New customers are either loyal advocates in training or a hole that will drain company resources from the moment they land in your database. Taking the long-term view of customer acquisition programs will give you tools to identify both types.
Naturally, not all one-time buyers are the same. The trick is to recognize who will become your customer advocates, buying across channels and promoting your brand to friends and colleagues. But with only one or two days’ worth of history, how can you separate out promising first-time customers from the run of the mill, coupon-toting switchers, who’ll jump ship the moment a sweet offer comes from your competitor?
Learn the answers and actionable tips for improving your acquisition strategy, including our top 10 tips for predicting which customers will buy again. Home Depot case study is included.
This 40-page webinar PPT is presented by Roy Wollen, president of Hansa Marketing Services. It covers how to identify your best customers, cut costs without reducing effectiveness, and more.
Don't miss our next free online webinar. Register here: http://hub.am/XwTIKo
www.HansaMarketing.com
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2. Who am I?
Roy Wollen is President, Hansa Marketing Services
Roy was Director of Consulting at Experian, the largest
database company in the world
Roy has also been on the client side, working for Federated
Department Stores and Hewlett-Packard
Roy worked at Ogilvy & Mather, the global advertising agency
Roy has a Master of Science degree from Northwestern’s
Medill IMC program
Roy has authored a book on database marketing
Roy is an adjunct professor of marketing at DePaul University
2
6. Today’s Agenda
What’s so bad about new customers?
Customer segmentation
– Customers see brands, not channels
– Measuring the bond
– Personalizing the message
How to cut costs without reducing effectiveness
Case study: The Home Depot
10 things that predict which customers will buy again
6
7. What’s so bad about new customers?
A few will blossom, but most buy once and never again
7
8. Old model
“The sale is the start of the relationship” (Levitt)
Continuum of your relationship with a customer
– Ignorance
– Awareness
– Interest
– Trial (acquisition)
– Repeat purchasing (retention)
– Loyalty
– Advocacy
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9. Notice
– Combination of acquisition media both mass and direct
– Customers zigzag in and out of media
– There is a lot of research and decision making prior to the sale
Attributing response is not only difficult but political
Display ad?
E-Mail?
TV Ad??
Price
Comparison
Search
Community
www.Brand.com
Store visit
Mobile
New model
9
10. From a customer’s perspective
– Customers are in control – more “pull” than “push”
– Customers see brands not channels
– Customers don’t care who gets credit for the sale
Display ad?
E-Mail?
TV Ad??
Price
Comparison
Search
Community
www.Brand.com
Store visit
Mobile
New model
10
11. Measuring the bond
How do you measure the bond between your brand,
your product/services, and your customer?
Strategic customer segments
Some marketers name their segments
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Advocates
Repeat buyers
Gift givers
Too good to be true
Trial buyers
Dormant
Defectors
– About to defect
– Baby come back
CustomersSegments
12. Sandra is a real customer
Sandra has information in a database
– Contact information and “preferences” (opt ins, opt outs)
– Transactional summaries at the customer level
– Order detail
12
Meet “Sandra”
13. Sandra’s purchase history tells a story
Sandra has a broad range of information in a database
– Purchase and non-purchase details (clicks, store visit)
– Merchandise detail associated with her purchases
14. Sandra’s purchase history tells a story
When you include long term behaviors, it completes the story
15. Personalizing the message for the individual
Thank you for your purchase
(Sales incentive disguised as a product review)
Attend a store event – clienteling example
What
Sandra
bought The store closest
to Sandra? Same
store as before?
16. Potential Customer 1
55 year old male
Located in Texas
Price conscious
Shopping for Golf Balls
Dynamic
Category/Subcategory
Text
Dynamic
Gender/Age
Range Image
Dynamic CountdownDynamic Product Image
Texas store locations
Dynamic store locator
Dynamic Content
Source: Dotomi, 2012
17. Potential Customer 2
35 year old female
Located in Washington state
Brand conscious
Shopping for Golf Clubs
Dynamic
Category/Subcategory
Text
Dynamic Image Rotates
between Product and Brand
Dynamic Countdown
Dynamic
Gender/Age
Range Image
WA locations
Source: Dotomi, 2012
19. Today’s Agenda
What’s so bad about new customers?
