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.
6sense Revenue AI for Sales helps prioritize account activity.
6sense released Revenue AI for Sales, its account prioritization platform that identifies in-market accounts and recommends contacts in an “anonymous world.” The service assists reps with prioritization, research, multi-threading, and personalization.
“Information overload is killing sellers’ productivity. In today’s rapidly changing business landscape, we need to give sellers the tools they need to reach new heights. This means giving sellers sales technology that helps them spend more time selling and less time on unproductive activities,” said CEO Jason Zintak. “We’ve already transformed marketing teams by revealing and targeting accounts and engaging anonymous buyers. Now we’re giving sales teams a massive upgrade from their legacy database vendors. This puts 6sense in a new category where we can innovate and lead, just like we have with others like predictive analytics and ABM. Early momentum from customers making the move to a better selling experience demonstrates the potential for impact.”
The Persona Map identifies engagement activity by role and level.
Revenue AI for Sales illuminates the “Dark Funnel,” where 97% of B2B research is conducted anonymously. 6sense ties new buyer intent signals with account and contact intelligence. Recommended Actions prioritize engagement and suggest which contacts to acquire and reach out to. 6sense offers first-party (visitor), second-party (G2 and TrustRadius), and third-party (Bombora) intent signals. It supports both topic and keyword intent alongside buying stage.
A Persona Map provides a visual map of the buying team, helping promote multi-threading and suggesting unknown buying team members. The map includes contact details, activities, and talking points.
People and company pages highlight company hierarchies, job insights, technographics, and psychographics. Contacts and accounts can be sent to CRMs, pushed to SEPs for engagement, and contacted via email, phone, or LinkedIn.
6sense insights are supported by a Chrome extension, allowing reps to prospect on the open web and identify potential buyers.
Prioritization Dashboards highlight in-market accounts and insights. 6sense also alerts reps to important account activity, recommended actions, and new buyer intent signals via email and Slack.
“Challenges exist on multiple fronts today as sellers have to navigate through a constant barrage of information and noise, plummeting productivity and increasing frustration,” said CTO Viral Bajaria. “With our AI-driven solution, sales teams will be able to focus on what they do best – building relationships and closing deals – while our technology takes care of the rest. 6sense Revenue AI for Sales uses the power of AI, big data, and intelligence to give sellers confidence in their ability to close more deals and be the trusted advisor their customers want and need.”
6sense maintained its momentum last year, growing revenue by 70%. The company attributed its ongoing growth to its “strategic focus on new product introductions, market expansion, and ecosystem growth.”
New product introductions included the October release of Conversational Email. The module, which leverages Generative AI, intent, and pre-intent data, dramatically enhances productivity when sending marketing and sales emails and fielding responses. Conversational email composes “relevant and hyper-personalized emails to qualify and convert leads at scale.” 6sense claims its customers enjoy a 50 percent reduction in deal-cycle time, a 150% increase in average deal size, and $900K of new pipeline activity in four weeks.
“The results of the past year’s performance are a major achievement that demonstrates how the team’s hard work has paid off,” said Brian Ascher, Partner at Venrock. “As 6sense continues executing against commitments and the product roadmap, we expect to see this upward trend maintain its momentum. This is what the larger investor community loves to see, and we are proud of the 6sense team delivering these results.”
Other enhancements include ongoing investment in the Slintel database and the release of 6sense Pipeline Intelligence based on Fortella. Both Slintel and Fortella were acquired in H2 2021.
“6sense offers billions of data points of market-leading account and contact data along with best-in-class curated data, enhancing a customer’s own first-party data sources and tech stacks to deliver powerful B2B go-to-market strategies, insights, and orchestrations,” claimed the firm.
6sense continued to grow its partner ecosystem with new integrations, including HubSpot, Microsoft, and Integrate. In addition, its integrations with Dynamics and HubSpot CRM support prescriptive sales dashboards and buyer insights.
“Throughout the past year, we’ve built upon our growth in meaningful ways and continue to provide our customers with tangible value that impacts their bottom line,” said 6sense CEO Jason Zintak. “Using our own platform is essential to our success and puts us in a unique position where 6sense Revenue AI is a competitive advantage – both in our own category and where our customers compete. Looking across our customer base, we see revenue generation is 120% more effective when using 6sense, their deal size doubles, and win rate increases 4X.”
The firm has expanded internationally over the past year with an increasing presence in EMEA and APAC. The London office grew to 45 full-time employees, and APAC has over 400 employees in India and Singapore.
Sales Execution Platform Outreach unveiled a series of product enhancements and dashboards at its Explore+ web conference earlier this month. New features include Smart Email Assist with Generative AI, a Create Pipeline Calculator, Buyer Topics and Reactions in Kaia, Deal Grid, Deal Overview, Success Plan Methodologies, and Data Sharing with Outreach.
