If you’re not using data science to bolster your eCommerce business’s success, you’re doing it wrong. 

From personalising the customer experience to managing and monitoring stock inventory, analysing and assessing dynamic pricing, preventing fraud, and boosting your marketing campaigns, data science – when used properly – is virtually priceless as an eCommerce tool.

For more on this subject, consider completing studies in the field, such as an online Masters of Data Science or Bachelor of Business Analytics. In the meantime, these are 5 ways data science can be used to optimise your eCommerce business’s daily operations. 

1. Personalising the Customer Experience 

Using data science to curate data-driven, personalised recommendations for future purchases is a surefire way to get your eCommerce customers to ‘add to cart’. 

Put yourself in your customers’ shoes. It’s Friday night, you’re in your cosiest pajamas, hair up in a messy bun, enjoying a glass of wine, and you’ve logged on to your favourite site to do some online shopping. But, as you scroll through the mini dresses and co-ord sets, you can’t help but notice it – suggestive, slightly cheeky, and yet somehow enticing: “You may also like…” – prompting you to click through to check out other similar products. 

Also known as ‘cross-selling’ or ‘upselling’ – this common, customer-centric, personalised eCommerce prompt is totally dependent on the data that businesses collect about their customers, and their buying habits. As an eCommerce business owner, if you’re not making the most of this data-driven strategy, you could be missing out on maximising your sales.

2. Managing and Monitoring Stock Inventories

Inventory management. Drawing on data to do it best is a no-brainer. For the best results, try using the element of data science known as predictive analytics. 

Using predictive analytics to preempt future inventory issues based on historical data can help you overcome common obstacles – such as how much stock to order, how much to keep on hand, and when to turn it over. 

In addition to this, data-informed insights about the risks, as well as the opportunities, that exist within your existing inventory management processes can demonstrate how best to future-proof the way you manage your stock moving forward. 

3. Analysing and Assessing Dynamic Price Points

What are dynamic price points? Commonly used in the travel industry, dynamic pricing lets travel providers such as tour operators, accommodation suppliers, and also, major airlines, change the price of their products (basically, as they see fit).

While this might sound unfair, it’s all based on data. Dynamic price points draw on real-time statistics concerning customer demand in the market. Is Bali accommodation trending? Likely, you’ll see a price increase in the Seminyak hotel you’re considering checking into. Are more customers booking on to a certain flight to Prague than another? The airline would be well placed to raise the price of that particular route to maximise its revenue. 

4. Detecting and Preventing Fraudulent Activity

Ah, fraud. Worryingly, it’s virtually unavoidable in our age of cybercrime, hacking, and ransomware. Fortunately, if you’re an eCommerce business owner, you can call on data science to both detect and prevent the risk of fraudulent activity. How? By using data analytics to identify any anomalies, and preemptively block hackers from getting access to your customer database. 

Truth be told, eCommerce businesses are vulnerable in terms of the potential for being hacked. Take popular online retailer, Temu, for example, which Australian consumers have been warned to buy from at their own risk. Yes, it’s cheap. But, if your payment details are at risk of getting hacked by purchasing through the site –  you have to ask yourself, is paying cut-price for cute homewares, colourful storage containers, and cheerful fashion accessories really worth the risk? 

5. Boosting Consumer Marketing Campaigns 

Lastly, data science can enhance eCommerce marketing campaigns. Frankly, why would you leave your marketing efforts to guesswork when you can use data science to inform them?

Knowing your customer is arguably the most important element of a successful marketing campaign. And the best way for an eCommerce business to get to know its customers is to analyse them. Find out their interests, their buying habits, and their socio-economic status. You can then use this data to curate campaigns that speak to your customers directly, and that encourage them to buy from you.