July 16, 2018

Fuze, RingCentral And Other Top B2B Brands Relying On New Signal Data To Identify and Engage Buyers

In a climate where buyers are expecting and demanding relevant engagement at every touch point, B2B organizations are looking for deeper intelligence on buying signals, even before a prospect visits their website or fills out a registration form.

While activity data has been the foundational source leveraged by B2B businesses over the past decade via form fills, clicks and open rates, new trends have emerged to help organizations gather greater insights into their buyers. These new components include:

 

Engagement Data — This includes the total number of touches a prospect has with the brand, the total number of buyers engaging with the brand within a target account, how key accounts are engaging with the brand and if any engagement with prospects outside of known accounts are fitting the company’s target profile.

Intent Data — Third-party intent data allows marketers to monitor web activity to identify companies who are actively researching specific topics.

Signal Data — This type of data helps inform marketing and sales teams of companies that they should be targeting but are not currently on their radar.

This year’s Buyer Insights And Intelligence Series featured case studies and new models highlighting how top B2B businesses identify, engage and convert key decision makers at target accounts. The weeklong webcast series, which ran from July 9-13, included insights from industry experts at brands such as Fuze, RingCentral, TechTarget, Demandbase and many others. Here is a quick recap of key takeaways from each of the 13 sessions.

Signal Data Delivers 95% Deliverability For RingCentral

Signal data was a key component for RingCentral, whose goal was to increase average deal size and expand its enterprise market share. The company developed account-based strategies across its sales and marketing teams, which relied on quality data for success, according to David Cowings, Chief Marketing Data Scientist for RingCentral, who presented a webinar alongside Chris Lynde, CEO of SaleScout. After defining personas across their target companies, RingCentral turned to different signals to grade its total addressable market (TAM):

Installed Technology — “We wanted to get a count of how many cloud technologies each company was running,” said Cowings. “We also wanted to get a better understanding of what kind of telecom communications products they used, as well as unified communications, collaboration tools and so on."

Growth Signals —“The growth signals that we used previously were things such as Alexa page rankings, Facebook likes and Twitter followers,” he said. “But what we wanted to go towards was something a little more scientific that was more indicative of a company size growing or shrinking. So, we were able to utilize a growth signal from SaleScout that identified how many employees a company was currently hiring to see if we can track the hiring growth patterns.”

Relocation Information — “It’s key for us to understand if the company is moving locations or if they are opening up a new office location,” said Cowings.

Behavior Signals — “Behavior signals were something that we leveraged internal first-party and some third-party signals for,” he said. “We wanted to measure how engaged these companies were based upon email activity with them, as well as activity on the website.”

During the webinar, Cowings revealed some positive results that RingCentral has seen after optimizing its contact data, including:

  • 95% deliverability;
  • 3%-4% lift in click-through rates; and
  • 5%-10% lift from MQL to SQL.

Fuze Aligns Internal Teams With Buyer Intent

Success at scale requires that sales and marketing work together as a unified team on a unified concept of their target audience.

For example, the unified voice, video and messaging company Fuzerecently won a SiriusDecisions ROI Award for its ability to pivot its marketing and sales teams to better focus on ideal accounts with clearer prioritization for sales reps. In a session hosted by TechTarget, the company discussed how it formulated a strategy to leverage intent insights and engagement data to better prioritize account selection.

Prior to resetting its account targeting and analytics strategy, Fuze piloted a predictive analytics solution that did not drive the expected results.

“We went down the predictive analytics route with this initially,” said Will Pringle, VP of Worldwide Demand Generation at Fuze. “We did a very elaborate exercise alongside our sales team and, in the end, it was a spectacular failure. That data was not acceptable to sales, it was so far off that it wasn’t usable.”

To recover from that, Fuze adopted SiriusDecisions’ Demand Unit Waterfall to better understand the flow of the account journey. The company also began leveraging Engagio for their analytics to give account scores based on engagement minutes, as well as TechTarget for third-party intent signals.

Ultimately, the Fuze team saw its marketing and sales execution start to get more relevant.

“Of all the accounts we’re going after, we can tell when they are not only on the website, but what they’re looking at, the topics they’re looking at and the competitors they’re looking at,” said Pringle. “None of it would be possible without alignment, but these intent signals are bringing it to the next level.”

All these parts of account scoring, along with the intent signals garnered from top-tier accounts, have a positive impact on the company’s KPIs, especially when it comes to “elevating contribution to new pipeline creation,” according to the company.

Best-In-Class Companies Leverage Buyer Insights To Align Messaging, KPIs

Alignment must also carry over into how both marketing and sales measure the success of their efforts. During her session at the series, Christine Chartier, Head of Marketing at Full Circle Insights, highlighted the importance of aligning marketing and sales on the right KPIs to meet business goals.

"It's critical that each step of the progression is captured, so all aspects of funnel measurement can be tracked accurately," said Chartier. "You need to know what's working sooner rather than later, especially pre-opportunity, so you can accurately understand how campaigns are performing."

Chartier highlighted the three foundational KPIs to measure marketing success:

  • Volume: Understand exactly how many leads marketing is driving at the top of the funnel;
  • Conversion Rate: Understand how these leads are progressing through the funnel; and
  • Velocity: Know how fast these leads are progressing through the funnel.

In another session, Katrina Leaf, Global Marketing Automation Manager at the industrial testing equipment manufacturer Fluke, shared her experience leveraging AI to better align her marketing and sales teams for better engagement and relevancy.

Through a combination of predictive scoring with Lattice Engines, along with help from an AI bot from Conversica, Leaf and her team were able to boost their sales development capabilities. The company ran multiple one-week trials where all PPC asset downloads were followed up by its AI bot.

"We were sending over all these leads to our inside sales team, and they would say, 'we don't want to call these people anymore. They are not really interested,'" she said. "So, we found that by sending these scores from Lattice, the potential to convert a purchase was much greater."

While a holistic view of accounts is crucial to both sales and marketing teams, being able to tie specific lead data to the account ultimately leads to enhanced visibility across those teams. In a session hosted by LeanData, CMO Karen Steele discussed the importance of having the right intelligence on contacts and key accounts to build successful attribution.

"The good thing about CRM is that it is the accepted system of record, many systems integrate directly with those platforms," said Steele. "From an attribution standpoint, it's important to pull all that data into a single location to have a system of record on how leads are tied to accounts, how accounts are getting routed to sales reps and how it's all being attributed to revenue."

But to get it right, Steele suggests that you need to solve the fundamental matching problem to be able to understand the context of the data and guarantee you're connecting all the right data together — which is vital to attribution.

Read more: https://www.demandgenreport.com/features/industry-insights/fuze-ringcentral-and-other-top-b2b-brands-relying-on-new-signal-data-to-identify-engage-buyers