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.
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.
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 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.
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.
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.
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.