Dun & Bradstreet announced the launch of D&B.AI Labs to lead the co-development of AI solutions that apply Generative AI and Large Language Models (LLMs) against its proprietary data and analytics.
“Over the last few years, Dun & Bradstreet has gone through a dramatic transformation driving a culture of innovation and making significant investments in technology, data, and analytics, including adding 64% more analytics solutions, evolving its scores and indices to leverage AI, LLM and ML capabilities,” claimed the firm.
A team of data scientists, data engineers, and solution specialists with expertise in AI, LLM, ML, and advanced business analytics staffs D&B.AI Labs. Lab members will partner with clients to formulate solutions, build prototypes, and deploy solutions that leverage Dun & Bradstreet’s data and analytics.
“Powered by innovation and in support of the rapid changes across the business landscape, companies of all sizes need access to an environment where they can fuse our trusted datasets, responsibly apply AI, and tap into our expertise to quickly develop prototypes and solutions to advance their businesses. We believe there is no company better than Dun & Bradstreet to accomplish this,” said Dun & Bradstreet CEO Anthony Jabbour. “D&B.AI Labs creates an environment for us to work side-by-side with our unparalleled client roster, including 93% of the Fortune 500, to understand their pain points and help them to swiftly design and deliver innovative solutions specific to their needs.”
Along with generative AI expertise, D&B.AI Labs offers expertise in Dun & Bradstreet’s ESG, linkage (e.g., family trees), Master Data Management, and sales and marketing solutions. Dun & Bradstreet’s MDM solutions help connect data within organizations, cleanse and enrich records, and apply predictive analytics against customer datasets.
“In a world where LLMs are trained on mainly uncontrolled publicly available data from the web, the value of trusted datasets such as Dun & Bradstreet’s will increase significantly,” said Gary Kotovets, Chief Data & Analytics Officer at Dun & Bradstreet. “Our products and services are underpinned by validated, historical, and proprietary data, which allows us to deliver reliable and interpretable AI-created results that drive our clients’ most critical business decisions.”
Dun & Bradstreet also announced that its Sales Intelligence solution, D&B Hoover’s, is now available on the Google Cloud Marketplace. D&B Hoover’s via the Google Cloud Marketplace allows for a “dollar-for-dollar drawdown against Google Cloud commitments.”
“The demand for trusted B2B data intelligence is ever-increasing. D&B Hoovers continues to be a solution that organizations rely on to help boost sales productivity and strategic targeting to drive business growth,” said Karlos Palmer, SVP of Sales & Marketing Solutions Product. “Having D&B Hoovers available on Google Cloud Marketplace makes it easy to use incredibly valuable data to build sales pipelines, and since we’ve migrated D&B Hoovers to Google Cloud, customers have already reported significant performance improvements.”
Revenue Intelligence vendor Gong unveiled Gong Engage, its entry into the Sales Engagement space. SEPs have been adding Conversational Sales tools for several years, so Gong adding SEP functionality should not be surprising. After all, Gong began as a conversational sales solution before widening its scope to Revenue Intelligence. Also, one of Gong’s top rivals, Chorus, is owned by ZoomInfo, which has been building ZoomInfo Engage for several years.
“Gong Engage serves as a single solution to streamline sales engagement for revenue teams by delivering AI-based sales guidance from the first touchpoint with a prospect to deal close,” wrote the firm. “Engage helps teams create and accelerate pipeline by delivering increased productivity with AI-driven automation and guidance, high-quality outreach to engage entire accounts, and a single sales engagement solution to streamline revenue workflows. Gong’s proprietary AI delivers three times more accuracy than off-the-shelf AI models.”
Engage supports core SEP features, including a web-based dialer, workflows, and email templates. It also sports generative AI models for deal prioritization and extracting call highlights, action items, and outcomes. AI features include:
Call Spotlight, Gong’s generative AI functionality that composes call briefs, account highlights, and action items from sales conversations
Automated call outcomes and email response classification that automatically categorizes calls and emails and syncs these insights with the CRM
Assisted writing, which helps reps personalize their outreach based on persona
“Engage’s contextual, account-based approach for prospecting and selling exceeds the limitations of traditional lead-based tools that encourage mass outreach with little targeting. Instead, it delivers a complete understanding of an account, including all touchpoints, relevant CRM information, and conversational history,” stated Gong.
