A Guide to Increasing Sales with Data Analytics for Ecommerce

Ecommerce analytics is all about answering questions.

As an eCommerce business owner, you most definitely have questions that, when answered accurately, can take your eCommerce business to new heights.

Questions like…

…Which among my products are generating the most sales?

…Which marketing channel is bringing in more organic traffic?

…Is my landing page design optimized for conversion? Which parts do I tweak if it isn’t?

WIth the help of data analytics for eCommerce, you can answer questions and obtain crucial insights about your eCommerce business using hard cold numbers as your basis.

That’s why data analytics is crucial for eCommerce businesses. The insights it gives aren’t biased. They have a strong level of accuracy since they’re based on collected and analyzed data.

To leverage your eCommerce data and put them to good use, continue reading this guide. 

What is eCommerce analytics?

Ecommerce analytics covers strategies that collect, manage, and analyze data to make better decisions for your eCommerce business.

It involves tools that track data and calculate Key Performance Indicators (KPIs) in various areas of eCommerce, like customer behavior, inventory management, sales, website performance, and digital marketing. 

If you want to grow a successful eCommerce business, don't rely on guesswork and trends to dictate your strategy.

Use eCommerce analytics to make data-driven decisions to improve your online store's performance and profitability over time. 

Types of eCommerce analytics

The known "types" of eCommerce analytics may vary slightly between sources, but they usually target the same data and objectives.

Below are the various eCommerce analytics types for specific business goals: 

1. Customer acquisition analytics 

This type of eCommerce analytics focuses on analyzing and optimizing customer acquisition strategies.

It helps you understand where your customers come from and how to make the most out of your customer acquisition channels. 

Customer acquisition reporting tracks the following metrics and KPIs: 

• Customer Acquisition Cost (CAC). CAC measures the average monetary cost of acquiring customers for your eCommerce business. To calculate this, divide the total costs of your marketing and advertising efforts by the number of new customers within a specific timeframe. 
• Demographic data. Understanding customer demographics is useful in developing and optimizing marketing strategies. Some examples of customer demographic data include their age, gender, language, and location. 
• Web traffic. This particular metric tracks the number of online visitors or "traffic" that go to your online store, regardless if they make a purchase or not. This includes traffic from search engines, paid channels, search engines, and referrals from other websites. 
• Conversion rate. Conversion rate measures the likelihood of online visitors converting into customers. It's calculated by dividing the number of conversions (sales, subscriptions, etc.) by the total number of visitors in the same period. 
• Click-Through Rate (CTR). CTR is tracked separately for each customer acquisition channel, like social media, advertising, or Search Engine Results Pages (SERPs). It's measured by dividing the number of clicks by the total impressions or views of your content. 
• Customer Lifetime Value (CLV). CLV measures the total revenue an individual customer generates for your eCommerce business throughout their lifecycle. This includes all recurring payments for membership subscriptions, repeat purchases, after-sales services, and other transactions. 

2. Sales and revenue analytics

Sales and revenue analysis is all about measuring sales performance and identifying growth opportunities. This helps you make more money with every transaction.

Take note that sales and revenue analytics integrate many advanced KPIs, such as:

• Average Order Value (AOV). AOV measures the average amount customers pay for each purchase, including revenue from all single-item and bulk purchases. Calculate AOV by dividing your total revenue by the number of transactions.  
• Average Revenue Per Customer (ARPC). ARPC tracks revenue generated for each customer each month, quarter, or year. This important KPI gauges your effectiveness in generating repeat purchases, achieving higher AOV, and ensuring healthy cash flow. 
• Customer retention rate. This KPI measures the likelihood of customers making repeat purchases, which are essential to long-term eCommerce profitability. Improving customer retention means increasing ARPC, fully utilizing CAC, and growing CLV.  
• Cart abandonment rate. This is the percentage of customers who leave your website during the checkout process before closing the transaction. Tracking cart abandonment rate is crucial in optimizing the checkout experience, which is influenced by factors like payment options, shipping costs, loading speed, and refund policies.

