Salesforce announced a pair of autonomous Einstein Sales Agents: Einstein SDR and Einstein Sales Coach. The products, built on Salesforce’s Einstein 1 Agentforce Platform, will be generally available in October.
Einstein SDR Agent, a chatbot, engages with inbound prospects and is not limited to pre-programmed responses. The multi-lingual conversational marketing agent manages top-of-funnel communications and hands leads off to sellers. The SDR Agent employs RAG to interpret and process information. It can answer questions, handle objections, qualify leads, and book meetings, with responses grounded by Salesforce CRM and Salesforce Data Cloud.
“Companies can upload existing sales materials like product FAQs, sales plays, and case studies for Einstein to use to generate a trusted and accurate response to lead queries,” explained the firm.”
Configuring Einstein SDR Agents.
Revenue Operations can customize the language, avatar, and tone. They can also set “guardrails for how often, what channels, and when Einstein should engage with inbound prospects.”
Einstein SDR Agent also lets RevOps set lead routing rules, log actions as Tasks, and monitor activity via existing reports and dashboards.
“Einstein SDR Agent makes decisions and prioritizes actions that align with the desired outcomes and analyzes a prospect’s question to autonomously determine what to do next — whether that’s answering product questions, handling objections, or scheduling a meeting,” stated Salesforce. “Each response is trusted, accurate, and personalized because it is grounded in a company’s CRM and harmonized external data using Agentforce’s retrieval augmented generation (RAG) service.”
When meetings are set, Einstein SDR Agent warmly hands off to reps with a pre-meeting summary that “critical lead information and previous interactions.”
The SDR Agent supports SMS and WhatsApp.
Einstein Sales Coach offers embedded role plays with feedback based on current scenarios.
The Einstein Sales Coach also employs RAG and text-to-voice to assist with sales role plays. Each roleplay is deal-specific, and Einstein provides post-roleplay feedback. RAG allows Einstein to customize sale scenarios based on Salesforce details about the deal, account, and prior correspondence.
The Sales Coach allows reps to practice pitching, handling objections, or negotiating before meeting with real customers.
“Using RAG, Einstein finds the relevant information in Salesforce — such as previous correspondence with that customer or external files provided, like buyer personas and buyer journey documents — and generates contextual responses in the buyer’s tone back to the seller during the role-play. For example, if a deal is in the negotiation stage, Einstein can create a role-play scenario sourced from the relevant context, including the opportunity record and buyer persona materials, to simulate the target buyer and engage in pricing negotiations.”
Einstein Sales Coach “incorporates insights from thought leaders and reputable publications when offering seller feedback.” Feedback includes next steps identified in Salesforce and overdue tasks and uploaded content such as sales methodologies and objection handling.
Einstein Sales Coach provides both positive and critical roleplay feedback for current deal scenarios. Next Steps are also called out.
During calls, Einstein provides real-time feedback, noting competitor mentions with competitive insights and providing negotiation tips.
“Every AI conversation needs to be an ROI conversation, and that will happen only when AI augments your team to accelerate growth,” argued Sales Cloud GM Ketan Karkhanis. “Every sales team needs more at-bats and more enablement to accelerate close rates, and that’s what these new autonomous sales agents will help drive. The sales team of the future is humans working with AI to drive sales success.”
Lavender applies AI to assist sales reps with drafting emails and recommending best practices.
Sales AI Email Coach Lavender rolled its V3 release into beta. The full release, expected later this summer, sports faster writing times through improved personalization tools and insights, and an enhanced coaching system with segmented and custom dynamic models.
By design, Lavender doesn’t want to replace sales reps but make them more effective, a sharp contrast with many SalesTech vendors. Lavender’s AI helps sales orgs understand why emails work and uses this understanding to help reps quickly write effective emails.
“Everything that we do is steeped in this concept of enablement and trying to get the user to think. There’s nothing I hate more than the concept of AI taking thinking away from sellers, because that’s where their growth is going to happen. The friction that we introduce is always intentional.”
COO Will Allred to GZ Consulting
The objective is to educate the sales rep on best practices that raise response rates and move deals forward. Blackboxing these practices doesn’t educate the rep and it ignores the wisdom of the rep.
While Lavender speeds up the composition process (efficiency), its true benefit comes in improving message quality through personalization and email best practices (as determined by AI analysis of client email data). Simply pushing out more quasi-personalized emails provides limited lift.
“If you actually customize emails to a one-to-one message, we’re seeing companies not only getting 25% plus response rates to their cold emails, but they’re generating a majority of their pipeline via those emails,” said Allred. “For example, a Forbes ‘Cloud 100’ company is seeing about 1900% more pipeline delivered via these emails.”
Sales reps struggle to provide “thoughtful personalization” as they need to search across their email, CRM, Gong conversations, and Sales Intelligence solutions. Reviewing and synthesizing this content can be quite time consuming. Furthermore, email platforms lack analytics, so are a “giant black box” when it comes to determining which emails are effective.
Sales reps have access to personal and conversational context when drafting emails.
Sales reps can select which context sources to employ when drafting an email, with Lavender recommending potential icebreakers and then generating the message.
Lavender addresses the issue of analyzing personalized emails, which creates a “complete blind spot” for Sales Ops. If each email is unique, RevOps can no longer perform A/B analysis of templates.
