Category: Data Quality

SalesIntel Unlimited Credits

B2B DaaS vendor SalesIntel shifted away from credit-based data pricing to unlimited data access to its firmographics, technographics, contacts (including emails and direct dials), and news alert intelligence.  Pricing is based on the number of users, with unlimited access to downloads, exports, and data enrichment.

”SalesIntel’s unlimited everything plan removes the friction, frustration, and predatory pricing so many customers experience when working with other B2B data providers.” comments SalesIntel CEO Manoj Ramnani. “We are proud to be a true partner to this industry by leading a pricing revolution that will help go-to-market teams build limitless pipeline.”

SalesIntel’s unlimited content includes:

  • 300 million unique technology installs across 22 million accounts.  Technographics span 18,000 technologies.
  • 100 million email-verified contacts.  Of these, over 17 million are maintained by SalesIntel editors and regularly reverified to maintain a 95% accuracy level.
  • B2B account news and alerts for 22 million companies organized into 32 categories.

Contracts include the RevDriver Chrome extension, Bombora intent data, and platform integrations (e.g., Salesforce, Dynamics 365, HubSpot, Outreach, Salesloft, Marketo).

Licenses also include access to SalesIntel’s Research-on-Demand editors for finding new contacts or reverifying contact information.  Research on Demand is subject to credits, but at 120 per seat, the cap is generous.

SalesIntel has simplified pricing based on the number of seats.

Under credit-based pricing models, “Marketing is worried about not having enough credits for campaigns, Sales is worried about not having enough credits to effectively prospect, and RevOps is worried that there won’t be enough credits to keep all this data clean.”

Removing credit-based pricing offers several benefits to customers: 

  • Budgeting is simplified as the total cost of a SalesIntel contract is known when the contract is signed.  RevTech teams do not need to create mid-year POs if credits are running low or additional marketing campaigns are planned. 
  • RevOps does not need to allocate and monitor credits across multiple teams or reallocate a dwindling set of credits at the end of the year.
  • Marketing can run enrichment, including visitor enrichment, and updates as frequently as they’d like, limiting the impact of data decay on their account, contact, and lead data.
  • Marketing can regularly analyze and expand its ICP and test new verticals without worrying about credits.
  • Sales Reps can research and sync key contacts to their SEP or CRM without worrying about using up their allotted credits halfway through the year.

Furthermore, SalesIntel does not include any “data destroy” clauses, a legal issue that some incumbent vendors employ to increase the cost to defectors.

CMO James Lamberti explained to GZ Consulting that credit-based pricing “becomes a barrier to value for the customer,” with customers feeling “trapped” by usage limits.  “We want people to begin to appreciate the full depth and breadth of our data and to leverage it in ways to make themselves more efficient.”

Ramnani argued that SalesIntel customers enjoy value via “three very simple steps:

  1. We help them identify their ICP using the intelligence from our firmographic and technographic data.
  2. Then, we apply the intelligence of news and intent data to see who from their ICP is in the market today.
  3. Within those in-market companies, our customers enjoy direct conversations using mobile phones and direct dials.”

However, “context is everything.”  Vendors that provide large contact sets without the context of an ICP, account news, and intent data (i.e., steps 1 and 2) are providing names and numbers but fostering inefficiency in their go-to-market.  Targeting is more than simply finding many names.  Revenue teams need to know whom to call, when to call, and what to say.

SalesIntel can offer unlimited data access because it owns all of its data except for Bombora’s intent file.

Historically, Sales Intelligence services offered seat-based pricing, and marketing data vendors provided volume-based pricing.  When services began serving both departments, credit-based models were crafted on top of seat-based pricing, creating complex and frustrating pricing.  SalesIntel is looking to return to simple pricing and “partner with the industry” based on “the value of our data and the quality of our software,” argued Lamberti.

Lamberti described the sweet spot for this model as the mid-market – firms between 40 and 50 employees and several hundred.  These firms have some maturity in their marketing stack and go-to-market motion, with multiple BDRs and sellers.

However, “if you’re just a ten-person team with one seller and one BDR, we’ll certainly do business.  We’re going to have a package for them.  But the unlimited package is really so that we can go after the market where we really are a great fit, where we win.”

“Strategically, we know that this is the time to strike.  We’re not VC-backed.  This is where Manoj has got the right [employee-shareholder] strategy,” argued Lamberti.  The firm is not subject to the financial pressure of outside equity investors or public markets.  Thus, the new pricing is designed strategically “to gain share and grow our market footprint dramatically.” SalesIntel contracts are annual with multi-year discounts.  Pricing starts at around $11,000, with additional seats priced at $1,200.  Current customers that renew early can convert to the new pricing structure.

