Category Archives: Driller Q & A

Marketing into a Downturn

Analytical Culture, DataBase Marketing, Driller Q & A, Newsletters

Jim answers questions from fellow Drillers
(More questions with answers here, Work Overview here, Index of concepts here)

Q: I have been asked to create a whitepaper on marketing strategy and tactics for a down or recessionary market. In your studies and travels have you come across any literature or have thoughts of your own that I may quote?

A: Well, I suppose someone has written something about it somewhere. The trades write about it for every downturn! But I don’t know of any primary work on the topic – case studies, research, etc.

I do know that when we get into a down / recessionary market my phone rings more and I work a lot harder. The “new client” customer retention business is counter-cyclical; people always wake up during the soft times and say, “Hey, if we can’t drive new customer volume, maybe we can sell more to existing customers!”. You know, the CEO or somebody read that somewhere…

The problem with this kind of thinking is, in most cases, it’s already too late to do anything about customer retention.  That’s not something people generally want to hear. I then say, “The economy is cyclical.  Do you want to be prepared for the next downturn?”

The people who answer yes to that question will often become clients; those looking for the “quick fix” generally won’t become clients – but they call again into the next downturn…

It’s a strategy thing, you know? Long term thinking? But I digress…

The insidious thing about customer defection is that it’s always there, eroding the asset base, wasting away the hard work. But people don’t see it until the flow of new customers shrinks, and then all of a sudden, the defection issue is laid bare.

This is why the retention business is so counter-cyclical; why “discovery” comes in the downturns.

What you normally find is whatever business change / policy / product is causing customer defection, it takes as long to build up the customer asset again as it did to destroy it. Here is a real-world example.

A retailer makes a significant change in the types of products it sells, because it wants to “attract more new customers”. For existing customers, revenue per customer starts to fall. This fact is masked on the revenue side by the attraction of new customers to the new products – for a while. But it ends up these new customers, in terms of revenue per customer, have a value about 30% less than the old customers? So even though new customer adds remain consistent, sales start to drop, and over time drop by 30% as old customers defect and are replaced by the new customers worth 30% less.

Two years into this process, a downturn in the economy causes more attention and analysis of the customer base, and this issue is exposed. Surprise! The newer kind of customers defect at a higher rate and in a shorter time than the old type of customers.

New management is brought in, and they decide to go back to selling more of the “older” product to attract the higher value customer. Once they make the switch, it takes just as long for sales to get back to where they were as it did to create this problem in the first place – 2 (very long) years.

And that’s why it is so tough to deliver a “quick fix” to these kinds of problems. They are systemic in nature and because you are talking about the value of a customer over time, take time to fix.

So, it may well be that your advice should ultimately be “use this downturn to prepare for the next one”, if you know what I mean. Investigate, learn, and understand what happens this time, so you know what to do next time. In terms of action items, a few:

1. Analyze the customer base, to understand the source of customer value. Who are the best customers, where do they come from Which media, sales persons, product lines, services, geographies, etc. create the “best customers” for the business?

2. Analyze these best customers, and understand their behavior. What would be a warning sign that these best customers – who are probably responsible for the lion’s share of your profits – are cracking into the downturn? Slowdown in orders per month, average order size, number of contracts, whatever the relevant metrics are.

3. Track a handful of these customer metrics and see how they change as the economy slows. These metrics will be a map for predicting actual trouble the next time – predicting trouble even before everyone is already talking about “a downturn”. This gives you the extraordinary advantage of lead time over your competition in reacting to the downturn in business.

4. Complete the same 3 steps above for medium value customers and low value customers, if you have the resources.

5. Now, fully understanding what you have to work with (perhaps for the 1st time?), what is the strategy for a downturn?  Generally, it would consist of a reallocation of resources away from lower productivity to higher productivity activity, in order of importance:

a. For best customers, how do we keep them?
b. For mid value customers, how do we grow them?
c. For low value customers, how do we reduce costs to acquire or service them? Note I do not advocate “firing” customers, but you certainly can cut back on acquiring as many low value ones.

For each group, you should have a specific (and probably different) strategy and set of tactics. What a lot of folks don’t understand is there is almost always a truly remarkable difference between these customer groups, and any “one size fits all” edict or direction is bound to screw up the business, just like the example of the “new customer” effort from the retailer above.

For example, we know that marketing spend generally softens in a downturn. Companies cut back on marketing because they feel like they are “pushing on a string”. They cancel or don’t buy advertising, they fire salespeople. This is the wrong move. The old saw about buying more marketing into a downturn to “grab share” can also be the wrong move, though has some “accidental” positive effects.

