loyalty, leading to repeat purchases and higher customer lifetime value, which can help sustain businesses through difficult economic times.

6) Create a sense of urgency or scarcity

These can be powerful motivators for customers to complete their purchases promptly:

Use limited-time offers or low-stock warnings to encourage customers to purchase quickly.
Include countdown timers on limited-time offers.
Always be transparent and honest about the scarcity or urgency of your products to maintain customer trust.

7) Display trust signals and security badges

Online shoppers need to feel confident that their personal and financial information is safe. Displaying these trust signals can reassure customers and increase their likelihood of completing a purchase:

Display security badges from reputable organizations on your site.
Include customer reviews and testimonials on product pages and throughout your site.
Ensure your site uses secure HTTPS protocols.

8) Implement a Remarketing Strategy

Despite your best efforts to optimize your site and checkout flow, some customers will still abandon their shopping carts. That’s where a robust remarketing strategy (such as checkout recovery email campaigns) comes in.

Remarketing involves reaching out to customers who have left your site without making a purchase, encouraging them to return and complete their transactions. This can be achieved through various methods such as targeted ads, personalized abandoned cart emails, and social media campaigns.

Retargeting cart recovery emails can be particularly effective. Cart abandonment emails should include a cart recovery link and serve as gentle reminders to customers of the items they left in their cart, possibly offer a small product discount or incentive to complete the purchase, and provide an easy link back to their cart.
Additionally, targeted ads can be used to remind customers of their abandoned carts as they browse other websites or use social media. The ads should be visually appealing, showcase the abandoned products, and include a clear call to action.
Make sure to personalize your remarketing efforts to make them more effective.

It’s Time for Effective Abandoned Cart Recovery

Shopping cart abandonment is a persistent issue for eCommerce stores, but it’s not insurmountable. By understanding why customers abandon their carts and implementing strategies to address these issues, you will be on a good path for abandoned cart recovery and boost your store’s profitability.

From optimizing your website design and user experience to offering enticing incentives, creating a sense of urgency, and implementing a robust remarketing strategy, there are indeed numerous ways to encourage customers to complete their purchases.

However, remember that every eCommerce store is unique, and there’s no one-size-fits-all solution to cart abandonment. That’s why it’s crucial to analyze your data, understand your customers, and continually test and optimize your strategies. With a data-driven approach and a commitment to providing an excellent shopping experience, you can reduce cart abandonment and set your store up for long-term success.

Posted on May 17, 2023

The eCommerce industry is living its golden years and there’s no doubt about that. As a matter of fact, retail eCommerce sales totaled roughly $5.7 trillion worldwide in 2022. Moreover, this number is projected to grow by 56% over the following years and reach about $8.1 trillion by 2026, speaking volumes about how rapidly the industry actually grows.

And while these numbers are quite promising, they also show that the competition for customers among eCommerce brands will only become more intense. To acquire new and retain current customers, optimize prices, improve efficiency and profitability, stand out in the sea of different eCommerce businesses, and ultimately increase their sales and revenue, companies will need to heavily rely on eCommerce analytics.

Keep reading to learn how you can use data and eCommerce analytics to grow your sales and why doing so is essential for your brand in 2023.

5 Areas Where eCommerce Businesses Can Use Analytics

Analytics for eCommerce involves collecting and analyzing relevant data to help eCommerce businesses gain an edge over their competitors. Then, companies can use this data to improve various aspects of the business, including customer acquisition and retention, logistics, and payments.

Acquisition

Analytics can help businesses understand how customers find them online, which products are most popular, which channels are driving the most conversions, and where their customers come from. This data can then be used to determine which marketing campaigns and channels to focus on.

Retention

Analytics can also provide valuable insights into customer retention, including the percentage of current customers who make repeat purchases, the average time between repeat purchases, and which product categories have the best customer satisfaction rates. This information can be used to encourage repeat purchases and increase revenue from existing customers.

Monitoring customer engagement with your company is another important use of sales data analytics. By tracking when a customer last visited your online shop, bought any products, or contacted your support team, you can prioritize any customers who haven’t been contacted for a while or any who are at risk of leaving.