3. Ecommerce marketing analytics 

Ecommerce marketing analytics evaluates the performance of your marketing channels. 

As an eCommerce business, you need to determine which marketing activities actually bring paying customers to your virtual storefront. Otherwise, you could end up losing more money than you make through inefficient marketing campaigns.

Marketing analytics share a handful of KPIs with customer acquisition analytics, like CAC, CTR, and conversion rate.

Below are a few other metrics and KPIs tracked in eCommerce marketing reporting:

• Cost Per Click (CPC). In Pay-Per-Click (PPC) advertising campaigns, CPC is the average amount businesses are willing to pay for ad clicks. The higher the CPC, the more profitable keywords tend to be. 
• Return on Advertising Spend (ROAS). ROAS is a KPI that compares revenue generated with the total cost of advertising within a campaign. To calculate this KPI, divide all revenue attributed to ads by your total ad spend. 
• Search Engine Optimization (SEO) metrics. SEO metrics like keyword rankings, keyword difficulty, and traffic value help measure the long-term profitability of your eCommerce business. Effective eCommerce SEO brings targeted organic traffic with high purchase intent. 
• Email unsubscribe rate. This email marketing metric measures the likelihood of customers to unsubscribe from your newsletter. You need to track this metric to ensure the relevance, quality, and value of your email content. 
• Social media marketing metrics. Metrics like follower count, engagement rate, and social media conversion rate are useful in optimizing your social media marketing strategy over time. Social media platforms like Facebook, Instagram, LinkedIn, and TikTok help eCommerce businesses raise brand awareness and attract prospective customers quickly. 

Try this free social media dashboard template from Polymer.

4. Customer behavior analytics

Behavior analytics is a specific type of eCommerce analytics that prioritizes customer data. 

Unlike customer acquisition analytics, which answers where customers come from, behavior analytics also dives into what customers do on and off your online store. 

To better understand how customer behavior analytics works, take a look at the metrics and KPIs it covers:

• Session duration. This metric tracks the amount of time customers spend on your eCommerce website (different from "time on page," which is another metric that tracks the time spent on a specific page). A high session duration, especially with multiple pages visited, is indicative of high engagement.
• Scroll depth. Another way to track customer engagement is through scroll depth, which measures how deep customers go when viewing a particular page. Tracking and improving scroll depth will help you create better content and write more captivating product pages. 
• Bounce rate. Bounce rate is the percentage of customers who leave your eCommerce website right away without interacting. A high bounce rate could be a symptom of various issues, like poorly written content, bad website design, slow loading speed, and misleading headlines. 
• Returning visitors. Returning to your eCommerce store is a good sign of interest. Tracking these users lets you measure the performance of your website, especially if you look at the pages they visit, how often they come back, and when they eventually make a purchase. 
• Pageviews. Total pageview is a simple metric that can tell a lot about your eCommerce site's performance. It gives you a firm grip on what type of products, topics, and other resources your audience wants to see. 

5. Customer service analytics

Not a single eCommerce business can consistently provide a perfect customer experience. However, only those that track customer service analytics can improve.

This type of eCommerce analytics looks into what happens after the sale, which is critical for building customer loyalty and generating repeat business. 

Below are a few pieces of data covered by customer service reporting: 

• Customer feedback. Testimonials and reviews are examples of qualitative data that shed light on how customers perceive the quality of your service. Not only do they measure a customer's likelihood to make repeat purchases, they're also effective in building buyer confidence and increasing conversion rate when utilized properly. 
• Customer Satisfaction Score (CSAT). Compared to raw customer feedback, CSAT offers a more technical and comprehensive view of the customer experience. It can highlight issues with your product, inefficiencies in your customer service, or problems with your website that discourage customers from returning. 
• Net Promoter Score (NPS). NPS is a customer service KPI that determines the willingness of customers to recommend your brand to their peers. It's usually measured and represented on a scale of 1-10, in which a higher NPS indicates a bigger chance that a customer will make recommendations. 
• Ticket backlog. If your eCommerce business uses a CRM or ticketing system, tracking your ticket backlog helps evaluate the efficiency of your customer service team. This data is supplemented by other KPIs like Average Resolution Time (ART), First Response Time (FRT), and Average Handling Time (AHT) to paint a clearer picture of your customer service quality.   

