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Drilling Down Newsletter # 22 - July 2002 - B2B Software Example, The Cost of Queuing Customers?Drilling Down - Turning Customer Get the Drilling Down Book! Check out: The Marketer's Common Sense Guide to E-Metrics - 22 benchmarks to understand the major trends, key opportunities, and hidden hazards your web logs uncover. To find out more about this topic: click here Prior Newsletters: In This Issue: This month we've got the usual "best of" Customer Marketing article links, the third installment of the B2B Software Real World Example, and a fellow Driller wondering how to measure the cost of queuing-up customers. A special note: I'm on a panel at the upcoming Search Engine Strategies 2002 in San Jose, CA Perfecting Paid Listings This is an "advanced class," for people who have some experience with paid listings but are looking to really crank up the ROI on them. Copy, tracking methods, tips and tricks, all up for grabs. Yours truly is of course addressing metrics and tracking... If you're around the show, please try to say Hi, I always like to put a face with the typing! OK - Let's do some Drillin'! Note to web
site visitors: These links may 10 Reasons to Do Web Site Analysis From an Ugly Duckling to a Swan Latency: The B2B Software Example #3 Why does this matter to the CFO? Cash flow is decreased because sales don't happen as quickly as they did last year - there is more profit in the later add-ons. If this is not enough information, you can read Part One of this case here, Part Two here. Fearing another phone call right away to the CIO, the CFO thinks: What I have here is change. There has been a significant change in the way this business works for some reason. Change doesn't happen in a vacuum though, something must have caused these changes to happen, a significant event now being reflected by these average weeks between add-on purchase numbers. What could it be? The CFO remembers the heads of biz dev and marketing saying the company was "penetrating the overall market more deeply, and as we penetrate further and further, add-on sales seem to have slowed." Was this the change the CFO was looking for? What did it really mean, in terms of how the business may have changed? Getting the heads of biz dev and marketing on the phone again, the CFO asks if this market penetration situation had created any changes in the way the company does business. The CFO hears for the first time about a new trade campaign and a new sales person hired to address a particular market segment. This is must be the change the CFO was looking for! Gingerly, most humbly, the CFO calls the CIO once again. This time, the CFO wants to see average number of weeks between add-on installs by add-on by salesperson. After a promise to review the hiring freeze is extracted by the CIO, this report is delivered: Average Weeks between Add-On Purchases It takes these customers on average 14% longer to purchase any add-on - 9.8 weeks versus 8.6, or 1.2 weeks. Over the entire purchase LifeCycle of the add-ons, this increases the purchase cycle by 4.8 weeks (1.2 x 4). If this new segment is doing a lot of dollar volume compared with the old segments, this could significantly affect sales and make add-on purchases look soft - even though they are in fact getting purchased! At his moment, the head of biz dev appears in the door with another person who turns out to be new Salesperson 4. The CFO looks up and the head of biz dev, somewhat sheepishly, introduces the new salesperson. "Glad to meet you," the CFO says. "By the way, can you tell me something? Do the customers in your new segment purchase and install our add-ons in the order we suggest in our operations manuals?" "No, they don't" said Salesperson # 4. They install them in a different order, because they are having some difficulty installing a couple of the add-ons, and usually delay those to the end of the purchase cycle when they have more experience with the applications. Is there something we can do about that?" The CFO just smiles, and thinks: Looks like I just found the money to pay for unfreezing some hiring in IT. "I think so," the CFO tells new Salesperson #4, calculating the improvement in cash flow if these add-ons were installed faster on the fly. "I really do think so." That's it for the B2B Software Example using Latency. The Latency metric is a rock-solid behavioral marketing tool - a bit blunt, but always a good place to start, sort of like the rough sandpaper or the ripsaw. I often find when beginning a project, hunting around for Latency variances does not provide the answer, but serves up plenty of clues to get you going in the right direction. The B2B Software Example points out the need for reconciling the differences between financial and customer
accounting in a customer-centric business. For more on how this
concept applies to CRM implementation, you might want to read this case study I
wrote, or�the companion article on how this issue�affects employee incentive
plan design: A: Frequently Asked Question for sure, and not one there is a lot of statistically believable data on...at least that people are willing to release. Kind of a sensitive subject, as you might think... Q: I work for a large bank. We have perceived queuing problems in some of our branches - generally due to layout restrictions. I say perceived because although a queue is long, it moves fairly quickly with the actual wait time to see a teller often less than 5 minutes (considered at par with our competition). However, customers grumble when they walk into the branch and see the line and continue to grumble out loud until they reach the teller and then continue to communicate their dissatisfaction to the teller. Do you know if any work has been done in this area with other large companies that tend to have long queues (like airline ticket counters, large retailers)? Thanking you in advance for your response. It's just the way the business works. Given the choice, which do you think consumers would select of the two alternatives, higher product prices or shipping charges that are fair and reflect what the consumer knows is tangible cost of delivery? Sure they complain - but they still buy. People have always hated queues. And why not? They are frustrating and perceived as a waste of time. And the alternative is? Raise prices to the consumer to cover extra staffing? But if you run your business correctly, you price with queues in mind and manage costs so that you still make a profit. It's just the way the business works. Given the choice, which do you think consumers would select of the two alternatives, queues or higher prices? So perhaps "queues" are being raised as an issue to deflect other service problems which are the real cause for whatever angst the company has, something to blame which is not really the causation. Regarding "solving your problem," I don't like benchmarking as a solution. Your bank has a unique persona created by advertising, staff training, corporate initiatives, the kind of customers it attracts, and so on. How can you benchmark against other companies who have a completely different persona? And - most importantly - does benchmarking really provide any insight that is financially relevant and actionable? What action do you take knowing this information? What if their bank queues up low value customers, and you are queuing up high value customers? A disastrous decision could result. Sounds to me like this issue is location-driven, which is perfect for an internal study. What the real question is here, I expect, is this: are these queues costing the bank money, and how much would it be worth spending to fix it (ROI), if at all? If this problem is specific to branches, set up a simple metric and use it to compare branches with no/short queues to branches with frequent/long queues. Perhaps annual churn of high total value customers? Annual churn of multi-product customers? Percent defection of whatever-you-call-best-customers? Take three branches with long queues and compare them to three branches with no queues. Do the queues make a difference where it matters - on the bottom line? What if your best, most profitable customers never are in a queue, and so do not churn at a higher rate in branches with queues versus branches with no queues? And then what does the bank think of solving queue problems? Let me know if you have any other questions or need further help
with this issue. A great question, and a perfect example of one
that needs to be asked in the context of customer value rather than
customer volume. That's it for this month's edition of the Drilling Down Newsletter. If you like the newsletter, please forward it to a friend - why don't you do this now while you are thinking of it? Subscription instructions are at the top and bottom of the newsletter for their convenience when subscribing. Any comments on the newsletter (it's too long, too short, topic suggestions, etc.) please send them
right along to me, along with any other questions on customer Valuation,
Retention, Loyalty, and Defection right here. Copyright 2002, The Drilling Down Project by Jim Novo. All rights reserved. You are free to use material from this newsletter in whole or in part as long as you include complete attribution, including live web site link and/or e-mail link. Please let me know where & when the material will appear. |
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