Profitability

Analyzing product performance from previous transactions helps you spot when a product is on the up or quickly declining. Analytics can help you increase profitability by identifying cross-sell and upsell opportunities, segments of customers that drive high revenues, product pricing that has the best potential for conversions, as well as products that have the potential to improve margins.

Efficiency

Data can be used to improve operational efficiency by identifying ways to speed up delivery times, forecasting future demand, managing inventory more efficiently, and planning staffing levels during high and low-traffic phases.

ROI

Finally, understanding the performance of marketing campaigns on various channels, including pay-per-click ads and social media, can help you measure the ROI of each campaign and identify which campaigns have the best potential for scaling up.

This knowledge can then be used across various departments of an eCommerce business:

Business and marketing departments can identify where to focus their resources and marketing budgets by acquiring insights on which marketing campaigns and channels are driving the most conversions, which products are popular, and where customers are coming from.
Product departments can make better decisions by analyzing product performance from previous transactions. This includes valuable insights into customer behavior, shopping trends, and product performance, which all help identify which products are on the rise or decline and allow for better decisions regarding product development, pricing, and inventory management.
Finally, technical departments can use data to identify areas of inefficiency in operational processes, which allows for better planning of staffing levels during high and low-traffic phases. Moreover, data can help streamline various customer service processes, reduce the number of tickets, and improve customer satisfaction by providing faster responses to customer inquiries.

4 Advanced Ways to Use eCommerce Analytics for Sales Growth

Analytics and data can sometimes be overwhelming, especially if you’re analyzing graphs and figures every day. And even when you understand what the numbers mean, it may not be completely clear how you can use them to increase sales figures.

Here are a few proven ways you can use analytics for boosting your eCommerce sales funnel.

Product recommendations

To cultivate customer loyalty, companies need to establish good relationships with customers. One effective tool for achieving this is a product recommendation engine, which utilizes machine learning algorithms to suggest items that a customer might be interested in. Recommendations can be delivered through a variety of channels, including websites, email campaigns, and online ads.

Market basket analysis

Market basket analysis is a technique that identifies the correlation between a pair or group of products that are frequently purchased together. In simpler terms, if a customer buys a product, they are more or less likely to buy another related product. This method also employs machine learning algorithms, similar to product recommendation engines.

Price optimization

Competitive pricing is one of the most important aspects of eCommerce shopping, so it’s crucial to establish optimal prices that balance customer satisfaction with profit.

Let’s take a look at three critical concepts related to price optimization:

Segmentation of customers and products: This entails grouping similar products and customers, with the aid of classification and clustering algorithms. This information can be used to create targeted marketing campaigns, offer product bundles, or provide discounts to specific groups of customers.
Regression modeling: After the segmentation process, regression models can be used to determine optimal product prices by analyzing sales data, conversion rates, seasonality, product attributes, marketing channels, and so on.
Dynamic pricing: Dynamic pricing uses competitor data as input into machine learning algorithms to establish the product’s price at various times. This allows products to remain competitive in the market despite frequent price fluctuations.

Through data analysis, you can optimize your pricing structure by seeing key financials for each product line from gross profit, costs, revenue, and quantities. This allows you to define the best value price for both you and your customers.

Demand forecasting

Another important use of data analytics for eCommerce is to predict customer behavior. By analyzing previous transactions, you can identify trends and patterns that help you anticipate future shopping behaviors, which is key to better time management, prioritization of key accounts, and creating realistic sales forecasts.

Demand forecasting involves using analytical techniques to forecast product demand and predict sales. When you know the sales trends in advance, you gain an advantage over your competitors by improving:

Inventory management: Effective demand forecasting allows for informed inventory planning, which saves you from both selling out of popular products and unnecessary storage costs.
Cash flow management: Additionally, it helps you plan your budget properly and utilize cash optimally, thus reducing financial risk.
Pricing strategy: Finally, a better pricing strategy can be achieved by charging more for high-demand products and properly planning marketing budgets, advertising investments, and discount plans.

7 Best Practices to Make the Most Out of Your eCommerce Data

It is estimated that as many as 218.8 million people will make an online purchase in the US alone in 2023. And if we’re to believe these predictions, this number will grow to 230 million in 2026.