Each type of eCommerce analytics is pivotal to the success of every online business. 

Collectively, they provide you with a 360-degree view of your performance — be it your website's optimization or your content marketing strategies. 

Leveraging eCommerce analytics also comes with a slew of game-changing benefits, which leads to the next point.

Benefits of eCommerce analytics

Here's a quick rundown of the benefits of eCommerce data analytics:

1. Optimize your marketing and advertising ROI. Using customer acquisition analytics to guide your decision-making helps drive more customers while spending less on marketing and advertising. 
2. Stay ahead of marketing trends. Tracking eCommerce analytics long-term enables you to understand data trends and forecast potential positive or negative outcomes. 
3. Improve the customer experience. You can't improve what you don't track, which is why eCommerce analytics is important if you want customers to be happy with their shopping experience. 
4. Build an authoritative brand. Ecommerce analytics can point to a long list of improvement and growth opportunities that will establish your brand authority.
5. Retain more customers. With eCommerce analytics, identify what your ideal customers look like, which products they love, and how to keep them coming back. 
6. Reduce operational costs. Analytics data can show you how to maximize your budget in other areas outside of marketing and advertising, like inventory management, customer service, and cybersecurity. 
7. Optimize pricing strategy. Ecommerce analytics will help you determine the best price points for your products based on sales performance and customer satisfaction. 
8. Create better products or deals. When combined, qualitative and quantitative analytics data lets you discover ways to improve your products or create better deals to boost eCommerce sales. 

Common challenges for increasing eCommerce sales using data analytics

Although eCommerce analytics provide a myriad of benefits, harnessing and integrating it into your business also has its challenges.

Remember, just like any business tool, eCommerce analytics will only be just as beneficial as your implementation.

You need a strategic approach to take full advantage of every piece of data.  

Below are some of the biggest challenges that prevent businesses from reaping the full benefits of eCommerce analytics: 

• Data collection and integration. Every eCommerce business faces challenges in terms of data collection, like finding quality data sources and refining raw data. Fortunately, these issues can be easily solved by investing in the right data management solution with integrations for seamless data transfers. 
• Data analysis strategies (or lack thereof). Given the right tools, any eCommerce business can start collecting hundreds of rows of raw data. But without effective data analysis tactics, it's impossible to obtain actionable insights that will boost sales performance. 
• Data quality. Issues like incomplete data, inaccurate data, and duplicates affect data quality and can potentially skew your decision-making process. Data quality is often a problem for eCommerce businesses that use several data sources. 
• Privacy and ethical considerations. Compliance with data privacy and security regulations will not only impact customer trust and confidence. In the event of a data breach, your eCommerce business may also face legal consequences that are extremely difficult to recover from. 

Be mindful of the challenges above in order to utilize eCommerce analytics effectively. The good news is, that no challenge in eCommerce analytics is too big if you're equipped with the right strategies. 

10 tips for using data analytics to increase eCommerce sales

Here are 10 eCommerce analytics tips to turn raw data into actionable plans for your business. 

1. Analyze your customers' buying habits

Use customer data to analyze their shopping behavior, create buyer personas, and fine-tune your strategies to maximize online sales.  

Ecommerce platforms like Shopify come with built-in customer behavior reports. These track customer activities on your eCommerce store, like: 

• Initiating checkout
• Adding products to cart
• Completing a transaction

With a little help from third-party platforms, like email marketing tools and form builders, you gain a deeper understanding of the extra steps customers take before making a purchase. This includes downloading resources, waiting for special offers, or reading in-depth guides about your products. 

