Identify Best Customer - iGODirect

Smart ways to identify your best customers – Entertainment Industry

Background

An entertainment group with over 100,000 members with loyalty card customers accumulating points each time they visit and transact. The group wanted to use the transactional behaviour data to develop marketing programs to increase the Frequency of customer visits to the venue and to increase the customer spend each time they visit. Our client also wanted to use customer data to target the best Prospective Customers and to learn about how customer residence proximity impacted on their responsiveness to various offers.

Marketing Objectives

  • Increase Average Current Customer Visitation by 10%
  • Increase Average Current Customer Value by 10%
  • Establish a relationship between Customer Residence Proximity to the venue and Current Customer Value
  • Establish a ROI matrix for offers based on Offer Value, Offer Type and Customer Proximity
  • Establish a ROI matrix for Acquisition of New Customers based on Offer Value , Offer Type and Prospect Customer Proximity to the venue
  • Establish key reasons for customers lapsing and develop a plan for reducing attrition
  • Test this activity over a period of 3 months with a view evolving it into an ongoing program

 

Strategy

Transactional analysis of the current customer behavioural data coupled with geo-demographic mapping identified patterns in customer behaviour. RFM data modelling was used to put customers into behavioural cells. Other variable attributes were then applied to the model.

A Direct Marketing/eDM strategy was developed with offers to increase customer visitation and spend. ‘Best Customer’ analysis enabled the identification of a prospect customer list based on behaviour and attributes of Best Customers.

Creative Solution

Identifying the right ’offers’ to put to the right customers and prospects at the right time was the trick. It was important to test the appeal of varying levels of offer value and type to statistically significant cells of customers and prospects.

Results

Current Customer Visitation rose by 19% and Average Customer Value by 14% during the period of the activity. Importantly, there was a long ‘tail’ of behaviour change that delivered additional revenue attributable to the activity long after it has finished.

We now receive a download of transactional daily from the venue and feed this into the ongoing behavioural marketing model. Customers and Prospects in different behavioural cells will receive different messages and offers to drive them back into the venue to spend more, more frequently. We test and trial different combinations of offers to continuously improve Marketing Return On Investment.

Our client is really committed to this activity as it is the most transparently measurable part of his budgeted marketing activity. Importantly for him, as a result of the tracking, it is very easy to develop business cases when needed to have new campaign budgets approved.