Customer segmentation
– Customers see brands, not channels
– Measuring the bond
– Personalizing the message
How to cut costs without reducing effectiveness
Case study: The Home Depot
10 things that predict which customers will buy again
19
21. Comparing the two approaches
Batch & Blast is an old model of marketing outreach
– Selecting audiences based on our marketing calendar
– “Batch and blast” – each campaign seen as a distinct event
– Response rates of 1% are acceptable (99% failure rate)
What’s wrong?
– Presumes customers are in market on our timetable
– Not aware of other media – particularly customer initiated
– Slave to “what have you done for me lately” mentality
• Audiences are selected based on Recency – Frequency model for
expensive media such as telemarketing and mail
– For less expensive media, one size fits all
• Anyone with an email address gets all email campaigns, no targeting
21
22. 22
Campaigns within a promo period
Campaign 1 Campaing 2 Campaign 3 Campaign 4 Campaign 5
What it looks like to a customer (mail edition)
23. What it looks like to a customer (email edition)
Customers being pummeled by email
Everyone gets the same level of attention
Clear differences in responsiveness
Not everyone has an active email address
RFM and Email analysis
Recency
Active
Email %
Total
Emails
Emails
/Buyer Openers
% who
Opened Opens
Opens
/Buyer Clickers
% who
Clicked Clicks
Clicks
/Buyer CTR
0 - 3 Mos 70,960 74.6% 2,124,751 29.9 43,580 61.4% 339,099 4.8 33,304 46.9% 115,778 1.6 5.4%
4 - 6 Mos 79,305 83.4% 2,212,122 27.9 42,724 53.9% 342,965 4.3 30,743 38.8% 102,063 1.3 4.6%
7 - 12 Mos 131,193 80.2% 4,161,901 31.7 57,161 43.6% 407,003 3.1 36,133 27.5% 95,216 0.7 2.3%
0-12M buyer 281,458 79.5% 8,498,774 30.2 143,465 51.0% 1,089,067 3.9 100,180 35.6% 313,057 1.1 3.7%
13 - 18 Mos 110,122 75.2% 3,550,586 32.2 44,609 40.5% 310,592 2.8 27,159 24.7% 65,970 0.6 1.9%
19 - 24 Mos 94,968 71.7% 2,813,285 29.6 33,669 35.5% 221,741 2.3 19,487 20.5% 43,939 0.5 1.6%
25 - 36 Mos 160,279 67.4% 4,036,381 25.2 49,156 30.7% 308,036 1.9 27,007 16.8% 57,400 0.4 1.4%
37 - 48 Mos 73,727 44.8% 2,173,384 29.5 21,294 28.9% 135,273 1.8 11,350 15.4% 23,129 0.3 1.1%
49+ Months 60,842 24.9% 2,035,069 33.4 16,946 27.9% 111,304 1.8 8,953 14.7% 17,889 0.3 0.9%
Grand Total 781,396 61.1% 23,107,479 29.6 309,139 39.6% 2,176,013 2.8 194,136 24.8% 521,384 0.7 2.3%
23
24. Contact strategy based on customers
Planning done based on a customer’s potential (value)
– How much should we invest in retention marketing?
– Where do we draw the line (lower bound)?
– Which channels does the customer prefer?
But implementation is reactive to customer actions
– Welcome streams
– Triggered by activities
– Triggered by non-activities (time going by)
– In b2b, triggers might come from site level activities
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25. Contact strategy experiments
Longitudinal planning = planning campaigns for a
period of time (e.g., 6 month season)
– Experiment with # of touches
– Experiment with cadence and rest periods
– Experiment with media (phone call followup)
– Experiment with offers
– Experiment with cycle time (e.g., how long it takes to get a
welcome kit)
Keep in mind:
– Control groups at campaign level
– Control groups at universal level (6 month hold out group)
25
27. Contact strategy can be extended to touchpoints
Clienteling at point of sale (POS)
– Data driven POS experiences
– Contacts then continue from store associates
Intelligent call center routing based on value and
customer segments
Dynamic creative on the web
– Landing page optimization
– Personalized display ads
Dynamic creative on outbound email
– Early morning test then change creative to everyone based
on results
– Keep track (a history of what interested customers) 27
28. Cost cutter ideas
Plan campaigns longitudinally
Envision media holistically, experiment
– Example: Email prior to direct mail
Direct mail reserved for best customers
– Use statistical models to select audiences based on probability
of sales or attrition
Make online communications relevant
– First class postcards with a special offer to drive recipients to
your website
– Specific search terms lead to relevant landing pages
– Data driven display ads, not generic “banners” people ignore
– Display ads on email 28
29. Today’s Agenda
What’s so bad about new customers?
