Marketing Automation data capture: what to collect and how to use it

I’ll be honest, our objectives with clients very rarely include automating much of anything. So we’re not setting up marketing automation content, forms and campaigns to capture data that would feed into being able to automate. We’re usually seeking to capture data that gives more decision-making insight for the marketers and salespeople involved.

More specifically, clients usually want to be able to perform qualification at the Lead-to-MQL (marketing-qualified lead) stage and the MQL-to-SQL (sales-qualified lead) gates. So the qualification criteria the client wants to apply feed into data collection and capture execution.

MQL qualification is really about whether it’s worth investing in further marketing to the prospect…are they in a situation/company/role/industry that would realistically make them a potential customer?

SQL qualification is determining if a salesperson should contact them. Every sales organization has a different threshold for this, so the criteria can differ quite a bit, but often involve some version of BANT and/or likelihood of a sales opportunity, in addition to stage of the buying decision and role in the buying decision.

So…then it becomes an exercise of deciding how to use the tools you have to collect and organize the data you need.  Here are some ideas for applying Marketing Automation features to enable lead qualification, and what you can discern from each data point:

  • Lead score is calculated based on activities, so it’s a good soft indicator for both MQL and SQL, but in itself tells you very little that’s definitive (my mom has a very high lead score in our database because she likes to read everything I publish).
  • Lead grade is a good accompaniment to lead score because it’s a) manual, and b) based on yes/no qualification questions. Also useful for both MQL and SQL.
  • In-depth activity data is where the real answers lie, and as you know, you really have to look at that one prospect at a time. So starting with prospects who have good score/grade combos, you then dig into what the other data tells you.
  • We have been so bold as to set up custom fields that ask prospects, with drop-down list choices for data consistency, which stage and role in the buying decision best applies to them. It’s amazing how many people will answer this question since they don’t consider it as confidential as name or phone number. That’s really helpful insight to have, obviously.
  • And if you’ve already figured out which content you offer aligns to which buying stage, then you should be able to eyeball someone’s content engagement (views & downloads) history to see where they’re most likely to be.

Add it all up, and you have information to help your sales team formulate an approach to contacting qualified leads in a highly relevant way.

Build some simple automation rules to manage lists of people against this field and activity data, and you can also compile some “segments” in your marketing automation tool and build more tailored campaigns (with appropriate content) for each.

Sadly there’s no one-size-fits-all out-of-the-box config for this, which I suppose is what keeps us in business. The best advice I can give you is to figure out your model first, and worry about automating it later. Automation is a useful tool, but as an objective in and of itself, can take you off track in your planning and execution.