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Commentary & Analysis

Good Data: The Foundation of VDP

By Barbara Pellow Success always starts with good data May 17,

By WhatTheyThink Staff
Published: May 17, 2006

By Barbara Pellow Success always starts with good data May 17, 2006 -- Data driven marketing is fundamental to penetrating new markets and farming existing ones. As the economy heats up, marketers are faced with tougher challenges, but probably not additional resources to get the job done. While we hear a great deal about variable data print and new application tools, success always starts with good data. Customers in today's market need help with both the acquisition of data and data refinement. Complex applications, such as campaign management and Customer Relationship Management (CRM), require complete and accurate data to achieve optimal results. Win, Grow, Keep, Repeat If done effectively, data-driven marketing combines data, structured and free-thinking analysis, and creative planning to: * Identify and acquire new customers that deliver higher profits (win) * Maximize the value existing customers contribute to current business (grow) * Retain more profitable customers and strengthen their loyalty (keep) * Kick-start lapsed or inactive customers to increase order rates again (repeat win) * Develop more relevant products, services and offers and identify target segments who are likely to be the most responsive towards those offers * Predict and increase the response rates from your campaigns and promotions, while lowering cost So What About Data? This past week, I talked with Jeff Cleary, Managing Director of Catalyst Direct Inc., and Kevin Seaman, Operations Manager from Equient, to discuss the challenges associated with data preparation and analytics for direct marketing campaigns. Founded in 1990, Catalyst Direct is a marketing communications firm with more than $39 million in capitalized billings. This past week Catalyst announced the acquisition of Equient, a division of General Dynamics. The objective of the acquisition was to improve Catalyst Direct's analytic offerings. Equient amasses information from consumer databases, manages and analyzes information about individual consumers and refines that information for clients by using computer applications. Using powerful computers and terabytes of data, their objective is to deliver lists of consumers that fit the profiles of the most likely buyers based on as many as 1,000 different characteristics. Savvy marketers demand results. While we hear a great deal about the importance of "good" data, we don't hear enough about how to achieve it. Jeff and Kevin are experts and know how to build a database that drives results. Knowledge is key: Correctly analyzed data drives the right target, creative execution, and offer, and ensures that results are delivered. Catalyst and Equient collaborated on a campaign for acquisition of new relationship checking customers at First Niagara Bank. It is a perfect example of the data acquisition and refinement process that needs to be used to effectively build a data base that delivers business results. First, Niagara Bank's objective was to develop a direct mail campaign that would attract more checking account clients to the bank. According to Cleary, "Knowledge is the absolute key to coming up with the appropriate strategy for any campaign. Data, when appropriately analyzed, drives the right target, creative execution, and offer, and ensures that results are delivered." The starting point for the campaign was the development of a detailed profile analysis for the branch's targeted area. The analysis identified the similarities and differences between customers and non-customers in terms of their demographic, behavioral, lifestyle and branch proximity attributes. They used existing customer data for current nonchecking customers and a U.S households database for non-customers. . Predictive analytics The strategy was to target existing nonchecking customers and prospects that fit the profile. Working with the profile analyses, Catalyst and Equient built a predictive model to determine the variables most significant in predicting similarity to current customers. Predictive analytics, a process used to create a statistical model of future behavior, is the area of data mining concerned with forecasting probabilities and trends. A predictive model is made up of a number of predictors; variable factors that are likely to influence future behavior or results. In any marketing campaign, a customer's gender, age, and purchase history might predict the likelihood of a future sale. From experience, Catalyst knew that proximity to a branch was a key consideration for consumers who are choosing a bank for their checking account. They started their work by analyzing each of the branch's current checking customers and the proximity to the branch. The objective was to determine the appropriate distance for targeting prospective relationship checking customers. A proximity "score" was then assigned to each record, part of a technique used in predicting future behavior. The score assigned to each individual in a database indicates that person's likelihood of exhibiting a particular behavior. They used the models to assign prospect probability scores to records in the U.S. household database for the various Relationship Checking Account options the bank wanted to offer. They created a hybrid prioritization score that weighted the proximity two times higher than the prospect probability. The highest scored records were selected for the prospect mailing list. Targeted non-checking customers were selected based on their qualifying bank balances. Once the target market was appropriately defined, the creative team developed a set of compelling messages. The creative execution and offer were designed to drive prospects and nonchecking customers into a branch to start a conversation and open a Relationship Checking Account. The offers of a free cargo bag, food carrier or cell phone were items that had value to the targeted prospect base. Using predictive modeling and establishing good data infrastructure meant that First Niagara Bank's program was not a "one size fits all" campaign. They could develop a message tailored to the customer's profile to yield a higher response rate. The Relationship Checking campaign was a huge success for First Niagara. There was a 1.1 percent conversion rate. 2.5 percent of the bank's non-checking customers that received the direct mail campaign opened a Relationship Checking account and 0.7 percent of the prospects opened accounts. This represented a 106 percent improvement, or lift, over any prior direct marketing campaign conducted by the bank. Data: Without It, You Are Nothing No matter how good a mailing program your customer has put together, it just won't work unless they are talking to someone who actually cares about what they have to say, and that's generally someone with a need or that fits a predictable profile of a likely purchaser. A perfectly tailored message can't suit anyone if it isn't delivered to the proper audience. Data comes first, before you even start thinking about what the mailing will say and what it is going to look like Your sales people are looking for opportunities to sell variable data solutions. Their focus is typically on the color quality and creative and how many pieces the customer will print. The bigger challenge is making sure that clients understand their target market and are using internal data or have sourced appropriate data to make the campaign a success. If your customer's experience with targeted direct mail campaigns doesn't yield results, they won't be back. As part of your business process, make sure that the data can deliver results. Understanding that data comes first, before you even start thinking about what the mailing will say and what it is going to look like. Zeroing in on the right person at the right time is the single most important factor in direct mail or any direct marketing effort. If your client doesn't have the right data and you don't have the skills inside your organization to provide appropriate guidance, you may need to look for partners that can help. There are direct marketing and data analytic firms that can work with you and your customers to enhance the performance of data driven endeavors. There are tools that can augment and refine your customer's data. Your objective is to ensure that your customers get maximum value out of their marketing campaigns. And it all starts with good data.

 

 

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