The eCommerce sector continues to thrive as an increasing number of people use online stores to make purchases. While this is good news for online businesses, it also implies that there is more competition than ever in the sphere of internet shopping.
Online business owners need to be able to understand their existing customers, as well as predict the needs of new ones to stay ahead of the curve and continuously grow sales. That is where eCommerce data analytics come in.
This article contains all you need to know about using data-driven eCommerce analytics to increase sales.
Ecommerce Metrics: the Basics
Many different sources, including search engines, social media platforms, CRM systems, and customer reviews, can be used to gather relevant data on your customer base.
Since the majority of these sources only offer raw data, retail website owners should employ analytics solutions that can gather and organize information on actual key performance indicators (KPIs) and analyze it to deliver actionable insights.
While there are excellent solutions to help you understand the results of your marketing initiatives, if you run an eCommerce business, it is also important to choose an analytics platform that includes data on your customers, products, and inventories.
General Ecommerce Analytics
Most data analytics tools nowadays can gather and analyze data on the following metrics:
- Financial — including gross and net profit margin, cost of goods sold, and operational costs to provide you with a comprehensive view of how your online store is doing. These metrics help online business owners make informed decisions that lower expenses and boost sales.
- Product metrics that deter customers from making a purchase. More specifically, analytics tools help track customer actions about a product’s pricing. For example, if a certain product has a greater cart or checkout abandonment rate, this may indicate that customers find the cost of the item too high.
- Audience-specific metrics offer current information on the percentage of repeat customers, how and where they engage with your store, what kind of devices they use, their common traits, and other pertinent data that help online stores take the first step toward creating better user experiences and products.
We will now delve deeper into more specific types of metrics you may want to keep an eye on when performing eCommerce data analysis.
Knowing who your customers are and what they have in common with others in your customer base is often the first step to doing eCommerce analytics.
Customer-specific data provides in-depth information on the gender, age, income, employment status, and location of your users. These metrics are crucial to monitor because they enable the following:
- Better customer segmentation — categorizing customers into specific groups according to their shared traits and interests helps you deliver highly targeted and personalized messaging to each of these groups.
- Improved ICP — knowing specific information about your customers helps you better define your ideal customer profile by finding connections between increased sales and customers’ characteristics and behaviors.
- Understanding your best-sellers — some of the reasons why certain products sell more successfully than others can also be traced back to the particular needs of your customers.
- Enhancing UX/UI according to the devices visitors commonly use to access your online store (e.g. desktop computers versus smartphones).
- Improving shipping policies and ad strategies based on the location of your audiences.
Engagement metrics help you discover how and where your customers interact with your brand and how successful your digital marketing efforts may or may not be in terms of engagement.
For example, insights such as click-through rates, likes, shares, and comments let eCommerce managers know which digital marketing channels drive the most traffic to their main storefront. This kind of data is also a good segue into understanding how well your content marketing efforts are doing (digital shelf analytics) and which channels lead to the most sales or conversions.
Therefore, knowing which platforms are (not as) effective can help you tweak and improve your digital marketing strategy. This strategy involves either focusing even more on the platforms that garner the most interest (e.g. Facebook and Instagram), or changing up your methods for those that do not seem to be driving that much traffic (e.g. email marketing).
When someone purchases a product from your online store, their customer journey is not over. All of your customers should ideally form a devoted following that promotes your brand to others and makes recurrent purchases from your business.
Tracking customer retention metrics reveals which of your customers choose to stay with your brand for the long run. These metrics are important because they help you understand which marketing techniques and/or channels lead to primarily one-time transactions instead of those that promote retention and brand loyalty.
Knowing your customer retention rate enables a more comprehensive view of the number of customers you have acquired, lost, and retained over time. Another related metric is the customer churn rate which reveals how many people only make one purchase and never return to buy from you again.
Retention metrics also revolve around knowing which of your items get frequently repurchased (i.e. the repeat buy rate). There’s also the product return rate which reveals which of your items often get returned by unsatisfied users.
As long as it is reasonable, you want your customers to continue doing business with you. By analyzing retention data, you can see if you are achieving that key business objective.
When and how do online visitors become paying customers? Conversion analytics will help you answer this question. It is crucial to answer, as you must consider it a key aspect of your marketing plan while it’s still developing.
Conversion metrics tell you how long it typically takes for a user to become a paying customer; whether customers purchase from your online store on their first visit or they need to make multiple stops before finalizing a purchase; and, among other things, how many customers decide not to buy after adding anything to their cart.
Knowing the above details should have an effect on your messaging and help you decide how to engage the best existing and potential users.
Additionally, cart and checkout abandonment rates enable you to provide discount codes and promotions that resonate best with your present customer base, which helps reduce those rates when needed.
Paid Digital Campaign Metrics
Your paid digital marketing metrics are yet another important area to consider in addition to all the previous metrics we have covered. These metrics should be used to calculate your precise return on investment (ROI) for different paid marketing efforts.
For instance, when determining how your latest paid campaign turned out, data analysis could help you answer the following questions:
- How many conversions did your social media ads manage to bring in?
- Have you made more money from subsequent purchases than you spent designing and running the ads?
- How much revenue did your business make from pay-per-click ads?
- How many clicks have you gotten from your email marketing initiatives?
Without these metrics, you are just shooting in the dark without ever knowing which campaign is bringing in more customers (as opposed to those flopped). If you don’t analyze your current paid marketing strategy, you face the very real risk of spending money on marketing initiatives that have no positive impact on your revenue.
Therefore, if you’re going into eCommerce analytics for the first time, it is essential to use a tool that gives you a comprehensive overview of how your paid ads have been doing on all of the above points.
Millions of online retailers are currently competing with each other to increase their consumer bases and revenue. As the value of the eCommerce market rises, so does the competition.
However, without data-driven conclusions, online business owners will find it challenging (not to mention risky) to make sound judgments about their marketing plans.
It all comes down to having a solid grasp of what works and what doesn’t and depending less on gut feelings or subjective input from a small number of customers.
By demonstrating how users interact with your brand and how your ad spend influences the budget and targeting decisions you make, eCommerce analytics tools can help maximize return on advertising spend (ROAS) and offer a layer of predictive information for all your future efforts.
When done correctly, data analytics can help you offer better products, foster customer loyalty, enhance the overall customer experience, and increase your sales revenue.