Using Google Analytics 4 for eCommerce tracking, easily consolidate tracking for all user behavior steps. It lets you track custom and pre-defined events like file downloads, form submissions, scrolls, video plays, and page views. 

Image Source: Analytics.Google.com

Google Analytics 4 also tracks user behavior during the checkout and purchase processes. This highlights problematic conversion steps with a high abandonment rate, letting you assess and fix issues before you lose more sales. 

2. Uncover top-performing products

Use eCommerce analytics to uncover your top-selling products to adjust your promotion efforts accordingly. 

Suppose you spend the same amount on promoting product A and product B.

Despite having the same price tag, product A still results in more conversions and profits than product B. 

Doubling down on your product A promotion budget while reducing allocation for product B could lead to even healthier profit margins. At the same time, you could make adjustments to your promotion strategies for product B.

Your eCommerce platform automatically tracks product sales. A better option, however, is to use a central Business Intelligence (BI) platform like Polymer for eCommerce sales performance analysis and reporting.

Polymer's flexible data visualization options let you view product performance data in multiple ways.

Create line charts, heatmaps, funnels, scorecards, pie charts, and simple column graphs using your eCommerce data with just a few clicks. 

Of course, knowing your best-selling products helps you make informed decisions when expanding your product catalog, restocking inventory levels, and managing your ad budget. You'll also be able to make more accurate revenue projections for your eCommerce business. 

3. Determine which marketing channels work best

Use marketing analytics data to help identify your most profitable acquisition channels and campaigns. 

Marketing analytics data sources include social media insights reports, web traffic analytics tools, and eCommerce platforms themselves. Shopify, for instance, rounds up your top-performing customer acquisition channels in their marketing report. 

Image Source: Shopify.com

If you know how to build an eCommerce dashboard, you can automatically feed your marketing channel data to a central location.

Consolidating your marketing data into Polymer, for example, lets you take advantage of advanced data visualization tools as well as AI-powered recommendations. 

Marketing performance analytics essentially lets you determine what strategies work and which ones don't. By analyzing KPIs like CAC and CLV, check if your marketing campaigns lead to profits or losses. 

Of course, tracking eCommerce marketing analytics also lets you review strategic changes in your campaigns over time.

Launching a new promotion campaign on Instagram, for example, should have a visible impact on your marketing channel numbers during the campaign period.

Here are other marketing channels that deserve your attention:

• Other social networks (Facebook, LinkedIn, X, etc.)
• Email lists
• Paid advertising 
• SMS
• Search Engine Marketing (SEM)
• Online business directories
• Q&A websites
• Online forums 

If a particular strategy works well, use it as a model for future campaigns. Scale up proven tactics to maximize your marketing efforts' impact on your bottom line.  

4. Optimize your content marketing strategy

Done right, content marketing will provide your eCommerce website with recurring, high-quality traffic. This includes strategies like blogging, guest posting, and social media marketing. 

Tracking content analytics ensures you produce and publish pieces that consistently pull in potential customers. 

Start by looking at the performance of existing content on your eCommerce website. Identify the topics and content types that draw in the most online customers. 

Google Analytics 4 unveils more than enough data on content performance. In the "Engagement" report, switch to 'Pages and screens' to view the performance metrics of your top content. 

These metrics include pageviews, average engagement time, and total conversion events.

Image Source: Analytics.Google.com

Analyze the pages that generate the most conversion events relative to pageviews. 

Alternatively, use Polymer and create a custom metric that automatically calculates the conversion rate on each page. 

(Must-read: How to Set Up GA4 Ecommerce Tracking)

5. Improve website usability

Website usability is an important factor in user experience that contributes to your online store's sales.

The bare minimum is to optimize your website's loading speed, which can be tracked using a tool like Google PageSpeed Insights. 

Simply enter your eCommerce website's URL and wait for your performance scores in terms of loading speed, accessibility, cybersecurity, and SEO.