Gong emphasized that it didn’t jump on the generative AI bandwagon following the breakout success of ChatGPT but has been working to integrate generative tools into its platform for over a year. Furthermore, its focus on sales-focused NLP offers it a leg up on vendors marketing generic ChatGPT tools or lacking years of AI expertise and product development.
“Gong launched in 2016 to harness the power of AI to rid customer-facing people of their day-to-day drudgery. We have been working with LLMs for over a year and see it as a major breakthrough. But highly accurate, domain-specific AI that delivers a deep understanding of what’s going on within a sales organization and the next steps needed to win deals is more elusive,” said Gong CEO Amit Bendov. “AI is the core of Gong’s platform, and our new models exemplify the sales-driven advancements we’re bringing to market to help our customers transform their teams and accelerate revenue growth.”
Along with conversational sales expertise, Gong offers Smart Trackers, a set of AI-based customized signals. Launched last year, Smart Trackers help revenue teams “identify deal risks and opportunities, understand the effectiveness of strategic initiatives, replicate best practices, and get ahead of emerging market needs.”
Engage’s Recommended Contacts feature analyzes historical deal data to recommend contacts for outreach. It feeds contact data from LeadIQ, Cognism, and Apollo based on target personas. Recommended contacts may be added to flows (cadences), or sales reps can reach out via email, phone, or LinkedIn.
Engage also displays buying signals from over 120 Gong Collective integrations “to help teams stay on top of their pipeline, no matter where signals are coming from.”
Along with consolidating conversational sales, sales engagement, and revenue intelligence in a common platform, Engage supports partnerships that include LinkedIn Sales Navigator, Chili Piper, and Calendly.
Engage workflow and dashboard features include Pipeline Views for viewing key tasks and insights across open opportunities, an Analytics Dashboard for sales management, and team collaboration tools for sharing and assigning tasks across teams.
“Gong changed how revenue teams build pipeline with our customer-centric AI – now we’re changing how they engage with customers at every stage,” said Bendov. “We have leveraged our market-leading AI technology as the foundation for Gong Engage, which sets the entire revenue team up for success. Engage is the only solution that harnesses customer interactions at scale to drive high-quality engagement and ultimately, grow revenue.”
“Delivering the perfect sales pitch is one of the most challenging sales skills to master—both for inside and field sellers. A sales pitch must be confident, impactful, and quick,” stated the firm. “It should grab a buyer’s attention, capture trust, and leave a curiosity gap. A great pitch doesn’t happen by accident—it takes practice, preparation, and feedback. Yet, sales managers and enablement teams aren’t always able to provide the thoughtful and attentive evaluations and feedback reps need to develop their pitch.”
According to a 2018 Gartner Leadership survey, only 42% of sales managers feel equipped to develop their staff. Furthermore, “sellers feel the shortcomings of managers as well. Just 38% of sellers report their manager helps them develop the skills they need for their role today, while only 34% report their manager helps them develop the skills they need for the future.”
PitchAI employs AI to record and analyze sales pitches, providing consistent, on-demand coaching. Feedback is instant, allowing the rep to iterate, refine, and build confidence.
Furthermore, PitchAI analyzes the seller’s “credibility, sincerity, and knowledge through non-verbal communication” and coaches reps on improving their messaging and presentation. Each pitch is benchmarked against top sellers across the industry “to provide context to PitchAI’s rating and performance scores.”
PitchAI evaluates reps across four dimensions:
Speed: How fast or slow the pitch delivery is and whether it’s understandable.
Body language: How trustworthy, friendly, and approachable the seller appears.
Silences: How and when to add or remove pauses.
Happiness: How enthusiastic the pitch comes across overall.
Tips are industry and language-specific. Showpad noted that “long silences make for a bad pitch in German, but a good one in Portuguese.”
Israeli playbook vendor Winn.AI now offers a self-service registration that allows sales reps to trial the Generative AI service for a month at no charge. Winn describes itself as an “AI-driven no-typing CRM that aims to empower the next generation of sales teams.” It joins calls and offers real-time tracking, capturing, and CRM updating features for Salesforce and HubSpot.