Echobot Rebrands as Dealfront

Karlsruhe-based Sales Intelligence vendor Echobot rebranded as Dealfront this week.  Dealfront is the combination of Echobot and visitor intelligence vendor Leedfeeder which merged last year.  The rebrand coincides with the merger of the two companies on a common platform. 

Dealfront content includes 30 million European companies, nearly 90 million contacts, 33 event triggers, and visitor intelligence.  Dealfront sources company intelligence from national registries, company news, and corporate websites.  Company content includes news, business events, corporate linkages, and registered financials.

Dealfront offers five products:

  • Target: ICP-based targeting spanning 30 million European companies and nearly 90 million contacts.
  • Connect: Sales Intelligence platform with company and contact profiles, build-a-list functionality, and Send to CRM.
  • Datacare: DaaS data cleansing and enrichment services.  Datacare supports Bi-directional integrations with Salesforce, MS Dynamics, HubSpot, Pipedrive, and Zoho. 
    Dealfront also supports Zapier integrations and Slack notifications.
  • Web Visitors: GDPR-compliant website visitor tracking that maps page-visit activity to customers and prospects.
  • Promote: New Programmatic display functionality that supports targeted campaigns and IP-based retargeting of website visitors.

CEO Bastian Karweg argued that Dealfront, a European-based company, offers multiple advantages over North American-based sales intelligence and B2B Data companies.  Dealfront differentiators include local market knowledge, European data hosting, and GDPR-compliant data gathered from company websites and local registries.  Furthermore, Dealfront is transparent in its data sourcing and does not engage in community data mining or email scraping.

Dealfront offers native language sales and support, with offices in Germany, Finland, the Netherlands, Denmark, Sweden, Italy, and Spain.  Dealfront has grown to 330 employees that speak a dozen native languages, providing its clients with a “distributed, diverse salesforce across Europe.”

To emphasize its European bona fides, it adopted the blue and yellow colors of the EU flag and the tagline, “The way to win deals in Europe.”

“You just can’t do business in Europe the way you do business in the US.  You don’t do business in France the way you do business in Germany,” remarked Dealfront CEO Bastian Karweg.  “You don’t even do business in Berlin the way you do business in Bavaria.  Dealfront delivers localized data, applications, and familiarity with European standards, culture, languages, and practices to give your sales and marketing team the advantage of feeling and acting at home in any European country or region – no matter where your business is based.”

The Dealfront platform supports four stages – Discover, Qualify, Convert, and Optimize – in a flywheel feedback loop that gains momentum as the platform refines each client’s ICP.  “This flywheel effect turns static ICPs into dynamic, self-optimizing, and real-time customer profiles that always improve in accuracy and reflect reality.  The result is more leads that end in sales, transforming businesses into a self-propelled revenue engine,” explained the firm.

“Our platform of data and applications shows you the best way to engage your ICPs in a localized way that’s effective in whatever country you’re in, in whatever region you’re targeting,” says Dealfront CPO Pekka Koskinen.  “Because we’re on the inside and speak the language, we’re working with higher-quality live intelligence on your ideal buyers.  Nothing gets lost in translation, nothing gets misunderstood, and nothing is outdated.  Our platform, along with our teams on the ground in each location, empowers you to convert leads to deals.”

Last year, Great Hill Partners invested €180 million to merge Echobot and Leadfeeder and set aside €50 million to fund future strategic acquisitions for Dealfront.  Clients include Hertz, Siemens, Eventbrite, and Pipedrive.

LinkedIn Sales Navigator Q1 Release


LinkedIn Sales Navigator rolled out its Q1 product, focusing on relationships, personas, and enhanced buyer intent functionality.

The new Relationship Explorer surfaces “hidden allies” and best paths into accounts, helping sales reps avoid cold outreach and “spam cannon techniques.”

“Instead of a blanket approach where you target everyone at an account, you can laser in on the people who are most likely to take a meeting with you based on their persona and what connection they have to you,” explained LinkedIn Senior Director of Product Mitali Pattnaik.  “You can also use it to multi-thread deeper into accounts by finding the next-best person to reach out to.  This creates a more efficient experience for buyers and sellers alike.”

Sales Navigator has long supported introductions and TeamLink (colleague) suggestions, but it has never fully leveraged the value of its economic graph for warm communications.  The Economic Graph supports 900-million-member profiles across 61 million companies, along with current and prior employment, educational background, posts, etc.

