Infer’s Sean Zinsmeister Talks AI in B2B Marketing, Best Practices and More

If you’re in B2B marketing or sales, chances are you’ve heard a lot of talk about things like account-based marketing and predictive analytics lately. Our very own Sean Zinsmeister is making the rounds in the headlines recently too, offering up his thoughts on those hot topics and more. From 2016 predictions to best practices, here’s a roundup of Sean’s insights from around the web.

As artificial intelligence technology gives us more data than ever, B2B marketers are taking a cue from B2C marketers on how to transform large amounts of data into actionable intelligence. In this Technology Advice podcast, Infer’s Senior Director of Product Marketing, Sean Zinsmeister, chats with TA about how predictive analytics are transforming B2B marketing by empowering a more strategic and personalized customer experience.

“The more we get to know the types of people that are interacting with us online, the more we can really structure a great conversation. At the end of the day, the key [to using data] is to solve market problems. When you start focusing on solving market problems… you’re automatically using data to improve the customer experience.”

Critical customer data is spread out all over the place, including across the web as well as systems inside and outside a company. Over on the Marketo Blog, Sean gives marketers tangible best practices on how to use predictive solutions to reinvent their approach to prospect management.

“Today, you can pinpoint the best net new prospects with unprecedented precision–a better way to feed hungry salespeople and avoid forfeiting deals you don’t know about to your competition.”

It’s a no-brainer that the sales and marketing world is rapidly evolving and 2016 will bring even more growth. Read more to find out which five key changes Sean predicts we’ll see in the B2B space this year.

“Powerful automation and sophisticated data science aren’t enough. It’s important to keep in mind that the roles, behaviors and processes of marketing and sales folks must adapt as well.”

Predictive analytics brings a whole new perspective to how marketers are developing and executing against their ABM, or account-based marketing, strategy. On Business2Community, Sean shares four best practices for how marketers can leverage predictive in their ABM strategy.

“…it’s no longer a pipe dream to be able to identify the universe of accounts that are a good fit for your product and deliver personalization at scale. ABM has the potential to open up entirely new revenue channels and marketing tactics.”

LeanData’s Adam New-Waterson sets the record straight on what ABM means for marketers and how it will enable them to be more results-focused than ever before. Infer’s Sean Zinsmeister is also quoted on how smart ABM strategies can enable marketers to fill the marketing funnel faster and, in turn, increase revenue.

“Marketers can’t afford to sit back and wait for all prospects to show up at their doorstep. They need to be filling the top of the funnel with outbound, or net-new, lead generation to feed sales reps and increase potential revenue. The last thing businesses want to do is forfeit a good account simply because they weren’t aware of it.“

Smart marketers don’t rest on their laurels; they evolve their skills to stay on the cutting edge of their field. In this expert roundup on Direct Marketing News, Sean shares his perspective on why mastering ABM is a must-have skill for marketers in the new year.

“ABM has the potential to open up new revenue channels now that all companies can easily identify best-fit accounts and deliver personalization at scale—via advertising, direct marketing, and more.”

Sean Zinsmeister is at it again, discussing how predictive analytics impacts account-based marketing and why are both such a hot topic right now. Read more now at Terminus.

“Predictive helps prioritize how you engage with the right customers when you have a large amount of customer data. It’s all about finding out who your best-fit customers are and then learning how to reach these customers.”

WSJ on “The Data-Driven Rebirth of a Salesman”

Last week, Elizabeth Dwoskin and Shira Ovide of the Wall Street Journal wrote a great article on predictive sales technologies. Their comparison of Willy Loman from “Death of a Salesman” to modern data-driven salespeople really brings home how much has changed for reps in the world of big data. If you don’t have time to peruse the full story, here are some key excerpts:

WallStreetJournal_0

“Silicon Valley startups are automating sales departments for a shot at the more than $23 billion companies spend each year on sales software. Some of these startups mine sales staff emails, calendars, social-media feeds as well as news articles and customer databases for patterns that help them predict the likelihood of a sale or the behavior of potential buyers.

Infer’s Sean Zinsmeister on the Gold Rush for Predictive Data

Our very own Director of Product Marketing, Sean Zinsmeister, recently sat down with folks from a couple great interview series — MarTech Heads and TA Expert Interviews. During these insightful conversations, Sean spoke with the podcast hosts about predictive sales and marketing, marketing campaign successes and challenges, third-party intent data, the shift from predictive to prescriptive intelligence, his favorite martech tools and tips, and more.

Have a listen:

The Math Behind SaaS

Math Behind SaaSOur friend Tomasz Tunguz at Redpoint Ventures recently asked Vik Singh to write up his techniques for estimating Infer’s customer lifetime value (LTV) and customer acquisition cost (CAC) using a rolling sales and marketing period. Unlike the standard formulas that most investors use to determine LTV and CAC, Vik’s “expected” CAC/LTV approach is more forward-looking and actionable for SaaS entrepreneurs because it doesn’t require years of historical customer data or perfect attribution of sales and marketing spend.

