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New AI-Driven Strategy Aims to Heat Up B2B Sales

By Richard Adhikari CRM Buyer ECT News Network
Jul 26, 2018 12:28 PM PT
everstring's new fire strategy promises to improve b2b sales performance

EverString, a San Mateo, California-based startup that offers artificial intelligence software for business-to-business sales, marketing and operations teams, on Wednesday released FIRE, a four-point strategy to improve sales performance.

The FIRE methodology is designed to unite and simplify the goals of sales and marketing teams.

"FIRE" stands for Fit, Intent, Recency and Engagement:

  • Fit - know which accounts are a good match for your product or service;
  • Intent - see who's doing heightened research, indicating a motivation to buy;
  • Recency - get insight on how recently an account showed intent or engaged with your brand; and
  • Engagement - understand when and in what way an account has interacted with your brand.

The strategy has been incorporated into EverString's predictive analytics platform, which uses AI and machine learning, said Matt Amundson, VP of marketing and sales.

"Our framework makes it simple to incorporate these data signals into an existing sales and marketing stack," he told CRM Buyer.

Customers feed existing engagement data from marketing automation platforms or account-based marketing platforms, such as Terminus or Engage, into the platform.

Companies are not required to purchase EverString's platform to use the FIRE strategy, but "we make it very simple and include FIRE as a dashboard in Salesforce and Microsoft Dynamics as a part of our install package," Amundson said.

EverString is offered as a Software as a Service platform, and "most companies are up and running within a week," Amundson said.

Pricing, which depends on the size of the purchasing company, begins at US$20,000 a year.

Companies on FIRE

A good fit assessment operates at scale using a data-driven platform that mines a company's existing data for the characteristics of a winning account. It cascades insights across the business Internet to identify who in the market is a likely match, EverString said.

Intent data reveals which accounts have been doing heightened research on topics related to a company's offering, indicating motivation to buy. This goes beyond intent analytics, which is based on who visits a company's website and what they do while there.

Intent data scans the entire business Internet for potential leads, spotting who is researching and engaging with other companies in the same business vertical and therefore might be a potential customer.

Fewer potential customers have been visiting company websites. Instead, they have been conducting research on third-party websites to read reviews, learn about products, and weigh their options without engaging directly with a brand or having to field sales calls and emails.

Good intent data follows prospects along their path, scoring behavior when they do research.

Recency data reveals how recently a prospect has demonstrated intent or engaged with a company. It lets sales teams prioritize target accounts by identifying who has been conducting active research within the company's category.

Further, it facilitates reaching out to existing customers who might be investigating alternatives, or who have shown interest in a newly launched product.

Recency data creates powerful opportunities for retention, upselling and cross-selling.

Engagement data shows when, and in what way, an account has interacted with a brand. When engagement data is combined with fit, intent and recency data, sales teams have the data needed to drive a powerful account-based marketing strategy, said EverString.

"When CRM came along, we discovered it was actually possible to swamp the sales process with too many mediocre leads," recalled Denis Pombriant, principal at Beagle Research.

"That was all about quantity," he told CRM Buyer. "At last, it seems, there's someone working on lead quality in a way that doesn't require human touch early in the process. This leads to much greater efficiencies and identification of which deals are truly best to pursue."

Tapping Into CRM

EverString's platform puts FIRE to work inside users' existing point solutions. It analyzes information from their Salesforce or Microsoft Dynamics CRM software to build a data-driven profile of the ideal customer. It then uses automated artificial intelligence and machine learning to scan the business Internet and sort and prioritize the best target accounts.

Every marketer, sales development representative, and sales rep across the user organization can access the data directly.

EverString's platform can be integrated with a client's CRM software in less than a week, Amundson said, adding that it integrates with all marketing packages.

"EverString offers the only platform incorporating Fit, Intent and Recency data that can be fully operationalized into an existing CRM and marketing automation stack," he noted. "We offer the only platform that can be deployed within days and requires little to no setup from our customers."

How Fire Works

Users plug EverString into their CRM and marketing automation systems and use filters such as employee size, industry and technology to create a model of the leads they want.

The platform crawls business websites to index them for demographic and technographic data for indicators of intent and interest.

"We don't collect people's data, only data about businesses," Amundson noted.

The system also uses Bombora data, which monitors intent on B2B publications.

Some vendors, such as InsideView, use analytics to identify prospects either in the news or in a business vertical, while others select targets based on a company's historic experiences with similar companies, Beagle's Pombriant noted, "but it takes a long time to train a model, and often a company's data is incomplete. Being able to reach out to the Internet to fill in the holes makes a lot of sense."

EverString "offers the most reliable B2B dataset to create confidence around a single source of truth to be utilized across an entire go-to-market team -- marketing, sales and sales development," Amundson maintained.

"Everyone and their dog is talking about sales-marketing alignment," remarked Rebecca Wettemann, VP of research at Nucleus Research.

"I'm not sure there's anything special here about FIRE other than a new acronym," she told CRM Buyer.

Further, "all their dogs are also talking about data platforms and using AI and big data to attack the marketing/targeting challenge," she said.

EverString's differentiator "is combining human intelligence and AI to discover, scrub and operationalize B2B data," Wettemann said. "For companies that already have technology supporting an ABM strategy in place, EverString should be a useful accelerator."


Richard Adhikari has been an ECT News Network reporter since 2008. His areas of focus include cybersecurity, mobile technologies, CRM, databases, software development, mainframe and mid-range computing, and application development. He has written and edited for numerous publications, including Information Week and Computerworld. He is the author of two books on client/server technology. Email Richard.


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