The Great DB8 on Predictive
Over 125 B2B marketers squeezed into Bloomberg’s San Francisco offices for a lively “DB8″ featuring prominent predictive technology vendors (e.g. 6sense). The event was produced by marketing agencies DWA and April Six.
Cory Johnson, Anchor and Editor-at-Large, Bloomberg, moderated the debate, and the panelists included:
- Amanda Kahlow, CEO and Founder, 6sense
- Darian Shirazi, CEO, Radius
- Doug Bewsher, CEO, LeadSpace
- Jamie Grenney, VP of Marketing, Infer
- J. Kardwell, Predident, EverString
- Tal Segalov, CO-Founder and CTO, Mintigo
Predictive analytics is the one of the most important technologies in B2B marketing in the last 10 years and is already significantly changing how businesses find, reach and target buyers. While all panelists agreed on that point, there were a several debate-worthy points and counterpoints:
- Do you account for that moment in time? Even if you collect attributes about your ideal buyers, those amount to little without visibility into time-sensitive information about what those buyers are doing, where and when. Otherwise, that ideal buyer just looks like 1 million other ideal buyers… The reality is… The most accurate predictive models use time-sensitive intent data to determine where prospects are in the sales funnel. But buying behavior data is always changing, and with the right predictive solution that takes time into account, marketers can gauge the appropriate time to reach out and if/when there is urgency (i.e. a prospect is ready to purchase, whether it’s your product or a competitors’).
- Context is king. How do structured and unstructured data play a role in predictive, and which matters more? This was a question Amanda tackled, explaining how structured data is now commoditized: anyone can crawl for or buy data to find attributes about a buyer. And further, does this firmographic data provide a real prediction or just a match? We’d say: “match.” What’s truly predictive is the logical and contextual meaning derived from multiple types of data– for example, unstructured data (pages, words and descriptions) — to find the gems that provide context, and as a result, a real prediction about who, when, where a sale will occur.
- You’ve got to tie it all together. While all predictive companies have varying inputs that affect results’ accuracy, tying data together in predictive is equally crucial. It makes me think of learning to tie shoelaces as a kid –over, under, around and through. Mastering the bunny ears was the first step. Like data, you must have a handle on that to proceed. But then, tying the bunny ears together, is where the preparation and inputs can fall apart. The same stands with predictive. Just like bunny ears, you’ve got to tie ALL the data together, which requires precision, accuracy and multiple predictive models in order to get strong results.
- I have enough data! What’s next? An audience member from Salesforce expressed a common concern: “I already have too much data about my prospects. Why do I need more?” First, predictive technologies help us prioritize the most promising prospects by using math and machine-learning to predict which ones are likely to buy. Predictive lead scoring solutions rank and sort those known prospects and customers. But, what about the buyers that are in market yet completely unknown to your marketing and sales teams? Two simple and powerful words: NET. NEW. That’s what 6sense does – finds net-new buyers your team was unaware of and who are ready to buy now.
- What is your goal? Before you embark on your own buying journey for a predictive analytics solution, think about your goals and your biggest pain points. Is your goal to find new leads or to get to the bargaining table before your competitors? Figure out what your goals are first, and then do your homework.
Last night was a great opportunity for predictive vendors to talk about their differences and views on what helps B2B marketers the most. As most debates go, participants’ answers raised even more pressing questions but everyone left with this common ground: the predictive industry is thriving and innovating in ways marketing and sales technology hasn’t seen before.