Sales Navigator has a second advantage: its profiles are maintained by its members, ensuring that profiles are kept up to date and contain rich data around education, interests, skills, employment history, etc.

“Teams have relied so heavily on cold outreach largely because they’re leveraging sales intelligence tools that are limited in showing how to get a foot in the door of an account.  These tools are chock-full of stale data: everything from incorrect contact info to the wrong person in the wrong role.  With reliance on tools full of stale data, reps end up spamming all potential prospects with a spray-and-pray strategy, leading to an abysmal 1-2% response rate,” argued Pattnaik.  “Looking forward, sellers are going to need to be smarter and reach out with a more personalized approach.”

Relationship Explorer recommends prospects at an account, leveraging the interactions and trends across its professional network “to provide sellers with optimal paths to connect with their target personas at their target accounts.”  As a result, Relationship Explorer saves time prospecting, cross-selling, and upselling at accounts, helping reps find the best contacts at target accounts.

The feature offers up to eight “of the most relevant individuals” based on their target persona and relevant, actionable insights (called spotlights by LinkedIn) based on interactions between members and organizations.  Spotlights highlight both biographic and dynamic information, including recent job changes, LinkedIn postings, and past customers.  As such, they provide timely reasons to reach out and content to include in their outreach.

Relationship Explorer suggests the best contact at an account based on the user-defined persona.

Relationship Explorer is available in all Sales Navigator editions.  However, while it displays a dozen spotlights, not all are available in each edition.  For example, Past Customer spotlights are only available in the Advanced Plus edition.

Personas help users identify their target audience by function, seniority level, geography, and current job title.  They are available on the Homepage, Search, Relationship Explorer, and Account pages.

Users can define up to five personas which act as templates for homing in on ideal prospects.

Persona definitions on the homepage.

Pattnaik suggested several use cases for personas:

  • Creating highly targeted Personas matching target customer profiles.
  • Leveraging Personas in Search, Homepage, or Account Pages to identify the most relevant opportunities.
  • Identifying warm paths and decision-makers at targeted accounts with Relationship Explorer.
  • Using insights from Account Pages, including Persona growth, to prioritize accounts composed of leads matching Personas.

Persona functionality is available to all users.

Over the past few releases, Sales Navigator has built buyer intent into its service.  Its latest intent-based feature is Product Category Buyer Intent, which identifies buyers searching for products in their category.

Product Intent Categories

Previous Sales Navigator intent was based upon research into a vendor.  Product Category Intent identifies prospects researching a product category but may not know a vendor or its offerings.  The two types of intent data can be compared to understand the level of interest in the company versus the interest in the company’s product category, informing sales and marketing strategy.

“Categories are created with AI by combining related keywords into one central category, which is then tied to products using publicly facing product descriptions.  For example, “fintech” and “financial tech” are individual keywords, which the AI model can combine into a single category,” explained Pattnaik.  “Intent is then connected using buyer’s members’ profile as well as recent buying activities on LinkedIn.com to help sellers find the buyers who are likely looking for a solution like theirs.”

LinkedIn is rolling out several new Buyer Activities that will be displayed on Account Pages and the Buyer Intent Account Dashboard.  Additional intent categories are rolling out over the next quarter:

  • LinkedIn Ad Engagement: Clicks and view activity data.  Both of these data points are private, so sellers will only be able to see the general profile of the buyer.
  • InMail Acceptance for a colleague: Displays the public identity of individuals who have accepted InMails from other sellers on the same contract.
  • Company LinkedIn page visits: Clicks on the company page.  Page visits are a private activity, so the buyer is anonymous.
  • LinkedIn profile visits to colleagues and leadership: A new activity that shows sellers when a potential buyer visits the profile of a colleague on the same contract or company leadership.  This is also a private activity.

Buyer Intent is available in the Advanced and Advanced Plus editions of Sales Navigator.

Users can now search against any account list or use an account list as a suppression list.  Other new search filters include:

  • Past Customer (Advanced Plus only)
  • Past Colleague
  • Executive TeamLink – leverages the networks of a company’s executives (Advanced and Advanced Plus only).
  • Viewed Your Profile
  • Product Category Buyer Intent

LinkedIn also enhanced its Sales Insights (LSI) service with the improved matching of companies to CRM accounts and Adjustable Growth Time ranges.

LinkedIn admitted that its previous LSI matching logic may have been inaccurate as it only matched against a few standard CRM fields.  LSI now supports CRM custom ingestion that improves match rates with customer-defined match fields.  There is also an option to force matches based on LinkedIn Ids or URLs.