Winn supports over twenty sales methodologies and is tuned to automatically capture playbook insights as they are organically discussed with the sales rep. Out-of-the-box methodologies include MEDDIC, MEDDPIC, Spin Selling, BANT, and Challenger. Additionally, playbooks are available for discovery calls, demos, and negotiations and may be customized.
CEO Eldad Postan-Koren emphasized the administrative burden faced by sales reps, citing a 2023 Salesforce report that claims only 28% of sales rep time is spent selling. 72% of sales rep time is consumed by record keeping, CRM updating, virtual meetings, email follow-ups, data entry, and lead management. Winn.AI promises to claw back one-third of the 8.8% of rep time spent manually entering information. Furthermore, reps have long limited their data entry to the bare minimum, so Winn.AI will capture significantly more detail.
Other tasks, such as prioritizing leads/opportunities, researching prospects, and preparation and planning, also benefit from automated data harvesting and synchronization, helping reduce time on such tasks and improving their quality.
“Interfering with salespersons in our daily conduct is not good. Adding another system for them to enter and changing the way they are used to working is a negative type of interference,” argued Postan-Koren. “This is the main reason I built Winn.AI as an augmentation of other existing systems. This will effectively disrupt the sales force where disruption is needed and welcomed.”
Winn.AI automatically joins conversational platforms such as Zoom, Teams, and Google Meet and supports time warnings, attendee lists, and post-call meeting summaries. Editable summaries are displayed as soon as the call ends, adding them to the standard call workflow but removing most data entry. Salespeople can also send a personalized recap email to call participants. This review-and-notification process is generally completed within four minutes of each call’s conclusion.
As playbook details are captured in real-time, reps can see which topics have been discussed and which ones remain open, helping ensure richer discussions. Following the call, reps are presented with a call summary, next steps, and playbook insights. Once reviewed, the information is synced with the appropriate CRM records.
Postan-Koren explained that Winn.AI employs NLU (Natural Language Understanding), which goes beyond NLP (Natural Language Processing).
“Understanding is not processing because I can ask you, ‘Michael, how many employees are you?’ And your answer will be 20 employees. But I can also ask you, ‘Mike, do you have 20 employees?’ And your answer will be yes. Or I can ask you ‘How many employees?’ and your answer will be 20. So here are three different ways to ask the same question to get the same answer, and the computer won’t understand it. Understanding context is the secret sauce here.”
What also differentiates Winn.AI is the combination of playbooks with real-time call coaching, data capture, and CRM syncing, allowing reps to be more present during calls. These elements are supported across many products, but I have not seen a company combine them into a single offering.
“The system is a personal assistant for the salespeople and relieves the burdensome administrative work of taking notes, having a list of answers, and entering information into the CRM,” stated Postan-Koren. “ It does so all at a level of detail that does not exist in other tools on the market, so much so that in real-time, it can exactly match a specific topic of conversation to the relevant field in the CRM. Also, the system knows how to follow the topics of the conversation in real-time, check the full coverage of the conversation’s agenda, and give instructions that will help improve performance. This is a new category in the SalesTech world, and Winn.AI aims to lead this category.”
The firm is not targeting specific verticals as it believes it has a compelling cross-industry solution that supports digital sales, customer success, and service departments.
The service is priced between $59 and $89 per user per month, with volume discounts available.
Winn.AI exited stealth mode last fall and now has a team of thirty. It has begun hiring in the Bay area. Postan-Koren noted that its $17 million September seed round provides it with a financial runway through the end of next year, allowing it to focus on go-to-market instead of hustling for funding in a weak VC market.
Winn.AI was named one of the “Top Israeli Startups To Watch in 2023.” The firm placed 16th on the list by Startup Stash.
Conversational Cloud vendor Drift announced it had integrated OpenAI’s API into its chat service. The GPT integration suggests chat replies to sales reps, helping them answer complex customer questions. Responses are based on a company’s website content, marketing material, conversational context, and GPT.
Reps can choose to send the response verbatim, edit it before responding, or request a refined response.
“The ability to generate suggested replies by repurposing any available content also provides real-time on-the-job training for new sales reps (which currently takes three months on average), teaching them how to respond accurately and in the right brand voice,” explained the firm.
