Ecommerce Customer Analytics: Your Guide to Smart Decision-making in 2024

Ecommerce Customer Analytics: Your Guide to Smart Decision-making in 2024

Elena Doynova

Feb 14, 2024 • 9 min read

Ecommerce Customer Analytics: Your Guide to Smart Decision-making in 2024

‘Build it and they will come’ is a good starting point for an ecommerce store strategy if you have no clue about the fierce competition in the industry. We bet you do have a clue and this is why you’re here – to learn how ecommerce customer analytics can help you cut through the noise (and have a fighting chance). This article will not only give you a working knowledge of the topic but will also equip you with valuable skills on how to use analytics data to assist you in making smart decisions about strategy and execution in your daily e-comm life.

What is Ecommerce analytics?

Ecommerce analytics is the process of collecting and analyzing customer data from various sources, such as website traffic and interactions, mobile app usage, purchase histories, surveys, social media interactions, and more. This data is used to discover insights into customer behavior, preferences, and needs. The analysis involves interpreting data points, like daily pageviews, click-through rates on featured offers, site searches, and checkout conversion rates, to understand customer interactions, segment-specific trends and customer experience in general.

The goal is to enhance digital marketing initiatives and overall site performance by acting on the insights extracted from the dynamic metrics. Analyzing ecommerce data helps online retailers optimize their strategies based on predefined key performance indicators (on which we will dwell later on).

6 Benefits of Ecommerce Analytics

Smart choices lead to big rewards, right? This is why smart e-commerce managers are data-driven – using as many data points and actionable insights to inform their business decisions. Let’s take a look at what benefits this brings to the org…

Benefits from e-commerce analytics: track customer data

Understanding Customer Data

Traditional data analytics tools such as Google Analytics give you tons of dashboards to monitor: website traffic, marketing analytics, data about ecommerce sales performance, and many more. It’s simply impossible to follow this incessant stream in a meaningful way. This is why an ecommerce analytics tool should be designed to provide only valuable insights and help you truly understand what all the numbers mean.

Assessing Marketing Performance

Ever wondered which channels bring you the most revenue? Which ones bring you the most engaged customers who just need a little incentive to convert? Or what channels are currently not part of your marketing mix but have the potential to bring you $$$? Ecommerce data analysis can answer these questions and give you a clear overview of the ROI of your marketing campaigns. Ending an experiment or increasing a campaign’s budget are not events that should rely on a certain alignment of the stars!

Finding Patterns in Customer Behavior

Each visitor who enters your online store weaves a story – a specific customer journey that bears their signature. Multiply this by the thousands of sessions you expect to get, and you have a whole narrative – enough data to predict what other customers would want and expect to receive. Customer behavior analytics gives you the perfect foundation to build journeys aimed at high engagement, customer retention, and conversion.

Improving the Customer Experience

Our favorite part, customer experience optimization. Even if you think your online store is the prettiest, chances are there are lots of user experience (UX) and user interface (UI) elements that can be improved. How do we know that? Because that’s what we specialize in – finding the web pages with sub-standard conversion rates and telling you what’s the reason behind the low CR.

Segmenting Your Customers

Analyzing customer segments may reveal a landscape that’s entirely different from the overall performance of your online store. And that’s normal – we already touched upon the fact that different people shop in different ways. You can leverage ecommerce analytics data to devise a strategy that helps each segment interact more intuitively and smoothly with your store to drive sales.

Customer segmentation can also be used for better-targeted marketing strategies and campaigns and for finding new marketing channels (something all ecommerce businesses love doing, non?).

Optimizing Your Conversion Rate

We left the best for last. The cherry on top of this list of benefits is conversion rate optimization (CRO) – the proactive search and removal of conversion blockers throughout the customer journey. This unassuming benefit is actually the most important one for your bottom line. Knowing what conversion blockers are present in your online store is the only way to know what to focus your attention on. And analytics is the key to finding them!

Types of Ecommerce Analytics

How do you know what types of analytics you need to inform your ecommerce business decisions? We’ve broken down the main categories for you.

Ecommerce analytics types

Customer Acquisition Analytics

Customer acquisition analytics in e-commerce is the strategic analysis of data that helps you to understand and optimize how you gain new customers. Metrics such as Cost per Acquisition (CPA), Customer Lifetime Value (CLV), and Conversion Rate play pivotal roles in showcasing if your ecommerce business is about to sink or swim.

