Hi there, Jim Novo here. Folks seem pretty excited about learning how to do their own Drilling Down, and that’s just great. Here are the questions I get most often from people wandering around the site. If you’ve got a question, send it to me!
Q: What the heck is this site about?
A: The site was designed to teach you how to get started with High ROI Customer Marketing concepts even if you don’t have any previous experience. The primary tool used is simple customer models anyone can create with a spreadsheet. These models tell you what offers to make and when to make them to drive maximum profits.
Q: You say these techniques work for “any size business.” How can that be? What kind of business do they really work for?
A: The Drilling Down approach uses customer activity profiling. Customer behavior is pretty much the same in a small or large business scenario; if visits or purchases are important to the profitability of the business, the Drilling Down approach works. These techniques work for both online and offline businesses, as long as customer transaction data is captured.
The tools used by each size of business are different, not the ideas driving their use. For example, a small business may be using MS Excel or Access to keep track of customers, and a large business would be using a CRM app. The small business would be exporting targeted customers to a file; large business would be using the Drilling Down ideas to build rules for the CRM engine. That said, different types of businesses will benefit most from different parts of the Drilling Down approach.
If you have long sales cycles, (durable goods like cars, appliances), sell very expensive products (enterprise software), or are a service business with ongoing billing which doesn’t vary much month to month (utilities, phone, ISP) then you will probably want to start with the Latency Model.
If you have tons of low value transactions with your customers – page views being a prime example – say in publishing / ad-supported / content oriented web sites, or are in retail with a low and narrow price range (books, CD’s), you should start out with the Recency Model.
If you are a general retailer with a wide spread of price points, either B2C or B2B, then you want to go with the RFM Model.
Ultimately, you will mix and match these 3 basic models to fit your business plan, using the models for different purposes or combining parts of them in unique ways to predict the Customer LifeCycle and create High ROI Customer Marketing programs. But that’s not where we start; that is where we finish.
Q: What’s an “activity-based” profile, and why is it important?
A: Activity-based profiles or models are more powerful than demographic profiles because they are about “action,” they attempt to predict the future. Will the customer visit again? Will they buy again? Will they respond to a promotion? These are the types of questions activity-based profiles answer. You will not get these answers from knowing a customer is 45 years old, lives in New York, and likes cats.
That said, adding demographics to an activity-based profile can be very powerful, because the demos supply some of the answers to “why” the customer may behave in the way predicted by the activity-based profile. This allows you to write better copy for promotions and more carefully target groups of customers.
Q: What kind of customer data do I need?
A: The least data you need is a group of customer transactions from a single source (purchases or page views, for example) having a date of the activity and customer identifier of some kind. Any data you have beyond this just improves your ability to profile your customers. You can use online data, offline data, or a combination of the two.
Q: What methods does Drilling Down use?
A: Drilling Down uses my own derivations of the classic customer behavior model RFM. The other two models – Latency and Recency – are related concepts. Latency is a special form of Recency, and Recency is a core element of the RFM model. So while it seems there a 3 models, the core concepts driving all three are the same. Learn one, you learn them all. Why 3 then? Because if all you have is a hammer, everything is a nail. Each model is good for some things and not as good for others.
The RFM model was developed in cataloging and TV Shopping for predicting the likelihood of a customer responding to promotions and judging a customer’s value to the company. Interactive customers behave differently than offline customers, so the “classic” RFM approach has to be modified somewhat for use on the ‘Net, and is simplified to make it easier to use for people new to data-driven marketing. These modifications do not make the techniques less effective offline, because the RFM model is being used in a different way than it has been traditionally used in mail order. This is not your father’s RFM.
And don’t think it’s just for retailers. That’s a mistake the old RFM made. The new RFM can be used in virtually any business, for example, in a Hair Salon or B2B Software business.
Q: Why is the Drilling Down approach unique?
A: Most books or articles on using RFM and related techniques are difficult to digest and hard to follow. They show you the theory but don’t teach you how to actually construct and implement it yourself. This book shows you how to actually profile and score customers, step by step, in simple language, with a spreadsheet (or any other program you want to use or write yourself to do the scoring – the business rules are provided). Then it shows you how to use these profiles like the big guys!
But the models are just where it all starts. This book extends the basic theories of RFM into a number of tools you can use to improve customer retention, measure the effectiveness of content changes to your site, put a valuation on your business, and more.
Along this journey you will also learn how ROI, Customer LifeCycles, LifeTime Value (LTV), and all the other little gems of data-driven marketing link together for a total picture of how marketing with customer data works.
Q: What’s the output of all this, what do I get in the end?
A: In the most simplistic case, each customer gets a “score” to start off their profile. This score ranks the likelihood of a customer to respond to a promotion relative to all the other customers. The score also can be used as a measure of a customer’s future value to your business. As the book advances, you see how to use these scores in a lot of different ways, both alone and in combination with any other customer data you may have. The actual “physical” output favored in the book is graphs and charts, so you can “visualize” customer retention and defection, and pick targets for marketing campaigns by looking at these graphs and charts.
Q: What if I don’t sell anything on my site? Can the book help me?
A: Absolutely. Any activity a customer generates (a page view or log-in, for example) can be used in profiling. Content only sites can benefit from using profiles to determine who their best customers are, what parts of the site they visit, and what areas could use improvement. Just because a page has high traffic doesn’t mean your best customers are using it. What if you found out your “stickiest” customers actually hang out more in a low page volume area? This would have tremendous implications for the site design and content. Profiles can also be used to assess the effectiveness of changes made to the site. There are solid examples of these approaches provided in the book.
Q: What about customer privacy?
A: Customer behavior profiling uses actual activity like purchases or page views for profiling. No intrusive personal questions need to be asked, and the customer activity used for profiling occurs through the normal course of business. For example, customers have a reasonable expectation you will document the date of a purchase; how else would you manage your business? Same thing for page views. In addition, behavioral profiling is more concerned with when activity occurs and how often, not the specific content of the behavior (area of the site, for example). While this more specific information can be very useful, it’s not required. For a detailed example of this “anonymous profiling” approach, see the tutorial on Comparing Future Value.
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