LinkedIn Sales Insights Field Mapping

Adjustable Growth Time Ranges can be set to 3, 6, 12, and 24-month increments.

Live Data Series A

B2B DaaS vendor Live Data Technologies closed on a $5 million Series A led by Entrada Ventures with “further participation from firms and individuals with deep backgrounds in data tech.”  Previously, the firm was funded from revenue, but “we raised this round when we saw the opportunities made possible by overwhelming investor interest and support.”

“We have been behind Live Data Technologies since the company’s inception,” said Entrada Ventures Managing Partner and Live Data Technologies Board Member Jason Spievak.  “The core technology has multiple compelling applications across industries and verticals.  The accuracy and quality of job change event detection are mission critical to anyone making informed decisions.”

Live Data focuses on contact changes and ensuring accurate contacts in the CRM.  It maintains data on 70 million contacts and 2 million companies, capturing 30,000 daily job changes from the open web.  Live Data argues that mining this intelligence from the web ensures more timely contacts than traditional data collection methods.

Contact data changes support:

  • Tracking champions as they move to new companies.
  • Highlighting account risk when champions or buying committee members depart.
  • Detecting promotions that create opportunities for success stories, upsell opportunities, and case studies.

“Each go-to-market strategy requires essential ingredients working together like a great recipe.  But, even the most perfect strategy will fall short if the people you put your message in front of are no longer relevant, or you lack up-to-date contact records, to begin with,” blogged Director of Growth Jason Saltzman.  “The bottom line is that business decision-making is done at the human level, and up-to-date contact-level data is essential for successful go-to-market programs.”

The firm will continue refining its DaaS offering and improving its data set and delivery. “Our Series A represents a confirmation that we are building something valuable,” said CEO J. Scott Hamilton.  “We see it, our investors see it, and our customers see it.  With all this recognition comes a pressure to take Live Data to the next level – and, in our eyes, pressure is a privilege.”

Winn.AI Launched

The Winn.AI Zoom app supports real-time playbooks and intelligence capture.

Conversational data capture has been a popular theme this month with announcements from People.AI and Nektar.  Winn.AI, a Tel Aviv-based AI Assistant and playbook vendor, came out of stealth mode this month to offer AI-based playbook coaching during digital sales calls.  Winn.AI also captures real-time conversations and syncs account intelligence with Salesforce and HubSpot.

“Winn.AI relieves salespeople of…administrative busywork so that they can focus on their customers — not their keyboards.  Its magic lies in its unique ability to monitor, interpret, and document sales calls,” said CEO Eldad Postan-Koren.

Winn.AI also supports playbooks and tracks key topics during calls, helping salespeople stay focused on their prospects.  Winn.AI captures all relevant data during sales calls, such as pain points, timelines, competitors, and team size.  Product, competitive, and technical information are also displayed during calls, reducing the frequency of “I’ll get back to you” responses and presenting competitive parries.

“One of our core competencies is that we’re training our AI in real-life sales meetings.  This greatly helps us make it more accurate versus standard training resources,” said Postan-Koren. “Furthermore, the more a customer uses the product in their own sales meetings, our AI capabilities will improve to match their exact needs.”

To speed up playbook definition, Winn.AI includes a set of templates based on common sales methodologies.

Winn.AI joins conversational platforms, beginning with Zoom.  Teams, Google Meet, and additional conversational platforms (meetings and dialers) are on the roadmap for Q4.

Other features include 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 call conclusion.

The Winn-AI post-call meeting summary pops up on call completion and supports editing and matching against CRM records.

Winn.AI does not create new records at this point but updates and enriches current Account, Contact, Lead, and Opportunity records.  Winn.AI does not yet support inbound calls or SDR outbound prospecting performed on dialers.

Playbook coaching reduces onboarding time and gives reps confidence that they have proper messaging, competitive knowledge, and technical details at the ready.

Like most SalesTech companies in 2022, Winn.AI positions itself around productivity and effectiveness during lean times.

“The funding round timing made perfect sense.  During turbulent times, when salespeople’s productivity and effectiveness are more critical than ever, a tool like Winn.AI provides the additional edge sales leaders and individuals are seeking,” Postan-Koren said.  “The Winn.AI real-time assistant acts as an extra pair of hands during meetings, giving salespeople the freedom to focus their attention entirely on the customer.”

Winn.AI is backed by $17.25 million seed funding from Insight Partners and S-Capital.  The firm has 25 employees and plans to double its headcount by the end of 2023.  The funds will be invested in “improving our deep technology” and building a sales and marketing organization.  All employees are in Israel, but they will be hiring in the US over the next two quarters.

