Make eCommerce analytics work for your online retail business.

Updated: Jan 11

Wouldn’t it be amazing if you could instantly make sense of all the data in your eCommerce site? Imagine millions of rows of data based on user behaviour, ad campaigns, demographics, product affinities, search keywords, marketplace sales and many such sources. But it can get daunting to process all this information manually in the form of charts and tables. It can get harder still to connect all the dots manually and arrive at any conclusions.

The good news is that eCommerce reporting and technology has evolved tremendously. Using heuristic analysis, machine learning and pattern recognition today data can instantly be processed to arrive at insights, which in turn can be used to identify risks and opportunities.

But, did you know that most business owners use just 0.5% of all the big data that they have access to?

When you set up your eCommerce business on a platform like Shoptimize, you have access to eCommerce data analytics in one place. It’s an integrated experience presented in a simple to follow and act upon format. You’ll have reports about customer lifetime value, returning visitors, time on site, pages per visit, bounce rate, custom dashboards and interactive reports, shipping, predictive recommendation tools, and much more.

These reports will let you review your site’s recent activity, learn about your visitor’s online behavior, and analyze your store’s speed and transactions.

You know that a delightful on-site user experience is the key to success. To enable the best experience, you need to know all about your user so that you can offer suitable products, prices, and advertising at the right time via the right platforms. That’s what eCommerce analytics does for your business. Data analysis is not just a business enabler, it’s a product that can hugely benefit your online retail business.

Let’s deep dive into how analytics can help your eCommerce business.

Product recommendations - Think about a shopper looking online for a pair of sunglasses. After browsing through different sites for retro oval shades, the shopper will probably notice ads for sunglasses coming up on her Facebook and Instagram. This happens via targeted campaigns run on ad platforms that suggest products based on what the shopper shows interest in. Recommendations like this can happen within websites, via pop-ups, recommendations on the product detail page, checkout page etc.

You can use a recommendation engine for example, to push your new flavor of coffee if you sell coffee online. Or let’s say you sell jewelry online. You could push your silver bracelets with evil eye stones specifically to buyers who have been searching for silver jewelry, bracelets, evil eye stones, and a combination of all three. Data exists about people’s purchase history, recent activity, online behavior and social media browsing. Using this information, eCommerce data analysis can predict changes of a customer’s buying behavior.

Imagine you are an online seller of stationery. You track trends and feel that a special wrapping paper selection will be the all new hit for the festive season. You want to go with additional advertising on social media to push this product range. If you run your site on an eCommerce platform like Shoptimize, the recommendation based on data will tell you to prioritize ad budget to push tape in a big way. The eCommerce data analysis can also tell you by increasing your daily ad spend by 10%, your revenue will increase by 50%. This could be due to the fact that Covid-19 has driven the packaging industry to new heights and tape is in high demand. You can say goodbye to expensive consulting firms as your integrated eCommerce platform will offer information and reporting as a standard service.

Before buying anything, shoppers switch between sites, search for online promo codes, and check reviews on trusted sites. A human analyst is not capable of tracking an online shopper’s behavior. But new generation data analytics in eCommerce gauge this information with ease. The technology puts together comprehensive user personas which are data rich profiles of different audience segments. Based on the information collected – viewed product, clicks, past purchases – the system can deliver personalized recommendations to your potential client.

Companies that have adopted a predictive intelligence solution have reported a 40.38% influence in revenue after just 36-months post-adoption.

Data rich information, can help you take informed decisions and craft highly targeted campaigns. For example, let’s assume that you are an eCommerce retailer of coffee. Data insights suggests you to run ‘buy 2 get 1 free’ on your website to all the millennial segment visiting your website. Ecommerce analytics allows you to be responsive to market changes. What’s more, the algorithms process all the data in seconds so that you can be more efficient.

Demand forecasting -Let’s go back to the online stationery example. Ecommerce analytics will tell you in August to start planning additional inventory for wrapping paper for the festive season. With this nudge, you can manage your inventory so you don’t run out of the product or have too much later, you can manage cash flow better, can plan marketing, advertising, and promotions in advance, and can offer better customer service.

The COVID-19 lockdown led to sudden spurts in demand of various products – including for one specific consumer durable brand. Data analytics, insights, and recommendations directly impacted the brand’s strategy around production, supply chain, branding, and marketing. But, based on past data they could speed up the production of a specific product line and meet the huge demand.

Marketing analysis Ecommerce analytics boosts your marketing efforts. Data-driven metrics calculate and suggest how much revenue a certain advertising campaign would bring in, which kind of advertising will lead to conversions, what platforms to advertise on, how to get your buyer to click on your ad, how to improve the chances of the customer buying the product, and ideal promotion options – when to push them and to which group of buyers. If your eCommerce business uses a platform like Shoptimize, you can direct action on all of this and more. Consider for a moment that you sell tee shirts for women and children.

Based on data, you might receive a recommendation that may ask you to offer a combo pack of tee shirts in sizes for mum and baby at a special rate to a family with a new baby. The platform will also give you insights about which channel to share the message on – those which have the most active ante-natal, pregnancy, and post-natal content, age group of women, which city has the most number of active users, and what kind of ad to create. Using this information, you can launch various campaigns on suggested platforms to the specific target audience.

Large eCommerce players are actively using data and analytics to influence their business strategies. Partner with platforms like Shoptimize to realize substantial competitive advantages for your business using only the best programs.