Drift listed a trio of capabilities it will be releasing later this year:
Automated content creation and ongoing optimization of playbooks
Automated onboarding and AI topic training
Personalizing sales outreach and prioritizing target accounts
“The buzz around ChatGPT, and the widespread experimentation that followed, has only underscored that conversation-based AI is paving the way of the future. But it needs to be tailored to solve meaningful business challenges,” said Matt Tippets, SVP at Drift. “With Drift’s ability to use Conversational AI to contextualize responses that augment the efforts of human teams, we’ve created a feature that helps sales reps of all experience levels be more productive, particularly relevant now with pressure on during a more difficult economic climate.”
Drift’s approach offers a human-in-the-loop option for sales chat that ensures responses are accurate and not subject to hallucinations.
“We have years of experience and real-life use cases that are already being applied to how we manage and bring GPT capabilities to our customers,” blogged Drift Senior Director of Product Marketing Aurelia Solomon. “And we’re excited to continue embedding GPT into our products for marketers and sellers to automate more of their workflows to save time and help them create quality pipeline, faster.”
Cloud Communications vendor RingCentral entered the Conversational Sales space with RingSense for Sales. The new service employs generative AI to summarize meetings and calls. Initially, RingSense supports the sales function, but RingCentral plans to extend the service to other roles, including support and marketing.
“We’re going to be helping businesses make their voice, their meetings, their email interactions more intelligent, so they can automatically uncover new, actionable insights that help reduce errors, overhead, and improve performance,” said RingCentral COO Mo Katibeh. “I think of it as a force multiplier for every single employee.”
RingSense for Sales analyzes customer interactions with sales reps and surfaces insights and performance metrics. These insights are also delivered to sales managers to assist with training and mentoring.
“Today marks an important step forward in our journey. Generative AI is a game-changing technology that will fundamentally transform communications and collaboration. Natural language, and voice in particular, has always been a universal interface for information, intent, and emotion that has been largely untapped,” said RingCentral CEO Vlad Shmunis. “Now with RingSense, we have the opportunity to inject cutting-edge AI across the entire RingCentral portfolio and make communications a powerful resource for businesses to unlock new potential and quickly extract meaningful information and insights.”
RingSense for Sales supports:
Automated follow-ups to drive productivity: RingSense’s AI gathers interaction summaries, notes, and follow-ups. It then syncs them with the CRM.
AI-generated summary scoring: Interaction-level scoring and reporting call out which conversations should be prioritized by managers, helping them identify coaching opportunities.
Integrations with 3rd party apps: RingSense for Sales integrates with Salesforce, HubSpot, Zoho, Google Calendar, Microsoft Outlook, and call and video meeting providers.
Ability to track keywords and phrases (trackers): Sales admins can set RingSense to track keywords and phrases such as competitor names, objections, trends, or product features. RingSense can also focus on relevant concepts instead of just keywords and calls out positive and negative deal signals.
“Over the last few years, RingCentral has developed a rich set of AI models that delivers conversational speech analysis and emotional sentiment recognition to the RingCentral platform,” explained the firm. “Last year, RingCentral rolled out numerous AI-powered video meetings capabilities and was first to market with Advanced Meeting Insights and Summaries, which uses AI to enable a user to quickly catch up on a missed meeting or use the tool for automated note taking.”
RingCentral also rolled out a set of AI APIs for accessing RingCentral transcriptions, summarizations, sentiment analysis, and interaction analysis for voice, video, and chat. These APIs will be available to their 85,000 registered developers and 350 third-party applications. RingSense, like RingCentral, is an open platform.
“Artificial intelligence (AI) is the fuel that will fundamentally transform how we think about digital transformation today. The era of deploying enterprise AI in isolation while wrestling with outcome uncertainty is over,” said Aragon Research CEO Jim Lundy. “RingCentral has created an enterprise-grade AI with a results-based design. Last year, they embedded this unique AI into their MVP platform to help make employees more productive. Now, with RingSense, they’ve taken it to a whole new level by focusing on bespoke use cases the industry truly needs.”