Near-term roadmap goals are expanding the set of supported conference platforms and dialers, broadening the set of supported customer-facing roles (e.g., customer success, support, SDRs), adding playbook measurement and optimization tools, and implementing multiple, dynamic playbook branching (e.g., competitive handling, verticalized playbooks, technical discussions).

Postan-Koren offered GZ Consulting a compelling vision of “automated knowledge and personalization” feedback loops with the sales enablement team.  Closing the loop helps the enablement team maintain playbook recommendations.  Winn.AI will collect common responses and discussion tracks and feedback this intelligence to sales enablement for review and adjustments.  This human-in-the-loop approach facilitates playbook and coaching refinement and filling in coaching gaps.  It also identifies potential training needs as markets evolve.

“Winn.AI’s innovative and intuitive technology has identified a solution that addresses the pain points of Busy work.  By allowing salespeople to focus on making the sale, Winn.AI enables organizations to Improve performance and increase the quota,” said Hagi Schwartz, Managing Director at Insight Partners.

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.”

Winn.AI is currently in beta with plans to formally launch in early 2023.  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.

Winn.AI is SOC II, Type 2 compliant.

Pricing has not been disclosed.

Nektar.AI Exits Stealth Mode

Nektar.AI supports automated activity capture and CRM sync across the full customer lifecycle.

After two years in stealth mode, Revenue Operations solution provider Nektar.AI was unveiled earlier this month.  Nektar looks to solve the “CRM data leakage” problem whereby critical lead, contact, and opportunity data is omitted or decays.  For example, Nektar recognizes meeting attendees missing from the CRM and automatically creates contact records that include email, direct dial phone, title, and buying committee role.  Out-of-date or missing data negatively impacts both the sales process and operational functions such as analytics, automated recommendations, and pipeline forecasting.

Nektar offers a no-code platform that applies natural-language processing against email, calendar, chat, and social touchpoints, capturing revenue activity data across the full customer lifecycle and syncing it with the CRM.  Automated activity capture improves rep productivity, allowing sales professionals to focus on selling instead of data entry and updating.

“Sales teams depend on their CRM data to gain insights into team productivity, pipeline insights, and revenue forecasting.  Despite a CRM being an important system of record for modern go-to-market teams, it still grapples with the problem of poor user adoption and missing data.  As per estimates, 40-50% of sales activity data remains missing from a CRM, while 27% of the data that’s available in a CRM decays every month.  This leads to major data and productivity leakage,” stated the firm.

Furthermore, deals are becoming increasingly complex, with larger buying committees and sales teams communicating across an expanding array of sales channels.  While most of these conversations are now digital, they take place across disparate platforms and channels, resulting in data fragmentation.  Nektar’s mission is to collect this fragmented intelligence and feed it into the CRM, making it available to the revenue team without requiring sales resources to key this intelligence.

“There are a lot of reporting and analytics solutions out there.  Other solutions have been investing primarily in the downstream problem with respect to visibility and analytics, an important problem to solve.  But the core problem actually starts upstream, which is where activities are taking place and where data is being generated.  A lot of that data doesn’t make its way into CRM, which actually results in downstream problems.  If there’s poor data in, you will have poor insights available,” explained CEO Abhijeet Vijayvergiya to GZ Consulting.

“We found our product-market fit when we found that more than 50% of critical revenue activity data is not going into CRM,” continued Vijayvergiya.  “This data leak results in productivity leaks, and that results in revenue leaks.”

Furthermore, as firms make staffing cuts, “they’re trying to do more with less” and losing implicit knowledge that never made its way into the CRM.  Nektar allows companies to recover much of this lost activity and contact intelligence, boosting a firm’s ability to manage revenue operations during a recession.

“There are tools like Gong and Clari and some other forecasting solutions which provide good insights,” expanded Vijayvergiya on Nektar’s value proposition.  But these systems are not resolving the data leakage problem. 

Nektar claims 95% accuracy in its data capture and syncing processes.  The service can go live in ninety minutes and begins providing time to value in three days as it gathers both historical data missing from the CRM and populates it with ongoing activity capture. 

Nektar operates in the background, collecting and syncing data.  Thus, there are no training sessions or additional UIs to learn.  Sales reps do not need to toggle to other platforms, and their data entry work is significantly reduced.

“Nektar plugs the CRM data leakage without a user lifting their finger.  We basically eliminate the need for user adoption and give all the time back to salespeople to go and sell while relieving their administrative burden,” said Vijayvergiya.

