Customer Analytics

Life used to be so simple for brands. They had absolute control over their image, messaging, and customer touchpoints. Then the digital revolution arrived and changed everything. A dozen new ways of buying products have seemingly popped into existence, user generated content and social media ensures a brand annoys a customer at its peril, and in order to secure any sort of internal investment to wrestle control of the customer experience you’ll need an exciting big data solution.

Thankfully, whilst the data streams have grown exponentially, the basic formula for successful customer analytics has not changed

    1. Create a single view of performance: optimise media mix through marketing attribution and optimisation
    2. Create a single customer view
    3. Segment and target accordingly: group people by behavioural, attitudinal, financial or preferred touchpoints
    4. Track and optimise through test and learn: App/web analytics,  campaign evaluation, and control cells

Some questions you may be asking, which we and the science of customer analytics can help answer:

  • Who will be the next customers to churn, and why?
  • Which channels are my true marketing channels and which ones merely assist a sale? How do they all work together in the customer acquisition journey?
  • How do I use pricing to maximise profit whilst keeping my best customers?
  • Where are the cross sell opportunities in the existing customer base?
  • Which customers are actually costing me money, once cost to serve is taken into account?
  • I need to lower cost to serve. How do I know which customers will be happy to be driven to digital and which will be just driven away?
  • How can I use my touchpoints to ensure every customer receives a unique experience, flawlessly tailored to their exact requirements?
  • What is the anticipated lifetime value of each of my customers?
  • How often should I contact my customers?
  • Which of my customers shouldn’t I contact? (Why wake a sleeping cash cow!)