RingCentral has long partnered with incumbent Conversational Sales vendors such as Gong, Chorus, Wingman (Clari), ExecVision (Mediafly), and Outreach. Many of these vendors have been offering conversational sales tools for three to five years. In addressing their delayed entry into Conversational Sales, Senior Product Marketing Manager Keith Renison listed the following advantages of the RingSense offering:
RingSense is easy to purchase, deploy, and configure. Get ready for faster time-to-value without the expensive startup, platform fees, and model retraining costs.
AI-generated summaries, topics, and follow-ups are automatic. This accelerates the disposition of customer interactions creating huge efficiency gains.
Out-of-the-box “trackers” with higher quality pattern matching. Trackers can be customized or created from scratch. Tune your system to what you’re listening for and make adjustments along the way. AI does the rest.
AI-generated summary scoring at the top level helps find the important conversations without sifting through conversations manually.
RingSense is built by a trusted leader in cloud communications.
RingSense is not industry specific but can be leveraged broadly across industries for analyzing digitized sales calls and meetings, said Chief Innovation Officer Kira Makagon.
RingCentral, which has built a customer base of five million customers over the past two decades, can deploy RingSense to “empower person-to-person communications.” RingSense helps “make sense” and “find patterns in these interactions.”
Due to the large breadth of business conversations hosted on its digital platforms, RingCentral is “in a unique position to make sense of all of the wealth of information that is flowing through our platform,” said Shmunis. “By applying these ultra-modern AI techniques, we can really empower users of our system to make better sense as to what is happening in their own employee bases, whether it be sales agents, customer service agents, and, in certain cases, even just knowledge workers who are communicating and interacting with the outside World.”
Shmunis emphasized that RingSense is a platform with RingSense for Sales as the first offering. As an open platform, partners can build verticalized solutions. Shmunis suggested applications in legal, finance, and healthcare. Open RingSense APIs are already available.
Zeus Kerravala, Principal Analyst at ZK Research, argued that businesses suffer from poor data quality in their CRMs, with reps often limiting the information they key into Salesforce to “Met with customer.” Thus, AI’s most significant initial impact will be improving “data discipline” in organizations. The initial benefit of AI will be as an “input mechanism.”
“So, when I do a call with you, an AI can listen to it, summarize the meaning, put it in [the] CRM [and] update the record. You have contact center agents. You can do that with salespeople and customer success,” argued Kerravala. “You could actually use AI to create a better dataset and so, in theory, good AI leads to better AI.”
Kerravala sees AI improving the pre- and post-meeting experience due to its ability to create, manage, and refine meeting data. “Most of the vendors do a pretty good job mid-meeting. We have virtual backgrounds, transcription, and translation capabilities. But what happens when the meeting is over? Help me get the meeting minutes out to people and help me prep for meetings. That’s where I see this stuff having a pretty big impact.”
RingSense is available in three packages based on function: Observer for Marketers helps them track customer and competitive trends, Coach supports managers, and Professional provides the full complement of deal intelligence and CRM synchronization. RingCentral did not provide any pricing details.
Revenue Intelligence vendor Clari announced Automatic Call Summaries to its Wingman Conversational Sales module. The new RevGPT functionality, powered by ChatGPT, supports call summaries, next steps, and suggested actions in Slack in a conversational format. Users can view the call or send follow-up emails from Slack.
Wingman already offers real-time cues and battle cards for overcoming objections during calls. Furthermore, it alerts managers to “high-impact coaching moments that define deal outcomes, like pricing hurdles, competitor mentions, and more.”
“Are you going to meet, beat, or miss on revenue? That’s the single most important question in business — and today’s introduction of RevGPT represents a quantum leap forward in helping companies get revenue answers. By training generative AI to harness the industry-leading store of conversational intelligence and historical revenue data contained in RevDB, we’re giving revenue teams the ability to identify sources of revenue leak and take corrective action at scale and with extraordinary speed. RevGPT will quickly become the indispensable guidance system that empowers every revenue-impacting employee to achieve more.”
Clari CEO Andy Byrne
By combining RevGPT and RevDB, Clari’s database of revenue under management, RevGPT will enjoy a feedback loop that continuously improves Clari’s recommendations. This “flywheel effect” will offer “better answers, better actions, better outcomes, and faster time to revenue.” Future functionality includes “recommended prompts for every revenue-critical team — sales, revenue operations, customer success, marketing, finance, and leadership — enabling even greater productivity gains and revenue outcomes.”