While there have been third-party solutions to populate and enrich account and contact data records for over a decade (e.g., Dun & Bradstreet, ZoomInfo), these vendors were blind to the demand unit unless a sales rep entered all members.  Nektar is complementary to third-party DaaS providers, Revenue Intelligence vendors (e.g., Clari, Revenue Grid), Conversational Sales (e.g., Gong, Chorus), and business intelligence vendors (e.g., Tableau).

“We are aware that some of these solutions have their own activity capture system, but most of their activity capture solutions work in silos for certain sets of users who adopt their solution,” continued Vijayvergiya.  “Users are not adopting the solution, or data loss happens anyway.   A solution which we replace, more often than not, is Salesforce Einstein Activity Capture.”

Nektar supports email and domain exclusion lists to prevent mining confidential information (e.g., legal, investor relations, partner development).

Nektar is generally available as a native Salesforce solution, with HubSpot and Microsoft Dynamics on the roadmap.  In addition, all of its system integrations are native, providing higher quality and performance.

Nektar.AI closed a $6 million seed round last summer, raising its total funding to $8.1 million.  The round was led by B Capital Group, with Nexus Venture Partners, 3One4 Capital, and angel investors also joining.

Nektar has not disclosed pricing, but it is per user per month with SaaS-based pricing billed quarterly or annually.

Nektar is a fully remote company with 32 employees across seven countries with plans to hit fifty employees by the end of this year.  Although emerging from stealth, it already supports over 1,500 users. 

Nektar’s goal through year-end is to focus on its go-to-market strategy and North American hiring.

Nektar activity tracking at the account level

Data capture as an AI tool is becoming increasingly important. It probably isn’t a standalone offering but an underlying capability for populating the CRM with harvested digital intelligence, monitoring buyer engagement, and building out the buying committee. As such, it is core to both CRM data enrichment and revenue intelligence.

I have seen a series of data capture announcements from vendors of all sizes: big (Microsoft Viva Sales), medium (People.AI, Introhive), and small (e.g., Nektar, Winn.AI). I also covered People.AI and Winn.AI this week.

Vainu for HubSpot

Vainu for HubSpot Data Mapping rules.

Yesterday, I posted about Vainu’s new Global Database. The firm also announced its Vainu for HubSpot connector for matching and enriching company data against its global reference database.

“Most sales and marketing teams want to be data-driven.  They want to run ABM campaigns, apply modern lead scoring models, and automate many parts of the sales process.  SalesOps and Marketing Ops professionals are there to facilitate all that, but there’s one common challenge they’re facing: CRM data is messy and outdated,” observed Vainu co-founder Mikko Honkanen.  “With that struggle in mind, we thought it would be a good time to launch a new HubSpot connector at the same time that we’re launching Vainu Global…so that it’s easy for companies using HubSpot to get their CRM data cleaned, updated, and enriched.”

As companies are being matched against Vainu’s new global database, not registered Nordic filings, the match field is URLs, not business IDs or VATs.  With forms, contacts are matched against email domains.  If a company is not already in HubSpot, new Accounts are created, and the Contacts are associated with the new record.

“This means it works very well with HubSpot CRM, because domain is often the company property that a business will have for almost all of the company records they have in their CRM, which means that it’ll be easier to match the companies in HubSpot to our database,” contended Honkanen.

During beta testing, match rates were as high as 99%.  For non-matched records, the firm offers on-demand matching against missing domains.  If they are valid domains, Vainu adds profiles to its company directory.

Along with standard firmographics, account enrichment includes Vainu’s Custom Industry segments, global web traffic ranking, and Vainu segments (e.g., website keywords or phrases).  Profiles generally have four to eight industry labels, helping with targeting.

Other fields include technographics and domain redirect information.  Redirects are often implemented after acquisitions or rebrands and are useful for assigning contacts.

Vainu for HubSpot Send to CRM

Vainu offers a field mapper for assigning Vainu data to HubSpot and setting update rules.  For example, admins can set field update logic to always update, update if null, or never update.  Vainu custom fields that are not in HubSpot are automatically created.  Along with companies, admins can map contacts, tasks, notes, and deals. 

Thus, admins can build a campaign and upload it to HubSpot with task assignments.  The inclusion of tasks and notes helps specify campaign details, such as recommended collateral and case studies, with the Vainu Custom Industry and Technology Intelligence assisting with messaging.

If companies do not exist in HubSpot, Account records are created.  If they exist, then the existing records are enriched. 