“In our dashboard, we’re helping managers understand exactly why reps are having success when it comes to email because it’s not an A/B comparison,” argued Allred. “There are hundreds of emails going out. They’ve all been personalized and customized. There are hundreds of variables that are at play here, and so we’re measuring all of them and pulling out what’s most important.”
Lavender’s email coach evaluates your message real time against your historical best practices to recommend changes (brevity, short sentences, non-spammy headers, questions) that raise response rates (2-3x on average) and continue deal progression.
Lavender’s email coach provides real time scoring. The AI detects reasons the email won’t get a reply and fixes them using a variety of LLMs.
Allred remarked that cold emails shouldn’t get all of the attention, arguing that the key to moving companies through various stages of the funnel is raising response rates. Unfortunately, one of the reasons that email threads die is because sales reps stop asking questions. So, Lavender builds in personalization and encourages questions in responses.
“If you actually customize emails to a one-to-one message, not only are the emails getting 25% plus percent response rates, but the pipeline that you’re driving from that is almost 2,000% more per email.”
Lavender analyzes data across the inbox (Outlook, Gmail) and SEP (Salesloft, Gong Engage, Outreach, Groove, Apollo) to create custom scoring recommendations. It also marries CRM (Salesforce, HubSpot), Conversational Sales (Gong) and third-party data to assist with drafting personalized emails with high response rates.
Lavender ingests activity from enterprise software platforms, analyzes the emails, and recommends edits based on best practices.
The AI can examine the emails and determine which phrasing, formats, styles, and wording are effective and which are falling flat. Lavender is diving deeper into AI analytics, looking to discern which emails are effective and why.
“Our approach to this [problem] is to stitch together an understanding of what’s happening in both inboxes, pull that together into a single pane of understanding, and then feed that back to the rep in real-time to give them the coaching they need. We pull all of that information to the forefront for the user.”
It’s a pure understanding of why an email works from an activity standpoint just like the metadata that we capture today, to the persona analytics, to the writing style data that’s been at the heart of Lavender since the beginning. Not just the style but the content itself.”
Lavender CEO Will Allred
The new release will also introduce a set of open-sourced email frameworks that help sellers tune their logic based on the scenario. For example, if a seller is trying to write an email to a prior closed lost opportunity, a framework would help the seller think through the message and subsequent follow-ups.
“We’re going to surface frameworks to help people think through better ways to write the message,” explained COO Will Allred to GZ Consulting. “We want our users to become better writers and better sellers. One of the things we found helpful in creating that was open-sourcing and bringing our frameworks to the surface so people could understand the logic behind what makes a great email.”
Lavender also added a ChatGPT style modal that allows the user flexibility to brainstorm, receive writing advice, or research via searching (or prompting) the web.
Lavender launched its service before the Cambrian Explosion of GenAI apps and subsequently built an “LLM stack” that includes its own models, Anthropic, OpenAI, Watson X, and more. This early mover advantage allowed it to build a solid customer base. According to the Chrome Store, Lavender has over 35,000 active users, a scale that exceeds its competitors.
“We have more daily active users than anyone in our space has downloads of their like products,” stated Allred.
ZoomInfo Copilot delivers account-based insights, buyer recommendations, and next best actions to sales reps.
ZoomInfo formally launched its Copilot service, which embeds GenAI capabilities within its GTM platform. The firm claims that Copilot “turns every seller into your best seller.”
Over 20,000 users have participated in the Copilot beta, and “their results and feedback have been overwhelmingly positive.”
ZoomInfo claims its users report being 60% more productive with Copilot. They also reduced time spent on research and manual tasks by ten hours per week, and 71% uncovered new opportunities at existing accounts.
Furthermore, ZoomInfo Copilot surfaced signals related to 45% of the open opportunities in their CRM.
ZoomInfo Copilot improves the efficiency and efficacy of sales reps. (Source: Q1 2024 $ZI earnings presentation).
“In today’s GTM environment, data by itself isn’t enough. Modern sales is becoming a science. It’s not enough to know who your buyer is — you need to know what they care about, exactly when they are in market, and what problems they’re facing right now,” posted ZoomInfo CEO Henry Schuck on LinkedIn. “And this information is out there in the form of digital buying signals. We have more information than ever about our buyers, but there’s too much noise.”
While signals such as sales triggers, visitor intelligence, and intent data sets continue to expand in depth and accuracy, delivering them in a coherent, holistic, and actionable way has proven difficult. Simply being told that somebody visited your website or there was an executive change at a prospect isn’t actionable because valuable signals get lost in the noise. Most individual signals do not assist with prioritization, identifying the buying committee, or writing an email that cuts through inbox noise. That is why sales assistants such as ZoomInfo Copilot will be warmly greeted.
“We built ZoomInfo Copilot to change that — to push these insights directly to sellers, teeing up outreach for the best leads at exactly the right moment,” continued Schuck. “Copilot turns ZoomInfo from a contact lookup tool into a platform that surfaces the key insights sellers need to take action against each day.”
Copilot also supports AI-guided prospecting that prioritizes sales rep activities on a redesigned home page. The ranked list of target accounts, based on historical deal analysis, employs sales triggers such as intent signals and executive scoops (ZoomInfo’s term for business events) to prioritize outbound activity.
CRM deal analysis identifies the “DNA of your best-fit customers and uses ZoomInfo’s leading go-to-market data to identify the best-fit accounts for you,” said CPO Dominik Facher. “Copilot generates natural language explanations of why an account has been prioritized so you have all the context to successfully engage.”
