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.

MarTech Landscape

Snippet from the 2017 Marketing Technology Landscape (Source: Scott Brinker, Chiefmartec.com)
Snippet from the 2017 Marketing Technology Landscape (Source: Scott Brinker, Chiefmartec.com)

Scott Brinker published the 2017 Marketing Technology Landscape, his annual exercise in shrinking thousands of logos into a super graphic.  This year, the list grew 40%, to a total of 5,381 solutions (from 4,891 unique companies).  Over the past year, 4.7% of the vendors were removed and 3.5% “changed in some fundamental way — their name, their focus, or their ownership.”

By size:

  • 6.9% have at least 1,000 employees or are public.  Brinker describes these 300+ firms as enterprises.
  • 44.2% are private businesses with either fewer than 1,000 employees or no funding data
  • 48.8% are investor-funded startups at any pre-exit stage

“So for those who assumed most of these companies are tiny, it’s worth noting that over 300 are enterprises of significant scale,” said Brinker.  “It’s also true that over 2,300 others have received some sort of investor funding — which implies scale beyond a couple of rogue developers in a garage (or, for a more modern-day cliché, two people in a coffee shop).”

The bottom group of “investor funded startups at any pre-exit stage,” which makes up nearly half the firms, is a growing phenomenon in the SaaS universe. Analyst Clement Vouillon of Point Nine Capital said that ten years ago, there were few SaaS companies that weren’t looking for VC-funding.  Growth in self-funded SaaS ventures has been fed by a growth in underlying platforms and advice.  Thus, “building and distributing a SaaS product is easier, faster and less expensive.”

Vouillon noted a number of additional reasons for self-funded bootstrappers:

  • Experienced founders have previously worked at VC-backed firms and are looking to avoid the model.
  • Competition prevents firms from scaling but permit the firm to operate as “a lean and profitable SaaS business.”
  • The SaaS firm is a feature that can operate on SaaS platforms (vs. being a full product).
  • The firm’s total addressable market (TAM) is not large enough to attract VC funds, but is sufficient to permit profitability.
  • The firm is local but not easily scalable.

“The majority of these companies have their sweet spot in the tens to hundreds [of] thousands dollars of MRR,” said Vouillon.  “Once reached they’ll continue to grow but more slowly and they won’t scale to millions dollars of MRR.”

The spectacular scope explosion of marketing — and the rate at which new disruptions and innovations continue to roil marketing and business at large — has made it impossible for any one vendor to deliver everything that every marketer needs in a digital world.  Almost all of the major providers now acknowledge this, and they’ve shifted their strategies to embrace the ecosystem — becoming true “platforms” that make it easier for marketers to plug in a variety of more specialized and vertical solutions.

  • Scott Brinker, Editor of ChiefMartec.com

Many of the firms covered in this blog are located in the Audience/Market Data and Data Enhancement section.  This group includes predictive analytics companies, tech data vendors, DaaS hygiene, and alerting companies.

Other groupings with covered firms in this newsletter include ABM; Predictive Analytics; and Sales Automation, Enablement & Intelligence.

ReachForce Unveils 3×360 Lead Hygiene

Data Quality Automation vendor ReachForce unveiled a new technology update it calls “3×360.”  The new release provides improved visibility & control, full-spectrum intelligence, and implementation & integration flexibility.  The MarTech hygiene platform provides real-time data enrichment, cleansing, and updating for Marketo, Eloqua (Oracle), Silverpop (IBM), Hubspot, and Salesforce.  The improved technology enhances both their SmartForms web form enrichment and Continuous Data Management services.

“Marketing technology stack options continue to evolve and change, however, a single fundamental factor remains unchanged in determining the success of any marketing operation – the quality and depth of the marketing lead data that flows through it,” said ReachForce CEO Bob Riazzi. “With our 3X360 update we’ve worked hard to consider multiple aspects of the marketing technologist’s needs and are proud to introduce a full spectrum of new product capabilities that will support them and the way they leverage data through their tech stacks. And why 3X360?…well, we’re a bunch of geeks from Austin.”