By default, HubSpot does not overwrite current account owners.

Updates can be performed on a scheduled basis or executed as a one-time batch operation. 

Vainu intelligence with tasks and notes displayed in HubSpot.

Matchbook AI Funding

Matchbook AI, which offers External Data and Data Hygiene solutions to enterprise clients, has announced a $3 million seed extension.  It previously received $1.7 million in seed and friends and family funding.

Matchbook was founded in 2018 but operated as a garage project for a couple of years before being incorporated.  CEO Rushabh Mehta had the idea for the Matchbook Data Hub while an industry evangelist and initially built the solution with Dun & Bradstreet data.  The Data Hub provides a configurable, hierarchical matching service that matches and enriches records with a single API call.  Both batch and real-time matching are supported, with cascading and waterfall matching processes.  In addition, a rules engine allows customers to construct bespoke data cleansing and filtering rules specific to various business units and use cases.  The Data Hub will be powered by Snowflake.

The system can use other identifiers such as domains or emails if the account cannot be matched by name and address.  In addition, the system manages deduplication and prevents creating duplicate records when onboarding accounts. The solution can also support more complex matching scenarios to allow for verification checks and multi-attribute matching.

“I can immediately see if I already have an existing relationship with that account,” Mehta explained to GZ Consulting.  “Just because I keyed in the name incorrectly or a previous account had a different address for that same company, I should still be able to identify and say, ‘Hey, no, it’s the same company to the same account.’”

The Data Hub also manages information for enterprise clients with multiple CRMs, helping “provide that visibility across CRMs, across ERPs, or CRM and ERP.”  Thus, Matchbook can identify whether “there is already an existing relationship within the organization with that particular entity” through third-party identification.  Furthermore, matching identifies parent-sub relationships tied together by D-U-N-S numbers.

According to Mehta, customers want controlled updates to their CRM or ERP, not real-time updates.  They also want to control which fields are updated with the data hub keeping “everything mastered in one place” with the intelligence accessible to the organization.

Matchbook AI’s data partners and supported platforms

Along with Dun & Bradstreet’s data sets (e.g., companies, contacts, hierarchies, beneficial ownership, D-U-N-S identifiers, technographics, competitors, company news, and credit and supplier risk profiles), Matchbook AI provides third-party reference data from ZoomInfo, Demandbase, Moody’s, Experian, Melissa, and Google.  The service also includes sanctions and terrorist watchlist data for compliance use cases.

The Data Hub operates as a centralized external data repository for maintaining data quality and standardizing data across platforms, including Salesforce, Snowflake, SAP, Informatica, Microsoft, Oracle, Certa, and Reltio.  The Data Hub supports a broad set of processes and departments, with sales, marketing, finance, IT, logistics, compliance, legal, and supplier management use cases. It also plays a critical role in MDM use cases through integrations with Reltio and others.

Matchbook claims implementations between two days and two months, significantly faster than its competitors.  Furthermore, as a DaaS solution, it is 90% less expensive than in-house solutions.  It also claims a 75% savings on expenses related to maintaining a data stewardship team due to “improved data quality and automated management.”

VP of Sales & Marketing Wesley Billingslea described a recent dinner with a Fortune 500 CIO who described Matchbook AI as “quite strategic and pervasive because we go across departments,” whereas “most MDM projects sit in the IT organization.”  This approach “empowers” teams across the organization with superior data and a plug-and-play solution.

Matchbook focuses on enterprise clients, with 59% of its customers in the Fortune 500.  It takes a land-and-expand approach that proves itself in one department or on one platform and then extends to others.  Contracts are usually written for a single year and then converted to multi-year contracts a year later.  The strategy has resulted in a 118% net retention rate and a projected ARR increase of 220% this year.

“As we gear up our sales and marketing efforts, we are confident that we will soon achieve $3.5 million in annual recurring revenue (ARR) with Current ARR of $1.85 million,” said Mehta.  “Data should be trusted, enriched, and always ready.  I feel very confident in our approach as we take these next steps and help companies understand their data DNA in this age of intelligent business.”

Matchbook claims an impressive LTV/CAC ratio greater than 12, an important indicator of stickiness, value, and an efficient go-to-market approach.

Mehta noted that it is just entering a large market with a rapidly expanding TAM.  According to MarketsandMarkets, data cleansing and global master data management were an $11.3 billion market in 2020, growing to $27.9 billion by 2025 (19.8% CAGR).

“Our value proposition to an MDM implementation can mean the difference between success and failure,” said Mehta.

