Relational vs. Transactional

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Q:  I am hoping you can help answer a question for our team.  By way of introduction, I am the CEO of XXXX.  We are a specialty retailer / restaurant of gourmet pizza, salads and sandwiches.  We would like to know  restaurant industry averages (pizza industry if possible) for customer retention – What percentage of customers that have ordered once from a particular restaurant order from them a second time?  I am hoping with your years of expertise and harnessing data you may be able to assist us with this question. Look forward to hearing from you.

A:  Unfortunately, in those said years of experience, I have found little hard information on customer retention rates in QSR and restaurants in general (if anyone has data, please leave in Comments).  It’s just the nature of the business that little hard data, if collected, is stored in such a way that one can aggregate at the customer level.  The high percentage of cash transactions doesn’t help matters much; there’s a lot of data missing.

Over the years, sometimes you see data leak out for tests of loyalty programs, and of course clients sometimes have anecdotal or survey data, but this is not much help in getting to a “true” retention rate.  More often than not you discover serious biases in the way the data was collected so at best, you have a biased view of a narrow segment.  Often what you get is a notion of retention among best customers, or customers willing to sign up for a loyalty card, but not all customers. And the large “middle” group of customers is where all the Marketing leverage is.

What to do about this predicament?

There are really two issues in your question; the idea of using industry benchmarks when analyzing customer performance, and the measurement of retention in restaurants.

As far as industry benchmarking, two things:

1.  Annual reports for publicly traded eateries may be of help.  Customer loyalty info may be disclosed in these documents or conference calls with Wall Street.  Still, it will probably be of the quality referenced above – narrow in scope or behaviorally biased.

Sometimes you can put snippets of different conversations into an equation that allows you to guess at repeat purchase rate; hospitality analysts often want to understand repeat behavior and do this kind of forecasting.

2.  Ignore the industry benchmarks.  If you have the capability to track repeat rates, simply establish what they are now and use them as internal benchmarks to not fall below or create programs to improve against them. 

Frankly, I tend to discourage using “industry benchmarks” because the kinds of businesses that can really leverage repeat behavior and retention (customer-centric model) are usually *different* from the industry, so using a benchmark (say, from Domino’s) is probably low-balling your potential. 

Not that Domino’s is a “bad” operation, mind you, but they are what they are, they tend to be more on the operational excellence side of the game than customer intimacy (that’s what we called the customer-centric / social approach back in the early 90’s). 

Product leadership, the 3rd value discipline, is pretty much table stakes for anyone in the restaurant biz, and I assume from your business description you just might consider this a primary focus which you then leverage to create power in the intimacy area.  This is essentially the Apple Strategic model.  If the product is not great, the love will not come.

My point is this: without understanding the value discipline and Strategy of a competitor, you can’t know if any benchmark is something you want to compare to, because the business may have a completely different focus than yours.  Worse, using industry averages simply hides any real information you might gain that is actionable for your business.

For example, even though Walmart and Nieman Marcus are in the same business, I don’t think anyone would say they have the same Marketing Strategy or core value proposition.  Walmart is of course the poster child for operational excellence with the end result being value pricing, which flows to the advertising content.  There’s nothing “wrong” with this approach, it simply is what it is, and customer intimacy / relational / social marketing simply doesn’t really fit here.  You certainly can try to be as intimate as possible; but it must be done within the constraints of the model and not reduce operational excellence.  Importantly, this is a “mass” concept, so Push media is the most effective.

Sam’s Club is an example of how one might accomplish this mix.  A “membership” is certainly more customer intimate and allows customized communication, a key component of customer intimate execution.  Again, this flows into the advertising content.  Sam’s gets to leverage the Walmart infra, so they can at the same time maintain a decent level of operational excellence.  Remains to be seen if they could do so without Walmart.

Nieman Marcus on the other hand uses a customer intimate value proposition, and their execution reflects that.  Value pricing is traded off for a high level of customization and personal service, where repeat business is very important since the number of customers this proposition attracts is smaller than the “mass” approach;  you have fewer, but each more valuable, customers.  In this model, mass media is not very effective because the audience is not mass; instead, you rely on the intimacy to Pull customers in, and much more of the Marketing budget is invested not in Advertising, but on in-store (employees, fixtures, locations) and individual communication. 

This relational or customer intimate model is the root of “social marketing” and why any attempt to turn online social activity into some kind of mass media advertising opportunity is a complete Paradox.  A step by step example of optimizing the relationship marketing / social model is here: Marketing Bands Series.  To optimize the social model, you divert Marketing budgets away from Mass Advertising and Push into Pull areas like Usability / Store / Interfaces / Packaging, Customer Service, and Customer Retention.

