Intent Data — Why and When?

One of the important recent B2B MarTech innovations is the development of intent data from vendors like Bombora.  As prospects are now using the Internet to self-educate, they are reaching out to a smaller set of pre-screened vendors later in the sales cycle.  But if firms are being stealthy to avoid detection during this initial phase, B2B firms have been looking to uncloak this veil of secrecy and reach out to firms during the initial phase.

One response to anonymity was content marketing which looks to deliver information (and perhaps uncover prospects) during this early phase.  But it is difficult to customize messaging to anonymous individuals.  Thus sprung up visitor id services such as Demandbase that map IP addresses to company firmographics in real-time.  For example, a visitor from a P&C insurance IP address would be shown a website and content that speaks to their industry specific needs.

Firms also engaged in SEO and SEM to drive traffic to vertical content.  While these activities were an improvement, they provided no indication concerning whether the prospect was in the market for a firm’s solutions.

Intent Data Publisher Network and Tracked Activities (Source: Bombora)
Intent Data Publisher Network and Tracked Activities (Source: Bombora)

Firms like Bombora work with B2B media sites to map site traffic and actions (e.g. downloading white papers, webinar attendance, site searches), to specific companies.  Thus, each IP address has a baseline activity trail which indicates topics of interest.  Intent firms then match B2B media site visitor actions to an intent taxonomy covering thousands of topics.  Of course, larger firms will leave more distinct trails and firms will display heavy footprints around their own industry and target segments.  These patterns are company-specific background noise.  To find the intent signals, intent vendor analytics determine which topics are surging at each company.  For example, If GE has X searches per week on cloud computing, then this activity rate is general background noise.  But if activity spikes to 2X, then there is likely to be some initiative underway at the firm concerning cloud computing.  It is these surges that identify firms to be targeted.  Intent data provides a mechanism for placing calculated bets on which accounts and prospects deserve additional resources.

Keep in mind, this activity remains anonymous.  A cloud computing vendor does not know who at GE is involved in cloud computing initiatives, but they know it is the appropriate time to target GE with stepped up marketing (SEM, email, sales calls, etc.).

Thus, intent data is integrated into predictive marketing platforms such as Lattice Engines, LeadSpace, Mintigo, Everstring, and Radius.

Just this month, Everstring added Bombora’s intent data to their Audience platform.  Surge data is also available for programmatic targeting on platforms such as BlueKai (Oracle), Krux, and Lotame.  Thus, it is possible to target advertising for firms that have shown a surge of interest in a topic.

Like any technology, intent data has its limits.  While it helps identify when to call into an account and topics of interest, it doesn’t identify whom to call and whether there is an actual initiative related to the topic.  Furthermore, intent data does not indicate whether a firm is a good fit (e.g. size, industry, technographics) or how far along they are in the discovery process.

In a blog earlier this month titled “Intent Data is Great. Except When it Isn’t,” Gartner Research Vice President Todd Berkowitz listed the following limitations concerning intent data:

There are a large number of scenarios where intent data and models don’t add nearly as much value (if any).  It’s not because the intent data is inaccurate. It’s because there is simply not enough data available to use directly or to put in models. They include:

  • New and emerging technology categories

  • Certain geographies, industries or other niches

  • Non-technology products

  • Solutions (especially services) that can’t be easily categorized

Thus, intent data works best for well-established technology segments (versus emerging ones).  Just make sure to also look at fitness indicators when building surge-based campaigns.

Addendum

Within 15 minutes of posting this blog, I saw that Bombora was named a 2017 Cool Vendor by Gartner.

“We believe it’s a true milestone to be recognized by Gartner as a Cool Vendor in SaaS for 2017,” said Erik Matlick, founder and CEO of Bombora. “Our customers choose Bombora so that they may access the largest source of B2B intent data for use in their account-based marketing strategies. For us, being a ‘Cool Vendor’ serves as a validation of our ‘everybody wins’ approach to the ecosystem and the impact that our dynamic, quality intent data is having across B2B sales and marketing.”

 

 

 

FullContact Cloud-based Enrichment

Contact data vendor FullContact offers a cloud-based contact enrichment service via a single user app, team app, and API.  Contact data includes publicly available contact intelligence such as social networks, headshots, and affinities.  FullContact suppresses personal identifiers such as mobile phones, personal email, and home addresses.  For individuals, FullContact supports a unified contact view across Gmail, Outlook, mobile, and LinkedIn contact networks.  For teams, FullContact offers a shared master address database.

