Ecommerce stores and marketing channels produce vast amounts of valuable data that retailers need to analyse and translate into actionable insights. This way, companies can identify the best way to improve their operational and business performance, adjust marketing strategies, and address persistent problems.
Given that ecommerce analytics can be a complex process, retailers can embrace its full potential by relying on ecommerce services. This article covers six major types of ecommerce metrics and how merchants can benefit by tracking them within their ecommerce analytics strategy.
What is ecommerce analytics?
Ecommerce analytics is capturing, measuring, and interpreting data relevant to an online store, helping merchants analyse every stage of the customer journey to better understand their audience, evaluate ecommerce performance, discover areas for improvements, and build future sales strategies.
Six types of ecommerce analytics
Since ecommerce analytics comes from various data sources, ecommerce experts can monitor hundreds of data points. Here are essential metrics to help brands monitor their store’s performance and discover underlying trends.
1. Audience
According to IMRG’s predictions for online retail growth in UK in 2023, 64% of shoppers admit that ecommerce experiences keep them loyal to the brand. Thus, getting to know your web store’s returning customers and new visitors is vital for catering to their needs and ensuring their loyalty.
The critical audience metrics include demographics, describing users’ age, gender, location, language, and income level. Store owners can also determine the audience’s interests, values, product or service preferences, and dislikes. The analytics data also provides details like the browser or device visitors use, operating system, and screen orientation.
With this data, ecommerce merchants can flesh out distinct buyer personas and use micro-segmentation to deliver more personalised ecommerce offerings and create tailored marketing strategies.
2. Acquisition
Ecommerce businesses can benefit from knowing how many people visit their store, how they found it, and the cost of customer acquisition.
Since audiences come from various sources, including social media, email, search engines, and paid marketing channels, businesses can use specific metrics to check what communication channels bring the highest number of visitors.
For example, click-through rate shows how many people clicked on a particular link or ad after seeing it and measures the channels’ effectiveness for reaching a target audience. If a channel has a high CTR, the store owner can invest more money and efforts in it.
Businesses can also calculate a customer acquisition cost that indicates companies’ total investment to acquire one new customer. The metric can be further compared against the average customer spending tracked as customer lifetime value. Using it, the owner can clearly gauge the web store’s profitability and the necessity to optimise customer acquisition expenditures.
3. Behaviour
Statistical data can be used to understand how users behave once they land on the ecommerce website. For example, digital merchants can track bounce rates to evaluate how many people enter a storefront and leave it without interacting with the page or viewing other products. If a store has a high bounce rate, then it’s likely that users are dissatisfied with the store or are not engaged enough to stay.
Other helpful customer behaviour metrics include the number of first-time visitors and repeat buyers, pages per visit, the time spend on the site, and time to first purchase.
Additionally, companies can track what site features are frequently used by returning buyers and position them as you competitive advantage to attract more customers. Finally, store owners can dig deeper and analyse site visitors’ paths to identify what marketing messages and products generate the highest conversions and sales.
On the whole, behavior analytics helps store owners understand how customers interact with the website and discover segments of the customer journey that can be improved.
4. Conversion
In addition to bringing people to their online stores, businesses need to understand how and when visitors convert into customers. Conversion rates help evaluate your ecommerce performance and identify possible issues and overlooked touchpoints along the customer journey.
Also, using the data about average revenue and the number of items bought per transaction, ecommerce stores can better plan discounts and promotion campaigns.
Unfortunately, some website visitors can add products to their shopping carts but leave the store without completing the purchase. Tracking the cart abandonment rate, ecommerce merchants can identify the percentage of people who don’t finalise the checkout and identify the drop off points and then optimise the checkout flow and increase sales.
5. Retention
Retaining existing customers is more cost-effective for ecommerce stores than converting new ones. Businesses can monitor customer retention and returning customer rates to track how many of their customers make a repeat purchase over a specific period.
In addition, the churn rate will show the percentage of customers lost over time, allowing companies to analyze when and why customers leave. For example, according to Qualtrifics’ UK Consumer Trends report, 46% of online shoppers are dissatisfied with their customer service experience. Digging deeper into your customers’ dissatisfactory experiences, you can take measures to timely remedy them and reduce customer churn significantly.
Another important retention metric is customer lifetime value. Indicating the monetary value customers bring as long as they purchase from the brand, CLV helps retailers find the best combination of short-term and long-term marketing strategies to maintain good customer relationships.
6. Website metrics
The way an ecommerce website functions affects its search engine ranking, customer experience, and, in the end, sales. For example, Unbounce’s survey states nearly 70% of consumers say page speed impacts their willingness to buy from an online retailer. Therefore, businesses should closely monitor the loading speed and other website performance aspects.
Key benefits of ecommerce analytics
A better understanding of customers
With accurate customer data on hand, retailers can better know their audience’s expectations, demands, and pain points to offer relevant products.
Uncovering trends
Analytics gives a clear picture of how an ecommerce business is performing now and in the future. By discovering trends and patterns, companies can keep their top products in stock, expand popular product categories, and invest in the channels their consumers use most often.
Price optimisation
Ecommerce merchants can analyse consumers’ behavioural data to understand how the audience reacts to different prices for a particular product and find the optimal price that will yield the highest revenue.
Personalisation
Ecommerce analytics enables retailers to accurately segment customers and craft personalized shopping experiences, boosting engagement and loyalty and increasing sales.
Product portfolio improvement
Digital merchants can not only detect their bestsellers and underperforming products but also uncover the reasons why this happens and optimise their product portfolio accordingly.
Improved inventory management
Customers shop online for convenience and don’t want delays in delivery, so products displayed in your web store should be available in sufficient quantities. Ecommerce analytics help determine the most optimal time to replenish the stock and plan inventory for the future.
More efficient marketing strategy
Analytics helps retailers gauge their current marketing efficiency and provides the foundation for improved data-based decisions, effective campaigns, and a strategy that will bring consistently favourable results.
Wrapping up
Companies that build strong relationships with customers and meet their needs will be best placed to profit in the competitive ecommerce industry. Ecommerce analytics helps to understand customer behaviour, optimise consumer touchpoints for more rewarding experiences, and encourage customers to buy more.
