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One simple way for B2B marketers to expand their audience

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By David Battson 2 min read

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#DataHQIDEAS

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Ditch your traditional firmographics as a way of selecting prospect data (industry, employee size, geography etc) and use a propensity model instead.

There, I’ve said it. I didn’t give you a long pre-amble or hide it in amongst 4 other tips.

It really is that simple.

Make the switch and you won’t fail to see:

- an increase in your prospect audience size

- a better conversion rate

Why does it work so well?

  1. Because prospects are modelled on the profile of your best trading customers.
  2. Here comes the science bit…. Because richer data sources compare more variables (and thousands of options within them), meaning you’re not accidentally excluding someone just because they’ve got 251 employees for example, when your threshold was set at 250, or because the geography field was blank when the count was run so it got missed off

The Venn image below shows the result of a propensity model I built recently.

Propensity Model Venn



The client had given us traditional firmographics (Industries, employee sizes etc) to license which is represented by the pink circle in the Venn below.

The green circle represents some of their existing customers that they were looking to find more of.

The blue circle represents those records with a positive propensity to convert according to our model.

As you can see their firmographic criteria only found 18 of their customers. This could be because the criteria was slightly out, some of their customers didn't fit the criteria as they expected or we simply didn't hold all of their firmographics against every record.

Whereas the propensity model found 117 of their target customers - a 650% increase vs the traditional data buying methods. This model opens up a whole new tranche of prospects.

Secret sauce for marketers big and small

Technology has made this kind of modelling available to marketing teams of all sizes. I imagine it won’t be too long before it becomes the mainstream method for data selection.

So long as you have 1-2000 records in your customer file to base the analysis on, you should get good results.

And it doesn’t have to be expensive unless you’ve got multiple segments to model or you require detailed reporting.

In our experience it’s quite common to see a 200-300% uplift in conversion when you switch to this approach.

This is my area of expertise (and passion) so I’m always happy to help out if you want to chat about this.

Dave Battson
Data HQ Operations Director
You can email me here if you need some help
Connect with me on LinkedIN for more #DataHQIDEAS

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