4 Powerful Applications of Data Analytics in E-commerce

4 Powerful Applications of Data Analytics in E-commerce

Imagine if you could read the minds of your customer to predict what products they wanted and at which price point to maximise your sales.

What if every cent you spent on a marketing campaign yielded results because you can predict the future and know undoubtedly that your strategy is effective?

In a nutshell, that’s what data analytics in e-commerce can do for your business. (P.S. It’s like magic)

It allows you to spot gaps and issues, and dive deep into the facts so you can make intelligent business decisions.

Here are powerful 4 ways data analytics is applied in e-commerce:

Data analytics can help e-commerce businesses to predict upcoming peaks and troughs so that they know which products to focus on, whether inventory needs to be adjusted, which marketing strategies need to be deployed, and which products to put into clearance.

This will ensure that your supply chain is prepared and your customer expectations are met.

Personalise customer experience

Did you know that 83% of customers are willing to share their data to create a more personalised experience? This is why you are optimising your value when you can sell to the same customer more than once.

Data analytics can determine what a customer is interested in buying with a high level of accuracy. Every time someone clicks on a product, if they see other products recommended, there is a high chance that they will explore and possibly buy something in addition to their original cart.

Optimise pricing

Pricing is a major factor that drives purchasing decisions in e-commerce because you have millions of competitor product options online. The prices you set will directly influence your product sales.

Data analytics can monitor the pricing of competitors in real time and analyse pricing trends to determine the optimum price for your product to maximise profits, as well as the right place and time to present the product.

Recover lost sales

If a customer adds an item to the cart but doesn’t check out, it can be for a number of reasons, such as pricing or boring packaging.

Data analytics can give insights into why they didn’t convert and suggest effective steps to bring them back to your site, such as through abandoned cart recovery techniques.

The Bottom Line

Data is an incredibly powerful tool in e-commerce to always stay one step ahead of your competition.

But how do you interpret this vast volume of information to get the most out of it?

Our data experts here at Polar Packet can help you to utilise data to your advantage. Learn more here.