Copilot supports Salesforce and HubSpot for building target account lists, with additional CRMs planned in subsequent releases. Data is ingested from the Opportunity and Account record types.
To further assist prospecting, ZoomInfo surfaces buying committee members “who are most likely to engage,” which admins can curate and push out to their frontline sellers.
Sales Intelligence vendors have long said that their offerings helped reps know “who to call, when to call, and what to say.” However, this data was often raw information that needed to be analyzed by reps and messaged to prospects on an individual account basis. Not only does Copilot prioritize activities across their book of business and suggest the next best actions, but it can even recommend the channels on which individual buyers are most likely to respond.
“Marketers can access a ranked and prioritized list of the companies and buyers in-market, based on millions of signals analyzed and prioritized by ZoomInfo Copilot’s AI every day, directly from the homepage feed,” blogged Schuck. “ZoomInfo Copilot’s intelligent recommendations are presented in the language of today’s sellers to make taking action as easy and intuitive as possible. Users can explore each opportunity in more depth and engage with those opportunities directly from the Homepage Feed.”
Users can select between different persona definitions and filter by CRM presence and “likelihood to engage.”
Copilot sports an AI Email Assistant that employs GenAI to compose messaging around selected insights.
The Copilot includes an AI Email Assistant to simplify outbound, personalized outreach. Emails are generated based on the seller’s objective, previous account context, additional context offered by the sales rep, and ZoomInfo insights. The sales rep can select from three generated options and adjust the length or tone. Users have the option to email one or multiple individuals and can specify which insights should be used when generating the email.
Copilot assists with buying group discovery, “Pulling insights from websites, case studies, earnings call summaries, and many more real-time signals, ZoomInfo Copilot automatically creates buying groups of individuals who are most likely to engage and align with their ideal customer profiles.”
Copilot shortens the time to value for new users by automating personalization, including ICP and persona definition. Traditionally, new Sales Intelligence platform users spend hours customizing the platform, defining target personas, ICP, companies of interest, topics of interest, etc. Much of this process is automated by Copilot, allowing sales reps to immediately begin deriving value.
“When someone gets onboarded, we build out what we call a customer context database. We essentially go and do a lot of research on that company, what are their value props? What are their pain points? Who are their end users? And then we start to infer what topics, buying committees, types of companies that they’re interested in,” ZoomInfo VP of Data Strategy Brandon Tucker explained to GZ Consulting. “And then as they start to engage with the signals, or set some of those configurations on their own, they start to get even more relevant insights.”
ZoomInfo Copilot supports GenAI account queries.
A GenAI chat interface answers account questions, “giving users the answers they need quickly using conversational AI. Users can request answers on a range of account-level topics to get up to speed as quickly as possible.”
Copilot “meets you where you are,” including desktop, weekly email digests, Slack alerts, Chrome extension, and a mobile app.
“ZoomInfo Copilot also allows salespeople to seize time-sensitive opportunities in real-time with Breaking Alerts delivered through Slack,” blogged Schuck. “These alerts can be shared across multiple channels, allowing teams to quickly triage emerging opportunities and act decisively on high-quality intent signals.”
The Personalized Target Account Digest alerts users when prospects are “showing the right signals” and explains why now is a good time for reaching out to the prospect. Users can drill down into greater detail, compose an email, or export a prospect to the CRM.
Thus, “signals drive your actions,” said Facher.
ZoomInfo Copilot ingests ZoomInfo’s first- and third-party data to deliver “detailed overviews of specific accounts, including pain points and use cases, upcoming deals, important contacts, a summary of previous engagements, and more.”
“Finding the time to understand every account is a tall ask,” stated Facher. However, “Copilot effortlessly summarizes the need to know and the nice to know for any account, based on ZoomInfo, your CRM, and the engagements you’ve had with your customers, like emails or calls, to generate a holistic picture of an account’s health, its history, and the opportunity.”
Thus, reps can have a “detailed understanding” of any account “in seconds” and establish a “shared foundation” of account knowledge across the account team.
“Get briefed, get aligned, and get selling,” concluded Facher.
ZoomInfo contends that its Copilot has a significant advantage over other offerings due to the breadth and quality of its reference content and engagement data.
Account AI summarizes the account with multi-dimensional views.
“What sets ZoomInfo’s Copilot apart from any other solution in the market is that it is sitting on top of our AI-ready trusted data foundation that drives decisions, personalization, and confidence,” said ZoomInfo CEO Henry Schuck. “AI is only as good as the data it’s built on, and most solutions are layered on top of static CRM data.”
Schuck argued that ZoomInfo is well-positioned in the emerging Copilot space as it offers high-quality data for maintaining enterprise software platforms and grounding its Copilot. Among its verified data assets are third-party reference data, second-party intent data, and first-party engagement and conversational insights:
“Copilot takes signals like website visitors, spikes in job postings, earnings call transcripts, contract renewal dates, and expert calls that indicate spending or competitive threats, then uses advanced entity resolution and matching to combine them with customers’ first-party data,” stated Schuck on ZoomInfo’s recent earnings call. “It then applies AI technology to model and inform users immediately about which companies are in the market for their product and how and why you should engage with them.
“For our customers, understanding firmographics alone is not sufficient to understand whether or not your next buyer is about to be in-market for your product,” continued Schuck. “It’s only when you surround that core data with signals that you’re able to predict who your next customer should be.”
