Among all the available business growth strategies, e-commerce analytics tops the list.
What is E-commerce Analytics?
E-commerce analytics is the collection and analysis of data from an online store to make business decisions. This analytics tracks metrics such as sales, customer behavior, and website performance, providing insights to improve marketing strategies, enhance customer experience, and increase overall profitability.
Benefits of E-commerce Analytics
E-commerce analytics help focus and manage data. Seva K. Palasubramanian, Dean and Professor of Marketing at the Stuart School of Business at Illinois Institute of Technology, points out that the emergence of multiple data sources to collect and integrate data about customers, products, and markets is a common issue for businesses today.
“Analytics provide useful techniques for dealing with this problem by organizing data to develop metrics that are most useful for continuously monitoring business performance”, says Palasubramanian. “Analytics focus on matters that concern businesses the most, and performance metrics are useful in identifying and resolving issues in real time”.
Types of E-commerce Analytics
There are many analytics indicators you can track, but if you are at the beginning of your journey as an e-commerce entrepreneur, this is the right place to start.
There are five metrics you can objectively track to ensure your store avoids the issues faced in the example above and grows in a timely manner:
Customer Lifetime Value (CLV)
This is the amount you will earn from the average customer during the time they remain your customer. For example, if the average customer returns to your store three times to purchase something, spending an average of $100 each time, and your profit margin is $10 (10%), then the CLV for that customer is $30.
Returning Visitors
This is the percentage of users who return to your site after their first visit. This number clearly indicates that people liked what they saw.
Time on Site
This is the average time users spend on your site during each visit. If people are spending time on your site, it means they are enjoying a good customer experience.
Pages per Visit
This is the average number of pages users navigate on your site in one visit. A high number of pages per visit (around four) indicates that people are interested in what you are selling.
Bounce Rate
This is the percentage of users who visit only one page on your site and leave without taking any action. A high bounce rate (typically above 57%) means that your site does not make a good first impression. High bounce rates can be caused by poor design, unmet expectations, or slow page loading.
Tips for Successful E-commerce Analytics
Here are some challenges you may face when analyzing data in e-commerce:
Data Inconsistency
Aggregating data from different sources can make analysis difficult. Imagine using various channels such as Facebook Ads, Google Ads, and email marketing. Each platform provides data in different formats and standards, making it hard to unify information for comprehensive analysis. Direct all data to one platform and one format for better understanding and utilization of the data.
Data Privacy
Ensuring data privacy and security is crucial. Failing to do so can lead to legal consequences and break trust with customers. Be sure to implement secure data storage and conduct regular compliance checks to ensure ongoing protection.
Data Quality
Poor quality data, such as incorrect, incomplete, or outdated information, can mislead your decisions. Imagine making inventory decisions based on inaccurate sales data. You could either have excess or insufficient inventory, negatively impacting profitability.
Choice
Appropriate Data
Choosing appropriate data means focusing on data points that support a certain conclusion, while ignoring or excluding other relevant data. Imagine you run an online clothing store and analyze sales data to decide which products to promote. You might select certain data that focuses only on a successful week of sales for winter jackets, ignoring the overall decline throughout the season.
Using the Best E-commerce Analytics Tools to Improve Your Store
Most businesses fail not due to a lack of effort or dedication, but because of executing the wrong things. The trick is to understand the important data at each stage of development and use that knowledge to make changes that will actually impact the bottom line.
Use the built-in Shopify reports and analytics to make smarter decisions faster. Choose from over 60 ready-made dashboards and reports, or customize your own dashboard to uncover trends, capitalize on opportunities, and enhance your decision-making process.
Are you ready to start your business? Begin your free trial of Shopify – no credit card required.
Frequently Asked Questions about E-commerce Analytics
What are common types of data in marketing analytics?
Common data in marketing analytics includes customer data, competitive information, market research, transactions, customer feedback, preferences, and interests.
What are the benefits of e-commerce analytics?
E-commerce analytics can solve common business issues, such as reducing revenue models and misleading forecasts. It also helps you understand marketing data, discover trends, utilize customer data, and optimize pricing.
How do marketers use analytics to make decisions?
Big data and business analytics can help you predict consumer behavior, determine the return on investment for your marketing activities, understand marketing attribution, and improve the decision-making process.
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