The science of loyalty

Transcription

1 The science of loyalty Steve Burnstone, CEO Eighty20

2 2 Loyalty programmes make you think of

3 3 Loyalty programmes make you think of

4 Loyalty Member Engagement survey

5 5 What is loyalty?

6 6 The theory of loyalty CUSTOMER NEED PROGRAMME STRUCTURE RELEVANCE (self actualisation) PERSONALISATION (targeted offers and communications.) RECOGNITION (social belonging) PEFERENTIAL TREATMENT (tiering ) REWARDS (economics) PROGRAMME OFFERING (earn, redemption )

7 A more scientifically rigorous approach can help generate additional value 7 SETTING UP A LOYALTY PROGRAMME Define the programme s CVP and business case Develop IT & admin infrastructure Partner acquisition Cards, application forms & marketing material Targeted offers and personalised rewards Measuring and improving Acquiring customers, managing earn and burn of rewards 7 6 Most loyalty programmes lose steam here 5

8 8 CVP and business case SETTING UP A LOYALTY PROGRAMME Define the programme s CVP and business case Develop IT & admin infrastructure Partner acquisition Cards, application forms & marketing material Targeted offers and personalised rewards Measuring and improving Acquiring customers, managing earn and burn of rewards 7 6 Most loyalty programmes lose steam here 5

9 A rigorous business case is important to test and refine the CVP 9 LOYALTY BUSINESS CASE Motivate internally and externally (IRR/ NPV) Plan Track performance Identifying operational / data issues Refine / Optimise CVP Identify sensitivities and risk

10 The classic loyalty business case is built on the assumption that customer behaviour will be positively impacted Sales Revenue 10 POTENTIAL FINANCIAL REWARD Incremental profit due to change in customer behaviour Cost of rewards Uplift Sustained growth with program Natural growth Drives rewards expenses Time

11 11 Top-down modelling approach Segment 1 Segment 2 Segment 3 Sample customer Sample Sample custome customer r 2 3 Sample Sample custome customer r 3... Total Book Sample customer 3 5 year Revenue Account Income Expenditure Expected NPV 5 year Revenue Account 5 year Revenue Account + + = Income Income Expenditure Expected NPV Expenditure Expected NPV year Revenue Account Income Expenditure Expected NPV X Y Z X + Y + Z

12 12 Bottom-up modelling approach Customer 1 Customer 2 Customer 3 Sample customer Sample Sample custome customer r 2 3 Sample Sample custome customer r 3... Total Book Sample customer 3 5 year Revenue Account Income Expenditure Expected NPV 5 year Revenue Account 5 year Revenue Account + + = Income Income Expenditure Expected NPV Expenditure Expected NPV year Revenue Account Income Expenditure Expected NPV

13 13 Measuring and improving SETTING UP A LOYALTY PROGRAMME Define the programme s CVP and business case Develop IT & admin infrastructure Partner acquisition Cards, application forms & marketing material Targeted offers and personalised rewards Measuring and improving Acquiring customers, managing earn and burn of rewards 7 6 Most loyalty programmes lose steam here 5

14 14 Quantifying behaviour change SHOPPERS GENETIC MATCHING ALGORITHM Genetic matching is used to create two groups of customers that are very similar in terms of their transactional behaviour but in one group all the customers are members and in the other group no customers are part of the programme

15 15 Quantifying behaviour change SHOPPERS GENETIC MATCHING ALGORITHM Joined Matched to nonjoiners Compare the spend of the two groups in future months

16 16 Targeted offers and personalised rewards SETTING UP A LOYALTY PROGRAMME Define the programme s CVP and business case Develop IT & admin infrastructure Partner acquisition Cards, application forms & marketing material Targeted offers and personalised rewards Measuring and improving Acquiring customers, managing earn and burn of rewards 7 6 Most loyalty programmes lose steam here 5

17 Profiling allows us to understand and serve customers better 17

18 Relevant communications have the most impact on behaviour 18 Relevance: Richer offers: Timing: 6x 3x 2x Creative: 1.35x Channel: 1.25x

19 Millennials are driving the need for businesses to send personalised communications 19

20 Targeted offers can add value, but can also annoy customers if it isn t helping them 20

21 Targeted offers can add value, but can also annoy customers if it isn t helping them 21

22 Thank you The science of loyalty Steve Burnstone

23 Some programmes are better than others 31

24 32

25 CUSTOMER ENGAGEMENT BEHAVIOUR CHANGE DATA COLLECTION Loyalty objectives need to be related to the CVP 33 Collected data should be actionable and useful Programme rules: Membership fees Earn Ease of redemption/ channels Tiering levels Point expiry Simple and transparent Perceived as valuable by customers Inclusive Represented well by staff