Tag: Personas

6sense Revenue AI for Sales

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.

6sense employment growth (Source: LinkedIn)

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.

SalesLoft Acquires Professional Services Partner InStereo

Sales Engagement vendor SalesLoft announced that it acquired professional services partner InStereo.  InStereo, founded in 2018 by Bill Galfano and Adam Post, was an early ecosystem partner that has grown alongside SalesLoft.  Last year, SalesLoft named them their “Partner of the Year.”

“We were impressed by their focus on what the customer is trying to achieve,” SalesLoft President and Chief Strategy Officer Rob Forman told GZ Consulting.

As a partner, InStereo helped “B2B Sales and Marketing teams better engage with buyers to create more demand, authentically engage prospects, and convert prospects into delighted customers.”

“Bringing InStereo directly into the SalesLoft family is a key way we are investing in our customers’ success.  Our customers will benefit from InStereo’s deep understanding of buyer journeys and engagement strategies.  Their experience and proven enterprise methodologies will help customers operationalize the SalesLoft platform and accelerate the value of Sales Engagement across their entire revenue organization.”

SalesLoft CEO Kyle Porter

InStereo focuses on go-to-market and implementation strategy for SalesLoft, HubSpot, and Salesforce delivered through a pair of consulting services:

  • Buyer Experience Strategy focuses on the buyer’s journey, ICP, demand unit persona, and the “buyer engagement blueprint.”

    “We believe customer journey maps are more than just wall art,” states InStereo.  “We create buyer journeys you can activate.  By understanding how buyers approach the purchase process, sales and marketing teams can better align people, process, and content to deliver just what buyers need, when they need it.”
  • Buyer Engagement Services pairs clients with a Strategist and Revenue Consultant to assist with enterprise software implementations.  For SalesLoft, they focus on “1:1, personalized engagement via cadences” and process automation.  For marketing automation, InStereo assists with nurture campaigns and optimization, and for CRM, they focus on leveraging CRM capabilities and improving data quality.  Other services include SalesLoft Admin as a Service and sales development services.

“At SalesLoft, our goal isn’t to just sell software; it’s to help our customers exceed their revenue goals,” said SalesLoft CRO Steve Goldberg.  “Too many times software companies focus on features and technology, not the success of their customers.  InStereo shares our passion for helping our customers get the outcomes they’re looking for.”

InStereo’s customers skew towards enterprise implementations.  SalesLoft “plans to take their methodologies into new areas of our business,” expanding InStereo beyond the technology vertical into financial services, SalesLoft’s second-largest vertical.

InStereo has completed over 150 customer engagements.  Joint customers include Cargill, Pegasystems, and 3M.

“This past year we tripled our investment into our alliance organization and programs because empowering our partners leads to success for our customers,” said Forman.   “InStereo leveraged the power of our partnership and consistently drove incredible outcomes for our mutual customers.”

All twenty InStereo employees will be joining SalesLoft, including their two founders and Carrie McGrew, InStereo’s VP of Strategy.  In addition, Galfano will be joining the CRO Leadership Team as the SVP of Consulting Services.

SalesLoft did not provide any pricing deals on the acquisition.

RevenueBase Launched

RevenueBase, which describes itself as a Revenue Database as a Service (RDaaS), formally launched on Tuesday as a “one-stop data solution” that recognizes data as a “strategic asset for a business.” 

According to 2016 research by SiriusDecisions, marketing databases are riddled with critical errors with bad data ranging from ten to twenty-five percent of records.  SiriusDecisions noted that the firms with higher data quality have shifted from periodic data cleansing projects with discrete completion dates to data maintenance processes with “ongoing policies and procedures to maintain data quality.”

