Out-of-date data, AKA data past its sell-by date
Desktop data, AKA data that lives in spreadsheets on your desktop (you know what I mean…and we’re all guilty of it)
Too many static lists
“Good enough” data
Does this sound like you?
If so, you’re not alone.
We’ve seen it many times—too much time is spent on campaign planning and perfecting content & design and not enough is spent on “the list”.
Even the best content and creativity can’t overcome bad data. Very simply, it can ruin a campaign.
- Defining your target audience
Be specific. The more narrowly you can define your audience, the better results you’ll get.
- Identifying the data (i.e. fields and values) of contacts who fit the profile
*Hint: Create a data dictionary that provides detailed info about your data(base) and acts as a guide to understanding and using your data.
- Auditing and assessing the quality of your data
We could spend an entire blog on how to assess the health of your database (and we will, coming soon!).
Until then, look at:
- Missing data – gap analysis on key fields (% fill rate)
- Field value standardization
- Wrong or inadequate data
- Capture all data in a centralized location AND ensure that data is standardized.
By “standardize” We mean to create a data cleansing process that regularly reviews and cleanses your data (which should fix the problems identified in #3).
- Create a dynamic segment in your MAS that pulls from the fields identified in #4.
- Run your segment and check the results.
Once we’ve configured our list logic, always spot-check the output as inevitably you can miss a detail (or two).
If need be, export the data and review it to make sure it aligns with your expectations. If not, tweak the criteria & logic and run again. Keep tweaking and reviewing until you are 100% confident in your list.
If these steps seem daunting, it’s cuz they are. But as with anything, start at the top and work your way down.
Now, you are ready to launch your campaign with full confidence that data isn’t going to jeopardize your results.