Increase Your Online Business by Hiring a Data Scientist — Ecommerce Analytics

Jay Burgess
12 min readJul 11, 2022


What exactly is meant by “Ecommerce Analytics”?

Did you know that 58.4% of internet users of working-age buy something online at least once a week? Consumer electronics, fashion, groceries, furniture, toys, food, and drinks are the most common product categories sold via e-commerce. Other prominent categories include fashion, groceries, and furniture.

In 2021, the value of the global e-commerce retail market was estimated to be $4.9 trillion. It is expected to grow at a rate of 13.25% per year and reach $7.4 trillion by the year 2025.

The data presented here demonstrate that the e-commerce business is thriving.

E-commerce businesses, on the other hand, are confronted with a number of difficulties, including but not limited to the following:

  • Streamlining the experience that the client has
  • Loyalty of the customer
  • Leaving items in a shopping cart unattended
  • The rates of conversion
  • Bringing in the ideal kind of purchaser

The question now is, how can online shops get over these obstacles?

The only option that is even somewhat feasible is to collect and evaluate data about customer habits, marketing channels, sales, product lines, and conversions. This information may then be used to drive suitable decision-making. E-commerce businesses may enhance their operational efficiency and build customer loyalty, which will ultimately help them retain more customers if they make the correct judgments consistently over time. When it comes down to it, it’s all about the data!

The data that is collected by e-commerce companies comes from a wide variety of sources. These sources include search engines, social media, inventory and sales systems, shopping carts, and reviews written by customers.

E-commerce managers should make sure they employ e-commerce analytics solutions that assist in evaluating data on key performance indicators (KPIs) for their shop and give actionable insights for decision-making, all in one place since the majority of these sources supply raw data. It is essential to have a deep and broad grasp of your company, which should not be overlooked.

This indicates that you need to have a platform that includes analytics and data across consumers, goods, and inventories, despite the fact that there are best-of-breed solutions available for things such as performance marketing. Imagine if you were only able to monitor which advertisements and campaigns created the most last-click purchases, but you had no clue how much profit those campaigns made, how much LTV they had, or which consumer categories they catered to.

This post will offer you all the information you need to know about how e-commerce analytics may assist you in driving more sales using data.

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Why are Ecommerce Analytics So Important to the Success of Stores?

E-commerce analytics is essential to the performance of a shop since it enables e-commerce administrators to comprehend the following:

  • Their performance at the shop
  • Things that put a damper on sales
  • Customer actions that contribute to the creation and provision of better goods

Be aware of your current level of performance

Tracking financial indicators like your shop’s cost of goods sold (COGS), gross profit margin, and net profit margin, as well as operational expenses, is one of the primary functions of e-commerce analytics, which gives you a comprehensive view of how well your business is doing. These indicators provide managers with the assistance they need to make choices that are suitable, are driven by facts, and help enhance their bottom line.

For instance, the cost of goods sold (COGS) is related to inventory expenses; nevertheless, it is also an important factor in determining your total profitability. When added along with the price of your products, the expenses of shipping, and the costs of acquisition, COGS may help you establish the tone and strategy for achieving the margins you seek.

Example: Your pricing approach could be heavily influenced by the number of times your cost of goods sold is multiplied. If you want your markup to be 5 times what it cost you to acquire the product and transport it, you can figure out what your margins should be by adding those two prices together. Your acquisition expenses are the most variable of these three costs (COGS, shipping, and acquisition), which is why it is essential to measure them at the channel level and find ways to improve them.

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See what deters sales

A recent study conducted by McKinsey found that efficient use of analytics is present in 53% of high-performing sales firms that are also experiencing rapid growth.

E-commerce managers are able to determine the reasons that prevent customers from completing a purchase by using analytics to examine customer behavior. For instance, it assists in monitoring the activities of customers in relation to the cost of a product. The greatest percentage of customer attrition for a given product may be an indication that the product’s price point is greater than what was originally anticipated.

Customers will often add items to their shopping carts, only to leave those carts once they reach the checkout process and discover that extra shipping prices, taxes, and the absence of discount codes are applicable to their purchases. Once these habits have been recognized, the next step for e-commerce managers is to address them, which is not a difficult task.

As a general rule of thumb, the more the amount of transparency that can be provided upfront — from price to delivery — the greater the likelihood that a consumer will convert and be happy with the whole experience.

Create and provide items of a higher quality

If the quality of your items is not up to par with what people anticipate, it won’t matter how effective your marketing, pricing, or other customer-focused strategies are; your shop will have a hard time staying in business. This suggests that the development of items that go above and beyond what customers anticipate should be the top goal for every e-commerce company.