“The industry has never had a single place to generate and manage pipeline, run sales cycles from creation to close, coach reps, and forecast – until now,” said the firm.
Over the past decade, sales teams have acquired a set of SalesTech solutions that create a “hairball” of point solutions that work poorly together and suffer from siloed data and regular system switching. Furthermore, a unified data platform supports advanced workflows, AI models, and account insights for sales coaching and deal management.
Outreach has enjoyed solid adoption of its new platform since launching it ten months ago. Multi-product adoption is strong, with over 400 customers using two or more products. Furthermore, multi-product adoption is driving platform ARR, which has grown by over 100% in the past two quarters. Since the platform was launched, Outreach’s new logo deal size has increased by 16%.
Outreach repositioned itself as a Sales Execution Platform as it expanded beyond Sales Engagement (Source: Outreach Analyst presentation).
“Today, Chief Revenue Officers are facing two major problems: pipeline coverage and conversion. They need to create an adequate amount of pipeline, and close it at a greater rate,” said CEO Manny Medina. “That’s why Outreach has been on a journey to expand our offerings to solve our customers’ biggest problems today. Our goal is to provide sales leaders with a single platform to manage all of their deals – from creating more pipeline to closing more deals. Today’s announcements at Explore+ are an important milestone in our platform journey, and we look forward to continue innovating for the 30 million B2B salespeople around the world to help them unleash their selling potential.”
Outreach Smart Email Assistant
The Smart Email Assistant generates automated email replies that go beyond email templates. AI factors in previous conversations between the buyer and seller when generating responses. By automating email responses, “sales reps can focus their time on editing and personalizing the AI-generated content, instead of drafting these emails from scratch.”
A new Pipeline Calculator recommends prospecting activities to fill pipeline gaps. The calculator utilizes historical pipeline data to determine the number of prospects that should be added to sequences to meet their quota. In addition, the historical conversion rate assumptions are displayed and adjustable. Thus, the assumed conversion or win rates can be adjusted to accommodate market shifts or new processes or messaging that boost historical results.
Outreach Pipeline Calculator
Outreach continues to develop Kaia, its conversational sales module, with the addition of Buyer Topics and Reactions. AEs and sales managers can revisit meeting recordings and review the buyer’s reaction to fourteen relevant sales topics, such as budget, legal, or support.
“Using AI, Outreach is able to understand the contextual utterance of relevant sales topics in any meeting or email – ranging from pricing to product to next steps to support – and can understand when the buyer raised an objection at any point in the meeting,” explained the firm. “It delivers invaluable insight into what is really happening in meetings, down to each moment, and at scale across all meetings.”
Success Plans now support popular sales methodologies, including MEDDIC, MEDDPICC, and SPIN Selling, helping reps “consistently and continuously qualify deals and align with champions to mitigate deal risk.”
Outreach added a single-pane-of-glass opportunity viewer called Deal Grid. Reps can view their deals sorted by health score and value to focus on their best opportunities. They can also edit fields such as Close Date, Amount, Stage, and Forecast status (e.g., omitted, commit, best case, most likely) with information synced to the CRM and forecasts updated.
Opportunity Viewers are a common feature of Revenue Intelligence platforms (e.g., Clari, RevenueGrid, People.AI), but with Sales Execution and Revenue Intelligence platforms expanding into each other’s domain, Deal Grid was an anticipated new feature. Opportunity viewers help reps review their deal status, update the CRM, and prepare for meetings with sales managers. They solve the problem of serially jumping between Opportunity records in Salesforce (which the firm has moved to resolve with similar functionality).
Outreach released several new reports and dashboards:
Create and Close Dashboard: Provides AEs and sales managers with a high-level forecasted revenue summary of the existing pipeline and highlights pipeline gaps and risks.
“The insight-laden dashboard shows the forecasted revenue from existing pipeline, and highlights pipeline coverage gaps for the current and future quarter, which helps reps proactively mitigate risk earlier and drive to success,” said Outreach.
Outreach Pipeline Calculator
Deal Overview: An overview of open opportunities with a deal summary, an engagement timeline, deal health, sales methodology insights, next steps, and the shared plan. The engagement timeline displays all sales activities and a heat map detailing customer engagement trends.
Outreach Deal Overview
Pipeline Dashboard: Displays all “relevant pipeline details to life in a single, sortable view, allowing sales managers to stay on top of their quarter.” The dashboard includes a pipeline activity summary by stage, projected finish, revenue to date, quota, and top deals with deal health scores.
Outreach Pipeline Dashboard
Outreach also announced bi-directional syncing with HubSpot. Earlier this month, it unveiled expanded Outreach Data Sharing with Snowflake.
Despite recent layoffs, Outreach continues to build its customer base. FY 2023 revenue (FYE Jan 2023) passed $200 million across 6000 customers. Outreach’s scale benefits its clients as it records over 25 million action/outcome pairings per week, helping refine its machine learning insights and recommendations.