Image Source: PageSpeed.web.dev

Clicking on your scores reveals in-depth details along with optimization opportunities. 

For example, if you click 'Performance,' PageSpeed Insights may provide suggestions like switching to faster image formats, reducing unnecessary JavaScript code, and enabling browser caching. 

Image Source: PageSpeed.web.dev

To improve your website's usability, don't forget to monitor user engagement metrics like bounce rate, scroll depth, and session duration. These numbers are tied to the quality of user experience customers get on your website, which has a direct impact on online sales. 

6. Learn more about your target customers' pain points

Both qualitative and quantitative data will help you learn more about your customers, including the pain points that influence their purchase decisions. 

Identifying their preferred topics and content types is a good start. To learn more, use qualitative data like reviews, support tickets, and user sentiment.

If you use customer service software like Zendesk, consider compiling your support ticket data into Polymer to speed up data analysis.

Use visualizations like pivot tables and scorecards for data like CSAT scores, ticket backlog, and case descriptions. 

To obtain more qualitative data, run polls on social media or automate feedback forms on your website. 

You can also check social media groups, Q&A websites, and forums to observe discussions around your industry. Find out what customers are looking for in your product category and the common issues they encounter with similar products.  

7. Find low-hanging fruit keywords

Ranking your web pages for meaningful keywords can yield meaningful results for your eCommerce business.

You can generate tons of organic traffic, put your pages and products in front of people who are eager to buy, etc.

Instead of targeting highly competitive keywords, consider optimizing your pages that currently rank for keywords within positions 11-20.

These pages are on the cusp of generating organic traffic for your business. Just put a little more effort into optimizing the pages for their existing keywords to gain a boost in ranking.

To uncover the keywords that your pages are ranking for and the ranking position of the pages for the keywords, use a keyword analytics tool like Ahrefs or Semrush.

Analyze your domain to get a list of your organic keywords, which you can filter based on search engine positions. 

On Semrush, set your positions filter to '11-20.' This will reveal low-hanging fruit keywords that deserve your attention.

Image Source: Semrush.com

8. Research profitable keywords for paid traffic

Keyword analytics also helps you monitor the profitability of your PPC campaigns. It helps ensure your PPC keywords have a CPC lower than your average revenue per customer.

PPC analytics also help identify weaknesses in your paid campaigns. 

Suppose your product page has a respectable conversion rate with traffic from other channels, like search engine results and social media.

If your paid traffic isn't generating more sales, you're probably targeting the wrong keywords (e.g. keywords that attract customers with zero purchase intent). 

Here's a tip: if you run ad campaigns through multiple platforms (Facebook Ads, Google Ads, etc.), use Polymer to bring all your PPC data into one dashboard. Create data visualizations and use interactive filters to streamline your eCommerce data analysis. 

Just follow the direct integration steps to automate data imports from advertising platforms. 

(Must-read: Facebook Ads for Ecommerce in 2023)

Without tracking PPC data like keyword intent, CPC, and conversion rate, it's difficult to ascertain whether or not your paid ads increase online sales.  

9. Monitor and improve customer service quality

Analytics data from your CRM or ticketing system helps evaluate your internal customer service operations. 

It allows you to gauge the individual performance of your customer support representatives. By analyzing your top agents, you can develop guidelines and other resources to help low performers improve their productivity. 

You can also use customer service analytics to anticipate your customers' biggest questions and challenges. This is useful in building workflows that improve their overall experience with your eCommerce business.  

10. Split test your product pages

Modern analytics tools like Hotjar let you conduct A/B or multivariate tests to optimize your online store's design. 

Split testing works by running multiple versions of the same page at the same time. By comparing their performance, gradually build towards the best page layout and elements for maximum conversions. 

Apart from split testing, Hotjar also generates heatmaps, scroll maps, and session replays. These tools and Shopify apps let you assess your online store's design from your customers' perspective.