ZoomInfo feeds data and buyer signals into Copilot to identify the right buyer during the buyer research process.
Copilot looks to identify in-market accounts and buyers during the research phase, relying on a broad set of hidden buyer signals (e.g., intent, competitive research, job postings, earnings calls, website visits) before the buyer raises their hand. The research window is the period during which sales and marketing have the greatest opportunity to influence the problem framing and preliminary vendor list.
But cold-calling into the TAM absent signals is very wasteful, as roughly only 10% of the ICP is in the market.
“Very few of the buyers that you’re looking for are in-market during the time you’re looking at them, and the ability to pinpoint those isn’t very easy today,” explained Product Marketing SVP Jam Khan to GZ Consulting. “So you can use predictive analytics. You can make your best guess when you have a fairly broken MQL system. ABM vendors have tried to come up with a different point of view, but it doesn’t quite replace the MQL.”
Copilot looks to identify the “chasm of opportunity” between signal generation and the first point of contact.
“The bridge we’re trying to gap is the difference between being first in a deal and being second in a deal,” argued Khan. “You’re never going to have a crystal ball that lets you anticipate before a buyer ever even starts making their decision. But that short little window is the difference between winning and losing.”
Copilot looks to “solve for the chasm” and give sales teams a first-mover advantage. While this “window of opportunity is really small,” it is the difference between hitting .200 and .300, analogized Khan. “To the extent where you’re able to act on those, that’s the difference between hitting your number and missing your number.”
Thus, other GenAI or Copilot offerings that pull data from the CRM face a trio of problems when generating recommendations. CRM data is limited to what has been keyed into it. As this data is historical (and reps hate maintaining CRM data), it is likely to be outdated, stale, and inaccurate.
“Third, it lacks the outside signals and insights that drive modern go-to-market motions. ZoomInfo Copilot delivers a full picture built on the foundation of the world’s most accurate and up-to-date business data, publishes real-time insights, and turns that into personalized and relevant content,” stated Schuck.
“Copilot is one of the best pieces of software we built at ZoomInfo, across ease-of-use, end-to-end understanding of our customers’ pain points and product market fit. We have had leading AI models in production for years,” crowed Schuck. “We expect to monetize Copilot and we’ll roll it out in a thoughtful way, focusing first on the customers who are most likely to get significant value out of the advanced platform. Our go-to-market teams are excited to bring this to their customers, and I have a lot of conviction around the upgrade paths in our customer base.”
Earnings Scoops, the latest content set to be collected and fed into Copilot, extend ZoomInfo’s technology and business event Scoops into SEC filing analysis. The service ingests 10-Ks (annual), 8-Ks (Material announcements), international filings, and earnings transcripts. It then outputs a set of condensed topical summaries. Earnings Scoops leverage GenAI to analyze customer and prospect competitors, goals, initiatives, pain points, and SWOT elements. They are also fed into its beta Copilot service.
Earnings Scoops are assigned metatags from a set of 150 Scoops topics that assist with searching and Copilot customization. This additional tagging helps tailor Scoop presentation to each firm’s ICP and is displayed in a Scoops Topics column (see a subset of topics from Meta’s recent earnings on the right).
“Many organizations still struggle to provide frontline sellers with actionable go-to-market insights distilled from the myriad of available signals,” said IDC Analyst Roger Beharry Lall. “While AI can sift through mountains of data, solutions must be built on a foundation of fresh, accurate, and clean data in order to deliver meaningful intelligence. Suppliers like ZoomInfo that can combine robust data sets with novel AI capabilities will help customers lead their markets by enabling engagement to the right people with the right message at precisely the right moment.”
While Schuck is confident in Copilot and ZoomInfo’s ability to monetize it, Schuck does not believe it will significantly grow revenue in H2.
“It’s going to take longer than that. I have a lot of confidence because I personally pitched this product across dozens of our customers, across all segments, and all industries,” argued Schuck. “From a product market fit, I don’t think we’ve been ever so close to fit as we have been with Copilot, outside of the core company and contact data. And so, I have a tremendous amount of confidence that we’re going to be able to turn that enthusiasm into monetization, but I also expect it to happen over time.”
The Homepage prioritizes accounts with next best action recommendations.
I have been posting my articles as LinkedIn posts for the past few months, but I wanted to link some of the recent articles. The biggest recent announcement was Informa’s bid to merge its Informa Tech division with TechTarget. I also covered their new IntentMail GenAI capability.
Informa Tech CEO Gary Nugent said, “This combination brings a new revenue scale, resilient revenue growth, and increased revenue stability.”
TechTarget Merges with Informa Tech
Informa PLC, a FTSE 50 UK Group company, announced a definitive agreement to combine Informa Tech’s digital business with TechTarget. The combined business will “create a leading global platform in B2B Data and Market Access, focused on helping vendors in enterprise technology and other markets accelerate revenue growth.”
The “New TechTarget” will be positioned as a “unique end-to-end solution provider across the go-to-market: from strategy, messaging and content development to in-market activation via brand, demand generation, purchase intent data and sales enablement,” declared the firms. “The combination brings scale benefits, diversified revenue streams, and strategic expansion opportunities by expanding TechTarget’s current addressable market and enhancing the resilience of its business by increasing its presence in new markets and new buyer personas.”