Customer segmentation
– Customers see brands, not channels
– Measuring the bond
– Personalizing the message
How to cut costs without reducing effectiveness
Case study: The Home Depot
10 things that predict which customers will buy again
29
30. Case study for customer centricity
Analytical challenge
– Home Depot wanted to know which online affiliates attracted
New- versus Repeat customers?
• When customers buy again, do they buy directly from The Home
Depot, or via the same affiliate channel (who’s the customer loyal to?)
• Which categories of publishers are best (not just biggest) for driving
loyal customers?
Solution
– Analyzing customer transactions and determined Lifetime
Value (LTV) to establish the base for measuring success
– Home Depot gained more control of its affiliate program at the
same time it increased repeat purchasing and LTV
30
31. Today’s Agenda
What’s so bad about new customers?
Customer segmentation
– Customers see brands, not channels
– Measuring the bond
– Personalizing the message
How to cut costs without reducing effectiveness
Case study: The Home Depot
10 things that predict which customers will buy again
31
32. 10 things to help you predict which customers buy again
1. Dollars spent on first purchase
2. Breadth of first purchase (# of departments)
3. Usage of a sales incentive or coupon
4. Payment method, especially house credit program
5. Degree to which customers tell you their
communication preferences
6. Sample or ancillary service on first purchase
7. Replenishment nature of product
8. What happened prior to the first purchase
9. (b2b) role and employee size
10. (b2b) activity of the site 32
33. How do I know this is true?
Repurchase rates by first dollar amount
This template can be used for any dimension
33
First Dollar New Customers Bought in 1st 3 Months Bought in 1st 6 Months Bought in 1st 12 Months
$501+ 5,284 1,793 2,345 2,850
$401-500 3,942 1,207 1,617 2,041
$301-400 12,223 3,557 4,898 6,130
$201-300 38,609 10,493 14,698 18,690
$101-200 151,955 35,659 52,210 67,978
$ 76-100 104,687 21,437 32,243 42,464
$ 51-75 105,149 19,925 31,015 41,667
$ 26-50 170,551 28,009 44,350 60,112
$ 25 or less 54,049 8,922 14,174 19,236
646,451 131,001 197,550 261,168
34. How do I know this is true?
Repurchase rates by first dollar amount
This template can be used for any dimension
Go on a treasure hunt for the most important attributes
34
First Dollar New Customers Bought in 1st 3 Months Bought in 1st 6 Months Bought in 1st 12 Months
