What Can You See In Your Own Customer Behavior Analytics?

Customer analytics has often been presented as a way to understand what your customers will want in future. It’s true that predictive analytics has been presented as a way to know who will order which product and how to prepare supply chains for this, but there are many different business areas and processes that can be improved with data analytics.

Let’s explore a few of them in turn.

Segmentation

Customer segmentation allows you to identify who are your most valuable customers, so you can then target special deals and service just for them. A great example of this is in free video games – you know the games you can download free to your phone.

These games make a profit by selling items and upgrades inside the game. Most players never spend anything, but some will spend a lot. They are known as ‘whales’ inside the gaming companies. Whatever your industry, if you can identify your whales then you can start prioritizing service and offers to these customers to keep them returning for more.

Retention

This is especially important for businesses that have regularly recurring revenue, such as a subscription. Your mobile phone contract or Netflix subscription are all good examples. If the business can identify that your behavior matches how other customers behaved before they cancelled the service then it should be possible to intervene – offer a special discount in return for another year of commitment.

Analysis

This is the more general analysis of your customer data. What trends can be identified when looking at the data? Can you find some preferences or trends that are not obvious to your human managers, but can be proven with the data?

Predictions

All businesses can benefit from modeling future situations. You can take your historic data, your real-time data, and then model into the future to create predictions about what might happen in different situations. This can help retailers to predict how much stock they might need to cover a holiday period or how many customer service employees are need to cope with all the Black Friday customer questions. Having the ability to predict what your business may need at a specific future date is incredibly powerful.

IBA Group has some good examples and case studies. I think this one focused on the banking sector is particularly readable and useful.

In this case study, the bank managed to increase customer engagement by 15%. They improved their response to marketing efforts by 20%. They managed to increase credit card sign-ups by 25% and achieved a 30% increase in the volume of card use. They also managed to create an entirely new revenue stream by anonymizing customer transaction data and selling it to retailers – this enhanced profitability across the entire bank by 5%.

These metrics really show how a technology-led initiative, such as a stronger focus on data analysis, can have very powerful real-world results for a business. What is your business doing with your data?

Follow IBA Group on LinkedIn for regular updates and comment. For more information on technology strategy and how tech connects to real business solutions please click here.