Terminus Funding Round

Terminus Funding Summary (Source: Crunchbase).

According to Atlanta Inno, ABX Platform Terminus has completed all but $1.5 million of a $24 million raise.  The round was smaller than its $90 million March 2021 round.  Twenty-eight investors participated.

The round follows a May restructuring.  At the time, the staffing cuts were estimated at 15% of its workforce.

In total, the firm has raised $140 million.  It also closed on a $50 million debt facility with CIBC in Q4 2021 around the time it acquired CDP Zylotech.

The funding round has not been press released, and Terminus did not provide any comments to Atlanta Inno or GZ Consulting on the round.

Gartner recently named Terminus a Leader in its Q4 2022 Magic Quadrant for Account-Based Marketing Platforms.  Terminus offers a “full range of ABM capabilities, including “broad support for channels including display advertising, retargeting, social advertising, website personalization, website chat, and tracking for email with personalized dynamic signatures.”

Gartner called out Terminus’ “strong and broad native channel support that includes advertising (display, retargeting, video, connected TV, and audio), site personalization, chat, and email tracking.

Gartner also praised Terminus’ “industry-specific playbooks” that “help customers implement use cases such as brand awareness, pipeline building, and acceleration, retention, and expansion.”

Salesloft Product Management SVP Frank Dale on Ethical AI

Frank Dale, SVP of Product Management, Salesloft

Happy New Year.  While off on vacation last week, I published an interview with Salesloft SVP of Product Management Frank Dale concerning Ethical AI.  He joined Salesloft in November 2019 when Costello, the opportunity management firm he founded, was acquired by Salesloft.  He has served as either CEO or COO at several investor-backed software companies, including Compendium, which Oracle acquired.

Dale earned a BA and MA from Valparaiso University with a concentration in ethics.  He also received an MBA from the Kelley School of Business at Indiana University.

What experience have you had developing AI tools?

As the SVP of Product Management at Salesloft, I am working with our team to bring Rhythm, Salesloft’s AI-powered signal-to-action engine platform, to life.  Rhythm ingests every signal from the Salesloft platform as well as signals from partner solutions via APIs, ranks and prioritizes those signals, and then produces a prioritized list of actions.  The action list gives sellers a clear, prioritized list of actions that will be the most impactful each day, along with an expected outcome prediction.  In addition to simplifying a seller’s day-to-day, it helps them build their skills by providing the context about why each action matters.

AI is becoming increasingly important in RevTech, with many of our interactions being mediated by AI.  Where do you see AI having the biggest impact on Sales reps between now and 2025?

AI will enable significant improvements in both seller efficiency and effectiveness.  The most obvious impact will continue to be automating away low-value, repetitive work.  What will surprise people will be the rapid advance and adoption of AI to suggest next best actions to take and content to use in those interactions with buyers.  A typical workday for a seller will see them greeted by a recommended list of actions to take each day.  Each action will be prioritized based on where the seller sits in relation to their targets, with each action accompanied by suggested content where appropriate.  For instance, I might see a suggestion to respond to an email from a champion in an in-flight deal.  The recommendation will include suggested text for the response as well as a resource to attach to the email.  That’s a future we are actively investing in at Salesloft, which is at the heart of our soon-to-be-released Rhythm product.

Same question, but looking further out to 2030…

As AI becomes more commonly deployed across the sales profession, buyers will experience a more consistent sales experience in each buyer-seller interaction.  As this becomes more common, it’s going to raise the bar on what buyers expect from a sales experience today.  That will put more pressure on sales teams to deliver consistently in ways that today may seem unreasonable but will be possible with AI assistance.

One of the key ways to raise the seller performance bar will be high-impact, tailored coaching.  Manager time is a constrained resource, and seller coaching augmented by AI provides a path to realizing performance improvement without manager time constraints.  We should fully expect AI to help coach sellers to hit their goals based on each seller’s unique profile.  We can expect AI to evaluate the seller’s entire game (activities, conversations, and deal management) to identify the highest leverage areas each individual seller should focus on to improve.  Some of the coaching will be provided by AI at the point of execution, like on a call or when writing an email, with the rest provided throughout the workday as recommendations.

What are the most significant risks of deploying AI broadly across the Sales Function?

Two areas come to mind.  First, AI used without clear boundaries in a sales process can lead to problems.  If you employ AI and automation capabilities, it should be to allow the user to be better armed to make a decision, not make it for them.  AI tools should not replace the human touch but rather augment it.  There’s a lot of pseudo-science tossed up around the topic of AI, but ultimately, humans understand the nuance of relationships better than machines.  One of the ways to address that concern is to deliver models that not only provide a recommendation but can provide the insights that led to it; humans will better trust the model when making decisions based on those recommendations as well as know when to ignore the recommendation.