Pricing is based on a records-under-management model, providing a predictable budget line to companies.  Implementations range from 50,000 to 100 million records. Matchbook has grown to 51 employees in the Americas and Asia.  The bulk of its R&D is conducted in Asia.

Lusha Salesforce Data Exchange

Lusha Enrichment Editor

Contacts database Lusha announced the general availability of its Salesforce Data Enrichment (SFDE) service.  The new service provides on-demand, periodic, or continuous data enrichment, ensuring that company and contact data remain accurate. 

An Enrichment Editor helps operations managers understand how many records need enrichment and the number of leads, contacts, and accounts recently added to Salesforce and available for enrichment.  The Salesforce admin can run an initial enrichment against the full database or target a subset of records for enrichment, with the Enrichment Editor supporting custom audiences for updates based upon multiple Salesforce field criteria.

The Salesforce admin performs the initial field mapping during the integration setup.  Custom fields are supported, and the admin can choose whether to override existing values during enrichment.  Lusha recommends that admins create special fields, such as Lusha Email, to avoid overwriting current field values.

SFDE is an Enterprise add-on and is subject to an access fee.  Analyst Relations Manager Alina Sharon-Green warned GZ Consulting that “extensive usage may require the purchase of additional data credits.”  As a launch promotion, enterprise customers will receive SFDE for free through the end of the year.

Lusha already supports Send to Salesforce functionality but does not provide I-frame support or “stare and compare” updates within AppExchange records.

“Companies spend huge amounts of resources building CRMs of both current and prospective leads but suffer from the speed the data becomes outdated and irrelevant,” said CEO Yoni Tserruya. “B2B sales organizations rely on their CRM to identify the right prospects – so when this data is incomplete or inaccurate, their time is wasted, and opportunities are lost.  With our new SFDE solution, sales teams are given direct access to Lusha’s extensive database of accurate contact and company information to automatically enrich their existing data and gain new insights on their prospects to scale business results.”

Lusha has grown its database to 100 global million contacts, which includes 60 million emails and 50 million direct-dial phones.  All contact records are processed through a seven-step verification process.  Lusha also profiles 15 million global companies. Lusha continued its rapid pace of growth, doubling its paid user base in H1, “with significant growth in Enterprise users,” stated Sharon-Green.

D&B Connect for Salesforce

Dun & Bradstreet announced its spring releases and enhancements at Forrester’s B2B Data conference in Austin.  Dun & Bradstreet launched D&B Connect for Salesforce, its new data management service, and expanded D&B Rev.Up ABX functionality.

“With more accurate, actionable CRM data, businesses can make more confident decisions, identify more cross-sell and upsell opportunities, and target with greater precision,” blogged North American Sales & Marketing GM Stacy Greiner.  “That’s the foundation for strong account-based strategies and digitalization.  It’s the foundation for a stronger business, period.”

D&B Connect for Salesforce is the next generation of Salesforce hygiene products, superseding D&B Optimizer for Salesforce.  Users have broader control over matching logic.  They can employ easy matching based on Dun & Bradstreet Confidence Codes or customize the match logic by leveraging Confidence Codes alongside country/region selects and match quality. 

The operations manager can set the importance of individual match grades by field (e.g., street number, name, etc.).  Admins can also set match inclusion criteria, defining which fields should be excluded from matching (e.g., Non-Headquarter locations, Out-of-Business locations, Non-Marketable locations, or Undeliverable/Unreachable locations).

Connect for Salesforce has dramatically expanded the data sets available for enrichment, providing access to over 1,600 data elements based upon subscribed data blocks. Admins also have control over refresh frequency and rematch rules.  Data may be refreshed every 14 days with the option of rematching unmatched records.  Transactional matching is also supported, allowing real-time match and append for newly created records.

D&B Connect match logic administration

Other features include data health reports, field-level mapping, out-of-business flags, and duplicate management.  In addition, Dun & Bradstreet offers 37 million subsidiary and branch linkages, ensuring proper territory management and lead assignment.

“What is preventing our marketing campaigns and sales plays from firing on all cylinders? asked Dun & Bradstreet Greiner.  “Quite simply, bad data that is outdated, incorrect, duplicate, improperly formatted, or just outright missing.  Let’s face it — we’re all to blame.  We’re just not good about keeping our data up to date and refreshed.  We don’t even do a good job entering the right data in the first place.  This may be due in part to subjectivity, in part to laziness, and in part because there’s just not enough time in our day to be thorough enough.”

D&B Connect for Salesforce starts at $5,000 per company per year.