RevenueBase was founded by industry veteran Mark Feldman, the VP of Marketing at NetProspex prior to its acquisition by Dun & Bradstreet.  As a marketing head at Backupify, Motion Recruitment, and Localytics, Feldman became frustrated with B2B data issues, including misalignment with the sales and marketing team’s go-to-market strategy, data decay, difficulty acquiring data, and managing disparate vendors and formats.  His stint as a B2B data customer led him to return to the B2B data space and create an RDaaS company that broadly aggregates company, contact, and technographic data that aligns 1:1 with customers’ go-to-market strategies.  It then builds a custom database for clients that it calls a Revenue Database, which is updated on an ongoing basis.

“When I was hired to run growth operations at Localytics, a web and mobile app analytics company, my first directive from the CEO was to put together a list of target accounts to assign to our new enterprise account executives. It was my first week and my reputation was on the line. I started by going to our data vendor and asking them to help me build a list of all of the companies in the world that were focused on mobile monetization strategies across millions of monthly active users. Seems like a slam dunk, right? Nope.

My list for Localytics was full of bad data. There was no way to confirm the companies listed had the mobile monetization opportunities that our software could solve, or that mobile monetization opportunities would be high up on their list of priorities. I quickly realized that, in the B2B world, not all data is created equal. Right then and there, I saw an opportunity to change the B2B data game by solving the major growth impediment challenges facing revenue leaders—acquiring, integrating and maintaining the quality of their data—by building the world’s first Revenue Database as a Service.”

RevenueBase CEO Mark Feldman

“Like so many B2B marketers, I was frustrated with the inadequacies of traditional list providers,” wrote Feldman.  “I saw an opportunity to revolutionize the B2B data game and solve the greatest challenges facing revenue leaders today. Our all-in-one Revenue Database as a Service solution provides next-level data quality, expediency, and accuracy.  We transform your data stack from a constant struggle into your greatest asset.”

RevenueBase takes a white-glove approach to serve its customers.  Revenue Archetypes are defined during customer workshops and consist of an ICP, market segmentation, pains addressed, buyer personas, sales showstoppers, and “jobs to be done.”  The Jobs-to-be-Done descriptor is a bit misleading as it is account, not persona-based.  Jobs-to-be-Done describes the core functional “job” that an organization is trying to accomplish.

Personas cover function, level, titles, buying unit members, demographics, behavior patterns, motivations, and goals.

RevenueBase then builds a revenue database for its clients and supplements it with custom data collected by its overseas team of fifty editorial researchers.

“A revenue archetype is a model of what your ideal customer looks like, i.e., one you can derive revenue from,” said Feldman.  “It’s where there is a mutual benefit.  They need your product/service and will pay a fair price for it.  They also will favor you over the competition because your solution will result in the best cost-benefit tradeoff for the customer.“

Conversely, the Revenue Archetype also defines companies that are not good fits (e.g., industries or geographies that require a standard not met by a firm’s offerings, such as HIPAA or GDPR).  It also identifies roles not involved in purchasing a company’s products or services.  These individuals may be too junior in the organization or not work in functions that use a company’s products or services.

Coverage continues with a discussion of RevenueBase’s ICP modeling and database.

Quora: Once your ideal client profile is established, how do you find the company’s decision maker and how to reach out to that person?

Your ideal customer profile (ICP) defines who are your best customers and prospects. It is defined by firmographics, intent data, technographics, business signals, etc. ICPs are focused on Accounts.

Your question implies that the firm has a single decision maker. But that is generally only the case at small firms. Generally, B2B mid-sized and larger procurement decisions are made by a buying team which can consist of multiple individuals at different levels and functions / departments. For these, you should define a set of personas that cover economic decision makers, users, influencers, reviewers (e.g. technology gatekeepers).

Many of the ICP vendors support contact searching for ABM accounts. Once the ABM list is defined, they allow users to prospect for contacts by persona (job function/level/title) at ABM accounts.

I discussed this process broadly on DealSignal’s blog and on my blog.