Second, there’s a privacy component as well.  Companies may create AI models that share data about a particular buyer with other companies’ sales teams without said buyer’s knowledge.  The buyer may know they shared their data with one company but have no idea that multiple other customers at this company are using that same data.  Creating models with this type of function puts companies and sales teams in a high-risk zone that can tread on the unethical.  It isn’t clear that building models in that way may be considered legal in the future.  If you plan to deploy AI in a sales org, it’s important to understand how data is collected and used.      

AI Models are only as good as the underlying training data.  How concerned are you about biased models recapitulating discrimination?  For example, emphasizing sales skills that are gender or racially biased when evaluating sales rep performance?

It is a legitimate concern.  AI products are based on probabilities, not certainties.  The recommendations you receive or workflow automations that fire happen based on the probability that the given recommendation or action is right.  Not the certainty that it is right.  In a good product, the model is correct more often than a human would be when faced with the same decisions.  At times, this is because the model can evaluate a larger set of factors, and in some cases, it is simply that machines can apply rulesets at a higher level of consistency than humans.

One of the key determinants of the AI model’s value is the dataset upon which it was trained.  If the dataset does not properly represent the real world, the model will produce results that are either biased or provide poor recommendations.  We’ve already seen several examples of that with image editing software that didn’t include black-skinned people in the training dataset.  This led to either poor outcomes or worse dehumanizing results when the AI product was used in the real world.  If you plan to deploy AI in your business, you should ask the provider what precautions they take to prevent bias in their models.  We are very intentional about removing factors that could lead to bias in our training datasets.  Still, it isn’t something I see most technology companies paying attention to in the revenue tech space.

How do you curb racial and gender bias when performing sentiment analysis?

We take great care at Salesloft to remove things that would lead to discriminatory factors.  For example, for our Email Sentiment model, one of the ways we prevent bias is by removing all mentions of people’s names within the email because that could provide clues to their gender, race, or ethnicity.  We do that kind of preprocessing with any data we use in an AI model before we build our models.

One of our assets is our scale.  We’re fortunate that we operate globally and are the only provider in our space with offices in the Americas, Europe, and APAC.  As a result, we work with organizations of all sizes globally, including many of the world’s largest companies.  That means when we build models, we have one of the largest datasets in the world for sales execution.  This enables us to train models based on datasets with both breadth and depth.  When we build a model, it is easier to train it in a way that fairly represents reality and includes safeguards to avoid racial or gender bias.

AI will increasingly be deployed for recommending coaching and mediating the coaching.  What concerns do you have about replicating bias when coaching?

As with any AI product making a recommendation, the potential to make a recommendation with bias is a concern that needs to be addressed when building models.

We take our responsibility to avoid bias in any product we release very seriously.  The revenue technology industry as a whole hasn’t demonstrated a similar commitment to avoid harmful bias as of yet.  I don’t hear other companies talking about proactive steps to avoid it, but I think that will change.  We’re monitoring potential governmental action in both the US and EU that will require companies to raise their standard in this area.  It is only a matter of time before laws are passed that require companies to prevent unlawful bias in their AI products.

Sales activities are becoming increasingly digitized, a boon for revenue intelligence, training, and next best actions.  What guardrails do we need to put in place to ensure that employee monitoring does not become overly intrusive and invade privacy?

Let’s start by recognizing it is reasonable for an employer to have insight into what work is getting done and how it’s getting done.  On the other hand, getting a minute-by-minute record of how each seller spends their day is unreasonable, as is dictating every action the seller takes from morning until nightfall.

We have to start with the right first principles.  I think we can all agree that humans have inherent worth and dignity.  They don’t lose that when they go to work.  The challenge is that we have some companies in the technology industry that forget that fact when developing solutions.  When you forget that fact, I believe that you actually harm the customer that you’re trying to serve.  That harm happens in two ways.

First, you lose the opportunity to realize the true potential of AI, which is to serve as a partner that enables humans to do what they do best…which is to engage with and relate to other humans.  AI should not be used to make final decisions for humans or to dictate how they spend every minute of their day.  Good AI solutions should be thought partners and assistants to humans.  It’s Jarvis to Tony Stark’s Iron Man.

The second way overly intrusive technology harms companies that employ it is via employee turnover.  It’s no secret that industries that offer low autonomy to employees suffer from high turnover.  Most humans fundamentally desire a base level of autonomy; if that’s threatened, they leave whenever a good option opens up.

In short, if the seller is working for the technology instead of the inverse relationship, we’re on the wrong path.

In 2018, Salesforce CEO Marc Benioff argued that the best idea is no longer the most important value in technology.  Instead, trust must be the top value at tech companies.  How does trust play into ethical applications and AI?