The company should invest in more marketing, but not across the board. They should buy the right marketing, the marketing that generates the best quality customers.

They should reallocate marketing resources away from generating “c” customers towards generating “a” customers. If you know trade shows generate leads which turn into “a ” customers and online ads generate leads that turn into “c” customers, you take the money you spend online and book more trade shows. You let go of salespeople that generate “c” customers and use that salary to bonus salespeople generating “a” customers.

Of course, this analysis and planning is an exercise that should be done all the time, not just into a downturn. A business should always be trying to understand where customer value comes from and how it is created. But unfortunately, this issue most often comes up going into a downturn.

You’ll have to excuse me now, the phone is ringing again…

Jim

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Commerce Channel Management

Brand Management, Driller Q & A, Newsletters

Jim answers questions from fellow Drillers
(More questions with answers here, Work Overview here, Index of concepts here)

Q:  We are a manufacturer with a cool product not really on the net and right now, but we are entering stores.  I wonder, is it wise to try to sell on the net before retail markets have the products or not – is it better to hold off until the retail markets first have the products and then launch them onto the net?  Does the net really help sell products or does it create copy cats?  Trying to find the best way to go – any advice would be greatly appreciated.

A:  Great question.  Answer is “it depends” and it difficult to be more specific without knowing more about the product and your marketing plans.  But in general, if you want to optimize the profitability of the product launch and you are paying for media, you should think about these choices as a “chain” or series of events each with a specific but interconnected strategy for each channel.

An example would be DRTV or infomercial products, which generally are launched at a higher price into the spot TV channel (cable networks, etc.).  Here sales are made at a very high margin but the volume is generally low; the Objective is to generate awareness and hopefully make a profit, but breaking even is OK because you essentially have the media “free” and that will help drive the next step.

Based on all the awareness you have generated with TV spots, you then can go to the TV shopping channels and say, “Look, people know this product because we have already pre-sold it for you.  We will let you sell it at a lower price if you will drive volume. And that’s typically exactly what happens; most of the profit on the product is made here.

From the spot TV, the audience knows the product sells for $19.95 or whatever, so when it is offered at $14.95 on the shopping channel they think it’s a great deal and the volume is tremendous.  Typically, the spot TV would still be running at this stage, though sales from that channel will have peaked.

Once sales get soft in the TV shopping channel, you then introduce the product online and in stores.  This is essentially “end of lifecycle” for the product, where you are simply trying to make sure you don’t get stuck with any.  You sell that at cost plus to the onliners / retailers and they blow them out at $9.95 or so.  You don’t end up wearing the inventory and everybody is happy because the spot TV / TV shopping has generated plenty of awareness, people pounce on the product, and it moves very quickly through retail.  Typically no TV would be running at this stage because you couldn’t sell any at the original price.

Now, I’m not saying you should follow this model.  But what I am saying is the decision you are trying to make is more complex than “should we”, it involves understanding which channel can do what for you and at what price.

For example:

You said you are “entering stores”, but did not say if you / the stores are running any media to support this effort.  If you are not running any media then I would get on the web and sell the product for retail price or higher.  This generates some awareness / demand / trial but preserves the margins of the retail partner, and hopefully your direct profits will cover costs.  You basically get “free media” from the web (as in the spot TV example above) and the retail folks will love it because it will drive sales in their channel.

If you / the retailers are doing a lot of paid media support, then I would not sell on the web until sales through retail get soft.  Then you are in a position to undersell them or liquidate on the web based on the awareness you have generated offline.  This doesn’t mean you should not have a web site, you should, and it should tell people which retail outlets they can buy the product in.

On the other hand, if there is a razor / razor blade model built into the product (think a doll with add-on sets of clothing), you could sell the primary razor product and some of the blades in retail, then develop more targeted / segmented / rare blade offerings that are exclusive to the web for online stores.

Again, it’s very difficult to make the “right” judgment on this question not knowing anything at all about the product, whether there are supplemental / follow-on products, whether there are continuity pieces involved (collections) and so forth; and especially not knowing what the nature of the retail relationship is.

But I think you get the general idea.  You play the strengths of the channels off each other, generally in some sequential way, depending on what the marketing / media plan is and the characteristics of the product.  That is, if you are interested in optimizing media spend versus sales.  If you have an unlimited media / PR budget, then sure, sell it everywhere!

Hope that helps!

Jim

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What’s the Frequency?

Analytics Education, DataBase Marketing, Driller Q & A, Measuring Engagement, Newsletters, Web Analytics

Jim answers questions from fellow Drillers
(More questions with answers here, Work Overview here, Index of concepts here)

Q: I ordered your book and have been looking at it as I have a client who wants me to do some RFM reporting for them.