Products which support both ICP definition and persona searching against ABM lists include (alphabetical list):

  1. Cognism
  2. D&B Datavision
  3. DealSignal Total Audience Platform
  4. DiscoverOrg AccountView
  5. InsideView Apex
  6. SparkLane Predict (UK and France)
  7. Zoominfo Growth Acceleration Platform

These vendors include emails and direct dials for contacts along with company profiles, sales triggers, financials, technographics, family trees, filings, etc.

While LinkedIn Sales Navigator does not offer an ICP tool, it includes a Buyer’s Circle which allow sales reps to quickly identify potential contacts at accounts and drag and drop them into their role. They can then review all open opportunities, including buying committees, via a single-pane Deal report which combines LinkedIn intelligence with Salesforce or MS Dynamics.

Sales Navigator Buyer's Circle supports dragging executives to their function within the buying committee.
Sales Navigator Buyer’s Circle supports dragging executives to their function within the buying committee.

DealSignal Total Audience Platform

DealSignal, which offers an on-demand platform for Total Audience and Contact Data Management for B2B marketing and sales, recently rolled out its Total Audience Metrics (TAM) module.  The new platform helps sales and marketing professionals improve Go-to-Market and Demand Planning processes by allowing them to measure and visualize their total audience and determine coverage gaps in their CRM and MAP.  The new platform analyzes TAM by persona, account segment, and buying committees (what SiriusDecisions calls Demand Units).

“We’ve run hundreds of TAM analyses for B2B marketing teams in various industries and customers are consistently surprised to find that they’re missing more than 80 percent of their target audience—the contacts that fit their target personas and ideal customer profile. TAM coverage is currently averaging 18 percent in existing CRM and MAP systems. It’s a big ‘aha moment’ to learn that you’re missing out on marketing or selling to a large majority of your potential buyers. Often, the best potential buyers – those most likely to convert – are among the missing contacts found in the gap analysis,”

  • DealSignal CEO Rob Weedn

The firm is seeing rapid uptake on its TAM service which is available as either a freemium (TAM Estimates) or paid option (TAM Actuals).  “Early feedback is that this is a great way to verify the counts and size up the Outbound and/or ABM marketing programs over the upcoming year,” said Weedn.

According to DealSignal, TAM Estimates are accurate to ± 20% of Accounts and Contacts.  “We’ve been offering this for a few months and it is very popular” with customers and prospects “leveraging this analysis for initial demand planning and budgeting,” said Weedn.  “TAM Actuals is a Paid Offering, charged based on credits on our platform, which provides perfectly accurate Total Audience metrics based on Accounts and Contacts.”

The DealSignal platform dynamically discovers, refreshes, and verifies records based on the TAM criteria.

DealSignal has adopted the term TAM, but calls it Total Audience Metrics instead of Total Addressable Market.  Weedn explained the difference between the DealSignal and Classic TAM approach:

Total Addressable market is classic and static top down analysis, based on sample/partial market data, typically performed by market research and analyst firms like IDC, Gartner, etc.  “Classic TAM” is not necessarily an accurate sizing of the market, it is not frequently updated, and, most importantly, there is no real way for marketing and sales teams to plan marketing and sales programs with a classic and static top-down TAM, and definitely no way to execute against the Accounts and Contacts in that TAM.

DealSignal, is here to help marketers market and sellers sell, so we perform an accurate, bottoms-up, dynamic analysis, based on complete market data, of the actual counts of the Total Audience – which we define as the Accounts that meet Target Market criteria (Industry, Employee, Revenue, Technologies Used, etc.) and Contacts that meet Ideal Buyer Persona criteria.  Further, our Total Audience Metrics/Measurements include a process to dynamically discover and verify the underlying Accounts and Contacts, so TAM Analysis is dynamic, based on actuals, and can be updated on demand.  The Accounts and Contacts can then be converted, with one click, to fully enriched and verified with full Account/Contact Profiles and Contact Information to be used in marketing and selling initiatives.