This means that the eCommerce market is only becoming bigger, so you stand a good chance of capturing a share of it. However, as you already know, second-guessing is an absolute no-no in the world of business.

If you want to fully rely on eCommerce data analytics, here are seven best practices to follow:

Start small. In the beginning, focus on the metrics that matter most to your business goals. Don’t get overwhelmed by the sheer amount of data available.
Build a robust system for collecting and organizing data. An integrated data stack that consolidates data from multiple sources into a single source of truth will improve data accuracy and enhance decision-making.
Consider data quality. Ensure that your eCommerce analytics data is always accurate and reliable by using advanced analytics tools, regularly auditing data sources, and using data cleansing techniques.
Use data ethically. Protect data privacy and security by being GDPR and CCPA-compliant, as well as only using collected data for its intended purpose.
And use it optimally. Use analytics to measure performance, validate assumptions, find opportunities for improvement, test new strategies, and inform all business decisions. Moreover, it’s a good idea to share insights with stakeholders throughout the organization.
Stay away from data silos. Centralize data from various sources to prevent misalignment between teams and obfuscated insights. Dashboards provide fast information on sales performance, enabling you to make better, informed decisions and take action more quickly.
Automate. Automating tasks based on your sales data enables you to streamline your sales process, save time and improve efficiency. By automating routine tasks, such as creating reports and adding customer details to your calendar, you can focus on high-value activities that drive sales.

Current Trends in eCommerce Analytics

As eCommerce businesses evolve, new trends emerge in analytics that can help them stay ahead of the competition. Here are some of the latest trends in analytics for eCommerce that marketers are observing:

Focus on customer retention

Many eCommerce businesses are now focusing on customer retention by using analytics to predict customer behavior and offer personalized benefits. By identifying customer segments based on their purchasing habits, eCommerce companies can prioritize which customers to target with retention strategies.

Predictive analytics

Predictive analytics is being increasingly used to predict market trends and customer behavior. By using machine learning algorithms and historical data, eCommerce businesses can anticipate which products will be popular, which customers are most likely to buy and when, and the most effective marketing strategies.

Multichannel retail

eCommerce brands are now utilizing multiple channels, including social media, websites, apps, email, WhatsApp, and even physical stores, to reach their potential customers. A sound strategy for managing, collecting, and utilizing data across all these channels is crucial.

AI and ML technologies

Using artificial Intelligence and machine learning for customer segmentation and personalization, businesses can deliver a more customized customer experience. They can also use sentiment analysis to understand customer feedback and build dynamic pricing for products to remain competitive.

Real-time analytics

Real-time analytics enables eCommerce businesses to quickly adjust their strategies in response to changing customer behavior and market conditions. This trend is critical for businesses that want to stay competitive and agile.

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Final Thoughts

From customer retention to real-time analytics and AI/ML technologies, the trends in eCommerce analytics are constantly evolving. To stay competitive and successful, you must keep up with these trends and invest in a robust analytics strategy that meets your unique business objectives.

By embracing the power of eCommerce data analytics, you can gain actionable insights that enable you to make data-driven decisions that can drive growth, improve customer engagement and ultimately increase sales. As a result, you will truly thrive in today’s dynamic eCommerce landscape.

Posted on May 16, 2023

Posted on May 12, 2023

Unlocking eCommerce Success: A Comprehensive Guide To The Data You Should Track

The old saying that applies to almost everything we do in life goes something like this—if you don’t know where you are, you can’t know where you’re going. And you can’t know where you are, nor where you’re going, if you fail to regularly monitor and assess the things that are truly important for you and your growth.

When it comes to managing and scaling your eCommerce company to unlock its full potential, we at Noibu find that this saying rings particularly true. The mere success of your eCommerce operations relies on the data you gather and the eCommerce metrics you measure. In fact, the most successful eCommerce enterprises like Amazon, eBay US, Alibaba, and others that are constantly winning at eCommerce, are doing so because they’re absolutely obsessed with their eCommerce metrics.