FullContact employs a FullContact ID to tie together global business and consumer identifiers.  Individual profiles include 4,500 affinity/lifestyle tags along with social medial links spanning 120 sites including LinkedIn, Twitter, and Facebook.

FullContact Enrichment may be performed via batch processing or API.
FullContact Enrichment may be performed via batch processing or API.

The team service, priced at $9.99 per user per month (when billed annually), provides team members with a master address book.  Team features include business card scanning, contact unification, public information contact updates, and the sharing of tags and notes across the team.

Individual users have access to a free single user Basic edition limited to 1,000 contacts.  A middle tier Premium Edition synchs contacts for up to five users and 25,000 contacts.  Premium is priced at $8.33 per user per month.

“When it comes to managing contacts, businesses, even more than individuals, face huge challenges today. When contact and relationship data is fragmented across many employees and tools, a business isn’t able to harness the power of their extended relationship network,” said VP of Product Matt Holden. “FullContact for Teams alleviates this headache by getting all team contacts in one place, so people can focus on getting their job done, not fighting their address books.”

FullContact offers both People and Company APIs.  The Person API returns social profiles, profile photos, basic demographics, and social influence.  The Company API call takes company names or domains and returns the Key People (CxO and VP) along with firmographics.  While titles are available, the firm does not support a job function and job level taxonomy.

Developers have access to 250 matches per month during the API testing window.  A Starter package provides 2,500 people and 2,500 company matches for $99 per month with a four cent charge per overage.  The Plus edition supports 15,000 people and 15,000 company matches for $299 per month with a two cent charge for overages.  Pricing is based upon successful matches, not total queries.  Both plans are throttled (300 per minute for Starter and 400 per minute for Plus).  Beyond that, the firm offers custom match quotas and rates along with a batch processing option.

FullContact maintains a Human Research team to assist with projects such as B2B Prospecting, large database match and enrich, influencer marketing, and B2C luxury marketing.

FullContact is US – EU Privacy Shield compliant.

Unique Company Identifiers

Amazon Family Tree (Source: D&B Hoovers)
Amazon Family Tree (Source: D&B Hoovers)

Associating company records with a common identifier is critical for Account Based Marketing as well as other sales and marketing methodologies.  Lacking a common identifier makes it difficult to

  • De-duplicate company records
  • Associate subsidiaries and branches with headquarters
  • Perform both real-time and batch data enrichment of firmographic, technographic, and social links.
  • Associate company news and sales triggers to key accounts.
  • Tie together company records across multiple platforms.
  • Assess the risk (e.g. credit, supplier, reputational) associated with a business.

The importance of a “unique identifier” was discussed by Owler CEO Jim Fowler in the Harvard Business Review:

The best way to keep data clean is to use a globally known, unique identifier, or a “data backbone.” My company prefers to use URLs as identifiers. They’re free, globally recognizable, high-quality data points that enable you to efficiently gather information on a business’s industry, online activities, and functionality. For example, Cisco is a company that also goes by Cisco Systems, Inc. and Cisco Precision Tools. If sales containers required users to type in one unique URL, http://www.cisco.com/ for all those different branches, it’d be much more difficult to create duplicate accounts, which helps keep data clean. Perhaps more important, URLs facilitate communication between people, systems, and even departments. Whether it’s the customer relationship management platforms used by sales teams, enterprise resource planning software used by purchasing teams, or the account-based marketing technology employed by marketing teams, the business intelligence platform can recognize a unique URL and attach it to clean, usable data. Unique identifiers let you know you’re pulling from the sources and contacts you’ve intended to track.