Using the DealSignal platform, users can define target personas and Ideal Customer Profiles (ICPs) to build out their TAMs, using micro-targeting criteria such as Titles, Profile Keywords, and Locations that yield results as ranked lists of relevant accounts and contacts. The module compares the TAM against the CRM and identifies gaps by account, industry, geography, etc.  DealSignal provides the TAM based not only on CRM data and large third-party sources, but through dynamic sourcing and verification, so the TAM results are “comprehensive and accurate” with net-new accounts and contacts.

DealSignal combines APIs, algorithms, and human intelligence to achieve a much higher level of contact accuracy (95 – 100% according to the firm) than most vendors.  The company provides a 100% guarantee on all Account and Contact data.  The system enriches and verifies existing leads, contacts and accounts.  As it conducts dynamic data sourcing, DealSignal claims account enrichment match rates between 95 and 100% and lead enrichment match rates between 85 and 100%.

DealSignal TAM Analysis Module
DealSignal TAM Analysis Module

DealSignal dynamically discovers, enriches and verifies account and contact lists through a combination of AI robots and researchers combined with CRM and MAP feedback loops.  The firm claims a deliverability rate between 94 and 97% and reverifies data on demand for every customer request, with a two week window for contact aging.  Records that fall outside of the two-week window are reverified overnight.

“Since static data-at-rest quickly becomes dated, we do not trust it, you should not trust it, and you should certainly not rely on it to define or optimize your vital marketing or sales programs. It must be renewed and refined at runtime,” said Weedn.  “We believe in dynamically refreshing and re-verifying data on-demand, when it needs to become active and put into a marketing or sales process—and we’ve uniquely designed the DealSignal platform to do just that.”

DealSignal has automated and editorial processes that place its data quality at a level claimed only by DiscoverOrg.  Both firms utilize editorial teams for staying ahead of the 25 to 30% contact decay rate suffered by static databases.  DiscoverOrg performs a full data verification every 90 days while DealSignal performs a just-in-time data quality review overnight.

“Marketers and sales teams currently rely on solutions that provide 50 to 80% quality.  That is a B- or F on a test, and we need to change the expectation to impeccable quality, at 95-100% (A or A+) to greatly improve marketing and sales performance,” said Weedn.

Last month, DealSignal released a GDPR risk assessment module which enriches CRM data with contact locations and flags EU-based leads.  Users can also choose to exclude EU-based leads.

“B2B marketers are faced with many challenges today: identify and engage their total audience, try to keep their audience data fresh and accurate, and comply with new regulations like GDPR. Given the negative consequences associated with GDPR, most marketers are scrambling to review and re-verify the location and status of their contacts,” said Weedn.

Leads are pre-purchased on a volume basis with 1,000 credits running $895.  Volume discounts kick in at 5, 10, 25, 50 and 100 thousand credits.

It is Time to Revisit Buyer Personas

Buyer Persona tools are a growing area of focus for sales and marketing teams.  Pragmatic Marketing and other B2B product marketing firms have long promoted the value of personas for product planning and marketing messaging.  They help identify customer needs and features as well as associated positioning.  According to B2B Marketing Strategist Ardath Albee, they help “build relationships based on expertise and authority that helps buyers see your company as a mentor and the best choice to solve their problem or capitalize on an opportunity.”

“Buyer personas are important because they allow us to focus our sales and marketing efforts on people who need our solutions to do their job better, to help their businesses grow, to help their businesses essentially reduce cost, to help the increase efficiencies, to help them realize the goals they are setting out to achieve.  In order for us to do that, we need to understand that buyer intimately,” said Ned Leutz of Zoominfo.  “By doing our homework fully we can better understand these people and then, of course, increase our success rate when we are reaching out to them.”

The problem with personas is that they have historically been high-level tools that quickly fall into caricature and disuse because they are not rigorously defined and maintained.  “Many customer intelligence efforts today are ad hoc, uninformed, and manual projects that are full of assumptions and rarely kept up to date,” says persona vendor Cintell.  “Even if you’ve hired a consultant to develop buyer personas, insights are often trapped in static PDF documents abandoned at the back of a desk drawer leaving critical customer intelligence underutilized.”

