Best Practice series: What’s WIIFM got to do with data quality?
Jul 29, 2009WIIFM (What’s In It For Me) is the mantra of sales people and marketers. To get prospects to consider your product, you better know what that product can do for them. How it solves their problem. Makes their lives better. Helps them sleep at night.
When it comes to CRM, there’s lots of research that shows that lack of user adoption—that’s consultant speak for people saying “no thanks"—is one of the main reasons CRM projects fail. The last Best Practice post "Adoption" included ways to measure adoption and tips for motivating people to use the app.
This post is about fixing one huge reason why people resist getting on board—the data is confusing, incomplete, or misleading. Ask them why they’re not using the app and they’re not likely to say “data quality.” But look at what’s causing their frustration with finding information, or knowing which information is “right,” and you can bet there's a problem with data quality.
The bottom line: Bad data is bad for business. Bad data makes people think there's not much in it for them. Do your business—and your users—a favor and make sure your data is clean, stays clean, and contains those special nuggets of information that make people love CRM.
Oliver Demuth, the author of this paper, also had this comment: "It's critical that you train your users in how they can contribute to data quality. If everyone contributes, everyone benefits from accurate data."
Has bad data affected your project and what have you done to fix it? And will the advice in this Best Practice help?
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If there is one piece of advice that a CRM champion should take, it is to follow these steps for data quality. There is often a lot of focus on feature-functionality when implementing a new system, but it is the data that will ultimately define success. When users have a lack of confidence is the reliability of their data in the system, they are much less likely to be strong adopters. This fact has been proven hundreds of time over in these types of initiatives.
This is a great summary of an otherwise complex topic.
Posted by: Bill Kalma | July 30, 2009 at 06:18 AM
Anyone interested in data quality and project success should take advantage of this document. Reading this short, concise, two-pager was time well spent.
Posted by: Mark Conklin | July 30, 2009 at 06:48 AM
Without a doubt this document is extremely valuable as it speaks to my efforts, as a new administrator to a company that has years of built-up bad data, to not only make our CRM more useful but provide our salespeople a reservoir of useful information. This document provides great insight and detail into how to boost user's adoption rate as well as improve accuracy of Data.
Posted by: Paul Bryant | July 30, 2009 at 01:34 PM
we use this document a lot in presentations with our products. get the data clean before you bring it into your CRM then keep it clean moving forward. once you lose the respect of your sales team with bad data it is hard to get it back.
Posted by: jay pitzer | August 03, 2009 at 07:06 AM
Jay, that's a great point for anyone who's tempted to "do it later." Also, it's really good to know you're using this document with your customers.
Posted by: Sylvia Lehnen | August 03, 2009 at 09:41 AM
This is a valuable resource document, particularly for organizations like ours as we migrate away from an old system full of bad data, to our new CRM. I will be keeping this document close by... a great tool for presentation and reference.
Posted by: Amy Dragovich | August 04, 2009 at 07:42 AM
As data quality has a tendency to be a one-off project and then forgotten for years I would recommend this document for companies new to CRM but also as a point of reference for companies wanting maximum ROI on their CRM investment post-deployment. The value lost due to poor data quality and the cost of the project to 're-clean' data are usually significantly higher than the cost of having proper data quality maintenance processes in place.
Posted by: Morten E Hansen | August 04, 2009 at 10:51 AM
Data quality can sink the ship. Customers really want sincerity in their relationships. This is a principle perfectly consistent with social marketing as demonstrated by Godin.
Posted by: Ian McGrady | September 02, 2009 at 09:47 AM