In this post, it's worth taking it one step further. Getting marketing data into a platform is one thing, but if the data is messy (and what marketing data isn't), it will not be of much use. If, for example, your marketing database has 100,000 names in it, and the titles are just as they were written, such as:
- VP Marketing
- V.P. Mktg
- Vice Pres Marketing
- Marketing Vice President
- Mktg VP
and you are asked to build a list of Vice Presidents of Marketing to target, how many will you find? 300? 800? We've seen many situations where dirty data returned 300 names, but the same query against cleansed data returned 17,000 names. Proper management of data makes a huge difference in your marketing results.
So, how do you test for this when considering a marketing automation software investment?
Quite simply - ask, in a demo, for each vendor you are considering to run a quick test. Here is a sample CSV file with typical marketing data. Titles, states, and countries are as they would be in a normal marketing or CRM database. The data is kept simple, and the titles are mostly in sales, marketing, and finance, while the addresses are in Canada, US, and UK.
Have each vendor run the following test for you:
- Upload the sample file
- Clean up the country fields so that US, USA, U.S.A, as well as the variations of Canada, and England/UK are normalized
- Clean up the "raw" job title fields to two new fields for "level" (VP, Director, etc), and "role" (marketing, finance, etc) so you can properly segment
- As a bonus, see if they can correct the missing leading "0" on New England zip codes - removed by Excel in many marketers' data files
- The only countries in the file are "USA", "GBR" and "CAN" or however you chose to normalize the country data
- The people can easily be filtered by role into "Marketing", "Sales", or "Finance"
- The people can easily be filtered by level into "SVP", "VP", "Director", or "Manager"
Many marketing challenges come from bad data. An inability to do proper segmentation, personalization, lead scoring, or analytics can quickly result if you are not able to standardize and normalize the data in your marketing database. To avoid getting into this situation, it's worth having the marketing automation provider you are thinking of choosing run through this quick test with real sample data.