Given the above, would Nieman Marcus ever consider using Walmart’s customer retention rate as a benchmark?  I think not; this approach would make no sense at all.  The mass model can’t leverage customer retention because it’s not intimate; if you can’t act on the metric, why measure it?  This is not to say Walmart “doesn’t care” about repeat business, of course they do.  But they can’t really lever it because it’s more operationally efficient for them to use the mass approach.

That’s a very long explanation for why I dislike using industry benchmarks but many, many people don’t realize how important this idea is; it’s why on a core business model basis some companies will not be able to realize significant benefits from “going “social”.  So on the whole, I would much rather use internal benchmarks that I can improve on that are aligned with the business drivers and are controllable through my own execution.

From looking at your web site, I’d judge you a Nieman as opposed to a Walmart, so customer retention can be a powerful tool for you. So let’s talk about measuring retention.

“Retention” is a very time-specific concept – over the course of 3 months?  A year?  Five years?  A 20% retention rate over a 5 year period and a 60% retention rate over a 3 month period might both be stunning achievements, if you know what I mean.

So, if you are able to do the analysis, I would pick some marks – 3 month, 6 month, 1 year, etc. – and see what you get for repeat buyer or retention rates.  The slope of that curve will determine where any danger points are that you might take action on. 

For example, if retention falls dramatically from 3 to 6 months, then you know that you should be watching for people who have not transacted in over 3 months, and for  those people you should craft mail / e-mail promotions designed to bring them back.

As often happens with restaurants, there’s probably a good chance that if the person is still living in the area (more on this below), the reason they are not coming back is probably  controllable – they had a bad experience.  A promotion like “We’ve missed you” or “Give us another chance” that is tightly targeted to known defectors will usually pay back quite handsomely in both the short and long term. Defected customers not only visit once on the promo but also (hopefully) have a better experience and re-engage as a repeat visitor.  If your value prop is customer intimate / social, you absolutely must invest in superior customer experience so repeat experiences are rewarding.

If you see some success with this approach, you could then fine tune the analysis to find out if the dropout has a peak in month 3, 4, or 5.  This fine tunes timing of your drop; the closer you can get to the behavior with the message the more effective the campaign will  be.  There is a “peak profitability” timing in one of these months. 

Then the program can be automated, for example: if we don’t see a transaction from this person for 120 days, drop the message.  This way, you end up mailing every month but the audience is completely different and very highly targeted each and every time.  You will find this “right message, to the right person, at the right time” approach is much more profitable than mailing all customers because it directly leverages the customer intimate value prop.

Speaking of mailing all customers, the people who are still active within this 4 month time frame are probably still loyal and you can improve overall margin by not sending these special promotions to those people until they “slip” out of the 4 month window.  There’s no reason to discount to people who are highly likely to purchase anyway.  This is the Pull part of a relationship or social  execution.  What you should be really concerned about are the people who are dis-engaging, where there has been product or service failure.

In fact, in a relational marketing scenario, there is no real need to market to these people at all, you’re basically “preaching to the choir” (example) and doing so is a waste of resources (and often margin).  You will be far better off taking the money you used to spend marketing to the choir and allocating it to in-store, core value proposition ideas.

Many marketing people (especially of the Push variety) find this difficult to understand, but there no more powerful Marketing tool than your value proposition when communicating to the active customer base.  It’s why they are coming back, your Pull is already strong with them.  Why beat them over the head with messages when they are telling you by continued transacting that they like what you are doing?  Wasteful.  (more detailed example)

Finally, in a location-based scenario such as restaurants (and since you are the CEO and not running a single store), you might consider factoring in local uncontrollable churn into any metrics you create as internal benchmarks. 

Households in different areas have different natural churn (move) rates.  Since you have stores in different states, for example, one would expect a lower retention rate from stores that have a higher natural household churn rate.  These stores might be doing very well with controllable churn (product, service) but without the household churn adjustment, they could be unfairly benchmarked “bad”.  HH churn numbers are generally available free from city / state government or the Census.

Hope that helps!


Note to blog readers: Do you see the parallels above to a lot of what is going on in online publishing / advertising / marketing?  If not, see Jonathan Mendez’s Reaping the Ads You Sow for a more direct analysis of the same concept online.  The strength of the web is in Pull, in converting demand, not Push or creating it.  Use offline for Push; that’s what it’s good at, and synch the two to optimize the entire Marketing ecosystem.

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