Lead Scoring and Data Quality: How Much is Dirty Data Costing You?

Qualifying, coding and ranking your leads so the hottest opportunities are the first to get distributed to your sales teams is vital to your company’s sales and marketing success. That’s a given.

Yet, what many companies fail to understand is that data quality is core to an effective lead scoring system.  

A SiriusDecisions study, “The Impact of Bad Data on Demand Creation”, shows that following best practices in data quality generates a 66 percent increase in revenue. 

The study summary cited in a CRM Magazine article, “Looking to Score”,  offers some key insights for B2B organizations, such as:

• 10 to 25 percent of customer and prospect records contain critical data errors.
• The amount of data doubles every 12 to 18 months.
• It takes $1 to verify a record as it is entered, $10 to cleanse and de-dupe it, and $100 if nothing is done, as the ramifications of the mistakes are felt over and over again.
• From inquiry to marketing-qualified lead: A data strategy that solves conflicts at the source can lead to a 25 percent increase in converting inquiries to marketing-qualified leads.
• From marketing-qualified lead to sales-accepted lead: Unifying the data, whether into one database or by using technology for virtual integration, can lead to a 12.5 percent uplift in conversion rates to the next stage.
• From sales-accepted lead to sales-qualified lead: Clean data can reduce by 5 percent the time spent conducting the kind of additional research that precedes initial contact with a prospect.
• From sales-qualified lead to close: Given that the average field-marketing function spends no more than 10 percent of its budget in support of this final conversion, accurate data is a must for applying the right tools and resources to the right audience at the right stage of the buying cycle.

Jonathan Block, author of the report and senior director of research at SiriusDecisions, writes, “A best-in-class data strategy is shared by marketing and sales, and is focused on quality from [inquiry] to close. Although it is a job that consumes both money and time, paying more attention to data quality is not only worth it, it is something that your organization simply can’t afford not to do.

I couldn’t agree more.  Have you reviewed the quality of your data lately? 

Comments

[Maria Pergolino @marketo]

I agree with your post completely. As I work in marketing automation and have also been a customer of marketing automation tools I have found the following is the best way to accomplish both lead scoring and data improvements to bet maximum results.

First, build a budget that includes both marketing automation and data clean-up tools. It's hard to quantify the return on clean data, so often companies won't see the value in paying for it. By incorporating the cost of a data cleansing tool into the purchase of a marketing automation tool both will be covered.

Select a vendor for data cleansing and deduplication and do cleanup of all your old data prior to integrating a marketing automation system.

Then select and implement a marketing automation system. Your marketing automation system should deduplicate all new leads that come into the system. This is important because with the implementation of marketing automation you are likely to start increasing the number of leads you bring in (because you will have the ability to create targeted landing pages, drive prospects back to your site from email campaigns, etc).

Also, marketing automation systems will help you clean up data, by letting you update large groups of records with simple drag and drop requests. Just makes sure this is something your marketing automation system can do before subscribing. Mine does and I find it a huge time saver and very valuable feature.

Now implement lead scoring. An additional benefit of implementing in this order is that you will feel more comfortable that your lead scores are accurate since you know your data is good.

Thank you again for the article.

[Chad Horenfeldt]

Completely agreed with this article and comment. A large number of my conversations these days with clients is around cleansing data which should be built into the lead management process and be part of your marketing automation tool.

We call this process "the contact washing machine" where leads are "cleaned" prior to being sent into the CRM. See Steve Woods' post on this: http://digitalbodylanguage.blogspot.com/2008/12/contact-washing-machine.html

I would also recommend Paul Teshima's article: Is Data Quality the "New Black"? http://digitalbodylanguage.blogspot.com/2009/06/is-data-quality-new-black.html

@chadhorenfeldt

[daily stock picks]

I strongly agree to that.

one of the most effective way to accomplish both lead scoring and data improvements at a shortest possible period of time...

great post..