It’s possible that in order for online retailers to effectively grow and provide better items, they’ll need to gather data that helps them better understand the causes for things like the following:

  • Alterations in the behavior of consumers
  • Poor sales numbers of a given product or numerous ones
  • Products with high margins and the highest sales volumes
  • Reviews

Ecommerce reports provide real-time insights on key metrics, including repeat customer rate, least-performing products (reasons for the poor product performance), customer churn, customer retention rate, and cart abandonment rate, which all help online stores take the first step toward developing better products.

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The Most Important Metrics and KPIs to Track for Your Online Store

Ecommerce analytics solutions make use of a wide variety of metrics and key performance indicators (KPIs) in order to monitor the effectiveness of an online business. For improved insights into decision-making, e-commerce managers may need to construct dashboards that include two or more important variables linked to store performance, goods, marketing, and consumers. These dashboards may be used in conjunction with e-commerce analytics tools.

Metrics for measuring performance

With the help of e-commerce analytics, managers of online stores may get a more comprehensive picture of the operation of their businesses. Ecommerce analytics can assist e-commerce managers in determining the causes of low revenues, an increase in the number of refunded orders, and a lower average order value by tracking metrics such as return on investment (ROI), gross profit/revenue, average order value (AOV), and customer lifetime value (CLTV).

AOV stands for “average order value,” which refers to the total dollar amount that a consumer spends on average whenever they make a purchase from a company. For instance, if a business has 1,000 orders in a month and makes a revenue of $30,000, then the average order value (AOV) would be $30.

Earnings from sales of a company’s products or services over the course of a certain accounting period are referred to as revenue. Revenue is also referred to as gross sales. For illustration’s sake, let’s say that a shop-made $10,000 in profit by selling one hundred items at an average price of one hundred dollars each.

Return on investment, sometimes known as ROI, is the ratio of income to investors. The return on investment (ROI) for an online retail business is calculated as the ratio of total revenue to total expenditures. The return on investment (ROI) would be 33.3 percent, for instance, if a retail establishment had total expenditures of $6,000 but generated sales of $8,000.

The metrics of marketing

E-commerce businesses often spend more than one-third of their earnings on marketing and new customer acquisition. Ecommerce businesses should make it a priority to monitor their marketing metrics because doing so enables them to benchmark the performance of their digital marketing channels against key performance indicators (KPIs) such as conversion rate, cost per acquisition, and profitability. Examples of digital marketing channels include search engine optimization (SEO), social media marketing (SMM), pay-per-click advertising (PPC), and email marketing, among others.

Profitability of channels: The profitability of a marketing channel is measured by the total amount of net profit that it has created. Let’s imagine that during one specific month, a shop invested $8,000 in a pay-per-click (PPC) campaign, and that campaign resulted in $14,000 in sales income for the store. In addition, the cost of goods sold was $2,000. In this scenario, the margin of profit for that particular campaign would be forty percent.

LTV, or lifetime value, indicates the value that a consumer brings to a business via a certain channel. Let’s imagine that one channel generates clients who have an average order value of $100 and who make 1.5 purchases each month on average. The lifetime value (LTV) of a client acquired via that specific channel would be $150. LTV by channel is an essential indicator since it takes into account subsequent purchases made by customers, which are otherwise likely to be forgotten in the mix. If you simply look at last-click attribution per channel, you run the risk of cutting off financing to a channel or campaign that generates a large number of repeat consumers despite the fact that the original purchase price may have been relatively modest.

Customer data metrics

It is essential to keep tabs on client data metrics since doing so enables you to do the following:

  • Sort your clients into categories.
  • Identify improved ICP targeting
  • Examine the movement of the average order value (AOV) and the customer acquisition cost (CAC) over a certain amount of time.
  • Determine which of your items are being purchased by your most valued clients.
  • Determine the degree of satisfaction experienced by customers.

When it comes to collecting and analyzing customer data, e-commerce managers could be required to employ key performance indicators (KPIs) including customer lifetime value, customer acquisition cost, customer segmentation, and repeat purchase rate.

The Customer Lifetime Value (CLTV) measures the overall value that a customer brings to a business over the course of their entire association with that business. For instance, the lifetime value of a client who purchases from the company for a period of two years and spends an average of fifty dollars per month amounts to one thousand two hundred dollars.

The amount of money a firm invests in order to attract a new client is referred to as the customer acquisition cost (CAC). The customer acquisition cost (CAC) would be $10 if a shop spent $10,000 over a certain period of time to attract 1,000 new customers.