For example, Jeff Bezos’s Amazon utilizes big data to improve one of their essential eCommerce metrics—average order value. Amazon sets its product prices in accordance with current activity on its website, product availability, order history, item preferences, foreseen profit margin, and other factors. Then, they utilize the so-called “dynamic pricing” method, which involves changing the prices on given items as big data is updated and analyzed. Thanks to this, Amazon typically earns more significant profits on their best-selling items and offers discounts to the less popular ones. According to a report, this strategy benefited the eCommerce giant by enhancing its annual income by 143% from 2016 to 2019.

Knowing the ins and outs of your key eCommerce metrics and analytics is crucial because it’s the only way to gauge your levels of success and identify critical areas for improvement. In the words of the late Peter Drucker—one of the most widely-known and respected influential thinkers on management—if you can’t measure it, you can’t improve it. In that context, knowing the data you should gather and the key metrics for eCommerce you should measure can definitely help you make better-informed decisions to achieve your business objectives.

In this comprehensive article, we’ll dive into the essential data eCommerce product managers and eCommerce teams should track in order to grow strong and profitable brands.

The eCommerce Metrics You Should Track To Take Your eCommerce Business To The Next Level

In a nutshell, eCommerce metrics can be defined as any measurable, consistent method to assess achieving a given eCommerce website’s goal. However, while there are many eCommerce metrics to monitor, it is unnecessary to monitor the indicators that do not significantly impact the financial performance of your eCommerce business.

For that reason, it’s far more practical to focus on a limited number of eCommerce metrics that have the most significant influence on your eCommerce business and use them as key performance indicators (KPIs).

KPIs stand for key performance indicators, and they should be the primary focus when tracking any kind of progress, even though all metrics are essential for monitoring. The most significant difference between eCommerce metrics and KPIs is that metrics measure and quantify processes, while KPIs assess the effectiveness of those processes in achieving the desired outcomes.

Below, we have compiled a list of the most important metrics that SMB, MM, and enterprise eCommerce teams should consider tracking to improve and optimize their company’s processes. As you review the following metrics, it is vital to keep your business objectives in mind to identify those relevant to your business.

Conversion Rate

Monitoring the sales conversion rate is a critical metric for eCommerce businesses. This rate represents the percentage of website visitors who make a purchase, and it’s important to maximize it as much as possible.

For instance, if 200,000 people visited your online shop this week and only 1,000 made a purchase, your conversion rate would be 0.5%. However, conversion rates vary greatly depending on the industry and product category.

In March 2023, the average conversion rate across eCommerce businesses was 1.75%, a slight increase from March 2022, at 1.66%. Wellness and health products had the highest conversion rate at 4.2%, followed by crafts at 4.07% and household and kitchen appliances at 3%.

For that reason, it would be best to research your industry and target market to determine a good benchmark for your online store’s performance. Nevertheless, some things that you can do in order to grow your eCommerce conversion rate include:

Enhance your product pages load rates;
Use only high-resolution professional photographs and videos of the products you sell;
Optimize your listings by using well-researched keywords;
Set a different conversion rate for every selling platform that you use;
Set conversion rates for every product category because some may have better conversion rates than others;
Set a conversion rate for each promotion, such as when dealing with influencers or affiliates.

All in all, it’s essential to maintain or improve your conversion rate over time. If you notice a significant decrease in traffic, it could point to an issue with your website that needs to be addressed.

At Noibu, we excel at just that! Noibu is a software solution designed to help eCommerce businesses quickly identify and resolve website issues that interfere with the customer experience and find their correlation with conversion rates.

Integrating with all popular eCommerce platforms like Shopify, Magento, BigCommerce, and others, Noibu is equipped to track website errors across different selling platforms in real-time, thus allowing eCommerce enterprises to identify and address issues before they significantly impact their sales and revenue.

This way, by catching all new website errors and maintaining functional and healthy eCommerce websites, Noibu actively helps eCommerce teams stay focused on the future of their business rather than consistently worrying about the state of their website and achieving long-term success.

Average Order Value

It goes without saying that one of the top objectives for any eCommerce shop is to maximize customer spending as much as possible. So, here comes the second eCommerce metric that eCommerce teams should track—the average cost of each purchase in their shop, which represents the average order value.

