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It’s safe to say that the next generation of successful businesses will look to Augmented Intelligence (AI) to revolutionize their entire organization. Look no further than IBM and Salesforce’s landmark global strategic partnership, which will seamlessly connect IBM Watson and Salesforce Einstein to enable new levels of intelligent customer engagement for companies of all sizes. Rather than be isolated to databases, pulled by queries in response to an ask, data is being integrated throughout an organization’s business processes–across Service, Sales, Marketing, and IT–turned into actionable and predictive analytics by intelligent customer and employee-facing apps.

However, the conversation in today’s global market pivots around not how much data an organization captures, but how it leverages that data to get closer to its customers while maintaining scalability across the enterprise. Data intelligence is powering a new kind of business-customer relationship, based on delivering personal, simple, and consistent experiences. This isn’t black magic, but solid science that can be grasped, tamed, and applied to a wide range of problems managers face all the time. Those who embrace this data intelligence revolution will lead the way to becoming a customer-obsessed business. Those who don’t will scramble to play catch-up and wonder how the others did it.

One such company that is embracing AI to transform business is, whose sales lead management software is powered by a predictive and prescriptive self-learning engine. I had the opportunity to chat with its CMO, Mick Hollison, to discuss the value of analytics.

There are a ton of conversations going on around data right now, and the first thing I want to address is this concept of predictive. Everyone says predictive, but what does that mean to you?

Mick Hollison: There’s a quote by Spanish philosopher and poet George Santayana that I think is pretty apt for this discussion: “Those who forget history are doomed to repeat it.” To me, predictive is about seeing into the future through the lens of the past. What’s interesting and new about that—and why it’s so important today—is that the advent of big data has made it possible to almost infinitely see into the past, whether that’s a past sales interaction or past customer engagement. In the end, predictive is about leveraging past insights to help guide you into the future.

Dialing it back to today, the terms analytics, big data, predictive and now AI are the latest buzzwords. You and I have been around long enough to know that once the buzzwords start hitting, it gets difficult for customers to figure out their true paths. What key attributes should buyers and decision makers take into consideration as they start to make investments in these types of technologies?

MH: The first is painfully apparent, but people love to ignore the obvious, so let’s start there. Is the company from whom you’re buying tools and tech built to last, or does it just have a new widget that solves a single pain point?

Second, infrastructure and security need to be rock solid. anonymizes buyer profiles, for example. When you give another company access to your most precious data in the world—your customer data—you have to feel confident in its infrastructure and security.

Third, make sure that whoever you buy from has an open platform with a great API set and development kit. Closed or proprietary tech just leads to problems down the line as business complexity increases.

Lastly, make sure that the platform you’re buying extends to multiple business functions. You don’t want to end up with 18 predictive tools solving discrete business problems. The smarter path is to pick a company that is thinking of predictive as more of a platform where the algorithm sets are horizontal enough that they can apply to more business challenges.

Prior to Salesforce, powerful enterprise software was reserved for the privileged few that could afford it and get through a nasty implementation. A big reason that Salesforce took the market by storm was that their product was so easy to buy and use that they flooded the market, drawing in customers of all shapes and sizes. As you look at predictive, do you see a solution like or other solutions having that same impact, so that it’s truly a democratized offering for organizations? Do you see history repeating itself there?

MH: Yes, absolutely. I think we’re going to end up with a predictive app ecosystem, much like what we have with iOS and Android on mobile devices. I’m an Apple user myself, and the reason I’m going to remain one isn’t just that it has a beautiful, powerful design; it’s the apps. The reason I can’t possibly fathom changing, even if somebody came out with faster processors or better screen resolution, is that I’m so wedded to that ecosystem. I believe we’re going to end up with a very similar thing [with predictive analytics].

There are going to be two or three predictive ecosystems with app portfolios that will distinguish those players from anyone else in the marketplace. I would argue that even today that’s the competitive motive for Salesforce. Is Microsoft Dynamics just as good of a base CRM? Yes, I think it is. Have they built up the same level of app ecosystem? Not even close. Predictive will become democratized, and we’re going to have a really rich set of predictive apps, but they’re only going to run on top of two or three platforms.

That’s a great way to look at it. Anything else you want to add?

MH: In the analytics market, it’s definitely still early, and everyone is trying to find their way in terms of predictive. What’s really going to separate the men from the boys, aside from an open ecosystem, is who actually has great data to derive great insights. If you don’t have a good underlying data set, it’s like anything else in computing: garbage in, garbage out.

One of the things is uniquely positioned with is that we already have over 100 billion sales interactions in our data store, and that number keeps growing. As the number of sales interactions increases, we’ll get even more accurate in what we can prescribe. The biggest differentiator beyond the ecosystem front is who’s got the best data—and those with the best data are going to win.

The interview has been excerpted from chapter 9 of Eric Berridge’s book, Customer Obsessed.