- 1. A Recency& Frequencypurchasing model Framework Managing
your customer database
2. Recency& Frequency classifications are powerful because
they can serve as surrogates for determining level of customer
engagment 3.
- Is the list of all people who have purchased from you
-
- It's a living, evolving asset
-
- It is the target of your acquisition program
-
- How is it doing Year-over-Year?
Your customer file Lets put it in perspective... 4. know your
brand been to your site "universe" customers 5. know your brand
been to your site "universe" customers customer acquisition 6. know
your brand been to your site "universe" email subscribers customers
retention 7. In Summary The R/F Model 8.
- It segments your customers by the length of time since their
last purchase, and by the number of lifetime purchases they have
made.
- Recency & Frequency are 2customer attributesknown to highly
influence a customer's futureprobability to make another
purchase
9.
- Recency & Frequency are easy to calculate
- The model is easy to build
-
- historical transaction log
-
-
- the more history the better!
- The Framework is easy to conceptualize
-
- provides intuitive vocabulary
-
- easy to adopt as a common vernacular in your organization
10.
- This presentation will focus on Recency only
-
- To keep it as simple as possible
-
- Recency is generally considered to be more predictive of a
future purchase anyway, frequency simply provides another layer of
insight
-
- Frequency's role is easy to conceptualize
11. Sub Title Building the Framework 12.
- split your yearly calendar into equal periods that make sense
to your business
Season 1 Season 2 Season 3 Jan Apr Jul 13. 0 - 3 months 3 - 6
months 6 - 9 months 9+ months
- the periods/seasons determine the periods for your recency
groups
Recency Groups: Season 1 Season 2 Season 3 Jan Apr Jul 3 months
14. 0 - 3 months 3 - 6 months 6 - 9 months 9+ months
- at the beginning of each season, classify all customers into
their recency groups
Recency Groups: Season 1 Season 2 Season 3 Jan Apr Jul 3 months
15. 0 - 3 months 3 - 6 months 6 - 9 months 9+ months
- Each recency group starts the season with abeginning inventory
(b/i)
Season 5 Season 6 Season 7 Jan Apr Jul b/i = 1000 16. 0 - 3
months 3 - 6 months 6 - 9 months 9+ months
- measure each group's purchase activity over the course of the
season and count how many from each group make a purchase
Season 5 Season 6 Season 7 Jan Apr Jul 3 months $ #buyers = 230
17. 0 - 3 months 3 - 6 months 6 - 9 months 9+ months buyer
rate=#buyers/b/i Season 5 Season 6 Season 7 Jan Apr Jul $ #buyers =
230 =230 /1000 =23% b/i = 1000 calculate the group'sbuyer rate $
18. Title Calculate buyer rates for each recency group 19.
- With predictable buyer rates, the buyer rate can be thought of
as the probability that a member of a given recency group will
purchase next season
-
- Monitor the health of your customer file each season (compare
season over season)
-
- Along with other metrics, like Average Order Value (AOV), buyer
rates allow you to project future revenue and file growth
Seasonal buyer rates 20. Consider what happens in Season 6 to a
customer's recency classification... The Evolution of your R/F
customer file 21. 0 - 3 months
- a '0-3 month' customer who purchases in Season 5 will remain in
the '0-3 months' recency group in Season 6
Season 5 Season 6 Season 7 Jan Apr Jul = "buyer" 22. The R/F
purchasing model Framework is easy 0 - 3 months 3 - 6 months 6 - 9
months 9+ months
- a customer who does not puchase in Season 5 "drops" to the "3-6
month" recency group for Season 6
Season 5 Season 6 Season 7 Jan Apr Jul = "non-buyer" 23. 0 - 3
months 3 - 6 months 6 - 9 months 9+ months
- one has a higher probability to buy in Season 6
Season 5 Season 6 Season 7 Jan Apr Jul 24. Sub Title Lets take
the example to Season 1 - your first season in business... 25. New
Buyer Season 1 0 - 3 months 3 - 6 months 6 - 9 months 9+ months
Recency Group Season 2 Season 3 Season 4 Season 5 Season 6 Season 7
26. New Buyer Season 1 0 - 3 months 3 - 6 months 6 - 9 months 9+
months Recency Group Season 2 Season 3 Season 4 Season 5 Season 6
Season 7 ? 27. New Buyer Season 1 0 - 3 months 3 - 6 months 6 - 9
months 9+ months Recency Group Season 2 Season 3 Season 4 $ Which
outcome would you prefer? $ Future Value 28. New Buyer Season 1 0 -
3 months 3 - 6 months 6 - 9 months 9+ months Recency Group Season 2
Season 3 Season 4 Season 5 Season 6 Season 7 ? 0 0 1 1 1 1 0 29.
Sub Title Over the years your customer database evolves.The more
successful you are at keeping customers RECENT, or keeping them
active, the more value you will extract from your acquired
customers over time 30. New Buyers Season 1 0 - 3 months 3 - 6
months 6 - 9 months 9+ months Recency Group Season 2 Season 3
Season 5 Season 6 Season 7 Season 4 31. Sub Title In closing...
32.
- Provides an effective framework to help you understand the
historic, monitor the present, & project the future performance
of the members of your customer file over time.
-
- Helps you establish (tangible, realistic) baselines
The RF customer file model... 33.
- Robust reporting allows marketers a way to monitor &
measure how their overall efforts impact customers at varying
levels of engagement, a way to manage the customer retention
program:
-
- How did your customer file evolve?(via historical
analysis)
-
- Helps you to identify and target historically lagging
groups
-
- Makes it easy to determine key performance objectives & set
short & long term retention goals
34.
- Really focus in on the effects of your email efforts by
building a RF customer file further segmented by opt-in status
-
- Understand the value of keeping your customers opted in
-consider file fatigue!
-
- Helps you effectively report on test groups (for subject line
or content testing in email, for ex.)
- Further segment by anything!
-
- First purchase channel - organic, paid, direct, email,
etc...
Extentions of the idea... 35. "If you're not segmenting your
data in some business-savvy way, if you're still talking about
averages, you're making gross errors in your analysis -me