A: Well, thanks for that!

Q: They are an online shoe shop who sends out cataloges via the mail as well at present. They have order history going back to 2005 for clients and believe that by doing a RFM analysis they can work out which customers are dead and Should be dropped etc. I understand Recency and have done this.

A: OK, that’s a great start…

Q: But on frequency there appears to be lots of conflicting information – one book I read says you should do it over a time period as an average and others do it over the entire lifecycle of a client.

A: You can do it either way, the ultimate answer is of course to test both ways and see which works better for this client.

Q: Based on the client base and that the catalogues are seasonal my client reckons a client may decide to make a purchase decision every 6 months. My client is concerned that if I go by total purchases , some one who was  really buying lots say two years ago but now buys nothing could appear high up the frequency compared to a newer buyer who has bought a few pairs, who would actually be a better client as they’re more Recent Do I make sense or am I totally wrong?

A: Absolutely make sense. If you are scoring with RFM though, since the “R” is first, that means in the case above, the “newer buyer who has bought a few pairs” customer will get a higher score than the “buying lots say two years ago but now buys nothing” customer.

So in terms of score, RFM self-adjusts for this case. The “Recent average” modification you are talking about just makes this adjustment more severe.  Other than testing whether the “Recent average” or “Lifetime” Frequency method is better for this client, let’s think about it for a minute and see what we get.

The Recent average Frequency approach basically enhances the Recency component of the RFM model by downgrading Frequency behavior out further in the past. Given the model already has a strong Recency component, this “flattens” the model and makes it more of a “sure thing” – the more Recent folks get yet even higher scores.

What you trade off for this emphasis on more recent customers is the chance to reactivate lapsed Best customers who could purchase if approached.  In other words, the “LifeTime Frequency” version is a bit riskier, but it also has more long-term financial reward. Follow?

So then we think about the customer. It sounds like the “make a purchase decision every 6 months” idea is a guess as opposed to analysis.  You could go to the database and get an answer to this question – what is the average time between purchases (Latency), say for heavy, medium, and light buyers?  That would give you some idea of a Recency threshold for each group, where to mail customers lapsed longer than this threshold gets increasingly risky, and you could use this threshold to choose parameters for your period of time for Frequency analysis.

Also, we have the fact these buyers are (I’m guessing) primarily online generated.  This means they probably have shorter LifeCycles than catalog-generated buyers, which would argue for downplaying Frequency that occurred before the average threshold found above and elevating Recency.

So here is what I would do. Given the client is already pre-disposed to the “Recent Frequency” filter on the RFM model, that this filter will generally lower financial risk, and that these buyers were online generated, go with the filter for your scoring.

Then, after the scoring, if you find you will in fact exclude High Frequency / non-Recent buyers, take the best of that excluded group – Highest Frequency / Most Recent – and drop them a test mailing to make sure fiddling with  the RFM model / filtering this way isn’t leaving money on the table.

If possible, you might check this lapsed Frequent group before mailing for reasons why they stopped buying – is there a common category or manufacturer purchased, did they have service problems, etc. – to further refine list and creative. Keep the segment small but load it up if you can, throw “the book” at them – Free shipping, etc.

And see what happens. If you get minimal  response, then you know they’re dead.

The bottom line is this: all models are general statements about behavior that benefit from being tweaked based on knowledge of the target groups. That’s why there are so many “versions” of RFM out there – people twist and  adopt the basic model to fit known traits in the target populations, or to better fit their business model.

Since it’s early in the game for you folks and due to the online nature of the customer generation, it’s worth being cautious. At the same time, you want to make sure you don’t leave any knowledge (or money!) on the table. So you drop a little test to the “Distant Frequents” that is “loaded” up / precisely targeted and if you get nothing, then you have your answer as to which version of the model is likely to work better.

Short story: I could not convince management at Home Shopping Network that a certain customer segment they were wasting a lot of resources on – namely brand name buyers of small electronics like radar detectors – was really worth very little to the company. So I came up with an (unapproved) test that would cost very little money but prove the point.

I took a small random sample of these folks and sent them a $100 coupon – no restrictions, good on anything. I kept the quantity down so if redemption was huge, I would not cause major financial damage.

With this coupon, the population could buy any of about 50% of the items we showed on the network completely free, except for shipping and handling.

Not one response.

End of management discussion on value of this segment.

If you can, drop a small test out to those Distant Frequents and see what you get. They might surprise you…

Good luck!

Jim

Get the book at Booklocker.com

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Download the first 9 chapters of the Drilling Down book: PDF