What is Ecommerce Analytics?

You may have heard the adage, “Data is the new gold.” But without ecommerce analytics, data is just information that hasn’t been applied. Businesses have been collecting customer behaviour, preference, and engagement data for years. How do they make it make sense — and use data to increase revenue? With the right ecommerce analytics tools and strategies. Here’s everything you need to know about how to turn data into sales.

Ecommerce analytics involves all the tools and processes you use to collect, measure, and analyse your ecommerce business data. The goal of ecommerce analytics? To better understand customer behaviour and make smarter business decisions. Some of the most valuable data and analytics come from customer interactions, sales, campaign performance, common complaint categories, and website traffic. You can think of ecommerce analytics as the backstage crew of a Broadway show. While users only see the performance, these behind-the-scenes experts help you orchestrate a great experience.

If you work in ecommerce, you already know that data is your companion — and there’s no shortage of it. Businesses are swimming in data: In fact, there's a 22% year-on-year (YOY) growth in data creation. If you want to put your data to good use, implementing an ecommerce analytics strategy is more crucial than ever.

These four types of analytics work together to provide a comprehensive understanding of your ecommerce business data:

1. Descriptive analytics: This perspective of your data focuses on the "why." Descriptive analytics helps you gather insights from past performance and trends. It tracks KPIs such as total revenue, conversion rates, seasonal buying patterns, and return on investment (ROI). Based on this data, you can identify potential areas of growth and improvement.
2. Diagnostic analytics: Diagnostic analytics focuses on "why something happened" by digging a little deeper into data. It helps you uncover the root cause behind specific challenges. For instance, your marketing team might use diagnostic analytics to discover why a campaign performed better or worse than expected.
3. Predictive analytics: This is the key to figuring out "what might happen in the future." Predictive analytics uses historical data and market demands to forecast potential outcomes and future trends, which helps you make proactive decisions.
4. Prescriptive analytics: This form of analytics puts "taking action" at the centre by suggesting strategies to optimise outcomes and eliminate roadblocks. For example, your operations team can use this to discover cost-effective delivery routes, inventory management, or shipping methods.

More than half (58%) of companies report making business decisions based on gut feelings — but the most successful companies make data-driven decisions. Ecommerce analytics can help you distinguish between guesswork and truth — and ultimately boost your revenue. Here are its top benefits:

• Understand your customers: Ecommerce analytics help you decode customer interactions, including patterns related to product search, cart abandonment, and conversion trends. This helps your sales, marketing, and commerce teams identify high-potential opportunities and deliver more targeted, personalised engagement strategies.
• Forecast more accurately: What are your fast-moving products? What's your average order value (AOV) for each different sales channel? Which products aren’t selling? By uncovering these insights, you can plan your inventory better and make critical business decisions involving adding new products or discontinuing them.
• Unify multiple teams: You can't achieve ecommerce success while working in silos. A good ecommerce analytics tool will democratize information across sales, customer service, marketing, and operations. Then, all of your teams can make well-informed decisions to drive business growth in their respective departments.
• Measure campaign performance: Whether you run Google Ads or email campaigns, you can get real-time insights and enhance your digital engagement strategy.
• Increase customer service efficiency: Thanks to ecommerce analytics, you can proactively identify and address customer pain points. Analytics tools should help you easily track common customer queries, average resolution times, and Net Promoter Score (NPS) to simplify support processes and win customer loyalty.

Ecommerce analytics helps you scale your business and quickly identify ways to generate more website traffic, increase customer acquisition, and establish stronger relationships with your customers. Here are some key areas where ecommerce analytics can drive revenue growth:

1. Improve customer acquisition

Nearly 90% of users begin their shopping experience with an online search. Ecommerce analytics provide unique insights that can help you optimise digital marketing strategies for search engine optimisation (SEO), and search engine marketing (SEM).

SEO: Ecommerce analytics help you discover what your potential customers are searching for. It involves analysing your search engine results page (SERP) rankings, examining your competitors, and positioning your business to become more appealing to search engines and real people. You should look for analytics tools that offer features like keyword planning, rank tracking, bounce rate monitoring, and conversion tracking.

SEM: While SEO is important, don't put all your eggs in one basket. Paid search engine marketing (SEM) can boost your business immediately, helping you reach customers faster and more strategically than organic methods alone. Tools that measure search volume, cost per click (CPC), average ranking position, click-through rate (CTR), and bounce and conversion rates are a must.

