What's in a name... job titles and normalizing data

Let's get right into the weeds for a second. When presented with a whiteboard and asked to describe how we'd target a segment, score leads, or personalize content, more often than not, we all tend to throw out "title" or "role" or "level" as a criteria at some point. It's important, and we definitely should. But, the reality is that most of us have fields like "title" coming in from a variety of free-form sources (web forms, lists, trade shows, sales, etc).

Think of the number of ways that one can type in a title that is essentially a Manager of Sales; "Sales Manager", "Sales Mgr", "Mgr Sales", "Manager, Sales", "Manager of Sales", etc. You get the point. When combined with all the other levels and areas of the business, it gets a bit mind boggling trying to come up with the right rule that would target a Manager of Sales.

If you are going to use Title for lead scoring, segment definition, personalization, etc, you need a better way. That's where data normalization comes in. Make it into a habit and you'll be much better off in the long run.

Luckily, it's easier than it seems. The best way is to build what our own Mike MacFarlane calls a "Contact Washing Machine". Every incoming list, form, upload, or data synch goes through this Program automatically, and is scrubbed, normalized, standardized, and cleansed. More on the whole "Contact Washing Machine" concept later, but for normalizing the Title field, here's how.

Add a step in the Program to run an Update Rule ("Update Contact/Prospect/Company Data"), and create a data normalization rule for titles. I'd recommend having two fields for title - the original field as the person typed it in, and a new field for "Normalized Title", it keeps things a lot saner than trying to maintain just one field.

For the data normalization Update Rule, you'll end up with a solid list of title options mapped to the roles you care about. Pull out a list of a few hundred actual titles in your database to get you started and use wild cards to look for the titles you are after.

Start with the most generic titles, and move down to the most specific, to make sure you catch everyone but are able to get the most precision possible. Building a list that looks for "*manager*sales*", "*mgr*sales*", "*sales*manager*", and "*sales*mgr*" should be able to find most of the ways of phrasing Manager of Sales as a title. Use these to set the Normalized Title field to "Manager of Sales", and you will then be able to use that field to look for any Managers or any Sales roles quickly and easily for scoring or targeting.