The concept of data analytics is nothing new. Simply put, it’s the science of collecting together facts and statistics and examining them before drawing conclusions.

Data analytics are an invaluable resource for business, they are vital to ensuring everything is running smoothly, performing at its optimum so profits are maximised. And the best part is that, when taken online, most of the data is automatically provided by the activities of your customers.

Let’s break down some of the benefits of data analytics and why it’s an imperative part of any e-commerce business.

• Personalisation

No customer wants to feel like a cog in a wheel. When a business talks to us with an understanding of who we are, it makes for a better experience.

Data Analysis helps to identify the demographic of your customers -age, gender, location- and target offers accordingly. For example, for any new online casino brand, it is essential they retain any players that have previously interacted with the site and one way in doing so is through targeted promotions. For players who have interacted with the casino site and may have downloaded the app or have signed up, the casino provider can target specific promotions for that player depending on which game they viewed or played to make sure the promotion is relevant, this is all found through data analytics.

Over 85% of consumers claim that personalisation is key to retention, simply, sticking with the business in question. Moreover, millennials actually expect personalised suggestions from the businesses that they’re using.

• Predict trends

One of the ways that (specifically) e-commerce can predict trends is by offering instant and/or limited one-off discounts. By checking out the results of the timing of said deals and identifying who picks up what, companies can get a better idea of what might be around the corner.

For example, a retailer can get an understanding of their peak or down periods and stock up/get rid of stock accordingly. When this type of data is analysed over a long period, a pattern will emerge that will allow a glimpse into what the future holds in store.

• Streamlining operations

Data Analysis isn’t just useful for predicting trends, it can help put a business ahead of the game in other ways too.

Crucially, it allows key decision-makers to identify issues before they’ve occurred. Using the retail example, data intelligence gathered over time can pre-warn of bottlenecks in a supply chain and allow a business to compensate accordingly.

Say a vendor requires more stock at a specific time of the year or, conversely, needs less of a product at other times. Now they’ll have the information to make an informed decision.

• Generating sales

We’ve already noted how data analysis can help sales with personalisation, but it can also help to create a bespoke marketing campaign tailored to specific individuals. This is achieved by using technology to collect and process data, and then using this information to target customers.

One of the ways to gather data is to inspire customers to make a purchase but, in return, glean as much information as they can about them. One example that’s frequently touted comes courtesy of a well-known fast-food chain.

While it might seem simple, the said business encouraged its hungry customers to make a purchase anywhere using their smartphones. The data collected could identify the location, times, purchases etc., to get an overview of their consumers.

• Mitigate risk with propensity modelling

Back to the retailer for an example of how data analysis can mitigate risk with the use of propensity modelling. And for best practice, propensity modelling is a technique that uses statistics to predict the chances of specific occurrences in the future.

With AI, a business can build a propensity model to accurately predict customer behaviour or determine which retail outlet is more/less vulnerable to shrinkage. Which is the industry term for shoplifting or theft.

Data analytics will help to apply the correct amount of security required for each specific store as well as identify the items most at risk of being stolen.

• Enhance security/compliance

Last but by no means least, data analytics are essential for security over and above those protected by the benefits of propensity modelling. Not only can data analytics track and trace a breach in security, but it will also provide the necessary information to present such breaches going forward.

It can also detect strange patterns of behaviour that may suggest a security breach is imminent, thus allowing a business to take action before any data is lost/stolen. These checks can be run permanently so data is being monitored and protected 24/7.

It should be obvious that the benefits of data analytics to a company -irrespective of whether it’s a brick-and-mortar concern or an online interest- are vital to every aspect of a business. When used correctly, data analytics don’t just determine in which direction a business is going to be run, it ensures that it’s as safe as possible too.

Technology has made data analytics possible, such things would have been unheard of relatively recently, so why not take full advantage of it?