Re: Ranking customers
This WebDNA talk-list message is from 2003
It keeps the original formatting.
numero = 48273
interpreted = N
texte = You need to determine their average purchasing per day * average number ofdays and when that equals their average purchase cost, they are likely tobuy. This only works for clients who have purchased more than once. You'dhave to bug one-time clients. This is basically just a tool to gague how much a returning customer is going to purchase Today... You can send out promotions based on that dollar value, or on the likelyhood that they will purchase soon.Variables:[date] Today's Date[early_date] Earliest Purchase Date[last_date] Last Purchased DateGenerated variables:[ave_purch_day] Average Purchase / Day[ave_next_purchase] Average Revenue next Purchase[early_to_today] Days from Earliest Purchase until today.[last_to_today] Days from Last Purchased Date until today[ave_purchase] Average Purchase[ave_days] Average days between purchasesHow to figure it out:ave_purchase=(average of purchases)ave_days=Average(Purchase 2 date - Purchase 1 date (Days between 2nd purchase and 1st, etc)Purchase 3 date - Purchase 2 dateToday's Date - Last Purchase date)early_to_today=[math]{[date]}-{[early_date]}[/math]last_to_today=[math]{[date]}-{[late_date]}[/math]ave_purch_day=[math][ave_purchase]/[ave_days][/math]ave_next_purchase=[math][ave_purch_day]*[ave_days][/math]When [ave_next_purchase] is greater than or equal to [ave_purchase] then thecustomer is most likely to buy something else and should be sent a promo.This can be based on how much the average purchase is. you can get them totry to buy a more expensive item, or you can offer them a deal based on howmuch they spend on average.I don't know if this helps at all, but it's what I came up with quickly. I have an excel spreadsheet that outlines it fairly well if you would like it.-- Matthew C. BohneWeb DeveloperSandusky Register314 W. Market St.Sandusky, OH 44870419-625-5500 ext. 253matthewbohne@sanduskyregister.comhttp://www.sanduskyregister.comOn Sunday, March 2, 2003 9:11 PM, WJ Starck
wrote:>We'd like a way to rank our customers so that we can target our better >customers with select promotions. One way would be to rank solely based >on $ amount, but that probably doesn't tell the whole story. For >example, someone might have purchase $750 from us on one order, and >then never returned.>>Accordingly, I imagine it should be a weighted mixture of total $ >amount purchased (+ weight), average $ purchase amount (+ weight), >total number of purchases made (+ weight), frequency of purchases (+ >weight) and time since last purchase in days (- weight)>>Any statisticians out there care to weigh in (no pun intended)?>>Comments, ideas, suggestions appreciated...>>>-->>Will Starck>NovaDerm Skincare Science>http://www.novaderm.com>wjs@novaderm.com>>>------------------------------------------------------------->This message is sent to you because you are subscribed to> the mailing list .>To unsubscribe, E-mail to: >To switch to the DIGEST mode, E-mail to >Web Archive of this list is at: http://webdna.smithmicro.com/>-------------------------------------------------------------This message is sent to you because you are subscribed to the mailing list .To unsubscribe, E-mail to: To switch to the DIGEST mode, E-mail to Web Archive of this list is at: http://webdna.smithmicro.com/
Associated Messages, from the most recent to the oldest:
You need to determine their average purchasing per day * average number ofdays and when that equals their average purchase cost, they are likely tobuy. This only works for clients who have purchased more than once. You'dhave to bug one-time clients. This is basically just a tool to gague how much a returning customer is going to purchase Today... You can send out promotions based on that dollar value, or on the likelyhood that they will purchase soon.Variables:[date] Today's Date[early_date] Earliest Purchase Date[last_date] Last Purchased DateGenerated variables:[ave_purch_day] Average Purchase / Day[ave_next_purchase] Average Revenue next Purchase[early_to_today] Days from Earliest Purchase until today.[last_to_today] Days from Last Purchased Date until today[ave_purchase] Average Purchase[ave_days] Average days between purchasesHow to figure it out:ave_purchase=(average of purchases)ave_days=Average(Purchase 2 date - Purchase 1 date (Days between 2nd purchase and 1st, etc)Purchase 3 date - Purchase 2 dateToday's Date - Last Purchase date)early_to_today=[math]{[date]}-{[early_date]}[/math]last_to_today=[math]{[date]}-{[late_date]}[/math]ave_purch_day=[math][ave_purchase]/[ave_days][/math]ave_next_purchase=[math][ave_purch_day]*[ave_days][/math]When [ave_next_purchase] is greater than or equal to [ave_purchase] then thecustomer is most likely to buy something else and should be sent a promo.This can be based on how much the average purchase is. you can get them totry to buy a more expensive item, or you can offer them a deal based on howmuch they spend on average.I don't know if this helps at all, but it's what I came up with quickly. I have an excel spreadsheet that outlines it fairly well if you would like it.-- Matthew C. BohneWeb DeveloperSandusky Register314 W. Market St.Sandusky, OH 44870419-625-5500 ext. 253matthewbohne@sanduskyregister.comhttp://www.sanduskyregister.comOn Sunday, March 2, 2003 9:11 PM, WJ Starck wrote:>We'd like a way to rank our customers so that we can target our better >customers with select promotions. One way would be to rank solely based >on $ amount, but that probably doesn't tell the whole story. For >example, someone might have purchase $750 from us on one order, and >then never returned.>>Accordingly, I imagine it should be a weighted mixture of total $ >amount purchased (+ weight), average $ purchase amount (+ weight), >total number of purchases made (+ weight), frequency of purchases (+ >weight) and time since last purchase in days (- weight)>>Any statisticians out there care to weigh in (no pun intended)?>>Comments, ideas, suggestions appreciated...>>>-->>Will Starck>NovaDerm Skincare Science>http://www.novaderm.com>wjs@novaderm.com>>>------------------------------------------------------------->This message is sent to you because you are subscribed to> the mailing list .>To unsubscribe, E-mail to: >To switch to the DIGEST mode, E-mail to >Web Archive of this list is at: http://webdna.smithmicro.com/>-------------------------------------------------------------This message is sent to you because you are subscribed to the mailing list .To unsubscribe, E-mail to: To switch to the DIGEST mode, E-mail to Web Archive of this list is at: http://webdna.smithmicro.com/
Matthew Bohne
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