We get to build the future we want to realize.  We can either build a future that perpetuates the things we don’t like about today’s world, or we can build a future that elevates human potential.  AI can be used to take us in either direction.  That means what we choose to build with AI and how we build it should be a very value-driven decision.

We can absolutely build highly effective AI-powered solutions that elevate the people who use them and deliver tremendous business value.  The people that believe otherwise simply lack the imagination and skill to do it.

What I love about our team at Salesloft is that we exist to elevate the ability of the people we serve and to enable them to be more honestly respected by the buyers they serve.  In sales and life, the way you win matters.  It matters to the people you serve on your revenue team, and it matters to your customers.

An emerging category of AI called Generative AI constructs content (e.g., images, presentations, emails, videos).  It was just named a disruptive sales technology by Gartner.  They stated that “By 2025, 30% of outbound messages from large organizations will be synthetically generated.”  What risks do you see from this technology?

There are two immediate risks that come to mind.  First, the messages need to be reviewed by a human before they are sent.  The technology has made extraordinary leaps forward.  I’ve spent a fair amount of time playing around with some of the tools released by OpenAI and others.  The output is impressive and also, at times, very wrong.  This goes back to the fact that the output is based on a probability that the answer provided is correct.  You can get a very professional, persuasive email, or you can get something that approximates a professional email but won’t land well with your intended customer.

Second, it has the potential to make every outbound message sound the same.  Generative AI doesn’t replace the need for human skill.  It changes the areas of focus for that skill.  Specifically, the opportunity for humans is to use Generative AI to help generate a higher volume and variety of ideas and then to edit and refine the output.  The returns available to creativity are always high, but they become even higher when everyone is doing the exact same thing in the same way. 

Having said that, I see tremendous potential in the technology and think if used properly it will be very valuable to revenue professionals.

SalesLoft CEO Kyle Porter has long emphasized authenticity and personalization in sales conversations.  Do you see Generative AI potentially undermining trust?

Kyle is absolutely right.  At the end of the day, a sale happens when a seller connects with a buyer to help them solve a problem.  You can’t do that without authentic connection and trust.  Generative AI should not replace that human connection, and I don’t think buyers want it to replace human connection.  A close friend of mine was a sales leader at a now-public PLG-driven SaaS company.  They added sales reluctantly.  When they did, the company learned that buyers both bought more from them and were happier customers.  That company now wishes it had added sales much earlier. How we interact with one another can evolve as technology evolves, but it doesn’t change the fact that humans are wired to connect with each other.  I think emerging tools like Generative AI will help us be more productive, but they won’t replace the need for authentic human connection and trust.

Salesloft Winter 2022 Release

Salesloft released a trio of enterprise-grade features to its Sales Engagement platform.  New Enhancements support account-based team selling, improved governance and access controls, and mobile app improvements.

Salesloft User Relationships

Account-based team selling allows multiple team members to work on an account and set multiple account owners with a single, shared view.  Furthermore, Salesloft automation rules support team selling with automated role assignments and account relationships across the customer lifecycle “so that reps can easily follow rules of engagement without losing time to admin tasks and workarounds.”

Expanded access controls provide complete control over which data customers have access across Cadences, Conversations, and Deals.  Organizations can limit access to sensitive opportunity data, call recordings, and customer records, ensuring security, compliance, and privacy.

Data access is based on the principle of least privilege, so users only have access to data required to do their job.  Thus, sales managers have access to all data relevant to their direct reports, while AEs can only view their data.

Salesloft Mobile App

Recognizing that field sales reps are returning to the road, the Salesloft Mobile App supports immediate customer engagement in support of time-sensitive communications.  Features include a Mobile Live Feed similar to the Salesloft Live Feed, person searching, email sending, and messaging (text).

The Mobile app lets sales reps make and log calls, send messages, and send emails directly from the mobile app using the mobile phone’s network.  The mobile app places a pair of calls that bridges the mobile device through the Salesloft dialer, with caller id displaying the dedicated Salesloft number.  Call recording, Live Call Studio, and voicemail drops are not supported.

Email enhancements are available now, with broader cadence step support in early 2023.

“Sales teams have adopted technology quickly, often at the expense of critical governance capabilities.  This exposes companies to policy or compliance violations,” said Salesloft CPO Ellie Fields.  “We believe it is Salesloft’s job to provide sales teams with technology they need to sell, and to make sure that technology is governed.  Especially in tight markets, our customers want to spend time selling, not managing disparate systems.”

Salesloft also announced that it rearchitected its Google Chrome extension, providing the “full Salesloft platform through one, consistent sidebar across Salesforce, Dynamics 365, and Gmail.”  The redesigned extension will be available in early 2023.

