Ecommerce continues to grow globally. By 2020, eMarketer estimates that retail ecommerce will be worth more than $4 trillion. If you’re into ecommerce, you can expect heightened competition as a consequence of global growth. As such, you must leverage all possible sources of competitive advantage especially data and analytics.
Analytics has emerged to be a difference maker in ecommerce. It can track all your customers’ activities to know where your traffic coming from, what products they are browsing, how long they spend on each page, what items they put in or take out of their carts, and how successful are you in closing sales. This allows you to understand your customer behavior.
Guy Greenberg, founder of business intelligence and analytics company CoolaData, believes that understanding buyer behavior is key to increased conversions. He writes, “Advanced behavioral analytics offers businesses this added advantage by collecting, storing, enriching and analyzing raw user data over time.”
By knowing these, you would know which areas you need to improve on in your products and services. However, this is predicated on enabling analytics early on. Here are 7 areas where analytics can help improve your ecommerce efforts.
1 – Tailor a customer experience unique to your market
Providing a superior customer experience is essential to ecommerce. You should minimize customer effort from the moment they land on your page until you wrap up the sale. While there has been plenty of research done to identify “best practices” to consider in crafting user experience, it is still crucial to monitor how customers behave in your own context especially if you operate in a particular vertical or niche market. For example, if you offer more big-ticket or upmarket items, buyers may want to research more on the product compared to cheaper items. Analytics can tell you what content buyers are looking for. This way you can strengthen features such as comprehensive product descriptions, user reviews, and Q&A.
2 – Curb cart abandonment
Cart abandonment remains a major concern for ecommerce. Ecommerce across all industries suffers from an average abandonment rate of 70 percent. The reasons behind are varied from unexpected costs to complicated checkout processes to limited payment methods. Through analytics, it is possible to pinpoint the exact instances when users leave your service. This way, you can improve upon these areas and even conduct interventions in order to win them back.
3 – Improve marketing efforts
You can craft engagement campaigns and loyalty programs based on customer behavior to further improve your business. Analytics can be integrated with automation tools to help manage marketing activities and campaigns. For example, in the case of cart abandonment, automation tools can trigger email reminders or pop up promo codes just as customers leave in order to entice them to push through with the sale.
4 – Manage stocks and pricing better
It’s easy to determine which products are doing well based on sales figures alone. However, this doesn’t paint a complete picture. Analytics can help you delve deeper into your sales data. You can explore if there are products that are popularly browsed or added into carts but don’t get bought. You can then decide on actions such as tweaking your prices. You can even narrow down your catalog and focus on the ones that generate the best profit for you. You can also consider moving upmarket if you notice that you are moving big-ticket items more than low-priced products.
5 – Minimize returns
If you ever shopped for clothes online, you know how difficult it is to get the right size even if there are size charts available. Even Amazon users have to rely on other buyers’ feedback to make sense of a garment’s true size. US fashion retailers report a return rate of between 20 to 40 percent. Faulty sizing is largely responsible for such a high rate. Merchants have to shoulder much of the costs from returns. With the high rate, returns are costing many businesses. To help combat this, personalization platform True Fit uses analytics to provide fit ratings and size recommendations for shoppers. This lessens buyer anxiety and saves merchants on returns.
6 – Enable personalized recommendations
Personalization is a key driver to customer engagement. A major ingredient in Amazon’s secret sauce is its personalized recommendations feature. Recommendations account for 35 percent of its sales. Powering the recommendation engine are algorithms that rely on the analysis of extensive historical customer data. You can definitely explore implementing your own recommendations engine and this requires tracking customer behavior on the onset.
7 – Prepare for cross-border ecommerce
Developments in logistics and payments services have enabled many ecommerce businesses to go global. However, a key challenge for cross-border ecommerce is localization. Culture has a great impact on buyer attitudes and preferences. For example, some regions prefer particular products despite not performing well in your other markets. By using analytics, you will be able to compare user behaviors specific to each market enabling you to customize your strategies and campaigns accordingly.
The essential thing to understand about analytics is that it gives you objective information about your business. In a high risk business environment such as ecommerce, it is important to rely on hard numbers rather than pure intuition. Adopting analytics early on will help you be mindful of all trends that are affecting your business. Using these insights, you can then pivot accordingly. By adopting early, you can also collect longer historical information about your customers and your business. These could prove useful for your business down the line especially when implementing engagement programs and personalization features.