Informa is contributing its Informa Tech digital business and $350 million in cash in exchange for 57% of the combined company. The cash is to be paid to existing shareholders when the deal closes. TechTarget’s shareholders will retain a 43% equity stake in the combined company…
IntentMail employs GenAI to draft Priority Engine Emails framed by Prospect-level intent.
TechTarget unveiled IntentMail AI, a beta GenAI feature that drafts Priority Engine emails. TechTarget emphasizes its intent data as it is tied to opted-in readers of its 150 B2B Technology websites. Thus, IntentMail AI offers opted-in prospect-level intent that supports precision messaging around top-of-mind topics when buyers are in-market.
“Unlike other offerings recently reaching the market, only IntentMail AI combines recent, relevant account information together with deep insights on what the specific targeted recipient has been actually researching on TechTarget’s global publishing network,” explained TechTarget. “As such, IntentMail AI will not only help drastically reduce the time it takes for sales teams to more effectively personalize outbound outreach, it stands to dramatically increase conversion.”
IntentMail AI is part of TechTarget’s “personalized assist AI-driven product strategy.” CEO Mike Cotoia believes that opted-in prospect-level intent will differentiate its GenAI offerings from competitors across three dimensions: relevancy, efficiency, and precision focus…
I have been experimenting with posting LinkedIn Newsletters, so I have not been placing my content here for the past month. I posted a pair of articles about HubSpot, which held its annual INBOUND conference in Boston.
HubSpot Brings GAI to Its Hubs
Like many other RevTech vendors, HubSpot is all in on Generative AI (GAI) and infusing it across its Hubs. CEO Yamini Rangan and Product EVP Andrew Pitre emphasized GAI in their INBOUND keynotes, emphasizing GAI’s ability to foster customer connection and please the customer.
Rangan stated that the “most intelligent way to use intelligence is to drive customer connection,” which can be “scaled to hundreds or thousands or maybe even millions of your customers by observing their patterns, anticipating their needs, and offering them insights.”
A decade ago, vendors looked at SAP and Oracle as the second CRM they supported after building their Salesforce connectors. Five years ago, the momentum had shifted towards Dynamics following the 2016 launch of Dynamics 365 in the cloud. It seems that HubSpot is now vying with MSD to be the second-supported CRM.
HubSpot has long been viewed as a decent CRM for SMBs to start on before they grow up and require enterprise features, and research from Adam Schoenfeld at Keyplay backs up this impression.
IDC, which doesn’t include HubSpot in its CRM market share analysis, noted that HubSpot has been growing much faster than the overall market, with 31% growth in 2020 and 47% in 2021…
Outreach announced that it is selling the Sales Hacker community back to its founder Max Altschuler and the GTMfund. Outreach acquired the site five years ago, and Altschuler served as the company’s CMO for several years.
Altschuler noted that sales has changed significantly over the past few years and is no longer a standalone function but part of a much expansive view of the customer relationship and go-to-market processes. Thus, the vision of Sales Hacker is being expanded to encompass the broader set of customer-facing teams.
Recognizing this change, Sales Hacker will be rebranded as GTMnow and operate as an extension of the GTMfund. The broader vision will encompass sales, marketing, customer success, operations, and product.
“Sales Hacker had an amazing, decade-long run, but sales is no longer siloed, and we saw an opportunity to transform it into something geared toward the broader GTM space,” Altschuler explained to GZ Consulting.
GTMnow is live with a broader coverage scope than Sales Hacker.
The new GTMnow website launched yesterday. The site offers a weekly newsletter, podcast, videos, and articles.
“Sales Hacker has been such a great vehicle, a great platform, for educating sellers at scale,” said Outreach CEO Manny Medina. “Sales [reps] learn from other salespeople. Sales is such an art that you always can learn a tip or trick or a move from other sales folks that are deploying this in their own shops.”
“We’ll be sharing the playbooks from our experienced GTM leaders as well as the experiments we’re conducting across our 100+ portfolio companies so that you can run them too,” posted Altschuler on LinkedIn. “We’ll stay focused on producing super high-quality content showcasing the ongoing innovation happening industry-wide.”
GTMfund is an early-stage VC fund “focused on investing in the most exciting, up-and-coming B2B SaaS companies across the world.” Its LP network of over 350 VP and C-level revenue leaders come from leading SaaS companies, including DocuSign, Salesforce, LinkedIn, Snowflake, Okta, and Zoom.
“This network acts as 350+ scouts as well as an expert network for conducting due diligence on companies. Our unique value add gives us access to the deal,” states GTMfund. “We help startups with distribution. With a network of proven go-to-market leaders, startups should never have to go at it alone again. We find the best companies and support them with revenue-generating playbooks, top-tier candidates, and all-around GTM support.”
Revenue Platform vendor Clari announced the acquisition of Sales Engagement Platform Groove this morning. The transaction is expected to close on August 21. No deal details were released.
“This is the most transformative day of our history,” Clari CEO Andy Byrne told VentureBeat. “It’s a big acquisition for us. When we started this company, our thesis was grounded in the belief that AI would revolutionize how businesses manage revenue. More specifically, our vision was to assist CEOs in answering the critical question of whether they would meet or miss revenue targets. We aimed to offer a predictive solution to address the common issue of revenue leaks that many companies face. Our goal was to help them achieve what we call revenue precision.”
The courtship began two years ago when Clari customers began asking about Groove. Around the same time, Groove was implemented internally. The firms launched a Groove / Clari integration last year with a strong UVP.