Other platform enhancements include automated data enrichment based on email signatures; out-of-office detection for Spanish, French, and German; Slack notifications for one-off tasks; improved email sentiment analysis; future period forecasts in Deals; and improved Deal Engagement Scores.

New integrations include Gryphon.ai (phone and email certifications), EveryoneSocial, Salesfinitiy (dialer), and StoryDoc (build presentations and share prospects via cadences).

Enhanced integrations include HubSpot (syncing of ownership data) and Vidyard (Live Feed notifications when a Vidyard video is shared).

Demandbase CRM Connectors

Demandbase sales and marketing engagement data can be visually displayed in Dynamics 365.

Demandbase unveiled a pair of CRM connectors for HubSpot and MSD 365.  The bi-directional, native integrations allow Demandbase One to push data into the CRMs for automated workflows, Lead-to-Account mapping, tracking, and responding to engagement activity.  Syncing is performed nightly.

“This release creates a unified interface that empowers revenue operations, sales, and marketing teams to grow predictable pipeline and close larger deals,” blogged Demandbase Senior Product Marketing Manager Travis Breier.  “The integrations enable a variety of rich workflows for customers to enhance their analytics, derive valuable insights, target more efficiently, and build reporting that aligns with their own CRM data set and their GTM needs.”

Demandbase launched the unified first and third-party view in its Salesforce connector this summer and has now expanded it to two other leading CRMs.

Demandbase offers a set of Calculated Fields that includes intent, engagement, and predictive scores that are synced and displayed in CRMs.

Demandbase feeds intent and engagement data, firmographics, technographics, and Demandbase Calculated Fields into CRMs.  With this data, operations can create CRM custom sales views, reports, and dashboards that display website activity, intent, and heatmaps.  Sales reps can view both sales intelligence and engagement data from a unified view. 

Furthermore, CRM data is available for list building and filtering in Demandbase One.  Users can define selectors, set up orchestration, create Demandbase campaigns, visualize and apply Demandbase intent and predictive scores, analyze journeys, and build reports.  Furthermore, “accurate account identification, combined with their CRM data, also means better predictive models, marketing and sales alerts, personalization opportunities, and more.”

For example, past opportunity data from the CRMs are now available to Demandbase pipeline predict and qualification scoring models to assist with account prioritization.  Demandbase also helps, “align messaging to each stage” of the buyer’s journey and assists with list building and campaign execution.

Conversely, Demandbase is syncing its insights (e.g., intent data, web traffic, most engaged contacts) with the CRM, helping reps prioritize accounts and prepare for account interactions.  Insights include Demandbase’s configurable data, such as its scores and engagement minutes that populate custom fields.

Demandbase brought firmographic, contact, and technographics databases in-house following the May 2021 acquisitions of InsideView (firmographics, contacts, and event triggers) and DemandMatrix (technographics).  Intent data includes first and third-party intelligence such as Surging Intent, Demandbase Keyword Intent, Campaign Responses, and Web Page Visits.

Revenue Operations can also select intent data from Bombora and G2, which are processed through the ABX platform’s predictive models.

“Both of these integrations improve orchestration, delivering greater sales and marketing alignment and a friction-free experience,” stated Demandbase.

“These integrations ensure our customers who use Dynamics 365 and HubSpot CRM realize the full value of the Demandbase platform.  Pairing Demandbase natively with the CRM allows our customers to orchestrate a seamless go-to-market motion with full alignment between marketing and sales.  We’re providing the full power of our Account Intelligence in these connected systems and saving sales and marketing teams time by providing them actionable insights wherever they want to consume them.  The result is better performance with less manual effort at every stage of the customer journey.”

Demandbase CPO Brewster Stanislaw

Demandbase is not done with the connectors.  It plans to add additional functionality to the CRMs, including “new sales-focused experiences, additional capabilities in the Demandbase app in Dynamics, enhanced Lead-To-Account functionality, and the ability to automate and scale account-based / people-based plays directly from your activities.”

Demandbase supports both HubSpot CRM and Marketing Automation platforms.

Chili Piper Distro for Salesforce

Calendaring vendor Chili Piper released its Distro app for Salesforce, providing revenue teams with automated lead routing and assignment.  Automated lead assignment improves speed to lead and bypasses spreadsheets, APEX code, and manual routing.  Marketing Qualified Leads can be distributed to sales reps when leads hit score thresholds or following events such as webinar attendance or downloading gated content.

Lead assignment details are synced with Salesforce, and users are notified via Slack or email.  In addition, a broad set of Salesforce record types are supported, including leads, contacts, accounts, cases, and opportunities.

Features include lead-to-account mapping, rule and trigger-based assignments, round-robin distribution, meeting reminders, and automated rescheduling.  The Distro Log provides a detailed breakdown of triggers, actions, and routes.

