Have you ever wondered how your marketing strategy ballooned to something that is too complex and not tightly intertwined?
Today, we’re bringing you a recap from one of the exclusive sessions at the 2019 B2B Sales & Marketing Exchange.
In this session, Jeremy Middleton, Senior Director of Digital Marketing & Revenue Operations at Pramata, shared how his company took a step back to review how they built out, and refined, their ABM program.
Here’s what we’re unpacking today:
- What they did
- How they used a data-based approach to simplify their model
- And how that increased efficiency, pipeline and deal speed, while unifying all data and decreased spend
This post is based on a podcast with Jeremy Middleton. If you’d like to listen to the full episode, you can check it out here and below.
First things, first…Who is Pramata?
Jeremy: We’re going to talk a little bit about who is Pramata, because you have to understand the business model before we get into the marketing model.
So, who is Pramata?
We are a company that helps businesses maximize customer lifetime value. Imagine a large B2B company, like Comcas. They have a lot of very large enterprise customers. And it can be difficult to track what their customers own, where it’s installed, when it renews, etc. So you end up with a lot of mistakes. That leads to billing issues, revenue that doesn’t meet your expectations, churn, etc.
So what we do is we come in, we take all their contracts, we pull the relevant information out of it, and then share it with the appropriate team, making it a lot easier for them to maximize CLV.
What they did:
Jeremy: This was our plan to change our marketing program.
We went out and we identified who really cares about us the most. And we figured out what message they cared about the most, too.
We did this through firmographic data. We also looked at our current customers assuming similar people would want to buy our product, too.
We then went in and we said, “Okay, we now have a strategy. We have a message. Let’s remake the process.” We wanted the process to be simple and we wanted to be able to optimize on it.
Finally, we figured out what tools we wanted to use along the way. There’s a lot of tools out there, but we really wanted to keep it simple, so we went from using 22 tools to 6.
Using data to refine the strategy
Jeremy: We prioritized our accounts into three tiers. Then we looked at our webpage and said, “Okay, great. So, we have basically 300 priority accounts we want to go after. How many of these accounts are coming to our website?”
We had a lot of web traffic, but it turned out that only about 19% of that traffic was from our target accounts. That’s very low.
We determined that we’d rather have the right people coming to our site than a lot of people.
So, we went through, audited all the systems, and identified key metrics. And we asked: “With these key metrics, what are some industry standards for them? What’s performing above industry standards? What’s performing under? And if something’s under, why is it not working?”
By focusing on a few key metrics, it was easy to identify what worked, what didn’t, and how we could make improvements.
How that simple strategy drove impressive results
Jeremy: So, what results did we see from implementing this strategy?
Well, we’re doubling the industry standard in ad clicks.
And we increased our sales acceptance rate from 12% to 76%.
In addition, since these leads are higher quality, our costs went down. We actually underspent our budget by 32%, just because we simplified things.
And since they’re higher quality leads, where we’re talking to the right people, our deals go faster.
So, by revising our marketing model, and keeping it simple and data-driven, we’ve achieved increased efficiency, pipeline and deal speed, while unifying all data and decreasing spend.