DRILLING DOWN: Turning Customer Data into Profits with a Spreadsheet - Third Edition (Paperback)

~ (Author) "It was a day just like any other day..." (more)
Key Phrases: discount ladder, breakeven response rate, customer lifecycle, Drilling Down, Jim Novo, Monetary Value (more...)

Editorial Reviews

Product Description

The addition of the Internet as a commerce and communications channel has forced many companies into direct contact with their customers for the first time, and kicked off the accumulation of transactional information companies have never had access to before. This situation spawned a tremendous amount of demand in the marketplace for "solutions", including CRM, the newer CLM (Customer LifeCycle Management), CRP (Customer Relationship Planning), and all the related approaches such as 1-to-1 Marketing, Relationship Marketing, Customer Retention Marketing, and Customer Loyalty Marketing.

This is a very confusing situation for most people, because they lack experience using customer data for marketing, and have been led down the wrong path before. For example, the rush to capture demographic data completely ignored what experienced database marketing people know - behavioral data is much more powerful as a marketing tool than demographics ever will be; it is also more accurate and easier to capture. If you want to know the answer to behavioral targeting questions like "will they buy or visit again?", demographic information won't help.

This fact may make things clearer for you: all of the data-related marketing hype boils down to tracking and understanding the customer LifeCycle. If you can understand this root LifeCycle idea, you can mold it to your needs and available resources and leave the marketplace noise (and costs) behind.

What is a customer LifeCycle? It is simply the behavior of a customer with your company over time. Customers begin a relationship with you, and over time, either decide to continue this relationship, or end it. At any point in this LifeCycle, the customer is either becoming more or less likely to continue doing business with you, and demonstrates this likelihood through their interactions with you.

If you collect data from these interactions (purchases for commerce, visits, downloads, or log-ins etc. for publishing) you can use this data to predict where the customer is in their LifeCycle - more or less likely to do business with you. If you can predict where customers are in the LifeCycle, you can maximize marketing ROI by targeting customers most likely to buy, trying to "save" customers who have declining interest, and not wasting money on customers unlikely to continue doing business with you.

Remote selling companies like TV Shopping channels and catalogs have been using a LifeCycle approach for years, and have developed methods for using LifeCycle information to increase profitability by driving customer sales higher while reducing marketing costs. It's a proven method, and it works with interactive customers very well. I know; as VP of Marketing and Programming for Home Shopping Network, it was my responsibility to maximize the value of TV, Internet, and Catalog customers. If you understand and can predict the LifeCycle of a customer, you can answer a lot of other important questions, including:

How can we compare the long-term effects on customer value of our different advertising approaches and product selections / pricing?

When will a customer stop buying or visiting and how can we most cost effectively delay this event?

How can we measure the impact on customer value of operationally oriented changes such as the implementation of CRM or changes in web site design?

What is the Lifetime Value of a customer relative to other customers and how do we increase it cost effectively?

My book (with free software application, more on this below) outlines a very simple method for creating and tracking customer LifeCycle metrics, and using these metrics to increase sales while reducing costs. There are no special requirements for implementing this method; you will use an Excel spreadsheet as the tool, and no programming skills are required. All you need are dated customer transactions, each having a customer ID.

The book explains in very simple terms exactly how to take your customer transactions, create a database of them in an Excel spreadsheet, and "score" each customer with LifeCycle metrics. These scores literally tell you where the customer is in their LifeCycle relative to all the other customers. Then the book shows you how to use these scores to dramatically improve the ROI of your customer marketing by choosing customers to target and customizing offers based on their LifeCycle scores.

Small companies (under 65,000 customer transactions, the limit of an Excel spreadsheet) can score all their customers by hand in under 30 minutes using an Excel spreadsheet. For larger companies (up to 100,000 customer transactions) or smaller companies with light technical capabilities, a MS Access application is included free (as a download) with the book (see download instructions at the end of the Introduction). The application will import all your customer transactions and create the LifeCycle scores for each individual customer. You can then view the scores for each customer, choose customers to target for a campaign, and export the targeted customers for campaign execution.

If you run a larger business (over 100,000 customer transactions in the database), the business rules for scoring customers are described in detail and can be put into action with a simple query system. Customer LifeCycle scores will help you solve the "drowning in data" problem by allowing you to organize your customer data/reporting around the LifeCycle and future value of customers.