Metrics for the optimization of conversions

Metrics for conversion optimization are very important to an e-commerce company because they provide e-commerce managers with the information they need to make educated choices that will lead to an increase in conversion rates as well as revenue per visitor. The conversion rate and the rate at which customers leave their shopping carts are the two metrics for conversion optimization that are utilized most often.

The proportion of site visitors that carry out an activity that you want them to on your e-commerce business is known as the conversion rate. The intended action, in the case of e-commerce companies and merchants, would be to make a purchase, therefore the calculation would consist of simply dividing the number of transactions by the number of visits.

The proportion of site visitors who add items to their shopping cart but do not go on to complete the transaction is known as the shopping cart abandonment rate (or simply “abandonment rate”). For instance, the shopping cart abandonment rate would be ninety percent if only 100 completed transactions were recorded out of a total of one thousand shopping carts opened.

Metrics of the user experience

User experience metrics are essential for online organizations since they assist in determining whether or not a company’s website has any problems with usability, findability, accessibility, or consistency. A better user experience may lead to more consumer engagement, which in turn can lead to greater conversion rates. Bounce rate and page load time are two key performance indicators (KPIs) that are related to the user experience.

The proportion of users that leave a website without clicking through to any other pages is referred to as the “bounce rate.” For instance, a website’s bounce rate would be equivalent to forty percent if two hundred out of five hundred visitors on a given day navigated away from the website without seeing the second page.

The time it takes for a web page to load is the standard length of time required for it to become visible on a computer monitor. There is a correlation between a faster page load time and increased visitor engagement and conversions on e-commerce websites. Under two seconds is the optimum amount of time for an online store’s page to load, according to Google.

Best Practices for Data Analysis in Online Shopping

In order to direct their companies in the direction of the intended outcomes, e-commerce managers may need to adhere to a few best practices for e-commerce analytics.

Employ the proper analytics tool for online shopping.

An excellent e-commerce analytics tool is unrivaled in its effectiveness. E-commerce managers will have to put in a lot of work to build their own indigenous system for reporting if they do not have access to an analytics platform that delivers industry-standard measurements and KPIs out of the box. If you are going to pay for a solution, you should make sure that you choose a tool that links and visualizes data on customers, goods, inventories, and promotions using prebuilt KPIs for improved e-commerce reporting. This will allow you to better understand how your business is doing.

Put all of your data in one location

All of an online retailer’s data should be centralized for a variety of reasons, including the improvement of data quality and accuracy, the unification of reporting, the acquisition of key decision-making insights, and the reduction of redundancy.

It takes more time and effort to manage, combine, and analyze data that is dispersed and incompatible with one another. Being able to divert those resources and efforts into generating value-added change is worth more than its weight in gold, considering that we’ve never seen a developing firm that had an abundance of accessible bandwidth. Because of this, many online retailers utilize a single backend source to combine all of their e-commerce data. This allows them to have a better understanding of their marketing efforts, goods, and consumers, which in turn enables them to make choices that are driven by data.

Keep experimenting with different techniques for your marketing

There is no such thing as a flawless marketing plan, and not all marketing approaches are going to be successful for your company. Because the target audience for each e-commerce business is distinct, marketing teams have to personalize their promotional techniques in order to obtain more desirable outcomes. There is no other way to increase the effectiveness of marketing campaigns than to conduct ongoing testing of various marketing strategies.

In order to test different marketing tactics, the following procedures may be helpful:

  • Establish advertising goals and key performance indicators (KPIs), or depend on measures that are customary in your business, such as lifetime value (LTV), conversion rates, cost per acquisition, and profit margin.
  • With the assistance of an e-commerce analytics tool, put in place a procedure to monitor how effective each marketing channel is doing its job.
  • Continue to iterate on your business plan (such as changing the content and copy of ads, dropping marketing channels that are not working, etc)

The process must be repeated. Allow the effectiveness of your marketing activities to be evaluated by the e-commerce analytics platform you choose.

Utilizing a Data Scientist can help you improve the analytics of your online store

An e-commerce company cannot function properly without its data. E-commerce administrators need to collect data on their customers, goods, inventories, and marketing activities in order to make educated choices that will ultimately increase sales.

For online companies that want to keep a close check on how their store is functioning and identify the variables that are driving sales or discouraging customers from making purchases, investing in an e-commerce analytics tool is a crucial choice to make.

Analytics for e-commerce help keep track of how well an online store is doing by using data from key performance indicators (KPIs) such as average order value, revenue, cost of goods sold, the profitability of the channel, conversion rate, customer lifetime value, customer acquisition cost, shopping cart abandonment rate, bounce rate, and many more.



Jay Burgess

I use data and innovation to help people and companies make better decisions. I also like writing about leadership. #BusinessIntelligence #datascience #ai

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