The deal brings the firms closer to creating a full customer lifecycle platform, with Groove supporting Sales Engagement and Engagement Analytics alongside Clari’s Conversational Intelligence (Clari Copilot), Digital Sales Room, and Revenue Operations capabilities. Clari will recommend sales actions that limit revenue leakage, which reps can execute in Groove without switching applications. Groove engagement data will be fed back into Clari, helping identify deals at risk.
“Most CEOs have a tough time answering the most important question in business: ‘Will we meet, beat, or miss on revenue? By bringing together Clari and Groove, revenue leaders can implement their revenue collaboration and governance strategy across all internal and external workflows, giving them full visibility and control over the company’s most important business process – Revenue.”
Clari CEO Andy Byrne
Clari’s vision is to “bring the entire revenue process into one unified platform so our clients can consolidate, simplify, [and] accelerate” their go-to-market.
According to Clari CMO Kyle Coleman, every CRO, CFO, and CEO he has spoken with over the last six months has emphasized the need to consolidate, simplify, and accelerate their revenue cycle.
“We’re really excited to be able to lean onto this macro trend of consolidation. But it’s not just consolidating for the sake of saving money. It’s consolidating for the sake of reducing complexity, simplifying, and improving your revenue results,” Coleman explained to GZ Consulting. He is ”really confident” in the firm’s expanded capabilities and sees them as “exactly what revenue teams [want] right now.”
From 2013 until 2021, Clari focused on building revenue reporting and a revenue database (RevDB) with time series data. Information is gathered from CRMs, emails, calendars, etc., with Groove soon feeding its activity data. RevDB also ingests external data from data warehouses and Clari’s digital sales room functionality. Data is stored and analyzed in RevDB with support for six products:
“Clari’s RevDB architecture has been a long-term investment by Clari and is the secret sauce that powers the company’s unmatched revenue AI (RevAI) capabilities,” stated Clari. “With Groove added to the Clari portfolio, revenue teams will get real-time insights and suggested actions across every revenue workflow to create and convert more pipeline, while company leaders will be able to see every input, tie every activity to results, and precisely predict revenue outcomes.”
Clari with Groove brings together six product categories to serve the full revenue team.
“We’re augmenting the CRM with information that reps are never going to create manually. And then we’re pulling that into our database to build our machine learning and AI models,” explained Coleman.
Last year, Clari acquired Conversational Sales Platform Wingman and added it to its deal monitoring and analytics workflows. The integrated service was recently rebranded Clari Copilot.
“It expanded the workflows that we’re running for revenue teams, bringing call recordings into the flow of work,” remarked Coleman. “You can actually hear and see what the customer is saying…Making CI less of a call recording solution for a call center and really more of a purpose-built solution for revenue teams. While we’re doing that, we’re also adding this whole new dataset into the revenue database that makes us very capable for NLP and prescriptive AI…The RevAI capabilities we have made us capable of recording all these new AI use cases…We have all these different types of AI that we leverage across the platform. We have the predictive components. We have the generative components, and we have the natural language processing. And we’re finding the right ways to expose that…in the flow of a rep’s work [and] in the flow of an executive’s work, so they’re actually getting the insight they need when they need it.”
Groove, already a Clari partner, allows sales reps to go from forecast and deal risk alerts to integrated actions, providing feedback loops and recommendations as a “closed loop of Insight and Action.”
When I spoke to the firms last year about their partnership, they presented an excellent joint value proposition presentation. This messaging continued forward into their acquisition briefing.
A common issue for revenue teams is identifying revenue leaks and mitigating them. Revenue leaks exist across the entire revenue lifecycle. For example, deal slippage is identified in real-time by Clari, 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. Groove activity will also begin feeding into Clari’s RevDB time-series activities and conversations database.
“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 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” and 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 them? Well, this is what’s so exciting to us,” said Coleman.
Clari customers benefit from a consolidated selling platform for prospecting and engagement. The platform will turn insight into action, allowing sales reps to kick off a Groove Flow immediately. They will also better understand “top-of-the-funnel effectiveness and tie it to down-funnel results.”
Clari customers “can use it [Groove] both to fill the funnel and execute the funnel, turning insights into action in real-time – closing that loop and knowing what’s happening at the top of the funnel.” Revenue teams can tie activities to revenue results and “hone and change” their revenue process.
Groove customers also benefit from platform unification as they prioritize activities, simplify forecasting, and enjoy a better understanding of deal status. They will leverage analytics that tie activity to revenue impact, thus improving outcome predictions.
Furthermore, leaders will receive “end-to-end visibility of the revenue process by connecting sales engagement with conversion.”
“The goal is to consolidate all revenue-critical technology for all revenue-critical employees,” stated Coleman. While the focus is on supporting the revenue team, Clari is finding that other stakeholders, such as finance and product management, also benefit from the ability to track sales activity.
For antitrust reasons, Clari has not discussed pricing with Groove for the six products but expects to have it locked down by the end of the month. Reps will be quickly trained on the combined offering, and a unified team will be at Dreamforce.
“We’re bringing all of our quota carriers together for a two-day super deep dive – everything you need to know about the Groove product [and] everything you need to know about the combined platform. We don’t want our sales reps to show up uninformed when they take the first meetings, and we expect there to be a healthy amount of demand coming in for this combination,” explained Coleman. “We’re on this path to be a truly multi-product company. And part of that journey is creating a true co-sell playbook. When does it make sense to sell the full platform? When should it be Groove standalone? When should it be Groove plus Copilot?”