RevGPT will soon recommend and automatically assist with follow-up actions, including drafting emails, scheduling meetings, updating CRM systems, and revising forecasts.
Wingman supports the following integrations:
Syncs with HubSpot, Salesforce, and Pipedrive
Records, transcribes, analyzes/summarizes Teams, Zoom, and Google Meet
Alerts via Slack and Teams. Alerts and guidance are also displayed in its desktop app.
“This is just the beginning of Clari’s RevGPT generative AI capabilities that are purpose-built to run revenue,” said the firm. “And we’re not stopping here. Soon you’ll be able to ask RevGPT to compose an email follow-up for you with just one click.”
Clari promises to address “revenue leaks,” including the difficulty of “combing through mountains of data buried in legacy systems — CRM software, spreadsheets, BI tools — to find, analyze, and take action on the information that can help them in revenue-critical moments.” By combining RevGPT and RevDB, Clari reduces “time to answers and action,” resulting in greater revenue precision and reduced time performing revenue-based search and analysis.
Last year, Clari identified $26 billion in annual revenue leakage across its 550 customers. Overall, the Boston Consulting Group estimates companies suffer $2 trillion in annual revenue leaks due to missed revenue capture, sales waste, and lost enterprise value.
Clari is offering thirty-day free trials to RevGPT, “ChatGPT’s cousin with a quota,” to revenue leaders. The functionality is live.
Wingman offers three packages: Growth ($60/user/month), Accelerator ($90/user/month), and Enterprise (starting at $110/user/month), with the firm planning on including RevGPT in the Accelerator and Enterprise editions.
Vendors are quickly moving to integrate generative AI into their offerings. This week, Qualified and Clari announced ChatGPT functionality. Qualified GPT, which the firm describes as “Generative AI for the Pipeline Cloud,” helps B2B vendors “harness the power of AI and engage and convert their website visitors at scale.” The firm views ChatGPT as a “new platform on top of which we will build the next version of Qualified.”
When launched four years ago, Qualified focused on predictive modeling and Predictive AI to identify buying intent signals, particularly those generated from website data.
“At Qualified, our core philosophy has always been to provide the most powerful approach to pipeline generation using a combination of people, data, and automation,” said CEO Kraig Swensrud. “With the rapid advancements in Generative AI, we will be able to provide even more robust automation to our customers, allowing them to scale their efforts, focus on their highest priority tasks, and ultimately crush their pipeline and revenue targets.”
Qualified GPT supports generative text apps that automate engagement prompting, copywriting, messaging, and chatbots. Initial features include:
Auto Pounce: Automatically sends engagement prompts (or “greetings”) that serve as conversation starters for website visitors that fall within a firm’s ICP.
Auto Correct: Qualified GPT corrects misspellings, fixes grammar errors, and proofreads responses, “helping your sales reps deliver speedy, professional responses.”
Auto Tune: Enhances rep dialogue while chatting “to sound more eloquent when speaking to potential buyers, helping every rep strike just the right tone with their important customers.”
Auto Expand: Reps can enter a few words or bullet points, and Qualified GPT will craft professional messages.
Auto Suggest: AI-powered recommended conversation responses that keep reps on message and speed up response times.
Auto Translate: Translates messages, displaying both questions and answers in the customer and sales rep’s language.
Auto Personalize: Changes or recommends website text “based on visitor data to drive the highest engagement and conversion.”
Auto Summarize: Summarizes conversations and website behavior, providing sales reps with a “succinct read out of Account activity to date.”
Qualified GPT will be rolled out as a “limited release to a subset of Pipeline Cloud customers this spring.”
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%.
“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.”
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 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.
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.
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 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.
On the same day that Microsoft launched Copilot, Salesforce announced Einstein GPT, its generative AI service that combines Salesforce’s own AI models with external models such as OpenAI’s. Einstein GPT supports personalized content creation across all of Salesforce’s clouds and Slack. For example, Generative AI functionality can write personalized sales emails, author customer support responses, compose targeted marketing collateral, and auto-generate code for developers.
