Jim Regan, CMO or MRP, speaks softly, but with conviction, about the challenges and opportunities of B2B marketing; about the imperative need to apply services and software from top to bottom of the funnel; and about how real machine learning will change the B2B marketing (and sales) world. I listened to him late one afternoon at the SiriusDecisions Technology Exchange in Austin last week. It was a fascinating insight into how B2B marketing has evolved over the last (almost) two decades, and a glimpse of the Demand Waterfall in practice.
Origins
Silly question to start, but MRP is an acronym for…?
“It stood for market resource partners. When we started the business 16 years ago we were focused on providing demand generation services for technology companies. My co-founder and I had been laid off after 9/11. Our idea was to start this company, and just make enough money until we could get real jobs.
“We got acquired by this public company in Northern Ireland in 2008, and they enabled us to move into the software space; we ported over the technology they use for investment banks into the marketing space, and gave us the balance sheet to be able to think a little bit bigger.” The Northern Ireland company is First Derivatives plc, a publicly held provider of technology and services to the finance, technology, and energy verticals.
And after the acquisition? “We just always felt like we had more to do. Sure, we’d accomplished a lot, but even now, when you look at AI and machine learning, this market is going to change so much in the next 2 to 3 years. To walk away from that never seemed to make sense.”
Times, they are and will be changing
“We started the business with this simple idea that if we could own MQL to SQL conversion in a business’s pipeline, we would grow. Everything else would fall into place. We were doing that, and then technology erupted. We were using ExactTarget, but Marketo, Eloqua hadn’t really started. In 2006, maybe, the pendulum swung so hard. Every customer was going to be acquired digitally. We were worried about that, but then things started swinging back. Still, I look at the explosion of the platforms, driven by private equity,but at the end of the day so much of the stuff out there is elegant widgets for the top of the funnel.
“Our DNA is, we really believe in MQL/SQL conversion, and if you lay that DNA on top of this Sirius waterfall, then we have software and services supporting our clients as they move organizations much deeper into the waterfall. It’s the combination of the software – yes – but also the people to make it work.”
So what does that mean?
“Now at the front end of what we do is predictive analytics, so we’re using the core technology of our parent company to ingest multiple big data sources to look at the intent or behavior an organization or demand unit is demonsting outside of our client’s firewall; and we’re merging it with their CRM data, their marketing automation data, historical data we have about that account, as well as whether that account has visited our client’s websites. We’re providing a streaming view of the pre-purchase research an organization is doing, outside and within the firewall.
“The second piece is helping our clients engage with those customers. As soon as one of these organizations enters the predictive algorithm, you need to engage with them immediately. So customer engagement needs to be programmed. We’re calling that “orchestration.” We’ve built a real-time bidder, so we’re executing IP-based display; we have our own team of people that are just creating email drips in both Marketo and Eloqua; we have whole teams which just focus on direct mail creative.
“Finally, now we’re up to 360 inside sales people all over the world, so that as [the prospect] moves through the funnel, somebody calls – being able to that consistently and at the right time is a real challenge for organizations, so they oftentimes outsource some of these functions to us; not all of them, some they do well internally.
No integration, no (real) machine learning
“Our pitch is, every time we make a prediction, and then execute to the individuals within that account, their interaction with our outreach is being fed back into the machine, and that’s how the machine learns. If you don’t have integrated services or integrated customer engagement, you’re not doing machine learning.
“Customer engagement has become something that is programmed and measured. Plugging this data into non-connected systems is great, and of course your numbers will get better, but you’re not doing machine learning; and the promise of this technology is that the next prediction will be smarter. You still have the human in the loop on the tactics and creative, but eventually the machine’s going to do that as well. Why would I want to have a marketing director making those decisions any more?
“Throw your hat in the ring, or you’re going to be eaten. You don’t have a choice in this matter.”
ABM: “I know you’re recording this, but…”
“When my co-founder and I first heard the term ABM, we were like, what is this…? We’ve been doing this from day one. The bottom line is that there’s so much money, there’s so much wind, in terms of private equity dollars in the marketing and sales of those organizations that are using this as an umbrella term, that to fight against those winds didn’t seem to make sense. And of course there’s some validity to this idea of ABM as opposed to marketing to accounts. I don’t think we were doing pure account based marketing the whole time, but we were always marketing to accounts.
“In our view now, unless you’re using predictive, you can’t do ABM, and you certainly can’t scale it.”
