MKTG 3000 Lecture Notes - Lecture 26: Taco Bell, Loyalty Program, Predictive Modelling
I. CRM and loyalty programs
a. Started with travel- no pervasive in retail and B2B
b. Provides marketer with helpful data for segmenting, promotion and product
development
c. Vesting helps from start
d. CRM very important in B2B—value of each customer greater
e. Lack of differentiation- does it make us loyal, or just cost $$, expensive to administer
f. Retaining custeorms reduces costs, and improves profits
i. 5% increase in retention=25% profit lift
ii. 2% increase in retention= 10% cost decrease
g. Might take you out of the consideration set
II. How many programs do you belong to?
a. Average American=18
b. Revolver: people who to reduce the interest rate you can incentivize them
c. Transactors: credit card companies get them attracted through rewards. Tie it to airline,
cash back, cash back on groceries.
i. Should’t sig up for credit card uless you get a icetie
III. Customer relationship management custeromer centric process
a. Figure out who you are selling to
b. Love customized
c.
d. offers
e. Take offers as customerizable based off past habits
IV. Data analysis- targeting and promotion
a. Customer segmentation
b. Recency-frequency-monetary analysis
i. A catalog retailer in deciding which group of customers to send a catalog. Based
on experience and an RFM analysis of customer database
1. Average order size for customers in cell $40
2. Contribution margin-%0%
3. Response reate- 5%
4. Cost of catalog and mailing $0.75
5. You are only making $0.25.
ii. Will the retailer make a profit mailing to this RFFM segment?
c. Lifetime value analysis
i. Estimate of how much revnue will you make from the customer through whole
relationship
ii. Taco bell: $17,000.
d. Predictive modeling
V. Criteria for good loyalty program
a. Easy to understand—transparency
b. Tiered rewards/levels
c. Choirces of rewards
d. Reward all transactions
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