Managing Your Customer Database
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Managing Your Customer Database

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Using a purchase recency/frequency framework to monitor the health of your customer file, gauge your customer acquisition and retention programs, and target email campaigns.

Using a purchase recency/frequency framework to monitor the health of your customer file, gauge your customer acquisition and retention programs, and target email campaigns.

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Managing Your Customer Database Managing Your Customer Database Presentation Transcript

  • A Recency & Frequency purchasing model Framework Managing your customer database
  • Recency & Frequency classifications are powerful because they can serve as surrogates for determining level of customer engagment
    • 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...
  • know your brand been to your site "universe" customers
  • know your brand been to your site "universe" customers customer acquisition
  • know your brand been to your site "universe" email subscribers customers retention
  • In Summary The R/F Model
    • 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 2 customer attributes known to highly influence a customer's future probability to make another purchase
    • 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
    • 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
  • Sub Title Building the Framework
    • split your yearly calendar into equal periods that make sense to your business
    Season 1 Season 2 Season 3 Jan Apr Jul
  • 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
  • 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
  • 0 - 3 months 3 - 6 months 6 - 9 months 9+ months
    • Each recency group starts the season with a beginning inventory (b/i)
    Season 5 Season 6 Season 7 Jan Apr Jul b/i = 1000
  • 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
  • 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's buyer rate $
  • Title Calculate buyer rates for each recency group
    • 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
  • Consider what happens in Season 6 to a customer's recency classification... The Evolution of your R/F customer file
  • 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"
  • 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"
  • 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
  • Sub Title Lets take the example to Season 1 - your first season in business...
  • 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
  • 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 ?
  • 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
  • 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
  • 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
  • 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
  • Sub Title In closing...
    • 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...
    • 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
    • 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...
  • "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