“Now more than ever, it’s crucial that high-growth companies optimize for efficiency in their marketing and sales processes without sacrificing on customer experience,” said Co-CEO Nicolas Vandenberghe.  “With Distro, revenue teams can effectively cover all of their routing and assignment needs while accelerating speed to lead.”

Chili Piper claims that it doubles top-of-the-funnel conversion rates.

A March 2011 article in The Harvard Business Review (“The Short Life of Online Sales Leads”) argued that speed to lead is critical for inbound leads.  Last year, XANT replicated the study las year and found that 57.1% of first call attempts took place after a week or more, and only 0.1% of inbound leads were responded to within five minutes.  However, firms that responded within those first five minutes had an 8X conversion rate versus later returned calls. 

A Lead Connect study found that 78% of companies that respond first to a demo request end up winning the deal.  Thus, firms that act immediately by returning a call or scheduling a meeting have a clear market advantage over firms with scheduling/call-back friction.

Chili Piper conducted a study earlier this year and found that 28.1% of demo requests submitted via chatbots or webforms to tech firms received no response after a week, and only 45% of requests were responded to within one hour.

Chili Piper studied response rates across technology firms.  Demo requests were placed via chatbots and web forms.

“In the past, marketers at leading organizations such as HubSpot and Vendasta have preached five minutes to two hours as the sweet spot for follow-up.  We, however, disagree,” blogged Chili Piper Content Marketing Manager Kelli Diffenderfer.  “In this day and age, responses should be instant.  And there’s absolutely no reason they can’t be.  If you’re not responding immediately, you’re losing out on a significant amount of revenue.”

Automated lead distribution and routing allows prospects to go from buyer research to an inbound inquiry to a scheduled meeting with a few clicks on a landing page or the corporate website, bypassing the delays inherent to traditional lead routing.

Yet, eleven years after the HBR first published its research, inbound response rates remain slow, with 26.8% of tech firms taking one to twenty-four hours to respond and 28.1% failing to respond.

“Distro for Salesforce is a welcome addition to AppExchange, as they power digital transformation for customers by simplifying lead management, improving conversion rates, and accelerating speed to lead,” said Woodson Martin, GM of Salesforce AppExchange. “AppExchange is constantly evolving to connect customers with the right apps and experts for their business needs.”

Distro is priced at $20 per user per month.  Chili Piper does not offer any discounts.

Distro supports automated lead routing and distribution based on triggered events including Lead Score thresholds.

Additional information about Chili Piper is available on the GZ Consulting blog and the Chili Piper website.

6sense Unveils Conversational Email

The new 6Sense Conversational Email Campaign Builder

At the 6sense Breakthrough Conference, 6sense unveiled its new Conversational Email module. Conversational Email employs AI models, psychographics, technographics, intent data, and predictive analytics to deliver “hyper-personalized, hyper-relevant emails to qualify and convert leads to sales meetings.”

Conversational Email supports campaigns across functions and the buyers’ journey. Marketing can send “personalized peer-to-peer nurture emails from multiple AI personas, and Operations can systematize meeting conversion and scheduling for qualified accounts. Sales teams can operationalize best practices and “scale across segments much easier.”

Marketing can also deploy Conversational Email to revive dormant accounts, qualify and convert inbound leads, and boost webinar and event registrations, participation, and follow-up.

6sense claims that beta customers enjoyed a 50% reduction in deal cycle times for marketing-sourced opportunities and a 1.5X increase in average deal size.

“A look at the basic process Conversational AI uses to nurture leads and turn them into sales opportunities.”

AI tools include a Visual Conversation Flow Builder, Email Assistant, and Qualification and Sales Handover. The Email Assistant employs AI to “effortlessly engage the correct buying team members, schedule follow-up based on out-of-office replies, book meetings with the right owners, and send targeted content.”

Dynamic content consists of multivariate blocks tailored to specific keywords, segments, personas, or products for personalizing messages.

Additionally, Conversational Email supports automated workflow triggers based on account buying behavior and contact activity.

“This launch is one of our most significant product updates yet,” said 6sense CTO Viral Bajaria. “Every company has overlooked and underworked, yet high-quality, leads. Critical outreach happens too late or simply never at all, which leads to missed revenue opportunities. The early results from customers in our beta program using 6sense Conversational Email demonstrates the impact: reduction in deal cycles, increase in average deal size, and new pipeline generated. While others in the market focus on sending emails, we are the first to focus on writing relevant emails and responding in ways that lead to more quality pipeline, more efficiently.”

6sense Contextual Targeting improves engagement and recall.

6sense also rolled out Contextual Targeting, which places ads alongside similar digital content. A study by Spark Neuro found that contextually relevant ads generate 43% greater engagement and double the ad recall.