This approach paves the way for any CRM efforts you may be considering, because the scores allow you to establish LifeCycles and project Lifetime Values for your customers, two metrics critical to the success of CRM and forecasting the ROI of CRM implementation. Using the methods in this book, you can get your company "half-way there" and "practice" analytical CRM before you install it. No vaporware, no compatibility issues, just a proven behavior-based profiling method you can implement yourself and use to start making more money with customer marketing. Call it "CRM Lite".

For years TV Shopping and catalog companies have organized their marketing activities around the LifeCycle of a customer, and now they are paving the way on the Internet with very high success rates and profitability. Find out how they are doing it (and start doing it yourself) with this book.

From the Publisher

Here's some Frequently Asked Questions on Jim Novo's book:

Q: You say these techniques work for "any size business". How can that be? What kind of business does it work for?

A: The Drilling Down approach uses customer activity profiling. Online 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.

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, the Drilling Down approach is probably least useful in very high ticket B2B shops, where sales cycles are quite long and usually handled by salespeople. Drilling Down is a "direct to customer" approach, and works particularly well in online content publishing and retailing.

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 visits, 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.

Q: What methods does Drilling Down use?

A: Drilling Down uses derivations of the RFM method 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. There are three important differences though. First, the original RFM model is a "one shot" model, taking a snapshot of customer behavior at a point in time. The Drilling Down method looks at customer behavior over time (Customer LifeCycles), which greatly improves on the original model. Second, interactive customers behave differently than offline customers, so the "classic" RFM approach has to be modified for use on the 'Net. Third, the original RFM model is difficult for people without a background in database marketing to deal with. The Drilling Down method simplifies the process to make it easy for people new to data-driven marketing to use, and adds the capability of using visual displays (graphs and charts) of customer behavior to aid in decision making.

Q: Why is the Drilling Down approach unique?

A: Most books or articles on the Latency, Recency, and RFM models are difficult to digest and hard to follow. They show you the theory but don't teach you how to actually construct and implement High ROI Customer Marketing campaigns yourself. This book shows you how to profile and segment or 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 the results like the big guys do to increase profits!

This is just where it starts, though. 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, LifeTime Value, customer LifeCycles, 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, and is a measure of a customer's future value to your business. The score allows you to rank your customers by where they are in the customer LifeCycle. 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 visit or download, 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.

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Product Details

• Paperback: 356 pages
• Publisher: Booklocker.com, Inc.; 3 edition (June 18, 2004)
• Language: English
• ISBN-10: 1591135192
• ISBN-13: 978-1591135197
• Product Dimensions: 8.4 x 5.4 x 0.9 inches
• Shipping Weight: 1 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars  See all reviews (4 customer reviews)
• Amazon.com Sales Rank: #291,887 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

2 of 2 people found the following review helpful:

5.0 out of 5 stars Excellent beginners guide to statistical marketing technique, July 1, 2003

By	Alan Eager (Charleston, SC USA) - See all my reviews (REAL NAME)

This review is from: Drilling Down: Turning Customer Data into Profits With a Spreadsheet (Paperback)

This is truly a great guide. The author assumes no prior knowledge and walks you through many examples about how to do Recency and Frequency (RF) scoring, hurdle rates, Lifetime value and how to apply it to your direct marketing campaigns. I got a lot out of this book as is deals with the scientific nature of transaction and customer analysis.

A little pricey, but you can get the pdf from the website...

5.0 out of 5 stars The How-to Guide for Unlocking the ROI from your customer data, January 24, 2009

By	A happy customer... - See all my reviews

Jim is a straight-forward guy and this book cuts to the chase. Are you segmenting your customer data... how hard? If you are not factoring in recency/latency and the previous purchase behavior to predict and quantify things like long term customer value, intent to repurchase, subscriber valuation you are probably offering incentives to customers who would have bought otherwise and lowering your margins and in turn letting customers who have fallen out of the buying cycle disappear completely. With the economy pinched your best ROI is in your customer data and you need to spend the $99 for this book as the key to unlock it. Get the book, your XLS data and get after it. Jim writes as he speaks, good author and even better guy

5.0 out of 5 stars Priceless treasure, June 23, 2008

By	Derick Jose (Bangalore, India) - See all my reviews

This is one of the most actionable book on Analytics I have seen in the market. Lots of specifics around scenarios which tell a layman how interplay between recency , frequency across various industries can be used to derive simple insights. One word of caution though. The RFM metrics have to be seen in the context of the business process cycle and the different rhythms of the industries they apply in. In short Jim makes the complex , simple .