🫣 Is it surprising to you?
It's not to us! Everyone has duplicates, floating lead records, and weird legacy automations doing even weirder stuff in the background.
What may surprise you are the answers to Openprise's core questions:
The one statement that made us read the whole report from end to end? Data quality has just as much (if not more) to do with public perception as it does technical quality. Download the report to get the details.
A sizable proportion of survey respondents said their data was "good enough" or better. A staggering 71% of those same people admit their data quality has negatively impacted their go-to-market team's ability to execute.
So, is the data really "good enough"?
And what do the people who actually have great data quality do differently to avoid negatively impacting GTM activities?
Well, if this isn't a cue to download a report, we don't know what is.
Operations pros are in a unique seat. They should have access to the overall go-to-market strategy and the know how to help teams take the tactical steps to get there.
But if we have blind spots (and humans always do!) it's putting a little too much faith into process and systems while ignoring how humans ::FEEL:: about things.
To prove our point, let's take data quality. A significant 40% of respondents are comfortable relying solely on technical data definitions. When it comes to what's standing in the way of data quality, 36% of respondents said leadership actions and behavior were the only problem. Maybe we should rethink our approach.
While AI has a ton of potential and is already showing promise in the arena of data quality, the answer is still:
Um. Probably not.
We have to go back to the human factors that get in the way, like focusing on trying to solve cold outbound instead of correcting more manageable problems like duplicates and misspellings.
But what do we know? We'll let you take the survey results and interpret them for yourselves 😉
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