In addition, 6sense offers over 100 new custom contextual topics for B2B marketers. “Advertisers won’t need to settle to use contextual segments that are largely designed for consumer marketers,” stated 6sense.

6sense claimed three benefits to Contextual Targeting. It:

  • Respects user privacy by targeting audiences without using behavioral or data profiles
  • Provides ready-to-use contextual topics built specifically for B2B 
  • Eliminates wasted ad spend on buyers that aren’t likely to engage 

Another new feature is Campaign Forecasting which estimates a campaign’s daily audience, daily impressions, and daily spend. Campaign Forecasting helps marketers assess campaign budget and reach before launching the campaign.

6sense also announced at Breakthrough that a sales intelligence data application would be released in Q1. 6sense, which bought data company Slintel last October, will offer global contact data, intent data (3rd-party data, anonymous web visitor insights), firmographics, psychographics, and technographics. In addition, the “intuitive” UX will provide “actionable insights and [an] orchestration layer necessary to identify, prioritize and engage with accounts in-market.”

“With B2B buying committee members increasingly choosing to remain anonymous through most of their journey, sellers need insight to earlier signals for their sales outreach to be effective. With our latest advancement in 6sense Sales Intelligence, we bring industry-leading intent data, contact data, and AI insights to help sellers efficiently identify priority prospects, personalize their interactions, and take timely action with ease to drive meetings and conversion of pipeline to revenue.”

Amar Doshi, SVP of Product & UX at 6sense

The Breakthrough Conference was billed as “an inside look at best practices to leverage AI and big data to accelerate revenue generation efficiently.”

“The Proceed with Confidence focus of our 2022 Breakthrough event couldn’t be more timely. We heard from more than 50 sales and marketing speakers at this year’s event that 6sense Revenue AI is the must-have competitive edge they can’t grow without,” said 6sense CEO Jason Zintak. “B2B companies are losing revenue opportunities and leaving money on the table. To deliver a better buying experience in today’s selling environment, it’s imperative to leverage AI along with pre-intent data, intent data, and predictive analytics to know which accounts are in market to buy your product or service, when and how to target them, and what messages to deliver to best engage.”

TechTarget: Priority Engine for Healthcare

Priority Engine for Healthcare offers topical intent for 400K registered healthcare administrators, IT professionals, and clinicians.

TechTarget, a leader in second-party technology intent data sets for sales and marketing, expanded the scope of its Priority Engine service to support the US healthcare sector.  The new Priority Engine for Healthcare service provides prospect-level intent gathered from Xtelligent Healthcare Media, its August 2021 acquisition.

“Being able to provide our customers with 1st-party intent data on the largest healthcare technology and information audience on the web is a true game changer in our industry,” said Sean Brooks, Co-Founder of Xtelligent Healthcare Media.  “Sales and marketing teams will now have direct access to entire healthcare buying teams, including Clinicians, Line of Business, and IT Decision-Makers, to find more opportunities and accelerate technology deals.”

Priority Engine for Healthcare Highlights for Top Accounts.

Priority Engine for Healthcare supports over 400,000 opted-in healthcare contacts, including Providers, Health Systems, Payers, Pharmaceuticals, Life Sciences, Accountable Care Organizations, and Federal/State Healthcare Agencies.  TechTarget claims that 90% of the US healthcare system is covered.  Xtelligent said its audience contains “70% Business & Finance Executives and Clinicians who have critical involvement across healthcare technology purchases that are becoming increasingly complex.”

The service is available for ten segments:

  1. Analytics
  2. Electronic Health Records (EHR/EMR)
  3. Healthcare Security & Compliance
  4. Health IT Infrastructure
  5. Life Sciences
  6. Patient Engagement
  7. Payer
  8. Pharma
  9. Revenue Cycle Management
  10. Telehealth

Intent data is gathered from 14 B2B healthcare media properties.  HealthTech sites include EHR Intelligence, Health IT Security, and Health IT Analytics.  Clinical research and medical sites include LifeSciences Intelligence, PharmaNews Intelligence, and HealthPayer Intelligence.  Over 400 healthcare topics are covered, with roughly half focused on Healthcare Tech.

Priority Engine for Healthcare also offers visitor intelligence and content view tracking.  Healthcare intent data from BrightTALK, TechTarget’s digital webinar and event platform, is also included.

Xtelligent, also based in Boston, has a similar content model to TechTarget.  When acquired last year, it had over 1.5 million healthcare-related visitors per quarter across ten websites, but lacked a platform for enabling its contacts and intent datasets. 

Xtelligent content focuses on healthcare-related software and technology decisions, aligning with TechTarget’s enterprise software focus but in an adjacent market.  Xtelligent topics include telehealth, healthcare analytics, revenue cycle management, healthcare IT security, and electronic health records.

