UCEA Mini-Workshop on Database Marketing Arthur Middleton Hughes Vice President / Solutions Architect KnowledgeBase Marketing Hyatt Fisherman’s Wharf San Francisco Feb 14, 2002
What KnowledgeBase Marketing Does
Compared with newcomers, Long term customers: Buy more per year Buy higher priced options Buy more often Are less price sensitive Are less costly to serve Are more loyal Have a higher lifetime value
Retention is the way to measure loyalty
Retention pays better than acquisition
What proves that relationship building works? Manufacturer of building products Catalog sent to 45,000 contractors Previous policy: wait for the orders Test: pick 1,200 customers, split into test of 600 and control of 600 Two person pilot program build relationship with test customers to see the results Credit: Hunter Business Direct
What did they offer? Follow up on bids and quotes Schedule product training Make aware of pricing specials Ask about customer needs Product comparison information New Product information They did not offer discounts
Improvement in Response rate
Change in the number of orders
Change in the Average Order Size
Total revenue gain: $2.6 million dollars
This stuff works! Building a relationship with customers can be highly profitable Using a database to recreate the old family grocer is a winning strategy Relationship marketing is the way to go
Why we need Lifetime Value Analysis We need to know the value of our customers, so as to properly target our sales and retention efforts We need to discriminate among our customers to acquire and retain the best
Lifetime Value Analysis Goal: Determine... where to put your retention dollars the value of each retention strategy where to put your acquisition dollars how much to spend on acquisition
What is lifetime value? Net present value of the profit to be realized on the average new customer during a given number of years. Lifetime value is “Good Will.” To compute it, you must be able to track customers from year to year. Main use: To evaluate strategy.
Discount Rate Basic Formula Market Rate of Interest...6% Assume Risk 1.2 first year, 1.1 afterwards Years = n Interest = i Formula: D = (1 + I * risk)n Calculation of rate after 2 years: D = (1.06 * 1.1)2 = 1.36
Convert to Annual Annual Rate = (Repurchase rate) (1/years) 77% repurchase after 11 years Annual Rate = (.77)(1/11) = 98% 45% repurchase after 4 years = 82% 99% per week = 59.2% per year Annual = (.99) (1/(1/52)) Annual Rate = 59.2%
New Retention Strategies Build a database linked to the website Web registration Frequent personal communications Web site cost $30 per student per year Communications extra cost $18 per student per year
Effect of adoption of new strategies $1.8 million in the third year Profit, after all expenses paid
What is the proper computation period? Which is the correct lifetime value? 1, 2, 3, 4, 5 or more years? They are all correct. Which you use depends on your product or service. Long lifetimes: banks, insurance, utilities. Short lifetimes: continuing education.
Five Ways to Boost LTV with DB Strategies Increase the retention rate Increase the referral rate Increase the spending rate Decrease the direct costs Decrease the marketing costs
How to use lifetime value Compute a base lifetime value Dream up a new strategy Estimate the benefits and costs Determine whether your new lifetime value goes up or goes down Don’t undertake any new strategy until you can prove it will be successful
Find LTV of Customer Segments Many UCEA customers are quite different in their purchase patterns Create actionable segments and determine the value of each Use the results to focus your retention programs and acquisition programs on the most profitable segments
Dividing Customers into Three Segments Develop a different strategy for each segment
Different marketing strategies Job training: market to companies Degree Candidates: market both to companies and individuals Senior Citizens: market to individuals
Using lifetime value to get budget approval Database marketing budgets are usually carved from somewhere else You have to prove that you will make better use of the funds than the others Lifetime value can supply testable numbers that CFO’s can understand Base your budget on solid numbers backed up by valid tests
What your new budget will buy
Using lifetime value to get budget approval Database marketing budgets are usually carved from somewhere else You have to prove that you will make better use of the funds than the others Lifetime value can supply testable numbers that CFO’s can understand Base your budget on solid numbers backed up by valid tests
Recency, Frequency, Monetary Analysis
How to attract and hold relationship buyers Forget price. Think and talk about quality and service. Build a relationship with the buyer Add value to product and relationship Find way for buyer to build equity Make it expensive to switch
How to identify responsive customers Some customers respond, some don’t How can you predict behavior? Best method: look at past behavior Behavioral indicators: Recent purchasers Frequent purchasers Large spenders
Not all responsive customers are profitable Responsive customers may not be the most profitable Responsive Customers Profitable Customers RFM LTV Not all responsive customers are profitable Not all profitable customers will respond when you write them.
RFM Can Predict Responders Use RFM to select most likely responders Use combination of mail, phone, and emails to responsive relationship buyers.
