MarketingSherpa – Drilling Down Handbook

MarketingSherpa – Drilling Down Handbook

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Required reading for direct response marketers. Practical hands-on instructions in how to spreadsheet your customer database to find out which customers are your most valuable, and then create campaigns that make the most of this demographic.

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Description

Drilling Down Handbook : Turning Customer Data into Profits

Required reading for direct response marketers. To find out which customers are your most valuable, and then create campaigns that make the most of this demographic, you need to know how to spreadsheet your customer database.

World-Class, Action-Oriented Analytics for Ordinary Marketers Without Fancy Software Programs

Customer marketing tips and tricks of the Pros have been revealed.

Is it possible that you are drowned in data? Can you tell me something I can actually do to increase profits? You are not alone.

There are easy to understand customer reporting techniques you can use. Tell me where the profit opportunities are. .

You don’t need any special skills or software to use these techniques. This approach to customer data is called. Behavioral analysis is done. It has been used for decades to boil marketing data. Facts that matter. You can spend more time doing something to increase your return on investment and less time looking at reports.

Jim Novo, a metrics analysis guru, shows you how to do this on your own. The pivot table capability is required to run the accompanying software. There is a software download link in the book.

The basic idea is here.

1. Data that can affect the profitability of your company is the most important data to pay attention to.

2. Reports pointing out specific problems or opportunities are the most likely to increase profits.

3. The best reports you could ask for would be those that use data known to be the most important to increasing profits, and are in a format that is easy to read. Will let you know. There are opportunities to increase profits.

Behavioral analysis takes the data generated by the actions of your customers or business partners and transforms it into a different view of the world, a view that is both more actionable than typical reporting and also is in a format that alert you to marketing or management problems and opportunities with the greatest potential for high

A person uses behavioral analysis as a business tool.

#1. I only take action when the problem is very profitable.

#2. I always time this action for the best return.

Every budget dollar works harder and your success rate goes up if you focus your resources on actions with the highest probability of driving profits.

How do you know if a problem or opportunity is profitable and when to act on it?

Both questions are answered by behavioral analysis. Here is what you can do. The drill is drilling down. on your desk

  • Predict which marketing campaigns are going to generate the most valuable customers – before the campaigns even end.
  • Emphasize the ads, media, and products creating long-term high potential value customers and downplay ones that don’t.
  • Create High ROI customer marketing programs designed to increase response rates while lowering promotional costs.
  • Determine when best customers are likely to leave you and react with customer retention and save-a-customer programs.
  • Quantify the profitability of marketing and operational initiatives by linking them to a change in potential customer value.

What can you do with behavioral analysis to increase profits? Here are a few examples.

You have a limited ad budget and want to test as many approaches as possible. You put all your money into the 3 remaining campaigns if you kill off 7 of them within 2 weeks, including some campaigns with high initial response rates.

The boss thinks you are crazy, but 60 days later you produce a report showing that the new customers generated by the 3 campaigns you kept were worth 5 times as much as the average customer generated by the other 7 campaigns. The boss is not aware of you. It was predicted. The behavioral metric is used to generate customers that buy over and over again. Recency. .

A base software product with add-on modules is sold by your company. The base product has been rising in sales, but the add-on modules are not. The CFO wants to know why this is happening. You will take care of it after you explain a new vertical market is causing the imbalance.

After a month, sales of the base software and add-ons are back to normal. The CFO thinks you are brilliant, but you didn’t do anything. It was predicted. This would happen regardless of the metric used. There is a delay.

You are going to miss forecast because the company is relying on your division to be the lead revenue source. You have a budget that will only cover 10% of your customers, so you need to generate some sales fast.

You can not make any special offers to anyone. Everybody thinks you are in big trouble, but you beat the forecast. The other heads are amazed, but they don’t know you. It was predicted. The behavioral model was used to determine which customers were most likely to buy. RFM.

competing products from other companies are sold by distributors or agents. There is a feeling that the distributors have been pushing the products of their competitors harder. The President of the company wants something done but there isn’t enough money to do it.

You grab the reins and tell the President that you can fix it. After a few months, you get a promotion for all your hard work, as sales are on the rise again. You focused the distributor / agent relations effort. Predicting. They are the most likely to switch to the competition. Recency. And. There is a delay.

Readers say:

Drilling down. It gives marketers the ability to score their customers quickly and easily. I used it on a time-sensitive project and it worked. Sheshunoff Information Services has a marketing manager.

Jim has a passion for customer database marketing and analysis. In a simple, straightforward way, he shows you the road to success. He puts everything you wanted to know about managing customer relationships in one place.

There is more real world information about customer analysis and database marketing in 180 pages than you can get in a year’s worth of seminars and consultant meetings. The tools of the professionals are given to everyone by Jim.

The book teaches you how to use customer relationship management to influence retention. You can use a simple spreadsheet to create action-oriented customer profiles and segment LTV’s for different groups, with different messages aimed at each group, with products and offers appropriate to the group being addressed. Getting other customers to move up to gold and acquiring more gold customers will increase your return on investment.

One of the techniques that I liked the most was how to personalize a Web page based on customer behavior. I was amazed that I could do this using a spreadsheet. A lot of people spend hundreds of thousands of dollars just to read this book.