The new intent topics identify HealthTech content consumption at the account and prospect levels, gathered from TechTarget’s 150 enterprise and health technology websites.

“By expanding the amount of permission-based, relevant 1st-party purchase intent data our customers have access to and delivering a full suite of marketing, sales, and go-to-market services to engage real buyers, we help companies of all sizes achieve better results at scale in this market,” said Michael Cotoia, CEO, TechTarget.  “As a leader in coverage of B2B enterprise tech for more than 20 years – combined with working very closely with our almost 3,000 customers – TechTarget has unique visibility into the buying dynamics across every major sector of the market.  Our experience positions us well to bring our model to adjacent vertical markets with similar attributes to enterprise B2B tech – long/complex-sales cycles, large purchases, multiple members of the buying team, and a strong need for 1st party data to enable marketers and sellers – just as we have done in healthcare.”

Priority Engine for Healthcare Prospect Insights

Company Links: TechTarget | Xtelligent | Priority Engine

Clari Optimize and Groove Partnership

Revenue Platform Clari made a trio of announcements related to a partnership with Sales Engagement Platform Groove, the full integration of conversational sales platform Wingman, and the pending release of its Optimize module for controlling revenue leaks.  Optimize helps revenue teams diagnose and address revenue leaks, reducing revenue loss due to deal slippage, bad data, and error-prone manual processes.

“The Clari Revenue Platform gives revenue leaders the past, present, and future data they need to not just control revenue but help grow it,” said Clari CEO Andy Byrne.  “Only Clari provides the full historical picture and adds real-time capabilities to act fast as well as the forward-looking projections to proactively strategize revenue precision.”

Optimize offers a “single, centralized view” of revenue metrics, including win rates, forecast accuracy, and deal cycle times.  In addition, Optimize helps revenue leaders answer questions such as “How is my team trending this quarter?  Are we going to meet, beat, or miss on revenue?  How can I ensure my reps are doing the right things to produce predictably winning results?”

Clari argues that market leaders have been unable to answer these questions proactively, making it difficult to mitigate issues and risks.  Clari combines historical and external data to assist with revenue benchmarking.  Thus, Clari can reach beyond the CRM to gather account intelligence.  For example, it can look at usage data to assess churn risk.

“Optimize is all about finding revenue leaks so customers can see not just where and why they’re missing revenue, but what they can do about it. No other solution on the market has the ability to harness past time series data to provide a historical view of revenue leak.”

Clari CEO Andy Byrne

Optimize, available soon, will provide a single view for the whole organization of revenue and insights, capturing CRM intelligence, activity data, and forecasts.  With the integration of Wingman, its recently acquired conversational intelligence subsidiary, the voice of the customer is fully embedded within Clari analytics and forecasts.

Furthermore, Wingman provides real-time coaching during sales calls, helping reps avoid mistakes and providing real-time intelligence (e.g., technical information, competitive battlecards) to sales reps.  By improving sales objection handling, parrying competitive attacks, and preventing delays due to technical follow-ups, Wingman also reduces revenue leakage.

“It’s not just about coaching your teams to sell more, or about deal reviews,” said Holly Procter, senior vice president and global head of sales at Clari.  “It’s more about running your revenue better—governing revenue-critical moments for success and collaboration across revenue-critical people, which includes buyers as well as sellers.  Nobody else offers this collaborative, real-time approach.”

The Clari + Groove Joint Value Proposition

Clari and Groove announced a partnership at Dreamforce that helps “joint customers run revenue with more precision, greater collaboration, and faster execution.”  Sales Engagement Platform Groove acts as a “system of action,” while Revenue Intelligence platform Clari acts as a “system of collaboration and governance.” Both platforms sync with Salesforce, which serves as the “system of record” for sales activity.

The partners argue that while revenue is at the heart of every business, CEOs struggle to get a handle on revenue and are uncertain about whether they will meet, beat, or miss revenue projections.

“Up to fifty percent of entire company employees are revenue critical.  They are responsible in some form or fashion for delivering revenue.” 

Clari SVP of Marketing Kyle Coleman explained to GZ Consulting

Revenue responsibility is broader than quota carriers and includes SDRs, CSMs, AMs, leadership, product managers, and engineers.  Unfortunately, “consistent, predictable execution and collaboration” across these employees remain “very challenging” due to the lack of a unified platform shared across all these roles.

“It’s also very difficult, therefore, to govern any sort of revenue process or sub-process in a repeatable way,” continued Coleman.  “What revenue leaders end up doing is every quarter, they’re trying to capture this lightning in a bottle to know whether they’re going to meet, beat or miss, but it’s sort of a scramble more often than not.”

With the Groove / Clari partnership, “we will be able to govern processes, we’ll be able to replicate the best practices, we’ll be able to do the right kind of real-time analysis that leads to action in a closed loop way so that we know that everything is happening as it should be when it should be,” argued Coleman.

