Behavioral Data on Ecommerce

ecommerce behavioural data

Consumer behavior analysis has been a powerful analytical tool in recent years for understanding how online shoppers interact with eCommerce websites.

Analyzing digital behavior is a common topic in eCommerce analytics. This is due to the availability of free, low-cost, powerful, and easy-to-use tools like Google Analytics. Ecommerce behavior refers to the digital interactions that a person has with the site. A clickstream is an example of digital behavior. It is a sequence of clicks or groups of clicks that occur on an e-commerce interface.

Each stakeholder in a business will need to have different information about customer and user behavior when analyzing e-commerce behavior. Marketing will need to understand channel behavior. The product team will need to understand browsing, shopping, checking out, and other behaviors.

The CRM team will need to know how loyalty and retention are perceived. The merchandising department will need to know how customers behave around brands, products, bundles, and promotions.

While each stakeholder may have different goals, the behaviors you analyze will all be described with the same concepts: clicks and events, screen views, page views, duration, and financial measures. Rates and ratios are also important.

A consistent framework is essential for behavioral analytics in e-commerce. This framework will help you to begin analyzing behavioral data.

Segment, Cohort, Cluster analysis

Although each behavior may be unique, the analyses assign a grouping that can be used to identify and associate a behavior. A segment could be either a returning or a new visitor. A cohort could include people who have purchased within the last 12 weeks.

This grouping relies on the assignment of behavior to an identifiable customer (or proxy such as a cookie or ID). Behaviors can also be associated with products and transactions so the behavior assigned to the segment or cluster does not have to be tied to people.

Acquisition Channel

It is the channel through which the customer was acquired, as determined by the attribution model. These marketing channels are organic search, paid searches, direct/unknown, and social media.


It measures the number of sessions visited by customers on the website. It measures the existence of virtual interactions, clicks and actions, events, goals, and other activities on a temporal scale. Recency, frequency, as well as time-based measures of behavior, are possible.


These are interactions between prospects and customers that occur within your e-commerce environment within a certain time. A session is when a user views pages, engages in behavior over time, accomplishes events and goals, and generates e-commerce sales.

Screens or Pages

These are unique renderings of user experience within an e-commerce environment. Screen views and page views measure the time that content loads fully on your screen, such as a product page.


These are interactions between users on pages and screens, independent of the screen view or page. A user takes an action within an e-commerce site and completes it. A visitor clicks on a link button touches a screen or taps a browser to create an event. You should track important events in e-commerce such as “add to cart”, “start checkout,” or “completed checkout.”


These are financial transactions between buyers and sellers that result in the exchange of something of value for another. The purchase refers to the transaction in which marketed products are purchased.


These are predefined interactions that result in a specific outcome. For example, the goal is to sell an item or register a new member or engage in other meaningful and measurable behaviors, such as an advertisement click.


These are the results of the actions, transactions, goals, or events that take place during an e-commerce transaction. The most common outcomes that are measured by behavior are financial in nature. These include revenue per visitor, revenue per customer, other revenue per measure, average order value, and cost per customer.

Key Performance Indiators (KPIs), for Behavioral Analysis

KPIs are used to measure behavioral analysis. They also include metrics that relate to sessions, pages, and segments. A metric is just a number. A KPI, on the other hand, is a meaningful metric that helps you reach your business goals. These are common ways that behavior can be measured and expressed in quantitative terms.

Average Session Length

It measures the time between the visitor’s first page and the last page. Most tools do not measure the duration of the last page. The duration of a page may not be measured if it is only one page.


A visitor who visits the site daily has a daily frequency. Frequency can also be used to measure other e-commerce goals such as adding products to your shopping cart and leaving feedback. Understanding frequency allows you to assess whether it is meeting your expectations and then take corrective actions to improve it.


If a visitor has not visited the site for 90 days, their recency is 90. Although frequency and recency are closely related, they are different. When you look at an example of behavior, recency will tell you if you are reaching the desired frequency. Recency should decrease, so you can take action to bring the person back.

Number of Events

It is possible to buy before you purchase. It is possible to track days, events, and marketing touches as well as e-mail openings or other important behavioral events. Again, the goal is to take action to move the metric in the desired direction.

Time to Buy after Purchase

This measures how long it takes for a customer to make a purchase after engaging with a marketing channel. This is related to attribution and allows you to identify which marketing channels are closest to purchase.

Session to be Purchased after Acquisition

It measures how many sessions it takes for a customer to make a purchase after he has been acquired through a marketing channel.

Conversion Rate

The percentage of visits that make a purchase by channel, brand, or product needs to be measured. It is important to define conversion. It is more common to measure conversion using the number of orders per session than by measuring it by visitor.

Every visit to a website is an opportunity for conversion. Customers might also purchase more than one product within a given time period. The conversion rate per session is the most conservative measure. Segmenting conversion rate by brand, channel, or category will help you identify areas that need improvement.

Average Site Search Before Transaction

This metric measures the number of internal searches that were performed before the transaction. This metric allows you to understand how your internal search performs and helps drive purchase. This metric allows you to separate customers who have searched from those who haven’t, and to compare their behavior.

Rate of Abandonment

It calculates the percentage of products that are not bought from a shopping cart. It is possible to combine all abandoned products into measures that determine abandonment rates by channel and category.

Checkout Abandonment Rate

This simply measures the percentage of shopping carts not completed. If a shopping cart contains products that haven’t been bought but others are, you can calculate the percentage of abandoned products compared to the total products that were purchased.

The Percentage of Customers Who Repurchase

By category, by brand, and by-product, the percentage of customers who return to buy again is measured by repurchase.


An analysis of the relationship between clicks and events, goals, transactions, provides an explanation for why one click or event or transaction is more likely to happen when another occurs. Correlations don’t necessarily mean that one variable caused another, but they can indicate an association or dependence.

Benefits of Customer Behavior Analytics

Online consumer behavior data is very important for making e-commerce marketing strategies. It is best to hire a dedicated team to do this job regularly. You can also have your sales team do this once per month. The analysis of consumer behavior data can have a number of benefits that could influence your growth rate. These benefits include:

Understand Customer Behaviour

Businesses can gain a unique perspective by analyzing customer behavior to improve their online store. Business owners and developers often have no idea how customers interact with their sites.

Although they see a clear path that is the shortest and most accessible, customers might find other ways to navigate. A customer behavior analysis gives you a true picture of your customers’ perceptions and highlights hidden patterns.

Better Product Management

Ecommerce analytics can also help your business gain insights into the performance of products. This provides insight into product sales over a period of time, product list views, and product list clicks. These insights can be used to help with inventory management and cross-selling and up-selling.

Better Customer Experience

It is important to understand that customers have different thoughts and behaviors than what you had envisioned. This can impact the way your organization approaches website SEO and development. There may be technical problems, design errors, or functionality issues that business owners don’t notice.

Customers may abandon their carts after completing a purchase through an inconvenient check-out process. A clumsy search feature may also prevent them from purchasing the product they need. These little issues can make a big difference in conversions, and result in revenue losses.

Measurement Marketing Campaign

Ecommerce analytics can help you improve your marketing. This tracking allows you to monitor both your internal and external marketing efforts. You can track metrics such as internal promotion views and promotion clicks. Additionally, you can monitor the performance of your order coupon regarding revenue.

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