We can’t bombard our customers with junk anymore. We can’t keep buying loyalty with ever-deeper, loss-making discounts. We need to find cost effective ways of meeting and influencing our individual customers. Those who wish to survive and prosper in this cutthroat web economy should read this book. Get this book! Leonardo Grinstein is a co-CEO of PercaGordura.com.

I am about to make a leap to a much bigger job as Marketing Manager of a large online and catalogue computer reseller, and your words are my holy grail, anyone cancceed in direct marketing, whether it be online or through an offline catalogue. -Luke Ashworth.

Concepts that may take companies and professionals years, huge budgets and expensive software to learn are explained in a very simple and practical way. The book is so clear that even non-native English speakers can easily understand it and put it to use. Every chapter gives you insight that can be applied to your business. Kessler is from Argentina.

You seem to be one of the few with real life experience in database marketing with the skills to simply explain with pragmatic examples of how RFM and LTV should be used. The Chief Technologist is Johnson Au-Yeung.

The complete table of contents There is a software download link in the book. Chapter 1: Customer Profile or Customer Model? The second chapter deals with data-driven marketing and service models.

There is anENCY METRIC TOOLKIT. Chapter 3 is about Trip Wire Marketing. There is a hair salon example in this chapter. Chapter 5 deals with B2B software. Chapter 6 is about turning data into profits.

There is anENCY METRIC TOOLKIT. Chapter 7 deals with customer value-based marketing. The ad spending example is in chapter 8. Chapter 9 shows howcency data can be turned into profits.

There is a ring tool kit. Chapter 10 is about marketing. Chapter 11 is a change for interactive customers. Chapter 12 is about no customer database. How to score customers with a spreadsheet. Chapter 13 is about how to score your customers. Chapter 14 is about turning scoring data into profits.

Lifecycle-based marketing tools. Chapter 15 uses customer characteristics and multiple scores. Tracking scores over time is the topic of chapter 16. Chapter 17 is about customer scoring grids. Straight Talk on Lifetime Value is the 18th chapter. Predicting campaign return is set up in chapter 19 The model is predicted in Chapter 20. Predicting campaign ROI is part of chapter 21. Chapter 22 deals with costs you don’t know about. Chapter 23 has some final thoughts. Software Download and Readme are included in this appendix.

There is a list of CHARTS and GRAPHS. The Customer Value Portfolio is Figure 1. The second figure shows lost revenue from defecting customers. The figure shows the average weeks between add-on purchases. The figure shows the average weeks between add-on purchases. The figure shows the average weeks between Add-On Purchases. There is no 4th purchase promotion in figure 6. Figure 7 shows the calculation of the discount promotional. Figure 8 shows the calculation of the overhead promotional. Figure 9 shows the total costs and return on investment. The figure shows the percentage of purchasing after the promotion ends. Figure 11 shows visitors bycency. The 90-Day Revisit index is figure 12. Figure 13 shows visitors bycency. Figure 14 shows Visitor Friction by Search Phrases. Figure 15 showscency percentage over time. Figure 16 shows financial analysis of campaigns. Figure 17 shows financial analysis of campaigns. The Discount Ladder Test segment performance is shown in figure 18. Figure 19 shows purchasecency. Figure 20 shows the last purchase date before the newsletter drops. The Discount Ladder Test segment performance is shown in figure 21. Figure 22 shows Newsletter Responders by Sign-up Recency. Content groups are ranked by total traffic andcency. Figure 24 shows Content Groups by Traffic, Recency, and Newsletter Conversion Rate. The Customer Value Portfolio is Figure 25. The percentage of the customer base is growing. Figure 27 has a sample of customer records. Figure 28 shows imported customer records. The most recent activity date is sorted by customer ID. Figure 30 shows a table of activity sorted by customer. Recency and Frequency pivot tables are shown in figure 31. Thecency scores were added to the scoring spreadsheet. The scoring spreadsheet has Frequency Scores added to it. The completed scoring spreadsheet was sorted by RF scores. The figure shows the average response rate bycency forcency. The figure shows that the average response rate is 9 times more responsive than the first one. The top RF Score is 700 times more responsive than the bottom RF Score. The figure is about determining thecency hurdle rate. The figure shows the percentage of customers recent in the subject area. Figure 40 shows how to determine the Frequency Hurdle Rate. Figure 41 shows how to determine the rate without inactive customers. Figure 42: RF Scored Customers Sorted by a Characteristic. Visit and purchase RF scores in the same spreadsheet. RF Scores, Visits and Purchases of a new customer are shown in Figure 44. The LifeCycle Grid is depicted in Figure 45. The Customer Value Portfolio has been revised. The first action behavior in the LifeCycle Grid is shown in Figure 47. The second action behavior is shown in Figure 48. The Delta LifeCycle Grid is showing healthy, growing and profitable business. Figure 50 shows Delta Grid Demonstrating Poorly Performing Busines. Unit profit analysis for LTV calculation Figure 52 shows sales by customer volume. The figure is titled Sales by Customer Longevity. The figure shows the response rate by RF Score. Figure 55 shows the financial performance of mailing. The figure depicts actual responses by the RF Score. The model uses actual RF score response rates for each level. As R score falls, effective discount rates need to rise. Figure 59 shows RF Score allow calculation of total promotional discount. There is a financial model with variable discount. There is a figure in Figure 61. The figure is called ROI.b. Figure 63 shows the return on investment. Figure 64 shows how to measure subsidy cost using a control group.

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