“The ultimate goal from a Go-to-Market standpoint is to be the single revenue platform that’s used by all revenue employees,” continued Coleman. “We feel really good about this vision that we have to be the most used platform.”
Clari already has $1.5 trillion in revenue under management and over 1,500 customers.
Groove co-founders Chris Rothstein and Austin Wang will join Clari and oversee the Groove product line’s strategy, product direction, and customer success.
“I’m incredibly excited about the power of combining Clari’s Revenue Platform with Groove’s best-in-class pipeline creation and conversion capabilities,” said Rothstein. “Together, we will create more pipeline and enable sellers to act on opportunities with incredible speed and effectiveness. Revenue teams are looking to win more, faster — and Groove and Clari are bringing the rocket fuel.”
The first stage of the Groove integration is planned for October.
“This acquisition will create a sense of urgency in the market that leads all key players to step up their focus to create their own version of a revenue orchestration platform,” opined Forrester Principal Analyst Seth Marrs. “It’s a significant win for all companies looking to improve sales performance.”
“Consolidating to create a more comprehensive platform is the best option in this environment,” continued Marrs. “Those that don’t, face the less appealing prospect of a down round or going out of business.”
“B2B sales tech buyers want to take advantage of AI for sales and simultaneously reduce complexity in their tech stack,” said Gartner Senior Director Analyst Dan Gottlieb. “Clari with Groove now has the pieces to deliver a complete revenue hub with interconnected workflows and deep data integrations.”
B2B data vendor Clearbit posted a demonstration video of its ChatGPT plugin that supports Reveal (visitor intelligence), Enrich, and Prospector API calls, helping marketers build free-form queries against Clearbit’s intelligence. For example, marketers can ask for lists of companies or contacts that match their ICP and demonstrate clear intent. They can also identify firms displaying clear purchase intent over the past week by analyzing Clearbit’s Weekly Visitor Report data.
In the demo, ChatGPT-4 queries are executed against Clearbit to identify three large companies in Japan. No coding knowledge is required, with ChatGPT leveraging Clearbit’s business intelligence API and Whimsical’s account mapping service.
A follow-on query displays a Whimsical account map of Rakuten execs sourced from Clearbit.
Rakuten exec account map, collected from Clearbit and processed through Whimsical, displayed in ChatGPT.
“With this plugin, anyone—be it a marketer, sales professional, or even a curious individual—can now create and utilize the same complex sales and marketing workflows that were once reserved for the most highly technical growth teams. It breaks down the walls that have long separated the technical growth hackers from the rest of the business world.”
Clearbit Group Product Manager Zachary Swetz
By grounding ChatGPT with business intelligence, Clearbit addresses the issues of data latency and hallucinations related to firmographic and contact queries. Furthermore, when third-party plugins are deployed, ChatGPT cites them, addressing the problem of attribution and GDPR compliance (as Clearbit is compliant). ChatGPT also displays which plugins are enabled within the model.
“While ChatGPT is extremely powerful, go-to-market teams currently can’t fully capitalize on its potential due to its out-of-date data—ChatGPT’s current knowledge cutoff is March 23rd, and it has limited knowledge of the world and events after 2021. And, it has a tendency to hallucinate, producing answers that seem accurate, but are incorrect,” wrote Swetz. “To remedy this, we’re bringing Clearbit’s reliable and accurate data to ChatGPT to make it an incredibly valuable tool for sales, marketing, and operations professionals.”
TechTarget released the latest update to Priority Engine, with expanded sales intelligence insights, workflows, and data syncing. Enhancements support greater Salesforce functionality and additional Prospect-Level Intent use cases. Prospect-level intent is generated from GDPR-compliant activity across its network of 150 enterprise technology media sites and over 1,000 topical video channels.
“To serve the more than 30 million opted-in members (your buyers) across our information networks and keep them coming back, we have to stay on top of their rapidly evolving information needs,” blogged CMO John Steinert. “We need to anticipate where categories and organizations are going and be there for our members. And that means, for our tech vendor clients, we can be the best possible source of insights into what’s happening in their hyper-specific categories, for both strategic and tactical – lead gen or otherwise — purposes. We help them turn our audiences (represent their markets) into more demand, better leads, and healthier opportunity pipelines.”
Furthermore, Prospect-Level Intent improves both sales and marketing performance. For example, email nurture campaigns that target active buyers and prospect interests “commonly result in dramatically higher CTRs vs. cold contact outreach.”
Likewise, outbound sales activity targeting active prospects with demonstrated intent enjoy “significantly higher” call conversion rate.
A TechTarget analysis of over 350,000 opportunities across 90,000 accounts found that TechTarget-influenced deals progressed to closed/won status 35% faster than other opportunities.
“When B2B tech buyers need to solve business problems, they come to TechTarget first because we provide both the independent decision-support editorial content they respect and the vendor content they seek in a context that caters to their buying ‘jobs-to-be-done.’ Priority Engine provides our clients with deep insight into these buying team and buyer’s journey interactions so they can better capitalize on real demand taking shape in their markets. This release gets this proprietary data directly into more GTM users’ hands and makes it easier for them to drive critical impact for their organizations.”
TechTarget CEO Michael Cotoia
TechTarget improved its Salesforce syncing and real-time territory management. Syncing supports both standard Account and Opportunity objects and custom fields associated with these objects.