A new 360° Console provides a central dashboard for tracking lead enrichment and data quality.  Analytics include

  • The health of web forms that use SmartForms and the enriched leads submitted.
  • Rich drill-down reporting for Submits by form, Abandons by form, Match Rate by Geo and Marketable Submits.
  • [A] “Service Snapshot” provides summaries of enriched leads, match rate & usage enabling timely tracking and management of service contract.
ReachForce Service Snapshot for SmartForms
ReachForce Service Snapshot for SmartForms

Future Console enhancements include “client-driven configuration management and on-demand file uploads for immediate data quality improvements and enrichment.”

While ReachForce has long provided firmographic enrichment combined with contact validation and verification, they are now supporting contact-level data enrichment.  The new matching capability enriches leads with business card details, job role and function, and a social profile.

SmartForms before and after Contact Enrichment.
SmartForms before and after Contact Enrichment.

ReachForce simplified their SmartForms integration via a “simple, one-line implementation” for one or multiple forms.  The new functionality helps marketers rollout SmartForms “via multiple unique configurations without additional implementation steps.”  Their JavaScript API also “allows developers to integrate SmartForms into dynamic lead form workflows and enables decision-making based on individual SmartForms interactions.”

DiscoverOrg Data Quality Put to the Test

DiscoverOrg contact and firmographic intelligence displayed within SFDC.
DiscoverOrg contact and firmographic intelligence displayed within Salesforce.com.

Sales Trainer Steve W. Martin recently ran an independent study of DiscoverOrg contact data quality which found that the vendor lives up to its high quality data claims and SLA.  According to Martin, “DiscoverOrg had no foreknowledge that I was measuring their data accuracy and no influence over the sample data set I used.”

Martin randomly selected 100 contacts from a file of 10,000 and conducted the study himself.  He evaluated seven fields and found very high data quality levels:

  • Full Name Accuracy was 99%, including spelling.
  • Contact Company name was 98%
  • Title Accuracy was 96%
  • LinkedIn URL accuracy was 97%.  The three contacts that lacked LinkedIn URLs confirmed that they did not have LinkedIn profiles.
  • Seniority Level accuracy was 100%
  • 97% of the emails were deliverable with only a 3% bounce rate.  As contacts decay at a 2% rate per month, 97% is at the upper end of expectations.
  • Twitter Handles were correct 100% of the time, but only 10% of the contacts had the field populated.

With the exception of Twitter handles where there is likely a significant underpopulation of the field, the dataset lived up to its 95% SLA and data quality claims.  It should be noted that Martin did not evaluate DiscoverOrg’s technographics, org chart relationships, responsibility data, or event alerts.  These are other areas where their editorial data distinguishes the firm.

“This study confirms what I have personally heard from a wide cross-section of the technology companies I work with,” said Martin.  “DiscoverOrg provides highly accurate contact data. In addition, this study was based on a small subset of the data that DiscoverOrg provides. Of primary importance to my clients are the detailed IT organization charts, the identification of the different technologies installed, recent trigger events such as personnel changes, and the direct phone numbers of contacts.”

These types of studies are often expensive to conduct and difficult to construct when comparing vendors.  I performed similar studies as internal benchmarks when I worked at OneSource (now D&B Hoovers) and for clients since becoming a consultant and no vendors approach this level of data quality (Note: I have never evaluated RainKing which utilizes similar data collection methods).  What is clear is that the smaller universe, editorially-crafted DiscoverOrg file of 60,000 companies and 1 1/2 million contacts clearly has higher contact data quality than other vendors (again, excluding RainKing).  When discussing DiscoverOrg and RainKing with clients, I describe them as using traditional artisanal research methods which entail focusing on a smaller universe of companies and contacts at these companies.  This approach makes for a strong fit for firms employing an ABM approach to target large accounts, but may be insufficient for more transactional marketing approaches which are more sales development and demand generation focused.  Both cost and lack of coverage of SMBs would be issues at those firms.

