Use Case

Customer Segmentation

Different customers have different needs and behaviours. By segmenting customers into groups based in different variables, businesses can get deeper insights on consumer behaviour and tailor products and services for these groups and individuals. Business can target these groups with offers and promotions resulting in higher conversions and profitability  

  • Automation of marketing campaigns
  • Lower cost per customer acquisition
  • Higher ROI from effective targeting

Challenge

The data collected in digital and physical platforms has grown exponentially. Understanding needs and behaviours of millions or even thousands of users is extremely difficult. Yet making sense of this data is extremely important for businesses so that they can tailor products and services based on individuals needs and offer better experiences for users. Marketers cannot tailor marketing efforts for individuals because it is difficult to learn about so many different users and create unique experiences for each one. 

Customer segmentation is a process of grouping users together based on different traits. This can enable businesses to learn more about the needs and behaviours of users and provide better products and services by ultimately creating personalised experiences.  

The Process

Our AI system uses data from different channels about customers, their preferences, behaviour data, purchase data and segment these users in groups. Modern Machine Learning techniques allow us to train models that can learn patterns from complex data sets. These complex relationships are impossible for users to process and make sense of but ML algorithms are extremely good at learning from complex non-linear datasets. 

These groups can help us understand what characteristics are shared by these groups and ultimately predict what actions will certain users take in different future scenarios.

Technical Bit

Our Machine Learning system combines supervised and unsupervised techniques to create these segments based on different marketable traits. The clustering algorithms help us with building these groups of users which share common characteristics and supervised ML models help predict things like which marketing material is highly likely to be effective with a user group.   

Results

Benefits

  • Automation of marketing campaigns
  • Lower cost per customer acquisition
  • Better consumer experience and satisfaction by personalizing content
  • Higher customer engagement
  • Higher ROI from more effective customer targetting

Our Analytics Dashboard gives visualization for different customer segments and the characteristics that form these user groups. This helps the business understands the needs of the customers and predict future behaviours with a much higher accuracy. Our AI system also provides recommendation and actions for relevant metrics for these groups and ultimately helps business track changes in performances, behaviours etc.