How To Gather Marketing Insight From Your CRM Data

This time last year, our marketing team consisted of one person – none other than Dan Hebert. Over the next 10 months, we revamped our content strategy, created three new roles in the marketing department, and widened our top of funnel by an impressive margin.

One of the key contributors here was our new Marketing Automation Manager, Anuj. Although he just joined us in February, he’s already done a fantastic job at overhauling our CRM processes and integrations. He’s helped us identify the weak spots in our strategy and has created some amazing new processes to address these challenges.

It’s been really cool for us to see the changes that Anuj has implemented.

I chatted with him to learn more about the improvements to our processes and how we intend to apply the findings.

Previous Marketing Automation Model

We had all the right tools in place for marketing automation, but there were still a few missing pieces.

The most notable gap, Anuj tells me, is that we weren’t segmenting our data properly, which had a bit of a domino effect on our drip campaigns. Although we had some pieces of the puzzle, it resulted in our messaging being a bit too irrelevant to prospects. We were trying to reach too many people with one message.

Pardot offers grading for prospect profiles, and that wasn’t being used to its full potential. This is partly because some fields were missing. Title and role were sometimes missing or not completed in detail, so as a result, we couldn’t pull any meaningful marketing insight.”

We knew we had to get a bit more detailed. Targeting by industry is great, but targeting by industry and size combined is even better.

It seems like an easy fix, right? Just fill in the missing fields and we’ll be fine. Well, with a database of tens of thousands contacts, that’s a bit tricky. But Anuj was more than up for that challenge.

Filling in the Gaps With Marketing Insight From Our CRM Data

Anuj immediately saw opportunities to further integrate our tech stack and make our inbound/outbound efforts align more closely.

“I started using Qlik Sense to get a better sense of what verticals have the most success with our product. We could visually map out our fastest closing deals, the size of the deal, the industry – all valuable data to have when coming up with messaging. We reverse engineered our own sales data to see what future data sets we should be measuring.”

So for example, if we plot all of this data in graph form, we can see the deals with the longest closing time juxtaposed with the size of the deal and determine whether there’s a discernable pattern in which industries have a shorter sales cycle.

Additionally, we’ve been collecting data around which titles have the highest response rate during outreach. So far, we’ve found that people that work in social media or digital marketing with “manager” in the title are the most likely to engage positively with our drip campaigns.

These new data sets combined with outreach.io are leading to a more thorough and targeted approach for our prospecting efforts. Oh, and I suppose our new account development reps are helping with that, too

Moving Forward

With this level of segmentation, we can run outreach sprints that are targeted to specific industries with companies of a certain size. All of our messaging for that time period will be targeted specifically to that industry and what they care about.

“We can provide these prospects with content that we know is relevant to them,” Anuj tells me. “Media companies, let’s say, might have a higher correlation with using our product for brand awareness. Or financial services might care about employer branding. We’ll be able to specify that exact use case and reach out to them with a piece of collateral that shows how we can help them solve that business problem.”

As with most things in marketing, it boils down to being helpful. In the end, complete datasets and tailored messaging are what will help us help our customers.

Have you made any changes to your marketing automation lately? What were the results? Let me know in the comments, or share your thoughts with me on Twitter

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