“Bad data is costly and can be the single point of failure in an otherwise successful campaign,” says the firm on their website.  “We don’t just pay lip-service to the quality of our data. We contractually guarantee it. We know that success in every sales and marketing effort begins with highly accurate, verified data that your team can trust.”

What is clear is that this quality-centric approach to gathering data has proven successful.  Both RainKing and DiscoverOrg have high growth rates and regular Inc. 5000 membership.  DiscoverOrg closed last year with $71 million in annualized recurring revenue so is almost assured of making the Inc. list for the seventh year in a row.

Martin published his results online as a PDF.

Sparklane €4m Funding Round

Sparklane Lead Scoring
Sparklane Lead Scoring

Sparklane, which describes itself as “a publisher of sales intelligence SAAS solutions,” announced that it received a €4m funding round from XAnge and Entrepreneur Venture Investment Fund.  The round raised its total funding to €7m.  XAnge also participated in Sparklane’s previous funding round.

“We were won over by Sparklane’s disruptive positioning and the impressive performance of its management team, prompting us to offer them our renewed support as we participate in this fundraising initiative alongside Entrepreneur Venture,” stated Guilhem de Vregille, Deputy Director of XAnge.

The round allows Sparklane to continue its European expansion.  The French company established itself in the UK in 2016 and is currently eyeing the German market.  The funding will also be directed towards expanding its artificial intelligence capabilities, and growth in their sales and R&D teams.

According to Chairman Frédéric Pichard, the funding round is a “real vote of confidence,” in the company.  “Our goal remains the same: to help marketing and sales people identify their future customers more quickly using Artificial Intelligence.”

Sparklane offers predictive lead scoring and prospecting tools for sales and marketing teams in the UK and France.  Their Predict platform processes client CRM data to define an Ideal Customer Profile (ICP), apply predictive lead scores, and identify look-a-like prospects.

Sparklane supports nearly 350 clients across banking, insurance, technology and business services.  The firm was listed in Deloitte’s 2016 EMEA Fast 500 list of technology companies with 265% revenue growth between 2012 and 2015 (three-year CAGR of 54%).

WorkBench: Profile Builder, TAM, & Look-a-Like Prospecting

Dun & Bradstreet, which has had a series of major product announcements over the past few weeks (the Avention acquisition, rebranding of its OneSource platform as D&B Hoovers, a Beneficial Ownership product), has quietly added powerful new functionality to their Workbench Data Optimizer platform.  The new Profile capability features an automated profile builder, Total Addressable Market (TAM) analysis, and look-a-like prospecting based upon the Workbench profiles.

The new functionality helps marketers evaluate the size of targetable sub-markets, identify audiences with a high propensity to purchase, discover overlooked whitespace opportunities, and target new accounts and contacts.  According to Alex Schwarm, Sr. Director of Marketing Analytics Products, “Profile enables our Workbench customers to begin to use data-driven, ABM-oriented Profiles based on their successful sales.  These automated analytics allow you to quickly and easily identify the best whitespace opportunities and characteristics of your target audiences including those with the highest propensity to buy – no data scientist needed.”

NetProspex WorkBench Value Proposition
NetProspex WorkBench Value Proposition

Profile is a black-box analytics engine which clusters customer files without biases.  Marketers upload a file of their customers’ data for a specific product or product family.  Workbench standardizes, de-duplicates, and verifies the input file; matches and enriches it with Dun & Bradstreet’s WorldBase firmographics; and then provides segmentation and file health analysis.  The Profile module identifies between two and eight distinct segments containing similar companies across multiple dimensions.  The user can define the number of profiles or the system can automatically identify the optimal number of profiles based on the variation of the customer file.  The marketer is not required to define the key segmentation variables.  Instead, the system automatically performs affinity clustering (my term) to build the segments.  Execution time is typically 5 to 10 minutes.

The results are displayed on a downloadable dashboard that provides a side-by-side firmographic analysis of the clusters.  Results include company size, ownership (e.g. parent, branch), primary industries, cluster size, and average deal size (if revenue figures are also shared with Dun & Bradstreet).  Thus, the system may identify segments with a lower average deal size but a larger number of prospects alongside clusters containing top customers with high average deal size but a small number of targetable opportunities.