To estimate your eCommerce store’s AOV, divide the total revenue by the number of orders. Measuring the AOV can provide deeper insights into the customers’ purchasing power and help identify growth opportunities. It will also help establish clear sales goals and identify what changes eCommerce teams should make so that their customers will willingly spend more with every new transaction.

To increase the average order value, eCommerce teams could utilize the following strategies for enhancing their AOV:

Offering supplementary goods and items that enhance or extend the functionality of the item the customers originally intended to buy;
Offer items or services as a bundle or a package so clients get a discount on every item compared to when they purchase them individually;
Offer free shipping on orders over a certain amount to encourage their customers to spend the most possible.

In addition to these strategies, eCommerce must regularly measure their AOV over time and change their business model, pricing, and product quality as needed to improve their marketing effectiveness and drive more revenue. By taking a data-driven approach to their AOV, eCommerce companies can make smart decisions to help their business thrive.

Customer Lifetime Value

The customer lifetime value (CLV) is a significant metric used to calculate the estimated total amount a customer is foreseen to spend on an eCommerce website during their entire relationship with the brand.

For eCommerce businesses, CLV is a crucial factor since it forecasts the future value that each customer will bring to the company. By understanding the CLV, eCommerce teams can make informed decisions about customer acquisition, engagement, and retention strategies.

For instance, if a customer’s CLV is high, investing more in marketing and customer service may be worthwhile to keep them engaged and retained. However, a customer with a low CLV may not justify the same level of investment.

By closely monitoring and optimizing their customers’ CLV, eCommerce teams can enhance their customer relationships and achieve sustainable growth in the long term. In essence, CLV acts as a crystal ball that enables companies to predict the potential value of a customer to their business.

Customer Acquisition Cost

Next in line, among the essential eCommerce metrics that eCommerce teams should track is the so-called customer acquisition cost. By identifying this key metric, eCommerce companies can figure out how much it typically costs to lure in a new customer to their business.

This metric can be calculated using the formula: CAC = total eCommerce marketing and sales costs divided by the number of new clients acquired. For instance, suppose you spend $30,000 on a social media advertising campaign, which results in 4,500 website purchases. In that case, the cost per acquisition for that campaign is $30,000 divided by 4,500, or $6.6.

eCommerce teams should keep a tab on this valuable metric and ensure it remains reasonable within their CLV expectations. For example, if your CLV is at $500 and your AOV is $450, your customer acquisition cost practically outweighs your profits.

In order to lower your customer acquisition costs, there are a few tactics your ought to try:

Boosting your conversion rate means that your CAC is going in the opposite direction;
Cutting down on expenses tied to marketing for client acquisition;
Engaging in organic and long-term marketing techniques like social media and SEO;
Spending more money on referral marketing so that your satisfied clients recommend your eCommerce shop to others for free.

Shopping Cart Abandonment Rate

When a prospective buyer begins a purchase but doesn’t go through with it, the process leads to abandoned shopping carts. And since you’re a seasoned eCommerce professional, you know that some customers select to withhold from purchasing even if your products are in great demand and your conversion rate is exceptionally high.

Nonetheless, while this scenario is unfavorable for any eCommerce business, it’s also to be expected. Therefore, monitoring the rate and why potential clients abandon their shopping carts before making the final purchase is an essential eCommerce metric to track and a vital sign of checkout (in)efficiency.

As of March 2023, the calculated data from 48 studies suggest that the average shopping cart abandonment rate is 69.99%. Put differently, this indicates that seven out of ten customers will click out of the eCommerce website without making a final purchase.

Statistic: Online shopping cart abandonment rate worldwide between 2006 to 2021 | Statista

In that regard, if you feel like your company can do better when it comes to the shopping cart abandonment rate, here are a few strategies you could try to improve your numbers:

You can work with your development team to make it more straightforward for shoppers to finalize their purchases by streamlining the entire shopping cart/checkout experience;
Start using retargeting to persuade wavering clients to come and purchase again from your business. For instance, you can do this by sending out follow-up emails or using tailored advertisements;
You can provide guest checkout so that clients can buy without creating an account.

