Leveraging data to understand customer behaviour

Leveraging data to understand and influence customer behaviour.

In a world where data is collected in abundance, businesses are trying to use this data to gain insight into their customers behaviours and habits. Efficiently using this data allows companies to understand their customer base, tailor products or services to meet the customers’ needs more effectively and even anticipate the customer’s needs beforehand.

To remain competitive in today’s economic environment, companies need to understand their customers. This can be achieved by analysing data on customer preferences, spending patterns and interactions with your business. Thus, giving the business valuable insight into the things that drive customer decisions to better meet their needs.

A key benefit of using data to understand customer behaviour is personalised customer experience. Tracking customer interactions across various channels allow you to create a personalised experience for each customer such as product and service recommendations based on browsing history.

Another important use for this data is predicting future trends and behaviours. Historical data analysis can potentially uncover future customer behaviour by analysing patterns and trends. A simple yet common example of this is seasonality. A business may sell more or less of a product or service in a particular season.

Segmenting customers is crucial for designing campaigns that target these segments to yield the best possible results. Methods for segmentation may vary although 2 examples are RFM and Churn.

RFM:

RFM is a model which accounts for recency, frequency, and monetary value. Using these 3 attributes segments can be created for the customer base from highest value to least value. People who shop frequently and have a high monetary value would be regarded as a high value customer whereas the inverse would be regarded as least value or even one-time shoppers.

Churn:

Churn is where a customer has been shopping consistently and then suddenly stops supporting you. This could be due to a multitude of reasons and it is a good idea to keep track of these individuals and create promotions catered to them.

To conclude, analysing customer data to identify patterns and trends in behaviour is essential for businesses to remain strategic and influence their customers to continue support. By using the correct tools and strategies business can utilise the full potential of the data they have collected to gain a competitive advantage in today’s market.