If you work on the demand generation side of B2B marketing, the email will surely arrive at some point.
While probably very short and light on empathy, what you'll hear in your head is something like this:
"Hey, you know the campaign strategy you so smartly came up with for our marketing automation and/or retargeting program?
The one where you built around segmented buyer journeys?
The one that was going to blow the roof off previous performance metrics through increased relevance to buyers?
Well, um, the basic segmentation data you assumed was in our CRM? It's not. So you're kind of…"
Why is this email inevitable? "Because the quality and completeness of B2B customer data is horrible all around," says Marc Blumer, our director of demand generation strategy.
According to a NetProspex study, here's where B2B companies stand in terms of the B2B data completeness you’ll likely need for segmentation:
- 82% missing employee information
- 71% missing industry information
- 34% missing title information
- 84% missing revenue information
Data triage time
Long term, successful B2B marketers create and invest in a comprehensive customer data strategy. Today is not the day to browbeat you on that. You need help…now.
With that, here are three tricks we've employed with clients over the years to meet deadlines, pipeline goals and non-forgiving bosses:
(1) Is there a way to pull and leverage data from another field?
Job function/job role is both a common segmentation need yet the field typically has a horrible completion rate in CRMs.
But as mentioned above, job title fields are much more often complete.
In several cases when under deadline pressure, we've hacked this exact problem by creating a matching table in Excel, adding a new, custom "role" field in our marketing automation platform and importing the new data.
Here's how we did it. First, we exported the records from both the unique customer ID field and the job title text field in the CRM and brought that data into Excel as two separate columns. Then, we created a third column called "role," which we would fill with our segmentation job role names.
Then, the icky part. We used the Excel search function on the job title text column using likely keywords to find groups of records that were likely to fit a specified functional role. For example, to identify marketing roles, we'd search for "marketing", "mkt", "mrkt", "advertising", "adv", etc.
Once we finished keyword searches for each segmentation job role, all records that were truly marketers had "marketing" entered the “role” column, and so on for each role. Once finished, you can decide if it is worth it to comb through remaining records.
Honestly, even for a database in the tens of thousands, if you don't need absolute 100% field completion, this can be done in a day or two.
(2) Is a QUICK third party data augmentation possible?
If what you are missing is basic firmographic data (e.g., SIC or NAICS codes, revenue, etc.), then you can likely execute a fast data append.
An append from major data providers such as infoUSA or specialty providers such as the NAICS association can be completed in days. Costs are reasonable (in the low hundreds to low thousands) and more than justified if you've promised a campaign will launch soon.
(3) Can you split the baby?
If the above hacks won't work and what you are dealing with is a poor form field completion rate for needed data and not the complete absence of data, consider a launch in stages.
Odds are, your data complete records are probably your most valuable customers and prospects (that's why sales captured more data).
If you can segment those records out, you can lower blood pressure by getting the campaign to these individuals out the door on your deadline.
Then, simultaneously, you can complete a more complex data append through a third party or, more likely, leverage low level internal staff or contract employees to research and augment records by hand using LinkedIn, Hoovers, etc.
In the latter case, you can release new groups in waves each week so that everyone sees progress Is being made and the pressure is reduced.
Done saving the day?
Then it's time to get around to thinking about that comprehensive data strategy if you haven’t already.
Need a little help with that? We talk data morning, noon and night.