For example, customers may now build and dynamically update Priority Engine Account Lists using customer first-party account attributes such as target account lists, accounts in specific geos, or by opportunity status.
Priority Engine also supports syncing of third-party data sources stored in Account custom fields such as 6sense stages, Demandbase minutes, or Bombora scores to build Account Lists.
TechTarget VP of Corporate Communications Garrett Mann provided additional detail on the benefits of improved syncing to GZ Consulting: “The ability to dynamically sync and automatically update Priority Engine Account Lists based on customer first-party data and third-party data enables several benefits across sales, marketing, and ABM use cases, for example: (1) The ability to set and continuously update sales rep territories based on Account Owner, ensuring sales reps using Priority Engine are always seeing insights and new prospects from current account targets; (2) the ability to integrate separately purchased 6sense, Demandbase, and/or Bombora data with Priority Engine Account Intent for a single source of truth; (3) the ability to export into MAP nurture opted-in TechTarget prospects from Accounts where both TechTarget and 3rd party intent providers are seeing down-funnel demand; (4) and the ability to target TechTarget lead generation or advertising campaigns using this data.”
Other Priority Engine enhancements include:
An improved user experience and navigation that expedites account monitoring. Intent insights include new buying team members engaging, named prospects and customers researching competitors, or accounts accessing late-stage decision-making content.
A new account journey visualization that displays valuable demand-related activities at accounts across both client systems and the TechTarget network.
Streamlined user management and administration for target account lists and territory management. Admins will also benefit from simplified seat license administration and usage dashboards.
A new Opportunity Dashboard in Salesforce that displays the progression of opportunities, where go-to-market teams should take action, and where TechTarget has influenced deals.
The new Opportunity Dashboard may be viewed by deal counts or dollar volume.The Opportunity Dashboard Top Influenced Accounts.
“No matter your stack, realizing the value of RevOps sinks or swims based on the accuracy and quality of the intent and contact data – and TechTarget has that in droves,” said Sales Community Founder Randy Seidl, “The backbone of any successful GTM revenue motion isn’t how many tools you have, it’s about the insights and data that you’re using in them that unlocks value.”
This is part II of my discussion of Data Axle. On Monday I covered the launch of its Audience360 cloud-based data management platform.
B2B data vendor Data Axle announced expanded US content coverage, including additional depth for federal contractors, startups, nonprofits, and medical professionals. Organizational counts grew five percent, with Data Axle “adding hundreds of thousands of sought-after businesses and millions of new or updated contacts,” with “new attributes [that] are incredibly accurate and reliable,” explained Senior PR Manager Courtney Black to GZ Consulting. “Businesses can use this data to effectively identify prospects, which is particularly important in the current economic climate.”
New coverage includes 20 thousand more startups, 100 thousand federal contracting businesses, 100 thousand medical professionals, 35 thousand restaurants and bars, 500 thousand nonprofit organizations, and two million other US-based companies.
The medical professionals dataset spans 44 medical occupation titles and 124 specialties.
The federal contracting coverage has long offered ownership flags for veteran, minority, and women-owned businesses. Data Axle added Unique Entity Identifiers (UEI) alongside the expanded coverage.
Startup profiles include names, address fields, phone numbers, industry codes, corporate email addresses, websites, Twitter, and other social media handles. The firm recently added a source of technology startups but did not disclose the name.
Nonprofit profiles include EINs (federal tax ids). As most nonprofits do not earn revenue, the data set focuses on modeled machine-learning employee counts. Board members are included in the coverage.
Data Axle publishes data on 16.8 million US and 1.1 million Canadian businesses.
Data Axle content spans nearly 18 million US and Canadian verified businesses and 150 million business contacts. Data Axle also added or updated 10.3 million contact records, with “superior coverages of firmographics, such as industry type, professional specialty, cuisine, and geocoding.”
“All our products benefit from the extended datasets,” explained Data Axle Marketing SVP Kara Alvarez to GZ Consulting. “Business data is added to Data Axle’s platform in real time as we identify updates, and each of our products and services leverages this central fulfillment platform as do many clients.”
Among the benefits listed by Alvarez were:
B2C Link connections offer more contact-to-consumer connections, tying together business and consumer profiles.
Data Axle products, including Genie (formerly Sales Genie), USA, Exact Data, and Reference, etc., enjoy expanded business data. For example, Genie contains “attributes specific to the use cases Genie clients focus on as opposed to the more extensive set available in our data platform.”
Data Axle’s standard and custom programmatic audiences “are always current” in any channel. Partner ecosystem audiences “also benefit as they ingest those updates.”
“At Data Axle, we are constantly seeking to expand the number of records available to our clients while simultaneously ensuring that the quality of our premium verified data remains at the highest level possible,” said Data Axle CEO Michael Iaccarino. “Our clients count on us for data at scale but also accuracy. We focus on carefully integrating machine learning into our processes. However, we will never cease leveraging human verification. We make over 20 million calls yearly to ensure details and key information are correct.”
Data Axle also gathers consumer data, so its B2C Link dataset benefits from the increased breadth of businesses and medical professionals.
“As a leading provider of consumer data in addition to business datasets, Data Axle plays a vital role in establishing a crucial connection between businesses and consumer profiles,” stated the firm. “The recent addition of business contacts in Q2 further strengthens this connection. Data is available separately for organizations looking to build insights between the two datasets or as a prebuilt set of audiences.”