A common issue for revenue teams is identifying revenue leaks and mitigating them.  Revenue leaks exist across the full revenue lifecycle.  For example, deal slippage is identified in real-time, allowing reps to take action via Groove to bring the deal back on track. 

When Clari identifies a deal slipping for competitive reasons, it can suggest a play be executed in Groove.  Likewise, Clari can identify sub-par win rates, overly generous discounting, and low conversion rates for early-stage opportunities.

As Groove is native to Salesforce, it records all activities in real-time, providing “full-funnel forecasting” and analytics to Salesforce and Clari.

“We can tie our campaigns through to revenue in Salesforce, and that is something that they (Groove’s competitors) cannot do,” argued Groove VP of Marketing Kristin Hersant.  “Then all of that rich data, tying engagement through to revenue is able to be pulled into Clari and used in the analysis, and that is available today.”

Coleman explained that while you can’t win a deal at any moment, you can certainly break a deal.  And once a deal is lost, “it’s very difficult to un-lose” it.  Thus, “if you don’t do the right thing at the right time – handle the right objection, or pull the right person in or do the right kind of follow-up” – the deal could be jeopardized.  Therefore, “handling revenue critical moments expertly and in a prescribed way” that is governed by best practices is critical in addressing revenue leaks.

“Having all of that insight into all these moments that exist and then having confidence that every one of your employees is going to be able to execute on this?  Well, this is what’s so exciting to us,” said Coleman.

“Clari has always been about providing companies with the collaboration and governance required to run revenue with maximum precision, and Groove completes the equation by enabling our joint customers to turn the insights we provide into action,” said Byrne.  “We’ve seen incredibly strong results from joint customers using our two platforms together, and this formal partnership will help us transform even more revenue organizations.”

Groove offers enterprise customers a Salesforce-native SEP that records all activity directly to Salesforce.

“Groove and Clari coming together is definitely a ‘1 + 1 = 3’ scenario for revenue leaders,” said Groove CEO Chris Rothstein.  “Bringing together Clari’s revenue collaboration and governance capabilities with Groove’s strength in sales execution and productivity provides the ultimate value proposition: See the future with Clari and then create that future with Groove.”


Company Links: Groove | Clari

LinkedIn “Deep Sales” Positioning

LinkedIn Deep Sales ad (Wall Street Journal)

Coinciding with its Q3 2022 release, LinkedIn is positioning Sales Navigator as a facilitator of Deep Selling.  Deep Sales positions LinkedIn as a new way to sell that addresses many of the current problems faced by sales teams (e.g., The Great Reshuffle, increased deal complexity following COVID, the digitization of communications, and an increase in SPAM).  This new positioning was announced in the Wall Street Journal.

“Too many sales professionals are stuck in what we’ve come to call “shallow selling” – an endless, frustrating loop of contacting more and more potential buyers in ways that no longer work,” posted LinkedIn Sales Solutions’ Marketing VP Gail Moody-Byrd.  “I’ve felt the pain of sales in my professional life.  I’ve consoled colleagues who were at risk of getting fired because they weren’t hitting their numbers or seen them committing “unnatural acts” to get a deal closed.  I’ve been on endless, painful pipeline review calls, looking at leads that will never materialize into a closed/won deal.  And I feel it daily in my personal life, as I try to dodge intrusive emails, texts, and phone calls that keep coming at me to purchase MarTech software.”

Moody-Byrd argued that shallow selling doesn’t work, but reps can employ deep learning software to support “deep sales.”

“Think of deep learning, where software learns from enormous amounts of reliable data to get to a meaningful answer.  Deep sales relies on that kind of data to deeply understand buyers and their context.  It helps sellers approach buyers in the way that is welcomed, at a time in the buying process that makes sense.  It helps develop deep relationships with buyers, based on understanding them – the opposite of shallow spray-and-pray tactics.”

LinkedIn claims that Sales Navigator customers enjoy a 38% increase in pipeline generated, a six percent increase in win rates, and a 47% increase in deal size.  The firm is positioning the combination of Sales Navigator and Sales Insights as its Deep Sales solution set.

“It’s good to see LinkedIn working on new ways to utilize machine learning to sort its various data inputs and provide a better experience,” stated SocialMediaToday Head of Content Andrew Hutchinson.  “Thus far, LinkedIn hasn’t really been able to tap into its unmatched database of professional insights, but maybe, through advanced machine learning on its huge dataset, it’s moving towards the next stage of becoming a critical companion for all HR and business professionals, by facilitating guidance on various fronts that can lead to smarter decisions.”

Sales Navigator actionable insights include relationship intelligence, buyer intent, and Account Insights.