Utah-based tech unicorn Insidesales has drastically shifted the way it sells its SaaS platform for salespeople, moving away from the small to medium sized business (SMB) market to focus on 2,000-employee+ sized enterprises.
Insidesales sells a software-as-a-service (SaaS) platform which utilises machine learning to suggest the best time to contact a prospect and provide the optimal steps to close more deals.
In a wide-ranging interview with Computerworld UK during Salesforce's Dreamforce conference in San Francisco last month, Insidesales cofounder and CEO Dave Elkington explained the shift in focus, how his company executed on the strategy and some of the early results, as well as his general thoughts on the enterprise AI market.
Shifting focus to the enterprise market is not as easy as it sounds. For Insidesales it took a drastic reorganisation of the sales team to no longer target SMBs, a complete rebuild of its product portfolio and perhaps most importantly, a lot of investment.
"To move into that large enterprise is completely different and extremely costly, so we have now raised over $300 million [£227 million] and I would say a significant component of that was in this transition," he said.
"You are rewriting product, in many cases from the ground up, you are building infrastructure, multi-language and multi-currency support, we have data centres in Singapore and Latin America, Canada, the US, western and eastern Europe, and we have all kinds of data security compliance like GDPR, you have to build capacity in your sales organisation, you have different onboarding processes."
Take regulation as an example, he said: "you need people, legal, PR, all of the things associated with communicating how important regulation is with these deployments. For us it is all about transparency and we are an open book, if you want to do audits feel free."
In terms of rebuilding the product for a more enterprise audience, the priority for Elkington was resiliency. "It's medical-grade technology versus consumer technology," he said. "If your consumer app is down you just come back in an hour, if you have 2,000 sellers living in your product for 6-8 hours a day, and you're down for 30 seconds, it is completely unacceptable.
"We built a user experience that is highly attuned to an enterprise engagement process. If you think about our products now it's a platform instead of a single solution."
The company is still private for the time being, so we can't quantify this change in tact, but if we take Elkington's word for it the result has been a number of "near seven figure deals" in the past two quarters, with customers like John Hancock, Microsoft, Cisco and Fidelity deploying the software across thousands of sales reps.
It's interesting hearing a vendor that promises to make its customers better at selling admit that it had to drastically change the way it sells itself, "but it plays out," Elkington said.
"Large enterprises renew at a high rate and they buy lots and lots, so the key is about helping them be successful on the platform," he added. "We are very focused on value selling, what I mean by that is we go into an organisation who isn't using us currently we do a data extraction and value extraction to say you have a $50 million [£38 million] opportunity and do a partial deployment to see if the numbers prove out and then do more, so it is very much a land and expand [strategy]."
Insidesales has recently hired a new COO, Chris Harrington, who held senior sales positions at fellow Utah success story Omniture before it was acquired by Adobe, and then Josh James' follow-up analytics vendor Domo as it went public.
The goal at Insidesales, he says, is very much to do the same, and help steer another another Utah tech unicorn to becoming a public company. Elkington has dismissed rumours that the company is planning an IPO in the past.
It's all about the data
Elkington believes his technology stands out from the crowd because of its ability to harness 'collective intelligence' of its broad customer base.
"Our ability to abstract the details of the data to protect privacy. A specific company's data set is never shared with another. It is anonymised," Elkington said.
This differs from Salesforce Einstein - the CRM giant's own AI powered insights product - which starts with just a customer's own data set unless they opt into a generalised global pool.
Speaking to Computerworld UK back in 2016 when it was launched, general manager of the Einstein group John Ball said: "I have spoken to big companies that are fine with the general models." The problem, Ball insisted, is finding the right language, and maths, to dispel these concerns with:."It is a nuanced discussion, the math gets super nuanced," he said at the time.
"They can opt in," Ball said. "You can build an org-specific model only using the data in that organisation, then there is a customer who would opt-in to a global or generalised data pool where they are still getting org-specific results. You are always getting an org-specific model, the difference is training only on your data or training on anonymised and sampled data."
Read next: What is Salesforce Einstein?
Elkington is a strong exponent of models built on pooled data because, if all you can look back on is your own data, then you can't learn anything new. "So as long as you don't mind looking in the rear view mirror, where you've been, it's great, but it's pretty much BI, so analysing information you already know," he said of Einstein.
"What it doesn't do is allow you to look forward, so the only way you can look forward is by having data you don't own and by going places you haven't been. If you are just looking at a single company's data it is a clever and interesting analysis of what you already know about yourself," he explained.
"The value of AI is directly proportional to the depth, breadth and quality of data," he continued. "The only way to unlock the value of AI and customer data is for the customer to participate with their data set. Customers who take the time to understand how we do things and the protections that go into data privacy, contribute their data for the greater good to get a significant benefit that is not possible otherwise."
This shift in product resulted in a fresh marketing push from the SaaS vendor last month, when it announced a new version of its product, which incorporates what it calls 'collective intelligence insights', collating 200 million buyer profiles and billions of sales interactions from across its platform to provide predictive insights for users.
The new product also features something the vendor calls 'NeuralMap', which promises to discover new contacts by tracking other vendors that sold complementary products into the same target companies.
The vendor also announced a partnership with SAP, which is pushing its new CRM product hard at this time. "Now SAP C4C users can compete using AI-powered buyer intelligence to discover optimal accounts, build more pipeline, and expand the value of deals by almost 85 percent," Elkington said as part of the announcement.
Suaad Sait, president of growth and products at Insidesales said: "We believe sales is only effective and efficient when it is informed by the behaviour of like-minded buyers. Just like Amazon provides 'People Who Viewed This, Also Viewed That' insights, we help sales professionals find the most likely buyers for their products."