Portion of Workbench Profile summary report
Portion of Workbench Profile summary report

While Dun & Bradstreet does not use the term “Ideal Customer Profile” (ICP) the system is basically identifying the attributes of a customer’s ICP, determining the average deal size, and sizing the overall market opportunity.

Dun & Bradstreet has two major assets in performing TAM analysis: The WorldBase file of global companies and trust built up over 170 years of credit research.  WorldBase provides them with a consistent, global file of 260 million active and inactive companies for credit and supplier risk research, sales intelligence, and B2B marketing.  The file includes broad global company linkages, corporate and location sizing, industry coding, Tradestyles, and D-U-N-S Numbers (the de facto global company numbering system).  This intelligence provides the core reference file against which market sizing can be performed.  But TAM analysis requires customer level revenue information against which company counts can be converted to market sizes.  And here is where a strong credit analysis brand helps build confidence amongst marketers to share company revenue data.  While they will be reluctant to share revenue details with most vendors, firms have been sharing private financial details with Dun & Bradstreet over the better part of two centuries.

Marketers can then take any of the profiles and immediately identify net-new similar companies as well as net-new contacts.  The system also sizes potential target market audiences that can be reached programmatically through their Audience Solutions group.

While prospect scoring based upon these definitions is not yet supported, that is a likely future offering for the platform.  Profile, along with a set of predictive scores and paired with D&B Hoovers’ business signals, represents a toe in the water of the predictive analytics space.

C360 Research Team Expansion

The Corporate360 Team in Kerala (Source: Corporate360)
The Corporate360 Team in Kerala (Source: Corporate360)

Indian-based technology sales intelligence vendor Corporate360 recently opened a marketing data research center in Pathanapuram.  The new facility plans to hire up to 100 new staff over the next year.  The additional headcount will support marketing campaigns and be staffed by data research specialists, data quality analysts, inside sales representatives, and data scientists.

The office park in the state of Kerala is designed to promote “impact sourcing that benefits in meaningful job creation and digital skill development among educated youth from rural areas,”  blogged VP of Sales Demy Dcruz.  Thus, local graduates with digital skills can stay in the region instead of moving to a large city for employment.  The facility supports up to 150 staff.

70% of Corporate360’s staff are women.  “By building a strong women team at Corporate360, elevating co-workers and ‘working smarter,’ we have been able to help them pursue all their innovative interests that make a difference,” blogged CEO Varun Chandran.

The goal is to provide local work opportunities for women and the disabled in Kerala.  “Because the bulk of Indians live in villages, governments are neglecting a critical opportunity to both improve economic potential and basic services by creating smart villages,” Chandran told Forbes.  “I believe in creating jobs for people who need them, where they need them.  “By going back to these small, often forgotten communities, we are able to offer them housing, scholarships and health assistance so they have a chance to grow without being forgotten or left behind.”

“Our new expansion into India fulfills that critical value and represents a strategic step in growing our company,” said Dcruz.  “With that foundation, Kerala is primed to enter into the next phase of support for Fortune 100 companies by supporting their marketing campaigns and by taking on more advanced Big Data-focused roles.”

Corporate360 solutions include a DaaS Cloud service which provides “full profiles of target prospects with contact intelligence and sales triggers;” CI-Square competitive intelligence and take-away campaign data; and Data Factory services for marketers.  Products include the ProspectR predictive marketing data cloud; Tech Sales Cloud IT sales intelligence; and EmailR email campaign data with real-time verification.

“Our customers aren’t looking to Corporate360 as a ‘data vendor’—they’re asking for ‘sales-intelligence’, which means providing them with the right data, in the right geographic markets and relevant sales triggers,” said Chandran.

“As we see a continuation of growth in our large western markets, our focus is to expand coverage in the Asia-Pacific and become a market leader,” said Sajeev Pushpamangalam, Vice-President and Head of Businesses.

The firm now maintains six locations including offices in Singapore, the Philippines, Dublin, and San Francisco.  Corporate360 has over 300 global customers.