Drilling Down: Turning Customer Data Into Profits With A Spreadsheet

Drilling Down: Turning Customer Data Into Profits With A Spreadsheet
by Jim Novo

Drilling Down: Turning Customer Data Into Profits With A Spreadsheet
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Book Summary Information

Author: Jim Novo
Edition: Paperback
Audio: English (Original Language); English (Unknown); English (Published)
Published: 2004-06-30
ISBN: 1591135192
Number of pages: 356
Publisher: Booklocker.com

Book Reviews of Drilling Down: Turning Customer Data Into Profits With A Spreadsheet

Book Review: Priceless treasure
Summary: 5 Stars

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 .

Summary of Drilling Down: Turning Customer Data Into Profits With A Spreadsheet

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.

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