I agree with 90% of what Fowler states, but disagree with his recommendation that URLs are the best unique identifier for his “data backbone”.  There are a number of reasons that URLs fall short:

  • URLs are not persistent.  If a company is acquired or renames itself, the old identifier (URL) is not retained.  This creates a potential disconnect between the old and new name.
  • URLs have a many-to-one mapping which treats most subsidiary and branch locations the same as the headquarters.  For some companies, mashing together all locations into a single record may be sufficient, but it is a highly flawed approach as it loses much of the nuance concerning companies that operate across multiple sectors and countries (e.g. General Electric).  It also makes it very difficult for sales reps to sell deeper into an organization which lacks linkage data.
  • Conversely, companies with multiple URLs are not tied together.  This could happen due to differing country identifiers (e.g. .UK, .FR), division names, brand names, and subsidiaries.  Each of these scenarios treats companies as a separate business.  Amazon has many distinct businesses including Amazon Web Services (aws.amazon.com), Zappos (www.zappos.com), Alexa Internet (www.alexa.com) Audible (www.audible.com), Internet Movie Database (www.imdb.com), and soon Whole Foods (www.wholefoods.com).  URLs do not provide a consistent data backbone when subsidiaries, acquisitions, and branches have different domains.
  • When a division or facility is divested, there is no way to determine which locations have been spun off.
  • Franchises are treated as part of the parent company when they are separate legal entities.
  • Not all companies have websites.
  • URLs can be sold.  They can also be reused if a company goes out of business or abandons a URL.

Finally, business decisions related to logistics, credit, supplier risk, and financing need to understand the underlying structure of companies.  It is not just marketing and sales that are impacted by standardizing on a non-persistent, quasi-unique identifier.

I would therefore recommend looking at credit data companies as a better source of unique identifiers.  Companies such as Dun & Bradstreet, Experian, Equifax, and Infogroup all offer location level detail and linkage associated with unique identifiers that have been developed over multiple decades.  They offer sophisticated entity matching and enrichment tools such as Dun & Bradstreet’s Optimizer service. Furthermore, these firms support multiple functions across the organization helping assist with cross-platform entity linking and on-demand decisioning.

DataFox Growth and Enhancements

DataFox grew its year-over-year annual recurring revenue by 150% and trebled its presence at Fortune 500 companies.  According to the firm, “Its exceptional growth has sparked a major hiring initiative as well as plans to secure a larger San Francisco headquarters office to accommodate a growing team of engineers and data scientists.”

The DataFox CRM Orchestration service  provides company profiles and insights for two million companies.  The firm collects 100,000 signals each week across seventy signal categories.  DataFox supports both an initial batch enrichment and ongoing data refreshes.

DataFox Signals
DataFox Signals

A unique feature is their coverage of conferences which helps marketing departments identify which conferences to attend and assemble conference based prospecting lists.  The service also captures major lists such as the Inc 5000 and Fast 500 along with niche lists.

“This is an incredible acceleration point. Customers are seeing the immediate benefits of investing in our solutions that automate grunt work and help guide better, faster decision-making,” said DataFox CEO Bastiaan Janmaat. “DataFox has been able to improve the way people approach their jobs in sales, marketing, and other growth functions by helping them find, orchestrate, and leverage CRM data so they can focus on what matters most – building relationships and growing their business.”

Along with Salesforce, DataFox provides integrations with Marketo, Google Chrome, and Slack.

D&B Optimizer: Global Contact Cleanse; Global Company Targeting

Custom Optimizer settings include match confidence, bad and dangerous email flagging, and technology enrichment.
Dun & BradstreetCustom Optimizer settings include match confidence, bad and dangerous email flagging, and technology enrichment.

This month, Dun & Bradstreet rolled out a pair of enhancements to their Workbench Data Optimizer product line.  The first release, which is already available, adds global contact cleanse and enrich functionality to the Optimizer module.  Additional features include URL matching, expanded attributes, and custom match settings.  The second release, with a planned release date of June 16th, provides global company targeting and an enhanced interface.

Our customers were asking for us to manage more of their data and for access to more of our data.  So, we really went for it with this release.  For one, we can now append up to 190 different data attributes.  We can also process contact records outside of the US.  We included 8x as many web domains to match to.  We added data stewardship rules to pass control to the customer.  Finally, we modernized the user experience.  If you combine all of this with the work we did to enhance our email verification process in March, it adds up to a complete solution for optimizing marketing data.

  • Director of Product Management John Zilch

Dun & Bradstreet acquired NetProspex and its Contact Optimizer product in January 2015 and has continued to invest in the offering.  The original product was already quite useful as it supported contact validation (email, phone, address), technographic enrichment (HG Data product vendor data), a freemium Data Health report, and segmentation analysis.  Post-acquisition, Dun & Bradstreet integrated WorldBase firmographics, linkage, and D-U-N-S Numbers into the product and implemented DUNSMatch logic for match and enrich.  More recently, they enhanced their Marketo and Eloqua connectors and added a Profiler module which supports advanced segmentation analysis and net-new account and contact prospecting based upon current accounts.  The most recent release continues the product evolution.

