enabling technology

Thinking about CRM data quality – what is that thing in the punchbowl?

Not too long ago, a prospect asked us to review their sales and lead generation programs because lead flow had dropped significantly. This concerned them because they had just finished a significant new product launch with a well- known interactive marketing agency. We agreed to sniff around.

Every reptilian instinct in my body wanted to find a way to bad mouth the agency’s work. But their creative, positioning and the execution was brilliant. We couldn’t find fault in the agency’s work.

We dug deeper and asked to look at their new CRM – the foundation for the entire product launch and the basis for all of their prospecting efforts. It fueled their direct mail, email newsletters, catalog mailings and sales outreach.

The problem was immediately obvious. The turd in the proverbial punchbowl was data quality. The client had spared no expense building world class creative and but left the task of data hygiene to a group of marketing interns who would rather mop the floors than scrub data.

In the post mortem, we learned the interns received various Excel files containing old data, questionable lists, incomplete lists and exports from a variety of personal contact management applications. Then, with bubble gum and bailing wire, the master list was normalized, checked for obvious data format requirements and imported verbatim into the million dollar CRM.

In hindsight, the client was incredibly candid. No one wanted to own the data hygiene. It wasn’t sexy and it cost a lot of money to do right.  So, in the hopes of prevent future CRM data quality disasters, here are few tips you can use to get the biggest bang from your CRM dollar:

1)    Data quality is not a one-time event. Your data will get dirty and cleaning it is an ongoing set of activities so it helps to design processes that keep data clean. For example, after an email blast, a single individual should be responsible for removing or updating undeliverables. In addition, sales people should also be responsible for keeping data clean. They own the accounts and it is in their best interest to champion the data. Additional quality checks such automation of duplicate record checks also stops problems before they get out of hand.

2)    Duplicates cost you. A single company record should be tied to a set of addresses and contacts. Failure to tie together information about an account to a single company record dilutes the effectiveness of the data – especially in key account selling.

3)    Humans matter. While automation of data clean-up is useful, humans are essential to the process. Computers miss things that are usually obvious to a human such as a division’s relationship to a corporate entity.

4)    Protect your data from good intentions. With CRM, it is far too easy for individuals without an understanding of data hygiene practices to import data from external sources. An equal opportunity automated and a manual review process should always be applied to external data before it is imported.

5)    Find a balance. It is easy to be compulsive about data quality but it is not practical. Your data changes every day, making sure it is always accurate is not financially feasible. That is why it is important to strive for “good enough.”

Good data is the foundation for effective CRM. In B2B it is impossible to build strong marketing unless you know the names of the people most likely to buy from you. Maintaining a clean CRM punchbowl requires more than a summer intern.

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