“Predictive” will become a very often-used adjective in IT in 2015, even more so than it has in the past. How do we know this? Simply by looking around at where an increasing number of venture capitalists and private investors are parking their money: Much of it is in intelligent software that “predicts” the future by analyzing the patterns of the past and producing scientific determinations.
Generally, there hasn’t been nearly as much analytic capability in as many applications as there is today, especially in mobile devices. One research house reported recently that, on average, smartphones contain seven to eight apps that use some sort of analytics. Examples might be apps involving traffic or finding rides, dates, restaurants, parking places and the like.
There’s been a lot of buzz for a long time about predictive analytics–software, for example, that will accurately predict a company’s spikes (or nadirs) in sales, so that the shelves can be filled with the right products at the right time to optimize sales and buying patterns.
Another, more recent trend involves predicting which types of customers are the best prospects for a company. Sales teams are now using data, from both internal and external sources, to help determine the most promising prospects, so they can save time, travel and effort.
Predictive Scoring Determines Best Potential Customers
That’s where Palo Alto, Calif.-based startup Infer comes in; it provides something called predictive scoring for sales organizations to add to their Salesforce and/or other tools. There’s little sense in spending marketing dollars and sales time on customers who have no interest in what you have to sell, so they need to be weeded out in advance.
Infer, available as a cloud service or as an onsite app, works by ingesting streams of corporate sales data from various CRMs (Salesforce.com, Marketo and Google Analytics, for example) and other sales and marketing databases. It then combines that key internal data with various other information available on the Web, such as company financials, corporate job listings, legal filings, and social media records of potential customers.
It all gets added up and analyzed to offer indications as to whether a potential customer really intends to buy whatever product or service an Infer client is selling.
With all this as background, Infer announced Dec. 11 that has raised $25 million in Series B funding from Redpoint Ventures. Previous investors included Redpoint, Andreessen Horowitz, Social+Capital Partnership, Sutter Hill Ventures and individual angels, including Pejman Nozad. To date, the company has raised about $50 million.
“In the last 18 months (since Infer obtained a Series A funding round of $10 million), the market has grown faster than we anticipated,” CEO and co-founder Vik Singh told eWEEK. “We’ve been doubling our bookings and customer base quarter for quarter since then. During the same period of time, our sales cycles have been cut in half, and we’ve been able to keep the same deal sizes. So, to us, it shows that there’s a lot of market acceptance for what we’re doing.”
Once a ‘Science Fiction-Based’ Concept
When Singh and his partners started up Infer in 2010, they researched who was using predictive analytics, and “almost every company we talked to wasn’t doing that. It was more of a ‘science-fiction’ concept,” Singh said. “It was up to us to prove that predictive can drive tremendous value for your business.”
Singh and co-founders Chung Wu and Yang Zhang started Infer after working in engineering and research positions at companies that included Google, Microsoft and Yahoo. It took them a year and a half to build their software-as-a-service platform, and now it is paying dividends.
Infer has signed up a number of high-profile Bay Area technology companies as customers, including Box, Cloudera, New Relic, AdRoll, Nitro, Optimizely, SurveyMonkey, Tableau, Xactly, Zendesk and Zenefits.