These metrics are insightful when measuring the efficiency of marketing efforts and the overall effectiveness of the sales funnel.

Customer Behavior Analytics

This analytical approach involves using quantitative data such as click-through rates and bounce rates, and qualitative data such as session replays, heatmaps, customer feedback surveys and net promoter score (NPS) software to break down customer behaviors. The results are important because they illuminate all the complex ways in which customers interact with your website. You can use the insights to devise strategies to improve the user journey and make shopping a smoother experience your visitors would enjoy more. This type of data is often used in predictive analytics as well.

Conversion Analytics

Conversion analytics can help you measure the efficiency not only of the online store in its entirety but also of various elements – such as product pages and checkout flows. Monitoring different types of conversion rates and devising experiments to improve them is at the heart of conversion rate optimization. You will need to make a distinction between conversion rates in your marketing analytics and your website analytics tools – one refers to how well your campaigns convert to traffic to your web pages and the other refers to how good your customer journey is in converting that traffic. This is ultimately reflected in your sales data and sales performance!

Key Metrics to Track With Ecommerce Data Analytics

We already mentioned a few of the key metrics ecommerce businesses need to track all along – let’s expand on them and add a few more so that your KPI toolkit is more well-rounded!

  • Customer Acquisition Cost: Customer Acquisition Cost is the total expense incurred to acquire a new customer, encompassing marketing, advertising, and sales costs. CAC helps you evaluate the efficiency of your customer acquisition strategies and monitoring it closely ensures that the cost of acquiring customers is justified by their long-term value.
  • Average Order Value (AOV): Average Order Value is the average amount of money customers spend in a single transaction. It helps you measure and optimize your marketing and sales strategies, and increase overall revenue by encouraging higher spending per customer.
  • Customer Lifetime Value (CLV): Customer Lifetime Value is the predicted total revenue an ecommerce business expects to earn from a customer throughout their entire relationship. It is important because it helps you see the long-term value of your customers, make informed decisions on resource allocation, and tailor your approach to maximize overall profitability.
  • Conversion Rate (CR): Conversion Rate is the percentage of website visitors or users who take a desired action, such as initiating checkout or making a purchase. A key metric for evaluating whether your e-store is delivering the right experience to the right people, it is often used to fuel optimization efforts.
Conversion rate optimization CRO formula

How to Use Ecommerce Analytics Tools

As with every other data analytics process, e-commerce analytics tools need constant monitoring. But how do you know you’ve set up your process right? Here’s a quick checklist to help you get started:

1. Set goals that you can actually stick to

The first step before you get to analyze data is to articulate clear overarching business goals – these might be boosting sales or enhancing customer retention, for example. We love the SMART (Specific, Measurable, Achievable, Relevant, Time-bound) framework for this step, but you can adopt any framework you find works best for you and your team. Everything you do needs to be guided by these goals – from CRO tests to new feature introduction.

2. Define Key Performance Indicators (KPIs)

Identify the specific KPIs directly linked to these goals (the list above may be helpful) and establish measurable objectives, like increasing conversion rates by a specific percentage or reducing customer acquisition costs. These KPIs can serve as a roadmap for the whole team to stay laser-focused on what winning looks like.

3. Set the tone with the right benchmarks

If you approach using analytics tools as we do (everything is an experiment!), you need to establish benchmarks for each step of the customer journey. We know that this can be difficult, especially if you’re just starting and don’t have enough data. So the earlier you begin to collect customer data, the better. If no data is available – simply go with industry benchmarks and adjust once you’ve gathered a meaningful amount of data to support your monitoring and optimization efforts.

4. Analyze the data

Data analytics and number-crunching are the toughest part. Knowing how to use data to take your e-store from good to brilliant is not an easy task as there will be so many numbers and charts to look at. A tip from us: always view the data in context, considering factors like marketing campaigns, search engine optimization, or website changes. Look for patterns, anomalies, or correlations that provide insights you can act on.

5. Strategy time

Now that you’ve had your Aha! moment following an intense analytics session, you need to act. How does the data you just digested relate to your operations? What improvements can you make now that you have a new golden piece of information about your customers? Do you need to adjust your marketing campaigns to better accommodate underserved channels with great potential? Or do you need to fix your checkout form to ensure a smoother customer experience?