“The world is experiencing one of the most profound technological shifts with the rise of real-time technologies and generative AI. This comes at a pivotal moment as every company is focused on connecting with their customers in more intelligent, automated, and personalized ways,” said CEO Marc Benioff. “Einstein GPT, in combination with our Data Cloud and integrated in all of our clouds as well as Tableau, MuleSoft, and Slack, is another way we are opening the door to the AI future for all our customers, and we’ll be integrating with OpenAI at launch.”
Einstein GPT is the next generation of Salesforce’s Einstein AI capabilities. Einstein GPT supports natural-language prompts that “trigger powerful, time-saving automations and create personalized, AI-generated content” within Salesforce. In addition, each application maintains a human-in-the-loop that reviews and edits client communications before they are sent out.
Einstein GPT reduces “the friction in sales reps wanting to move fast to meet their quota, having to leave Salesforce to send customer communication or do prospecting research, and spending too much time finding information stored in various parts of the CRM,” wrote Salesforce Ben.
New functionality includes:
Einstein GPT for Sales: Auto-generate sales tasks like composing emails, scheduling meetings, and preparing for the next interaction. It can also provide external news for prospect research, add contacts not already in Salesforce, and generate additional collaboration channels on Slack.
Einstein GPT for Service: Generate knowledge articles from past case notes. Auto-generate personalized agent chat replies to increase customer satisfaction through personalized and expedited service interactions. Einstein GPT for Service also auto-generates case summaries and knowledge articles from past case notes.
Einstein GPT for Marketing: Dynamically generate personalized content to engage customers and prospects across email, mobile, web, and advertising. The service can generate content with brand-compliant images and layouts. Marketing content can then be uploaded to Experience Builder.
Einstein GPT for Slack Customer 360 apps: Deliver AI-powered customer insights in Slack (e.g., smart summaries of sales opportunities) and surface end users’ actions. The Slack service supports writing assistance, background research on accounts, and instant conversation summaries.
Einstein GPT for Developers: Improve developer productivity with Salesforce Research’s proprietary large language model by using an AI chat assistant to generate code and ask questions for languages like Apex.
“Salesforce can be a powerful multiplier of generative AI experiences because Einstein GPT blends public data with CRM data, and when several million of our customers are all using Einstein GPT, the model gets refined with each instance and becomes more accurate,” explained Salesforce’s SVP of AI and Machine Learning Jayesh Govindarajan. “It’s a cumulative effect and is really a huge differentiator for Salesforce.”
Salesforce is also looking to establish an AI ecosystem, with OpenAI as the first integration.
“Einstein GPT will infuse Salesforce’s proprietary AI models with generative AI technology from an ecosystem of partners and real-time data from the Salesforce Data Cloud, which ingests, harmonizes, and unifies all of a company’s customer data,” announced Salesforce. “With Einstein GPT, customers can then connect that data to OpenAI’s advanced AI models out of the box or choose their own external model and use natural-language prompts directly within their Salesforce CRM to generate content that continuously adapts to changing customer information and needs in real-time.”
As part of the announcement, Salesforce established a $250 million venture fund to develop “responsible, trusted, and generative AI.”
OpenAI CEO Sam Altman said using ChatGPT in CRM services “allows us to learn more about real-world usage, which is critical to the responsible development and deployment of AI—a belief that Salesforce shares with us.”
“It will be fascinating to watch how this plays out,” opined Fortune editor David Meyer. “On the one hand, we’re now in the territory of serious businesses using generative AI for serious things, as opposed to playing around to see how long it takes to get a chatbot to say something offensive. On the other hand, some of these applications involve customers who may have some curveball questions. And it’s worth remembering that generative AI technology like OpenAI’s ChatGPT will occasionally ‘hallucinate,’ that is, basically make up fake information.”
“In theory, Microsoft’s and Salesforce’s new offerings should be safer to use because they only draw on information from companies’ own websites and internal databases—the customer-facing elements will in that sense be a bit like those Google search boxes in websites,” continued Meyer. “But that won’t necessarily make these AIs immune to occasionally emitting bogus information. Companies will find out soon enough how carefully they need to monitor their new copilots.”
Einstein GPT is in closed pilot.
A ChatGPT for Slack app is in beta. The ChatGPT app was built by OpenAI on the Slack platform and “delivers instant conversation summaries, research tools, and writing assistance directly in Slack.”