Unfortunately, there were few tools available for identifying and researching personas.  Instead B2B marketers focused on building segments that approximated their personas for marketing campaigns while product managers posted persona profiles in meeting rooms during road mapping and feature definition exercises but failed to use these tools beyond the early product definition stage.

Recently, three vendors have begun to address the B2B persona problem.  Zoominfo focuses on  amongst a company’s best customers.  These personas capture enough information about the attributes of their best customers to help identify similar prospects at other companies.  Such a tool operates as a next generation customer cloning tool as it looks at both firmographic and functional information around leads.  The tool can also be used to evaluate attendees at conferences or webinars to help tailor discussions.

ZoomInfo Personas provide a multi-dimensional cluster analysis for identifying persona categories and prospecting against them.
ZoomInfo Personas provide a multi-dimensional cluster analysis for identifying persona categories and prospecting against them.

Avention also recently rolled out its OneSource DataVision platform for enrichment, segmentation analysis, and Look-alike prospecting.

Leutz recommends that the firm ask questions such as

  • Who are your top performing customers?
  • Who are your best leads?
  • What were your biggest deals?
  • Which customers close faster?

This information that can be gathered from the CRM, marketing automation platform, webinar attendees, and trade show lists.  It can also be gathered from your sales reps, the CFO, and customer conversations.

While Zoominfo can assist with answering Who, they fail to provide insights into What or Why.  In short, Zoominfo’s personas are basically the next generation of peer listings;  they are a starting point for the persona process, but they do not assist with identifying persona needs; determining whether the cluster contains economic buyers, influencers, or users; or specifying what kind of content would be of interest to them.  They also do not assist product management in determining product roadmaps and future capabilities.

There are also several vendors that recently launched tools for defining and maintaining buyer and user personas.  Cintell and Akoonu offer marketers tools for defining personas in a centralized platform that collects survey data and research alongside the profiles.  Both of these services were launched about a year ago so will be evolving quickly.  The two services are cloud based hubs for collecting persona information and sharing it with both platforms (e.g. Marketing Automation and CRM) and employees.  They are ongoing intelligence gathering services for continuously refining and updating personas and then disseminating this intelligence to marketing, sales, and product management.

Cintell Personas cover professional insights, social insights, content trends (intent data), and personality data.
Cintell personas cover professional insights, social insights, content trends (intent data), and personality data.

They also promise to immediately map leads to personas, helping inform messaging, campaigns, and targeting within the marketing automation platform and segmentation and analytics in the CRM.  When tied to a well-researched persona, sales reps would have a better understanding of the prospect’s role, needs, and informational requirements.  Personas provide sales reps with a summary of buying habits, preferences, and motivations along with market research reports, customer interviews and surveys, and persona specific articles.  As living documents shared across the organization, they would also assist product management in identifying latent needs and customer pain points and marketing communications in tailoring content for the persona.

“Our new empowered B2B consumer seeks relevancy and empathy,” said Cintell Co-Founder Katie Martell.  “And marketers know this: In a recent ITSMA study, technology marketers  predicted that understanding buyers will soon become their #1 responsibility.  But getting to this insight is not easy. Efforts to research and leverage personas today are highly manual, shallow, very static, and fragmented throughout the business. The opportunity here is to empower B2B organizations with a platform to gather primary research, enhance it with external market and buyer insights, and combine it with data from internal business systems. The new competitive advantage for companies is a richer understanding of buyers through meaningful, ongoing customer intelligence.”

I don’t see these persona definition platforms as long-term standalone offerings as their functionality is a tight fit for marketing automation.  They will likely be folded into marketing automation platforms once the technology has matured.  It is also possible that predictive analytics companies fold these tools into their products as persona assignments would inform lead scoring and messaging.  Furthermore, several of the predictive firms aspire to becoming recommendation engines, a feature that persona platforms could easily support.  Conversely, business signals would be valuable in building out a fuller understanding of personas.