On Marketing Technology

MTS: What inspired the creation of Openprise, how did you get here?

Prior to founding Openprise, I was VP of Marketing and Product Management at a number of startups. Over the years, I deployed marketing automation technologies three times at different companies. Each time, our team was frustrated at not being able to do more with our technology investment once we got the very basic web forms, email campaigns, and activity based scoring set up. We were stopped in our tracks every time we tried to do anything more advanced like profile based scoring, segmentation, or account level engagement analysis. This was mainly because the amount of time and effort required to get the data in good enough shape to support those initiatives was prohibitively high. We couldn’t find a solution that had enough flexibility, at a price we could afford, that could be usable by the marketing team without developers. So, I founded Openprise and built a product that I wished I had in my prior roles.

MTS: Given the massive proliferation of marketing technology, how do you see the martech market evolving over the next few years?

I see a couple of major trends

– Any market that has proliferated like MarTech is bound to go through a consolidation phase. Expect to see leaders emerge in each category with point solutions consolidated by broader platforms.

– AI/machine learning /deep learning /predictive analytics is powerful technology, but it is also overly hyped. I expect to see customer’s expectations for this technology to become more realistic, so it matures from being perceived as a “silver bullet” to more pragmatic solutions that deliver concrete value.

– Over the last five years marketing was in a “data generation” phase. With the broad adoption of marketing automation technologies, data was generated at unprecedented rates, to the point where any marketer with a budget could buy as much data as he or she wanted. In the next five years, I see the focus shifting toward getting better insights and automation from this new data. In a nutshell, marketers need to figure out which data is relevant, mash up all of the data silos, and derive value from it.

MTS: What do you see as the single most important technology trend or development that’s going to impact us?

I believe that easy-to-use data automation and process integration technologies will be the most important technologies for the next five years. As I mentioned earlier, we have now moved from not having enough data to having too much data in silos. All of this data needs to be integrated and mashed up to drive decision-making and automate processes. The traditional middleware products are too difficult for marketers to use and cost too much. To address these issues, a whole new generation of technologies is emerging, purposely designed to meet the requirements of marketing and sales professionals.

MTS: Product integrations, partnerships or ingenious innovation—Which eventually lead to the most $ value in a B2B ecosystem?

Partnerships and integrations go hand-in-hand. The best partnerships are driven by a large integration base from ISV partners, such as the Salesforce AppExchange. Innovation comes and goes. Even the most innovative companies will have slow stretches. Larger ecosystems can sustain innovation by leveraging large partner bases.

MTS: What’s the biggest challenge that B2B businesses need to address to make marketing technologies work?

Solving any business problem means figuring out the people > process > data > technology parts, in that order. The biggest challenge in optimizing marketing technology is to have the discipline to figure out the first three parts (people, process, data) and not jump directly to technology acquisition. Automating bad people, inefficient processes, and poor quality data just creates an even bigger problem, faster.

MTS: What advice do you have for new businesses making their first foray of investments in marketing technologies?

Understand your people, process, and data first. That understanding will dictate which technology you require and identify what will work best for your needs. Buy the technology best suited for your company’s maturity and resource availability. Marketers occasionally suffer from “shiny new object syndrome” and are sometimes dazzled into making an unsuitable purchase.  I’d advise a new business to stay away from scenarios where you buy technology you “want” rather than need, or because everyone else is buying it, or because industry analysts say you should have it. There is no “magic bullet” solution that can deliver value instantly without you putting in the effort to make it fit with your people and process, and getting your data ready to support the technology.

MTS: How do you see data automation affecting people-based marketing and the analytics ecosystem in the next few years?

In the last ten years, marketing has moved from being a creative discipline to a data-driven discipline. As a result, a lot of manual efforts are now invested in making the data work, and 80% of that work is very laborious and repetitive. As data automation technology becomes more widely adopted and frees up that 80% of manual work, I see marketing creativity taking center stage again. However, it’s going to be a bit different this time around. The creativity is now driven with better data about the audience and facilitated by the ability to get almost instantaneous feedback. Data and automation technology will help us be more creative and have more time to be creative. Maybe we could call it, “Data-driven creativity!”

MTS: How well are today’s marketing technologies solving challenges in data management, customer experience and marketing attribution?

Not very well, yet. Data is still mostly in silos, and that’s the limiting factor to everything MarTech. Bringing data together from different silos and mashing it together to make it useful and available in the various operating platforms is still too hard and too technical. Until we can make more progress in making data more usable across systems and departments, any MarTech solution will only be minimally useful, with limited ROI.

MTS: What start-ups are you watching/keen on right now?

I won’t name names, but I do see some very compelling ideas around algorithm-based solutions. However, I think the key is not who has the best algorithm because there will always be another better or more suitable algorithm. The most successful solutions will be the ones that can figure out how to best integrate their algorithm into existing processes and work with people based constraints. In other words, how to make the “machines / bots” fit into intrinsically imperfect processes powered by imperfect humans.

MTS: What tools does your marketing stack consist of in 2017?

Our core stack is Salesforce and Marketo. Other key solutions are Google Analytics, WordPress, and ZoomInfo. We leverage Openprise extensively ourselves to keep our own MarTech stack working well and to automate many processes. It also enables us to keep our stack as simple as possible with the minimum number of technologies and data silos. For example, Openprise takes care of data cleansing, enrichment, lead routing, lead segmentation, list loading, deduplication, account based analytics, as well as being our marketing dashboard.

MTS: Could you tell us about a standout digital campaign at Openprise? (What was your target audience and how did you measure success) 

There are way too many martech vendors trying to get the attention of the same prospects, so I won’t share our best campaigns with the thousands of marketers reading this interview. That wouldn’t be a very good idea. Given how fast our customer base is growing, however, I’d say we’re doing a lot of things right.

MTS: How do you prepare for an AI-centric world as a business leader? 

I believe AI has huge potential to help human beings become more efficient, but will not replace human decisions and creativity. It’s a company leader’s job to ensure the company embraces AI technology to get its benefits, and to use it in a way to augment the human workforce and support decision-making. It’s also important for business leaders to not let AI become a crutch for the team to become “intellectually-lazy” or let the fear of “robots will take my job” to cause resistance towards technology adoption.