$501+ 100% 34% 44% 54%
$401-500 100% 31% 41% 52%
$301-400 100% 29% 40% 50%
$201-300 100% 27% 38% 48%
$101-200 100% 23% 34% 45%
$ 76-100 100% 20% 31% 41%
$ 51-75 100% 19% 29% 40%
$ 26-50 100% 16% 26% 35%
$ 25 or less 100% 17% 26% 36%
100% 20% 31% 40%
Retention
Rate
35. How do I know this is true?
Repurchase rates by presence of sales incentive
Conclusion: Bribery has a short term benefit but
downstream drawback
35
Retention
Rate
Premium New Customers Bought in 1st 3 Months Bought in 1st 6 Months Bought in 1st 12 Months
Yes 13,848 1,819 2,928 4,205
No 631,516 131,582 197,776 260,459
Premium New Customers Bought in 1st 3 Months Bought in 1st 6 Months Bought in 1st 12 Months
Yes 100% 13% 21% 30%
No 100% 21% 31% 41%
36. What customers did prior to their first purchase
36
Source: Joe Stanhope, Forrester 2010
37. Key takeaways
Not all first-time customers are created equal
Most won’t buy a second time
37
38. Other takeaways
Take a long term view of customers, which will provide
feedback on acquisition marketing decisions
Envision communication as streams, conversations
Plan contacts based on customer value and
longitudinally, not batch and blast
Then embed triggers to react to customer activities
Make your messages relevant
Set aside control groups
Measure what’s working
38
39. Above all: measure what’s working
From campaign analytics …
– Basic response analysis with ROI
– Responses across channels (response attribution)
– Experiments in market for offers, audiences, selections
39
Channel Buyers Trans Sales Sales/Piece Margin GM% AOV
Resp
Rate
Resp
Rate 2
Retail 200,000 250,000 10,000,000$ $2.50 5,000,000$ 50.0% 45.00$ 4.0% 4.5%
Direct 100,000 130,000 5,000,000$ $1.50 2,500,000$ 50.0% 35.00$ 3.0% 3.2%
Total 300,000 380,000 15,000,000$ $3.00 7,500,000$ 50.0% 40.00$ 3.8% 4.0%
List Priority Circ AOV Resp Rate Sales/Piece
1. List x 1,000,000 $55.00 3.2% $2.00
2. List y 2,000,000 $45.00 4.9% $3.00
3. List z 2,000,000 $35.00 4.6% $4.00
5,000,000 $40.00 3.8% $3.00
Market Circ AOV Resp Rate Sales/Piece
Key market 1 1,000,000 $50.00 6.0% $4.00
Key market 2 4,000,000 $35.00 2.0% $2.00
Grand Total 5,000,000 $40.00 3.8% $3.00
Discount Circ AOV Resp Rate Sales/Piece
$25 off 1,000,000 $55.00 5.0% $4.00
$35 off 2,000,000 $65.00 6.0% $1.75
Gift w Purchase 1,900,000 $25.00 2.0% $2.00
Control group 100,000 $40.00 3.0% $2.00
Grand Total 5,000,000 $40.00 3.8% $3.00
Distance to Store Circ Buyers Trans Sales Sales/Piece Margin AOV
Resp
Rate
Resp
Rate 2
Within 1 mile 300,000 90,000 110,000 4,000,000$ $13.33 2,000,000$ 55.00$ 7.0% 7.2%
2 miles 200,000 50,000 75,000 3,000,000$ $15.00 1,500,000$ 45.00$ 6.0% 6.5%
3 miles 500,000 40,000 55,000 3,000,000$ $6.00 1,500,000$ 50.00$ 6.0% 6.4%
4 miles 500,000 40,000 50,000 2,000,000$ $4.00 1,000,000$ 45.00$ 5.0% 5.5%
5 miles 500,000 35,000 40,000 1,000,000$ $2.00 500,000$ 25.00$ 4.0% 4.0%
6 to 10 miles 1,000,000 20,000 22,000 900,000$ $0.90 450,000$ 40.00$ 2.0% 2.2%
11 to 15 miles 1,000,000 15,000 16,500 650,000$ $0.65 325,000$ 35.00$ 1.5% 1.7%
16 to 20 miles 1,000,000 10,000 11,500 450,000$ $0.45 225,000$ 35.00$ 1.0% 1.2%
TOTALS 5,000,000 300,000 380,000 15,000,000$ $3.00 7,500,000$ 40.00$ 3.8% 4.0%
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Customers
40. Above all, measure what’s working
…to customer analytics
– Value of a lead, then optimizes investment in both
acquisition and retention programs
– Hidden influencers, specifiers and site level and buying cycle
dynamics (by role, industry, employee size)
– Finally dashboards drive action not just recite KPIs
40
41. Roy Wollen
President, Hansa Marketing Services Inc.
(847) 491-6682
roy.wollen@Hansa-Marketing.com
www.Hansa-Marketing.com
Blog.Hansa-Marketing.com
http://www.linkedin.com/company/404316?trk=tyah