6. Implementation: Better UX = Happy customers

Speaking of experience, customer satisfaction should always be a top priority – not only because happy and satisfied customers will come back for more, but they will also recommend your e-comm haven to their friends. This is how data-driven decisions lead to customer loyalty!

UX is not a fancy abbreviation, it’s what will make your website stand out amidst a sea of mediocrity. An intuitive navigation, a well-developed product page, a quick and easy-to-fill-out checkout flow ensure that your high-intent visitors don’t leave before they finish their purchase due to UX frustrations. Removing conversion blockers is an ongoing challenge you will get better at with time!

Try your hand at data analysis with our Advanced Funnel Analysis Guide 👉 

Challenges With Ecommerce Analytics Tools

As with every other technology, these tools have their challenges. While not showstoppers, the following have to be taken into consideration…

Data can be inconsistent

Data accuracy is a challenge with all types of analytics tools – the notorious “no single source of truth” dilemma. Is your marketing data and advertising in-platform analytics tool going crazy or is the attribution modelling done by Google Analytics wrong? While we still don’t have a viable way to solve such conundrums, providers like SessionStack ensure e-commerce analytics data is being handled with more accuracy than ever.

Privacy and security are a high-stakes risk

Analysing ecommerce data is a great way to improve efficiency but what happens if your data storage is not secure? In an age when cyber threats are becoming more common, securing your infrastructure is an important part of managing a database securely. Your customers have entrusted you with their personal and payment details, make sure it is protected.

And don’t forget to protect yourself from fraud, as oftentimes the unsuspecting victim of a data breach is… the business itself.

Data quality can make or break your analysis

Corrupt data is worse than no data – this is a hill we’re ready to die on. What can you do? Ensure data accuracy through rigorous validation at entry, establish standardized formats to reduce errors, and conduct regular cleaning to fix inaccuracies and maintain data integrity. Having a responsible person at your company to deal with data is a great way to ensure someone is taking care of the process.

How SessionStackAI Helps You Find Answers


You might be thinking that sticking with Google Analytics forever is the smartest choice – all of these challenges and the complexity of introducing new ecommerce analytics tools can be overwhelming. Think again, as we explain what SessionStackAI is and how it can help you stay on top of your data!

SessionStackAI is an industry-first platform for ecommerce businesses that combines powerful session recording, machine learning and generative AI to help online retailers extract valuable insights from their data. The process is automated so you no longer need to waste time and resources watching session replays or staring at dashboards to spot (un)expected customer behaviors or frustrations that lead to drop-offs. With a weekly delivery of insights, you have a clear path to hitting your conversion rate optimization goals and increasing revenue.

SessionStackAI integrates with all major ecommerce platforms to collect data, crunch the numbers, dig out the insights and serve you hot new insights to boost the UX experience for a higher conversion rate and customer retention rate. This is a qualitatively new way to inform business decisions and take meaningful action against stagnating CR.

Ready to take some data-driven decisions?

Learn more about SessionStackAI 👉

Frequently Asked Questions:

What is the role of ecommerce analytics in creating business value?

E-commerce analytics drives business value by providing actionable insights into customer behavior, illuminating unexpected roadblocks, and enhancing marketing strategies. It enables informed decision-making, personalized customer experiences, and agile responses to market trends, thus contributing to increased online sales, customer satisfaction, fostering customer loyalty, and overall growth.

How are customer insights tracked in ecommerce?

Customer insights in e-commerce analytics are tracked through analytics tools that monitor purchase histories, website interactions, and engagement metrics. Techniques might include tracking user behavior with various analytics tools, using customer surveys, and analyzing data from various touchpoints such as social media.

What is the ecommerce customer lifecycle?

The e-commerce customer lifecycle encompasses stages from awareness to loyalty. It begins with customer acquisition through marketing efforts (marketing data), followed by conversion (conversion data), post-purchase engagement and retention (surveys, NPS scores, etc). Analyzing this lifecycle helps devise personalized marketing strategies, enhance customer experiences and foster long-term relationships for sustainable online sales growth of an ecommerce business.

See what SessionStackAI can do for your business