Data Insights Analysis (New UX)
Data Insights Analysis (New UX)

The Optimizer module first matches using company name, address, and phone.  If it is unable to match to specific locations, URL matching is performed as a secondary match process.  The firm has 8.3 million mapped domains.  Domain matching associates contacts and companies with D-U-N-S Numbers and associated firmographics.  However, domain matching is less accurate as it is likely to map to the ultimate parent or a major subsidiary (if the subsidiary has a separate domain).  Thus, domain matching is more generalized.  It should be noted, however, that several vendors only offer domain matching so using domains as a secondary match algorithm still provides stronger matching and enrichment than these vendors.

Domain matching is also useful when address information and phone information is not provided by leads.

Dun & Bradstreet extended the number of fields available for matching to over 170 from their SDMR “Strategic Layout.”  As the firm offers custom layouts, admins can choose which fields to map between Optimizer and their company and contact data sets.

Custom Optimizer settings include match confidence, bad and dangerous email flagging, and technology enrichment.
Custom Optimizer settings include match confidence, bad and dangerous email flagging, and technology enrichment.

Users can also employ confidence codes for matching (they recommend using match confidence levels of six or higher for the “best quality and output”) or select from turnkey file layouts.  Thus, matches based on the name (but not address) or address (but not name) are excluded.  Workbench supports native integrations with Eloqua (Oracle Cloud) and Marketo for lead matching.  Contact matching adds phone; job title, phone, and level; social handles; and firmographics.

On June 16th, the firm will begin adding net-new accounts to its Target module.  Target defaults to US companies but can also be run at the global or country level.  Coverage has been expanded to 110 million companies including 9 million UK entities.

When prospecting in Target, users are provided with four counts:

  1. Contact Records Company Type (emails)
  2. Contact Records Campaign Type (emails and phones)
  3. Company Records Firmographics
  4. Cookies and Mobile ID’s for programmatic and mobile targeting

Emails have a 90% confidence rate for deliverability.

Bureau van Dijk Document Retrieval (aRMadillo)

Orbis provides global original filings.
Orbis provides original filings from 200 countries.

Earlier this quarter, Bureau van Dijk announced that it integrated aRMadillo’s original document ordering system into their Orbis platform.  Documents are available from over 1,000 registries spanning 200 countries.

Original document research is important for compliance, legal, and anti-corruption research. Sourcing original images from official registries helps safeguard against forgeries.

Registered filings include

  • Registry extracts
  • Incorporation documents
  • Articles of association
  • Accounts
  • Annual returns
  • Directors’ appointments
  • Shareholder
  • Registered agents

“All of our documents are sourced directly from official sources – where they physically scan the original documents – so you can be sure of their provenance,”  said aRMadillo CEO Manny Cohen.

While filing is centralized in the UK (Companies House), it is split across fifty states in the US, 32 jurisdictions in Mexico, and 28 in Brazil.  “People assume that because it’s so simple here [in the UK], it must be as easy elsewhere,” said Medina. “It isn’t.”

Mattermark: Dataset Growth and Enhancements

Mattermark rolled out a set of enhancements to their product and content over the past few months.  The PE/VC funding data firm added Revenue Range and Zip Code to company profiles delivered via Mattermark Pro, Mattermark API, and their recently released AppExchange connector.   Mattermark now supports over 80 variables.

The Old Growth Score (Blue) was based upon historical growth data. The New Growth Score (Blue) is limited to the past 12 weeks.
The Old Growth Score (Blue) was based upon historical growth data. The New Growth Score (Blue) is limited to the past 12 weeks.

Mattermark also revised its Growth Score.  Previously, the firm evaluated the Growth Score over the company’s lifetime, which resulted in the ongoing display of Uber, Accenture, Amazon, and Google.  The new model employs a rolling twelve-week score which “better captures the dynamic changes over time,” said Marketing Manager Nick Frost.  “By reducing the span by which we calculate the Growth Score, our customers have a better representation of a company’s activity.”

Mattermark has been actively growing its company database, hitting four million profiles in February.  The firm continues to add missing firmographics.  For example, they added location data for 300K companies and industry tags for 700K companies.  Most profile vendors require these fields prior to publication.