Jim answers questions from fellow Drillers
(More questions with answers here, Work Overview here, Index of concepts here)
Topic Overview
Hi again folks, Jim Novo here.
This time, a Real World question from a practitioner who wants to prove to management they have to spend less to make more money. Spend less to make more? How could that be, and what kind of person would want to go down this road? A real world Driller, of course …
Q: I’m a “long time listener, first time caller,” and a big fan of your site and your approach to data-driven marketing. I also have two copies of your book – one was not enough.
A: Well, thanks for your kind words. I love the talk radio reference, that is so funny. Never though about it like that, but makes perfect sense! Glad to know I’m actually helping people with the book too.
Q: I have a question relating to some work I am doing now with our best customers that other users of your site may have.
I work for a medium sized DTC company selling skincare products (high margin) via space ads, direct mail, and online. Our best customer “Gold Club” has about 8000 members at the moment, although members are being promoted and demoted all the time.
According to my initial analysis, if a member does not purchase a product for more than 60 days, the chances are that they are defecting. I would like to attempt to bring them back with an offer, and leave those that don’t reply for at least 6 months for a deeply discounted “kickstart” offer (although the logistics of sending out very small mailings are a pain.)
A: This is a common and logical approach, particularly for “renewable products.” You don’t say what the product is, but if it is “typical” skincare product, it has a sales cycle very tightly tied to product use. In this case, Latency usually makes more sense to use than Recency as the primary trigger for a campaign.
If you have people on different “supply amounts” (some get 30 day, some 60 day, some 90 day) then it can get confusing and be ineffective to just say “60 day Latency gets contact”. 30 day should get 30 day contact, 60 day should get 60 day contact, etc. in the optimum scenario. You have to, obviously, understand what the costs are to do that and optimize around the schedule with the most bang for the buck overall.
Q: I am having some problems convincing management that these former best customers are a lost cause, they don’t like the idea of “losing contact with our customer base” and want to prolong the contact longer to see if we can bring some of these customers back. In fact, when I first looked at the data around 2000 people hadn’t purchased for at least 6 months, and were receiving mail from us every month at $1 US a pop.
A: This is a very typical attitude in small DTC companies, particularly high margin ones. But what they don’t realize is there is tremendous leverage in there, absolutely tremendous. The question for the owner is something like this: would you give up 10% of annual topline sales for a 30% improvement in annual profits? That should get their eyes sufficiently bugged out to listen a bit more.
Q: Is there any sense in the “losing contact” hypothesis or is it best to let customers go without undue struggle and prevent them from getting to the defection stage in the first place? What about a short “grace period” that includes customers a bit longer than necessary? There may be a situation in which a certain RF group is unprofitable for a DM, but the few people that do repurchase buy again, thus coming into the black again (keeping in mind the high margins.) Any insight you have would be greatly appreciated.
A: Look, most DTC companies blast contact to people up to 2 years after the last purchase. I think that’s silly and wasteful, and you are on the right track. They have to learn to “let go.” The grace period idea is a bit unclear to me, but in general, there is some “optimized” grace period, yes. For example, a customer on a 60-day supply cycle might most profitably be approached 10 days before it runs out, 5 days before it runs out, or 5 days after it runs out, or 10 days after it runs out. When your are talking profit (as opposed to response), there is no way to know without a test of the concept
My suggestion would be do what I call a 30-60-90. This idea is very similar to the “RF Grid” from the Drilling Down book in nature:
1. Segment by supply cycle, if there is one. Don’t mix in “90 day supply” people with “60 day supply people” – if it is efficient to mail them separately. If not, well, this will still work, but won’t be as profitable.
2. Take a 10% random sample of the population by Latency – 30 days before supply runs out (if applicable), 30 days after, 60 days after, 90 days after, 90-120 day after, 120-180 days after, etc if applicable. Execute the mailing to the segments.
3. There should be a 30 day (or larger, depends) window where it is the most profitable to mail based on supply run-out date. It should be very clear how much money is wasted “chasing” dead customers in say, the 120-180 day Latency window.
Use these results as ammo with management, should be glaring proof that targeting “distant” segments versus a more pro-active and behaviorally responsive approach is not optimizing use of budget. If they really don’t care about wasting money, well, not sure what to say – maybe substitute email or direct mail? :)
But if they still don’t want to let go, perhaps say you’ll reallocate the money to really work on the “window size” (for example, even though 120-180 day is not profitable, 120-150 only might be) and test a bi-annual or annual postcard to “the dead,” to keep in touch.
That way you efficiently “scrape the dead” for the few you can get back for very little cost, and focus the majority of the resources where the money is, and simultaneously possibly reducing the tendency towards defection in the first place.
Hope the above helped. Thanks again for the kind words, and good luck with it. Any questions, let me know!
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