(Must-read: Top 10 Ecommerce Apps for 2023 )

Difference between metrics, KPIs, analytics, and reporting

We used the terms metrics, KPIs, analytics, and reporting — but they're not interchangeable. 

• Metrics. Pieces of data tracked in analytics, like traffic, bounce rate, and CPC. 
• KPIs. Key Performance Indicators pertain to a type of metric used specifically to measure success in business objectives (net profit, year-on-year revenue growth, etc.). 
• Analytics. Analytics is an umbrella term for data analysis activities over specific business areas, like customer behavior analytics, website analytics, and marketing analytics. 
• Reporting. Reporting is the process of compiling analytics data into readable pages. 

In eCommerce analytics, understanding when to use metrics, KPIs, analytics, and reporting is integral to success. You need all four to guarantee your data analysis efforts fulfill your analytics goals and answer vital business questions. 

Important business questions you can answer with analytics 

Speaking of questions, here are a few business questions you absolutely need to answer using data. 

1. What does our ideal customer look like? 
2. Where do high-value leads usually come from?
3. Which digital marketing strategies bring the best results? 
4. How can we maximize the ROI of our marketing and advertising strategies?
5. When do leads become ready to make a purchase decision?
6. How can we improve the shopping experience on our online store?
7. What content types should we publish on our blog?
8. Which social media platforms should we focus on?
9. What unnecessary expenses should we cut from our business processes?
10. Where should we reinvest our revenue? 

Ecommerce analytics best practices

Remember the following eCommerce analytics best practices to unlock the full potential of your data: 

1. Prioritize data quality 

Put some work into data cleansing, deduplication, and standardization to improve data quality. These activities may add to your analytics workload, but they also ensure your data leads to positive decisions instead of the other way around.  

2. Use the right data visualizations

Data visualizations make it easier to turn massive amounts of data into actionable insights. Make sure you use the ideal data visualizations for your data sets.

3. Keep experimenting 

If your eCommerce analytics data is stagnating, it means you're not experimenting enough. Put your data to use by running split tests, implementing design changes to your website, and launching new marketing strategies. 

4. Consolidate your data analysis

Use platforms like Polymer to centralize your data collection, management, and analysis efforts. This will provide you with a single source of truth for your business decision-making while preventing data quality issues and streamlining data reporting. 

Case studies

To wrap up this guide, check out the following case studies for ideas on how to use eCommerce analytics to boost your online business:

• Data-driven PPC analysis and optimization increased online transactions by 72% for eCommerce business (Source)
• Ecommerce business conversion rate increased by 25% while shopping cart abandonment decreased by 20% (Source)
• Ecommerce manufacturer increases checkouts by 421% after using Google Analytics (Source)

Ecommerce analytics FAQs

What is eCommerce analytics?

Ecommerce analytics is the process of analyzing eCommerce data to help online businesses improve their decision-making. Various types of eCommerce analytics are used for specific goals, like behavior analytics, website analytics, marketing analytics, and customer service analytics. 

Why is eCommerce analytics important?

Ecommerce analytics removes the guesswork from business decision-making, allowing businesses to implement new strategies and changes to achieve specific objectives. Without analytics data, eCommerce businesses can only rely on trends, unproven hypotheses, and competitor strategies to shape their growth plans. 

What are the key concepts in eCommerce analytics?

Ecommerce analytics involve several important concepts that pertain to the different types of analytics and their steps. This includes data collection, data analysis, data management, data cleansing, and data reporting. 

How Polymer can increase your eCommerce sales

Polymer is a feature-packed, flexible, easy-to-use, and cost-effective BI platform that can address your eCommerce analytics needs. 

It will equip your eCommerce business with all the data visualization tools you need — be it charts, funnels, scatter plots, scorecards, or interactive data filters.

Polymer also lets you use AI-generated recommendations that instantly turn your eCommerce data into actionable insights. 

Get started today with a free Polymer trial.