Over the last five years or so, e-commerce has grown hugely around the world, as consumers take advantage of great online pricing, the convenience of shopping from anywhere at any time of the day or night, and the ability to discover a whole raft of products that otherwise would be beyond reach.
However, although it has been getting continually cheaper and easier for entrepreneurs to create an online store with the advance of technology and growth in the market, the influx of new e-commerce stores also means that there is more competition than ever.
If you want to wow customers, grow your business, and blow your competitors away, then it’s important to be aware of all the best ways you can build an online store that thrives. One of the best things to do in this field is to make use of big data. Read on for some prime ways that the growth in data science, and the subsequent ease of access to information, can help you to grow your business today.
One of the best uses of big data for e-commerce businesses is personalization. By analyzing a wide variety of data about your customers and their shopping habits, you can provide a more individual browsing and buying experience that will help to convert more sales. Take a look at the different ways that consumers shop with you (for example, through different touchpoints and for different reasons and occasions), and you can find out how to offer these people content, promotions, products, and processes which suit them.
A prime example of personalization for online stores is the ability to reward loyal customers. Once people have purchased from you a few times, you can see what types of products they buy, at what prices, at what time of day they shop, where they have goods delivered, and more. You can then use this information to reward shoppers with ideal promotions plus product information and suggestions.
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A great way to use personalization effectively online is via the “Customers who bought this item also bought...” recommendation feature. Initially seen on Amazon years ago, but then made more readily available to other e-commerce entrepreneurs because of open-source software and cheaper digital shopping cart software, this function enables you to automatically recommend products to customers that they may like, based on their browsing or buying history. This can increase the average dollar order of each transaction quite dramatically because it keeps shoppers on your site for longer and helps them find more products.
Many companies selling clothing and accessories online are also starting to use personalization to make finding the perfect fit much quicker and easier for customers. For instance, shops can get customers to input details about their height, weight and other body measurements (or potentially take this from items of clothing purchased in the past) and then use this data to generate a standard measurement for each customer that will ensure a perfect fit every time.
Due to the fact that this removes extra effort for customers, and ensures that they receive tailor-made items in the future, e-commerce stores can see a significant rise in sales over time, as well as increased loyalty from shoppers to boot.
Reducing Shopping Cart Abandonment
Another incredibly beneficial use of big data for online stores is the ability to reduce shopping cart abandonment rates and boost conversions. One of the biggest pain points for e-commerce businesses worldwide is, after all, shopping cart abandonment (where people place items in the shopping cart but do not complete the transaction) and it affects sales revenue significantly.
Why They Abandon
Consumers abandon their online shopping carts for a number of reasons, including:
How to Fix It
If you want to reduce your shopping cart abandonment rate and enjoy a much higher conversion rate, you can take advantage of big data. For starters, analyze where in the checkout people get to before they abandon the cart, to see if there is one or more particular issues that might be turning people off.
Once you remedy this you should see a rise in completed transactions as a result. You can also use the information to provide offers to shoppers which will incentivize them to complete their transactions, such as free or faster shipping, or a discount.
Cross-device tracking (that is, tracking the course of a consumer’s buying journey across multiple devices) is available due to big data too. Also known as re-targeting, this tracking means that businesses can repeatedly deliver relevant content and advertising messages to shoppers as they browse online.
As many consumers conduct research on up to three or even five different devices before finalizing a transaction, this repeated contact during a customer’s transition between devices helps to boost conversion rates and decrease shopping cart abandonment rates.