Among the many announcements at this year’s Dreamforce conference, a well-attended corporate confab in San Francisco for Salesforce users, one in particular stood out: a startup that Salesforce spent nearly $400 million acquiring was being fully integrated into the corporate mothership. RelateIQ, a data-driven company that was once seen as a future competitor to Salesforce, announced that their tech is being used to fuel two new Salesforce products. RelateIQ’s algorithms and interface, which functions roughly like a Google Now or Cortana, are now being used to create two new software programs for small businesses and Salesforce’s large corporate users.
RelateIQ’s main product, an intelligent email client, calendar, and work dashboard that does things like automatically determine which salesperson has the best relationship with a customer or intelligently predict when you need to start filing a project, is being rebranded as a new tool called SalesforceIQ for Small Business. In addition, the company is making a new mobile app and Chrome extension for Salesforce’s existing larger customers called SalesforceIQ for Sales Cloud.
When I spoke on the phone with Steve Loughlin, RelateIQ’s CEO and cofounder, he related a quick anecdote about developing the product out of his house alongside a few coworkers when his wife went into labor. Four years later, his company’s brainchild is getting rebranded and receiving a major market push behind it.
“This jumps on the trend of sales reps being overwhelmed by customer data,” Loughlin told me. “Every time they schedule something in their calendar, it’s an explosion. Sales reps spend more time filtering data and less time selling. On average, they spend 28 hours weekly reading and answering emails, and representatives update their CRM (customer relationship manager) four times a week.”
RelateIQ’s answer, and now Salesforce’s answer, is to create an intelligent piece of software that runs in the background. In marketing materials, they say their software “manages the details of every customer and prospect for you. We even enter info automatically from email, calendar, marketing automation systems, and many other data sources so you don’t have to.” In other words, it sits on top of inboxes, calendars, and productivity software and automatically builds maps of who’s talking to who and what’s due when.
This created a software package that, prior to Salesforce’s acquisition, threatened to unseat Salesforce–a maker of sales productivity software that operates over the cloud and, as of July 2015, makes a staggering $1.63 billion per quarter. RelateIQ was marketing similar cloud-based software that arguably edged ahead of Salesforce in terms of their data-science ninjutsu. So in the summer of 2014, Salesforce did what so many companies did to rivals–they purchased RelateIQ for nearly $400 million. Salesforce has aggressively purchased other companies to both expand their product portfolio and acquire talent; they acquired three companies in 2015 alone.
Salesforce’s two new RelateIQ-based products, the small business client and their sales cloud app, are based on vacuuming up mass amounts of data and making inferences from them. This requires considerable computing power and is part of a larger data revolution that’s influencing both the software businesses use to operate, and software used by ordinary people in their daily lives. RelateIQ, IBM’s Watson, and a host of smaller companies like Sentient, Gluru, and Clara offer this technology for the enterprise; meanwhile, ordinary users understand the potential of data science through Siri, Google Now, and Cortana.
In the case of RelateIQ, their emphasis on using data science as a selling point to customers led to an alumnus entering a very accomplished position. DJ Patil, RelateIQ’s former vice president of product, spoke with Fast Company last year about his company. (He is also a member of our Generation Flux.) After leaving RelateIQ, Patil eventually became Chief Data Scientist of the United States Office of Science and Technology Policy.
John Somorjai, an executive vice president who oversees Salesforce’s mergers and acquisitions, told me that what fascinated his company when it came to integrating RelateIQ was that “their approach at data science brings data science and machine learning into enterprise context. You track deals, and your system tells you automatically how to follow up with somebody . . . it creates a prescriptive way of helping the sales person close a deal more effectively. That was interesting, and we hadn’t seen anyone do that before.”
RelateIQ’s rebranding also puts them into context at an expanding Salesforce that’s doing two very distinct things: Serving customers who prefer to do work on tablets or smartphones, and expanding into industries that don’t have much traditional need for hyperpowered sales software. After being acquired by Salesforce, their new corporate parents continued to target RelateIQ towards small businesses rather than scaling them towards mid-sized companies or corporate giants. Meanwhile, Salesforce is promoting a redesigned core product called Salesforce Lightning that takes heavy design cues from mobile app UI, and new products aimed at electronic medical record management and other areas far-flung from salespeople managing customer records.
According to Mike Rosenbaum, a Salesforce executive responsible for their Salescloud product, “As product managers here, we see hundreds of thousands of users, and we see patterns develop in how they use the product. This includes patterns in certain sectors like finance or health, and we then productize so our customers can get to that success more quickly.“
More simply, Salesforce is finding themselves in a bind: Their CRM product is so popular that the majority of potential users who could use it do use it. As it stands, their main competition comes from alternative firms who offer lower-cost products for companies that can’t afford Salesforce. It’s an enviable position to be in, but one that essentially forces them to diversify in order to expand. And as it goes, it seems data science is part of that diversification.
Correction: An earlier version of this article incorrectly listed Patil’s current job. He is Chief Data Scientist of the United States Office of Science and Technology Policy.