Below are the formulas Vik uses to measure our business, building off of some basic metrics like cost per opportunity, win rate and average deal size:

Expected # of New Customers = Opportunity win rate X # of opportunities

Expected CAC = Fully-loaded growth spend / Expected new customers

Expected Payback Period = ECAC / Average annual contract value X 12 months

Expected First-year ROI = First-year ACV / ECAC

Congrats to CRM Market Elite Winner

It’s great to see the smart folks over at Concur be recognized for their impressive results with our predictive lead scoring. CRM’s 2015 Market Elite Customer Company winners all demonstrate how technology can impact operating costs and efficiency, and Concur is no exception. Here’s an excerpt from the company’s profile in this month’s issue of CRM Magazine:

Infer’s predictive lead scoring helps Concur close more deals more quickly

The Infer solution helps Concur identify and prioritize the marketing-qualified leads that are most likely to convert to closed deals. It pulls in thousands of external signals, going well beyond what most organizations track in their basic CRM and marketing automation tools.

Greg Forrest - Concur“We’re finding leads a lot quicker and getting them into the pipeline a lot faster,” Forrest states proudly, “and we’re closing at a much higher rate.”

Based on the results Concur has seen in the first six months, the company is expanding the Infer solution to its cross-selling and upselling activities, account scoring, and direct marketing.

REAL RESULTS

  • Five thousand marketing-qualified leads were uncovered in its database, leading to a dramatic run-rate increase.
  • The number of leads converted to closed deals tripled.
  • Conversion rates increased by 150 percent, from 0.8 percent to 2 percent.
  • Closed deals for new solutions were boosted by 76 percent.

For more details, check out the magazine’s full story on Concur.

Jerry Yang on His Investment in Infer

Jerry YangI’ve been very lucky during my career to work with some brilliant mentors, one of whom is the founder of Yahoo!, Jerry Yang. I worked with Jerry at Yahoo!, where he helped me push an ambitious product called BOSS (which stands for “Build your Own Search Service”). We’ve stayed in touch since then and he’s been incredibly supportive of Infer’s approach. Many Yahoo! products related to web search, content optimization, etc. live and die on data science, so he’s passionate about the opportunity to bring this rigor into enterprise software.

Following a recent Business Insider profile, we asked Jerry to answer a few specific questions about why he decided to invest in our company, and in the predictive analytics space in general. Here’s what he shared:

Why do you think there’s such a big opportunity in predictive analytics? Yahoo! through its development of Hadoop witnessed what predictive analytics could do with the massive scale of user data. Now it’s exciting to see companies like Infer bringing this technology to other vertical industries that can benefit from it. There’s definitely a huge opportunity for businesses to transform their operations and decision making by using data.

Why did you invest in Infer? For me, I place a very high value on the entrepreneur and founder. In the case of Vik Singh, we go way back to working closely together while we were at Yahoo. Vik was working on Yahoo! BOSS, a search product that quickly became strategically important to the company. We had a great relationship that continued beyond Yahoo!, and it’s a pleasure to support Vik in this venture.

Take a Listen to “Moneyball for Marketing”

This week our CRO, Jim Herbold, got a chance to sit down with B2B marketing thought leader, Glenn Gow, for his popular Moneyball for Marketing podcast.

Jim Herbold

Jim and Glenn talked about all things predictive – including marketing use cases for predictive intelligence, real world success stories, and four B2B barriers to predictive analytics adoption that are rapidly disappearing. Check out this excerpt from their lively discussion…

Glenn: Tell us an example of what companies are doing in the real world and how they’re taking advantage of predictive analytics.

Jim: Well, there’s an easy example I can speak to. I was the first customer of this company Infer when I worked at Box. When I was running sales at Box, I had the luxurious challenge of dealing with very large lead flows. We had a freemium aspect to the business. We also had a very vibrant free trial aspect to allowing people to get into our service pretty quickly. So, very large flows and leads, we’re talking tens of thousands and I could never afford to apply a lead qualifier to plow through all of those leads systematically over time. I needed a way to find the proverbial needle in a haystack and I started working with Infer.

Predictive Will Be Abuzz at SXSW

Predictive is well on its way to becoming one of the hottest technologies of 2015, so it’s not surprising the topic will be featured at one of the biggest tech conferences of the year – the SXSW Interactive Festival, which kicks off this Friday. On Saturday, we’ll be facilitating a session titled “All Signs Point to Yes – Predictive is Here.”

SXSW Predictive

The panel will be moderated by Ryan Sarver, formerly an early Twitter employee and now a Redpoint Ventures partner who’s making big bets on intelligent applications in the B2B and B2C space. He’ll lead a discussion with our own Vik Singh, as well as Jonathan Foley, vice president of science at Gild, and Karl Rumelhart, vice president of products at Gainsight, about how predictive is making its way into every part of the enterprise.

Infer’s Billboard on Highway 101

Look for Infer’s Billboard as you’re driving northbound on 101 heading into the San Francisco. Below is a map. Let us know what you think of it and share your pictures of the billboard! You can @mention Infer and use the #predictwinners hashtag on twitter. It is our first foray into billboard advertising so we’re excited to see the response we get from prospects, customers, and new recruits.

Infer's Billboard - Highway 101

How LinkedIn Could Take On Salesforce

Originally Posted on TechCrunchlinkedin-salesforce-collide

Today’s B2B sales and marketing folks struggle with the overwhelming number of channels for finding and reaching new leads. The customer “funnel” continues to expand as buyers do more of their own research before raising their hand to connect with a sales rep. But imagine if you could make the funnel wider by identifying leads when they’re just browsing your site and haven’t yet filled out your “contact me” form, or leads who haven’t yet visited but are likely to be a good fit for your product?

That’s hard to do with the primitive tools that are available for sales and marketers today, unless you bring together some very rare assets — which just so happen to all exist at LinkedIn.

LinkedIn is the only company with… Continue Reading on TechCrunch