Ecommerce analytics can also provide insights into your website traffic and take the guesswork out of the equation. It helps you figure out how visitors interact with your site, what’s driving sales, which products are popular, and how long they spend on different pages. You can improve your ecommerce storefront based on such analytics.

Pro tip: Make your customers’ journey seamless by including a simple checkout process, visual product presentation, personalised recommendations, and mobile-friendly usability. We also recommend using an analytics tool that enables conversion rate optimisation (CRO), A/B testing, heat mapping, click tracking, and visitor recording.

2. Optimize retention strategies

Customer retention is the true sign of customer satisfaction. While acquisition gives your business legs, retention is the backbone of your brand's sustained success. A significant chunk of your revenue comes from existing clients, so focusing on customer loyalty management, repeat business, and overall customer service is crucial. An ecommerce analytics tool can help you identify the types of offers, experiences, and products that keep customers coming back — and the ones that don’t.

To improve customer relationships, use ecommerce analytics tools to track customer lifetime value (CLV), returning visitors, purchasing behaviour, social shares, subscription renewals, and upgrades. But to truly foster great customer satisfaction, ensure that your commerce tools are connected with other back-end systems. For example, when your commerce platform works in sync with your customer relationship management (CRM) tool, you gain comprehensive tracking capabilities and a better view of all customer activities over time. This helps you improve segmentation, targeted marketing, centralised customer information, and AI-powered analytics to help you make informed decisions and reach a wider audience.

3. Uncover trends and actionable insights from customer feedback

Ecommerce analytics can analyse your customer interactions across channels, conduct sentiment analysis, and determine how your brand is perceived in the market — and what actions you can take to address the feedback. Some analytics tools even use generative AI to uncover trends from reviews that can be used to make decisions about how you market your products. For example, if you’re an apparel company and you sell a shirt that customers say runs too small, you can get ahead of returns by adjusting your product descriptions: “Heads up! Many customers say this blouse runs small. If you’re between sizes, best to size up.”

Artificial intelligence (AI) and ecommerce analytics go hand in hand. Thanks to advances in generative AI, it’s faster and easier than ever to glean actionable insights from all the data you collect. And with AI agents, businesses can now rely on autonomous systems to pursue goals, make decisions, and dynamically adapt to changing conditions without human intervention. AI agents can independently think, process, and act to help you achieve your business goals and augment human work. Using machine learning, reasoning techniques, and your data — agents can make decisions independently, ranging from simple to complex tasks. Here’s how AI agents can help:

• Analyse customer behaviour: Agents can analyse vast amounts of customer data to forecast future purchasing patterns, customer preferences, and the likelihood of churn. All this data can help you enhance your marketing campaigns, pricing and promotions strategies, and product recommendations.
• Automate ecommerce reporting: Automated analytics eliminate error-prone processes and time delays that manual reporting can cause. It provides instant, precise insights to help you make real-time decisions.
• Reduce cart abandonment: Agents can proactively alert you to common issues that lead to abandonment, analyse potential friction areas, and address them automatically with tactics like dynamic pricing and targeted remarketing. Overall, this helps you improve the buying process and increase conversion rates.
• Suggest competitive pricing: Agents work 24x7 to analyse market conditions, competitor pricing, inventory levels, and customer demand to propose pricing strategies that maximise revenue.
• Gather sentiment analysis and feedback: Agents can seamlessly examine customer reviews, support tickets, and social media comments to fetch meaningful insights about product satisfaction, red flags, and emerging trends.
• Prevent fraudulent activities: They’re capable enough to identify suspicious transaction patterns in real-time. It can protect your ecommerce platform from fraudulent activities to safeguard your business and customer information.
• Optimise user experiences: Agents have a hawk-eye vision of your website interactions and can suggest improvements, including design, navigation, the checkout process, etc.
• Forecasting demand: AI agents can predict future product demand based on peak shopping seasons or emerging trends. You can plan your inventory levels, prevent stockouts or overstock situations, hire staff, and work with them to help address ‌demand.

All teams benefit from ecommerce analytics. That’s why it’s best to have analytics tools that are easily accessible to all necessary business users, from merchandisers to marketers and developers. To get the best ROI from your ecommerce analytics, choose a unified tool. For example, Commerce Cloud is an all-in-one, unified ecommerce platform that’s easily integrated with best-in-class systems for marketing, service, sales, and more.