How to Apply Recency Codes Put most recent purchase date into every customer record Sort database by that date - newest to oldest Divide into five equal parts - Quintiles Assign “5” to top group, “4” to next, etc. Put quintile number in each customer record
Response by Recency Quintile
How to compute a Frequency Index Keep number of transactions in customer record Sort Recency Groups from highest to lowest Divide into five equal groups Number groups from 5 to 1 Put Quintile number in each customer record
Response by Frequency Quintile
How to compute a Monetary Index Store total dollars purchased in each customer record Sort Frequency Groups from highest to lowest Divide into 5 equal groups (Quintiles) Number Quintiles 5, 4, 3, 2, 1 Put Quintile number in each record
Response by Monetary Quintile
Monetary Response to $5,000 Product Percentage of households promoted who purchased 2 1.68 1.5 1.17 0.88 1 0.66 0.5 0.32 5 4 3 2 1 Monetary Quintile
RFM Code Construction R F M One Sort Five Sorts Twenty-five sorts Database 5 4 3 2 1 35 34 33 32 31 335 334 333 332 331
Appended RFM Codes
Creating an Nth Customer Database Nth 300,000 Records 30,000 Records For Nth by 10, select every tenth record. Nth Result will be statistical replica of database 30,000 Records
Result of Test Mailing to 30,000
Test Response Rate by RFM Cell
Profit from Test Mailing
Determine Break Even and Test Sizes
How to Compute the Response Rate Divide number of responses by number mailed. Multiply by 100 Example: Responses = 1034 Mailed = 40,000 Rate = 1034 / 40,000 Rate = 2.59%
Test, Full File & RFM Selects Compared
Test Vs Rollout Response Rates
Retroactive RFM Test Many times there is not enough time or funding to run an Nth test in advance Solution: apply RFM codes to your last completed outgoing promotion. Since you know who responded, you can determine response rates by cell Use previous rates to govern this rollout.
How Many RFM Cells Needed? Test File = (Test Budget) / (per piece cost) Example = $15,000 / $0.76 = 19,737 Cells Needed = 19,737 / 274 = 72
Cell Division Determination To create 72 cells, some must be less than 5 Recency most powerful. Do not scrimp. Example R-F-M = 6 X 4 X 3 = 72 Is this best? Test and see.
RFM For Business Databases Business databases are small For small databases, use quartiles or thirds Quartile = 4 X 4 X 4 = 64 Cells Thirds = 3 X 3 X 3 = 27 Cells Custom = 5 X 2 X 2 = 20 Cells
Recent Case History User sells personalized product by mail 45,000 selected for a test
Second Recency Quintile Had More Responses. Why?
Even so, First Recency Quintile Had Higher Sales
Recent buyers spend more per order
Lowest two recency quintiles did not break even
Frequency was very predictive of response
Monetary did not predict response rate very well
But Monetary does predict average sales by quintile
RFM Cells clearly show who to mail to, and who to drop
When NOT to use RFM If you use it all the time, half your customers will never hear from you They will be lost The others will suffer from File Fatigue Use it sparingly Product launch is ideal use
THE COMPLETE DATABASE MARKETER by Arthur Middleton Hughes Chicago: McGraw Hill 600 pp Glossary Revised Edition 1996 This is the bible of database marketing. Over 16,000 copies sold. John Stevenson Exec. VP of Krupp Taylor: "Not only does this book succeed in being clear and accessible, it is also the first complete treatise...The full power and practice of database marketing are here, to be sure. This is the long awaited survival manual for every marketer on the cutting edge. I can't think of a book that is more rewarding." This comprehensive book covers such subjects as how to build customer loyalty, lifetime value calculation, RFM analysis, customer service, telemarketing, fulfillment, hardware and software, clustering and profiling, prospecting, media selection. Order from www.DBMarketing.com
STRATEGIC DATABASE MARKETING 2nd Ed. by Arthur Middleton Hughes Chicago: McGraw Hill 2000 400 pp Millions have been spent on database marketing programs that did not work. In this book Arthur Hughes shows how to evaluate strategies in advance using lifetime value analysis. He explains how to use RFM analysis to boost profits. Russ Richmond, President of Grey Direct said: "Well, Arthur has done it again. He has not only integrated the complicated world of databases with the traditional concepts of direct marketing, but he accurately points out the pitfalls and the how-tos. I know of a few careers that would have been saved had this book been available sooner. Without a doubt this will be the cheapest investment you'll make in your database, and perhaps the most important one." Thousands of customer marketing databases are being built. Unfortunately, many mistakes have been made. The reasons for these failures center on one central fault: the inability of marketers to develop logical, practical and winning strategies for their database marketing programs. We must study past mistakes to develop sound principles for marketing strategy. Order from www. DBMarketing.com
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