Benefit Focus Series – Augmenting Segmentation Data

April 26, 2020 Richard Boardman

In the last post, I used a case history to try to illustrate a number of things:

1. Highly targeted, relevant, communications can be a very effective way of generating business
2. While this might be fairly obvious, few businesses are doing it well
3. Generally because they don’t have reliable segmentation data in their CRM system
4. Often because they unsuccessfully try and gather too much information rather than focus on a few key fields

I just wanted to follow the post up with a few ways of helping improve the quality of usefully segment-able data in your system:

Firstly, by integrating with other internal systems, such as the finance/ERP system. This is something that’s generally relatively inexpensive to do, but surprisingly rarely done. The power however of understanding a customer’s transactional history and be able to target communications based on it is potentially hugely valuable.

As an aside, what I commonly see in the B2B space are finance systems with a wealth of useful trading data, but little or no information about the individual decision makers that would allow them to use the data for marketing purposes.

It’s only when the finance system is married to the CRM system, that the value of the transactional data can be unlocked. The return on investment based on doing this can be huge, and I will go into more detail on this next week.

The second means of improving the availability of potential segmentation data is to plug the system into third party data augmentation services which can fill in blanks in your data set. Examples are ZoomInfo, InsideView, D&B Hoovers, and LinkedIn Sales Navigator. This can be a very effective way of gathering information such as industry or number of employees without having to ask system users to maintain the data.

Finally, and again something that’s not done as often as it might be, is to employ or contract someone to manually research data. This can be a very cost-effective way of building out the data set without the reliance on users.

So, in summary, if you’re expecting your users to maintain segmentation data, it best to keep this as limited as possible, ideally to what you can’t easily gather through other sources or means such as other internal systems, third party services, and researchers.