In this week’s Brand Innovator series interview, I speak with Jamie Grenney, the vice president of marketing at Infer—a predictive lead-scoring solution for sales and marketing teams. Grenney began his B2B tech career at Salesforce when the company was still in its earlier stages. After contributing massively to the company’s efforts to go public, Grenney saw an opportunity to board another start-up with high hopes for success.
Below we discuss the need for an end-to-end predictive lead-scoring solution, and how Grenney and his team use content marketing to fuel awareness around a new, and rather unknown, technology.
I came out to San Francisco in 2002 and was very fortunate to land at salesforce.com. At the time, there might have been 140 people. While I’ve always been a marketer at heart, I took a job on the inside sales team answering the 800 line. As Eric Schmidt from Google puts it: “If you’re offered a seat on a rocket ship, you don’t ask what seat. You just get on.” I learned a ton from the three years I spent in sales. I had the opportunity to define our inside sales playbook and I moonlighted on marketing projects. Eventually I was tapped to focus on marketing full time. I spent 11 amazing years at Salesforce helping write marketing playbooks and evangelize cloud computing.
When I was introduced to Infer, it felt like an opportunity to board another rocket ship—only this time at a much earlier stage. With big data and predictive modeling, we’re on the precipice of another disruptive shift. Similar to cloud computing, it’s going to unlock huge productivity gains and fundamentally change the way businesses operate. For a marketer, being on the leading edge of a shift like this is really exciting.
Every sales and marketing organization is faced with a similar challenge. At some point, sales will inevitably say, “We need more leads,” and marketing will shoot back, “Why aren’t you following up with the leads we generated?” to which sales will reply, “We need more good leads.” Applications like Salesforce go a long way in helping bridge this divide. But even still, most companies don’t have an automated and objective way to measure lead quality.
Even though we’re a relatively small company, we use predictive scoring to automatically research leads and determine which ones are marketing qualified. We do this for leads that come off our website, but an even better example might be how we approach events. At our trade-show booth, we have an app we call “Score-O-Matic.” When people come by, we have them type in their email addresses. In real time we’ll go out, crawl the web, and add thousands of external signals about the individual and the organization they work for. Things like relevant job posts, employee count, patent filings, social presence, website traffic, and even the technology vendors they use are all added to the app.
Score-O-Matic returns a score highlighting how good a fit people are for our product. We also include the top 10 signals from the model to help facilitate a conversation. For people who score low, we don’t want to force it. And for people who are great fits, we can go deep and have longer conversations. In the past, we might not have known for weeks if an event was successful; with predictive scoring, we’ve got instant insight.
Because our space is so new, not a lot of people are searching Google for “predictive lead-scoring solution.” Therefore we’ve got to use content marketing to capture their attention and get them thinking about why they should prioritize this forward-thinking initiative. It is difficult to take someone from 0 to 60 in one session. You’ve got to nurture them along. We use targeted advertising and promoted content to attract the right audience. If we can get people to click through to our site, we can set a cookie and re-market to them using AdRoll. It’s very similar to an email-marketing journey, only we don’t need their email addresses. We’re able to reach them on third-party sites, expose them to our messages and content, and hopefully educate them toward conversion.
When I think about content, I think about three buckets: premium, fast food, and community driven. Premium content takes time to create, but it shapes your brand and defines your place in the industry. Fast-food content serves a purpose. It is cheaper to produce, it tastes good, but it offers less nutritional value. And then there is community-driven content. You might set up an influencer program or an MVP program. This is the most scalable form of content creation if you can create the right environment for it to work. All three approaches have their place.
At Infer, we’re focused on premium content today. We believe that predictive represents a shift in our industry that could be every bit as disruptive as cloud computing was a decade ago. We’re trying to get ahead of that wave with thought-leadership content and actionable playbooks. Over time we’d like to create a vibrant online community, and maybe we’ll reach a point where fast food also makes sense.
We think that “cost per good lead” will become a metric that many marketers gravitate toward, especially content marketers. As we try to reach buyers further up the funnel, it becomes harder and harder to connect our efforts with pipeline impact. The advantage of using predictive to quantify return on investment (ROI) is that you can see into the future. The moment someone fills out a form, you can accurately predict whether or not that person is a good lead. That allows us to adjust quickly and place the right bets. And it gives us due credit for our top-of-funnel programs.
I think Marc Benioff did an amazing job of turning a simple idea into an epic journey. When he founded Salesforce, the question he asked was, “Why can’t all business applications be as easy to use as Amazon.com?” He capitalized on people’s frustration with client-server technologies and declared the end of software. Framing Salesforce’s story into a David and Goliath narrative gave him a consistent story line that people could follow and write about.
Finding your story is so important, especially when you’re trying to disrupt an existing market. At Infer, the question we’re asking is, “Why can’t every business operate with the same data-driven intelligence as Google or Amazon?” While companies have invested heavily in the promise of automation software, most applications still rely on brute force and human intuition. We think there is a better way. Companies of all sizes should be able to automate basic decisions by tapping into predictive-as-a-service.
The projects we’re working on right now that I’m most proud of are our customer stories. There is nothing more rewarding than packaging up inspirational stories and turning our customers into heroes. It’s still the early days when it comes to predictive, and it is so exciting to hear about innovative use cases and the amazing results that companies are achieving.
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