, the big data unicorn that is transforming the sales industry with its predictive cloud

Coming out of the Silicon Slopes of Utah, the enterprise startup was valued at $1 billion as long ago as April 2014, following a $100m funding round. The company has been focusing on establishing a European presence, launching new products and establishing key partnerships with the likes of Salesforce and Microsoft since.

Share was founded ten years ago by Dave Elkington. The philosophy major from Brigham Young University with no background in sales wanted to see if human behaviour could be predicted and how this might affect business. The explosion of big data and developments in machine learning and AI gave him that opportunity.

So, why sales? Cynically, it’s because this was an industry where the product was ripe for monetisation.


Over the past decade Elkington has quietly been going about collecting huge volumes of sales data, more than 120 billion sales transactions to be exact. On top of that the company has been applying machine learning algorithms to create a predictive analytics platform. The result is called Neuralytics and the desired result is “an Amazon-style recommendation engine for businesses”, as Elkington put it in a press release.

Martin Moran, general manager EMEA for, told ComputerworldUK: “What we’ve found over the years is that not all data is equal. It’s the data that is important. You can build the world’s best algorithm but if the data isn’t right it’s useless.”

Industry changes has been able to take advantage of a rapidly changing sales landscape. Cold calling has never been effective and wants to put the final nail in the coffin. Buyers are more discerning and more likely to purchase online than ever. Salespeople need to be thinking more in line with the buyer’s habits than ever.

As Moran sees it: “Sixty percent of buying decisions are being made before talking to the vendor, so companies want to get into that buying pattern earlier.”

This, of course, is difficult, which is where the predictive Neuralytics engine comes in. Moran explains: “Either you insert yourself into that digital process, which is pretty difficult, or predict the potential buying patterns of your customers and therefore be able to engage at the right time, with the right offers, in the right way.”

The system isn’t a silver bullet for underperforming sales teams though, it requires a change of culture. “If you have a broken sales process then predictive analytics isn’t going to help you,” says Moran.

Microsoft announced the full integration of certain products into Microsoft’s Dynamics customer relationship management (CRM) system in December. Microsoft is also an investor in the company.

The company is focusing on pushing out its Accelerate product for Dynamics. This allows salespeople to prioritise leads using the Neuralytics engine to identify sales patterns and prescribe recommended actions for staff to boost sales. The company claims that this can help boost revenues by up to 30 percent.

Accelerate for Microsoft Dynamics CRM will become widely available in April next year and is priced at $125 per user per month.

Additional CRM products to come include predictive tools for forecasting and pipeline management, as well as a Sales Advisor tool that should help salespeople focus on deals that are the most likely to close. These products are currently for early access partners only.

Moran sees the new partnership with Microsoft as potentially very beneficial for customers. “Most companies have invested in CRM and in some respects they haven’t quite seen the return they hoped for” he says, “the biggest issue we’ll see is that salespeople purely see it as a management tool, and that’s pretty typical."


When asked if is reliant on the popular CRM platforms integrating and working with them, such as his former employer, he hesitated before admitting: “Yeah. I mean, reliant? Yeah, I think we are.”

He goes on to explain: “The reason we’re tied to CRM is that in-essence that’s where you get the biggest bang for your buck as a user. So if I’m a salesperson trying to sell to you, if I can have immediate information about your propensity to buy and when you are most likely to be contacted, then having that dynamically in my CRM is most useful to me.”

The second point here is a key one to salespeople. Wasted hours trying to contact customers is an inefficiency, and as with any inefficiency it’s one that companies are keen to cut down on. The data can be used to predict patterns of contactability and also the modality.

Moran led on a research project with MIT and Harvard Business Review to look into the “cadence” of sales-buyer communication. “If I’m trying to contact you,” Moran says, “generally there is a cadence, and it can vary between phone, voicemail, email etc. We give people the ability to track those contacts and start reporting patterns and use those to inform their sales teams.”


It doesn’t stop with sales and the predictive cloud though. is currently working on ways to use their data and algorithms to improve everything from reporting to recruitment.

What Moran is seeing is a change in the culture around enterprise sales, in particular: “A lot of enterprise sales people come from a perpetual licence background,” he says, “so working with the likes of Microsoft, SAP and Oracle. You have no idea how they’re going to perform in the cloud.”

Moran explained: “When you look at what most companies do, they hire a recruiter, or they outsource it, they get CVs, they interview people, some might do Briggs Myer (sic) personality testing, but in essence what it comes down to is: Does the CV look good, do they have the skills?”

This led to the creation of Sales Indicator,’s attempt to predict performance in terms of if a new hire will be able to hit a set quota. currently reports an accuracy rate by this measure of 80 percent. Recruiters are apparently around 60 percent accurate.

Other products being built on the back of the company’s predictive data includes HD Forecast for sales pipelines and PowerDialer, a dialling technology that integrates with your company’s phone system so that the system not only tells you when the best time to contact a customer is, but dials the number for you.

LogMeIn Case Study

Boston-based cloud tech company LogMeIn started working with two and half years ago and, according to Chris Perrotti, senior director of sales systems at LogMeIn, the partnership has been “evolutionary”, driving his sales team’s call rates up “around 30 percent”.

© LogMeIn

LogMeIn wanted a product that integrated with Salesforce and could provide automated logging for its CRM. The company now uses’s PowerDialer, PowerStandings (see below) and Vision (email tracking) products as the backbone of its inside sales team and how they measure their success.

What impressed Perrotti was how, within five minutes of finishing the introductory video on the website he received a call from a local number asking him if he liked the video and wanted to talk to someone about trialling the product. As Perrotti put it: “As a potential customer, and someone hoping to drive the same sort of thing, that got my attention.”

Perrotti says it has been challenging bringing an American attitude to sales over to the European teams but that as the salespeople realise that the prescriptive tools can help free up their time and drive better call rates, rather than making them feel like an “automaton”, as Perrotti put it, they have been more open to the tools.

One of these is the PowerStandings tool. This is a form of gamification as it pits the global salesforce against one another to deliver on key performance indicators (KPIs). When a salesperson jumps up the leaderboard or achieves a goal their personal song is played around the global offices and is displayed on a sports channel-like ticker tape on screens in the offices.

Martin Moran sees this new visualisation of the natural competitiveness within sales teams as indicative of a broader change in the sales industry. “The interesting thing here was the way [] started looking at the motivation aspect,” says Moran, “some people are individually competitive and some people are competitive in a team environment.”

“The other thing that becomes apparent is that the new workforce, the millennials, apart from the fact that they aren’t career focused any more, is that they are motivated by different things. As long as they’re basically happy with what they are paid, recognition plays a much bigger part, and what these games do is really drive home recognition. That seems to be a really powerful motivator.”

Perrotti isn’t all compliments though, stating that the tools work better in the USA as the telephony networks are more solid, saying: “US infrastructure works better. The apps work the same [in Europe] but the underlying partnerships are more immature.”

In the long term this doesn’t worry him though. The two companies have had a “relative evolution” according to Perrotti and, “we’re both growing fast and have had similar maturation struggles, so there is a general empathy for each other as we grow. We’ve had challenges but I believe in their thinking and strategy. The products sometimes don’t keep up, but I’m more interested in the thinking behind them.”

Conclusion is a genuine unicorn and has the advantage of being able to develop a suite of products in a focused industry that is always looking for a cutting edge. The business and key partnerships are already there, so the revenue should follow.

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