"Our CRM data is perfect," said no one ever.
The challenges of poor CRM hygiene are not news to anybody. If you work in sales or marketing, complaining about a lack of high quality data in CRM is a cliche. When it comes to the lack of visibility into who your sales reps are meeting with, however, the magnitude of the problem genuinely might surprise you.
We've analyzed a lot of email and calendar data over the years.
How much data?
Last year alone, the Clari AI engine processed nearly 200 million emails and 30 million meetings. Through our analysis, we found that, on average, 50-70% of the people your sales reps are meeting with do not exist as contacts in CRM. Yes, that much—and in some cases much more than that.
That's clearly a problem, but what are you really missing out on?
When reps don't log contacts to CRM, you miss out on 50-70% of the people that could be associated with won deals to understand marketing attribution and which campaigns are moving the needle.
You also miss out on 50-70% of the highly qualified contacts that could be nurtured to accelerate opportunities in flight.
Let's be clear: this is not a knock on sales reps. Being a great sales rep is an intense, high-value job, and the last thing reps should be doing is wasting selling time logging contacts.
So how do you get the data you need while giving your reps time back to sell?
This is where Clari's Autocapture comes in. Autocapture harvests meeting attendee data from your sales reps' calendars and uses it to automatically create new contacts and associate both new and existing contacts with the right opportunities. When analyzing meeting attendee data, we intelligently determine which account and opportunities a contact should be associated with, check for existing contacts to avoid duplicates, then sync updates with no manual work required by the sales rep.
Often, new people get pulled into a deal late in the sales cycle. Unfortunately, their contact information rarely makes it into CRM, but it's critical in connecting the dots between marketing efforts and revenue. We call this the "last mile problem" of marketing attribution.