When it comes to improving your shopping and checkout abandonment rates, Noibu is the perfect eCommerce monitoring solution that identifies technical issues in these crucial parts of the customer journey.

In 2022, the total eCommerce revenue lost due to cart abandonment was projected to be north of $443 billion. 13% of those $443 billion is expected to be caused by website bugs, errors, and shopping cart malfunctions.

Noibu helps eCommerce teams monitor add-to-cart functionalities, diagnose all potential checkout errors, and get notified when an error or a bug arises in this part of the online funnel to prevent lost sales.

To put it in a numbers perspective, Noibu practically services a $53 billion problem globally, which speaks volumes about why SMB, MM, and enterprise eCommerce companies are eager to implement an error detection solution like Noibu.

Email Opt-In Rate

Although social media has become an essential aspect of digital marketing, email marketing remains a crucial tool for eCommerce companies. Email marketing is still handy for encouraging repeat purchases and remarketing products to potential customers.

Like with website traffic, the aim is to experience a rise in the number of email subscribers, even when they don’t make a purchase immediately. While website visitors may be intrigued by your products or services, those who subscribe to your newsletter have a vested interest in your company and its future, which means that they’re more likely to convert into loyal and paying customers soon.

To encourage people to subscribe to your emails, offer them something valuable in return for their email addresses and other personal contact information. For instance, consider offering your new subscribers an exclusive discount on their first or next purchase through a code or voucher.

Additionally, providing a customer-friendly positive email communication experience (such as understanding your brand and being steady in messaging) along with a simple registration process and effective calls to action can increase subscription rates.

It’s crucial to keep the rate of unsubscribes to a minimum. Though unsubscribers are inevitable, you should aim to keep the number to less than 0.5%. If many people are unsubscribing themselves from your email list, it’s time to reevaluate your strategy.

Cost Of Goods Sold (COGS)

Establishing the right price can be tricky, even for experienced online sellers with solid educational backgrounds. However, it’s critical to determine a pricing strategy that generates profits while being competitive enough to foster repeat business from your existing customers.

When evaluating the appropriate price point, it’s crucial to account for several variables that may be concealed, such as product demand, competition, perceived value, and customer expectations. However, the most critical factor to have in mind when determining the price of your goods or services is your cost of goods sold (COGS).

COGS measures the direct costs associated with producing your goods, also known as the “cost of sales.” By calculating your COGS accurately, you can estimate the minimum amount you’ll need to charge to cover your expenses and make a profit. It’s critical to ensure that your price is high enough to cover your costs while being competitive enough to remain attractive to potential customers.

For a clothing manufacturer and retailer, the cost of goods typically includes the expenses for fabric, buttons, thread, labels, equipment, machinery, and personnel directly involved in production and manufacturing.

Accurate COGS data can help you determine your products’ correct pricing and profitability. In essence, you must know how much your company spends on the products you carry to determine the appropriate pricing and how much revenue you generate.

Moreover, knowing the COGS can guide you in promoting the best products based on their profit margins. For instance, a long-sleeved blouse with an 18% profit margin could be an excellent candidate for a small-scale yet scalable email marketing campaign. In comparison, a high-end designer pair of shoes with a 65% margin might benefit more from expensive marketing methods like social media advertising or PPC marketing.

Want to uncover errors impacting your eCommerce revenue potential? Let us show you with a free checkout audit.

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Final Thoughts

In the end, monitoring the key metrics for eCommerce is critical for the success and growth of your online business, and there’s no way around it. These metrics provide insight into customer behavior, marketing efficiency, operational efficiency, and financial performance.

By regularly tracking and analyzing these metrics, eCommerce businesses can make informed decisions to improve their operations, increase customer satisfaction, and drive growth. From measuring your conversion rates and bounce rates to knowing your customer lifetime value and customer acquisition cost, each metric provides a unique perspective on the performance of your eCommerce business.

A comprehensive understanding of these metrics will help you identify areas for improvement, optimize your operations, and achieve your business goals by providing you with a big picture of where your eCommerce operation is and where it should be headed.