As we are one month away from the new year, it is a good time to think about budgeting for data quality in 2018.
I know it isn’t glamorous, but that doesn’t mean it is unnecessary.
Data Quality software is markedly improved over the past few years. No longer is it necessary to download and forward a file to a vendor and wait for them to process your marketing file. Sales and Marketing Operations can now setup automated cloud cleansing that works within Marketo, Eloqua, Salesforce, Microsoft Dynamics, and other enterprise applications. B2B vendors to consider include Dun & Bradstreet, InsideView, Zoominfo, and ReachForce.
These platforms perform both initial batch match & append and ongoing enrichment, ensuring that your sales and marketing files have both accurate and complete data. These services also support company and contact prospecting, data health reports, suppression lists, and segmentation reporting. A few even offer free data quality reports, deduplication, technographic enrichment, nixie files (defunct companies and departed exec files), web form support, sales intelligence services, and contact verification and standardization (e.g. address, phone, and email) for non-matched records.
As these services reside in the cloud and offer cloud connectors for the major MAPs and CRMs, the operational overhead is minimal allowing operations to focus on ABM look-a-likes, segmentation, and improved targeting instead of file management.
What’s more, data quality improvements benefit sales, marketing, and downstream systems. A record cleansed and verified as it is created costs much less than a bad record passed down to other enterprise platforms. Beyond direct cost reduction (storing bad data, marketing to departed execs, sales calls to abandoned voicemails, reduced time keying and updating records manually), there are improvements to segmentation, targeting, lead scoring, lead routing, and messaging.
So budget for data quality in 2018. It isn’t glamorous, but it is effective.
Salesforce announced the launch of two new AppExchange partnership categories offering native Lighting functionality: Lightning Bolts and Lightning Data. Bolts are Lightning Components which offer customer data and business logic.
Lightning Data provides new Data as a Service (DaaS) partnerships in the wake of the non-renewal of the Dun & Bradstreet – Data.com licensing partnership. Three of the partners were announced as Data.com Exchange partners at last year’s Dreamforce:
Initially, Lightning Data only supports ongoing match and enrichment services for Account records. As many AppExchange partners offer batch and continuous services for Account, Contact, and Lead records, Lightning Data will need to round out its enrichment capabilities for it to become a full hygiene and enrichment solution.
Lightning Data is an indication that Salesforce never really bought into the idea of being a DaaS company. Since August 2011, they have promoted Data.com, but never fully committed to the data ecosystem they promised when they launched Data.com. The original idea was to take the Jigsaw file they purchased in April 2010 for $142 million and integrate it with the D&B WorldBase company file. They were then going to partner with other leading data companies to integrate third-party data matched to either Data.com contact intelligence or D&B Account intelligence. These data sets were to be delivered via Data.com Prospector sales intelligence and the Data.com Clean match and append service.
It was the right idea at the right time. They were playing catch up with OneSource for Salesforce, InsideView for Salesforce, and Access Hoovers, but had the technical and financial resources to quickly leapfrog these offerings (Access Hoovers was phased out as part of the D&B deal). Furthermore, they had a first mover advantage in cross-selling Data.com to their customer base. It could have been a home run, but they rarely hit the ball out of the infield. What’s worse:
The Jigsaw file was never truly internationalized. It remained a U.S. contact file with underwhelming executive coverage for nine other countries.
The Data.com contact counts increased, but only because they were adding contacts at the same rate as they were decaying. Meanwhile, their top two contacts competitors, NetProspex and Zoominfo, continued to expand both their active and inactive coverage in the U.S. and internationally.
They never added biographic details or social links to the contacts file
Prospector features remained underwhelming. They would add small features such as improved industry and geographic screening, but not anything significant until 2016.
They quickly dropped all discussion about an ecosystem.
Then at Dreamforce 2015 and 2016 they seemed to have found their mojo, addressing key weaknesses such as pricing, sales intelligence (Hoovers profiles, First Research industry overviews), and a data ecosystem.
Data.com hit a few doubles and outlined an aggressive 2017 and 2018 roadmap. It looked good. It sounded good. But then Salesforce severed their partnership with Dun & Bradstreet and now only legacy customers have access to Dun & Bradstreet content. For everybody else, there were nine months of deafening silence until yesterday’s announcement of Lightning Data.
The devolution of Data.com will not have a significant effect on Salesforce’s bottom line as it represents perhaps one percent of company revenue (hence, the lack of urgency in replacing Dun & Bradstreet content). Furthermore, the legacy offering will continue to be supported for several more years so the revenue decline will have little material impact. Perhaps we’ll hear about replacement content at Dreamforce, but Lightning Data suggests they are leaving B2B DaaS to partner companies.
Openprise launched a Data Marketplace to assist with ingesting and normalizing third-party B2B and B2C data. Amongst the platforms supported are Salesforce, Marketo, Eloqua, and Pardot. The Data Marketplace, part of the Openprise Data Orchestration platform, includes built-in rules to ensure data is properly onboarded. Users can set primary, secondary, and tertiary providers with multi-vendor data normalization rules.
“We’re excited to make ZoomInfo’s 210 million businesspeople and 11 million businesses available on the Openprise Data Marketplace,” said Phil Garlick, VP Corporate Development at ZoomInfo. “Openprise’s data cleansing and unification capabilities, combined with ZoomInfo’s data accuracy, provides marketing and sales teams with an unparalleled solution to run more effective campaigns.”
Other B2B Partners include InsideView, Orb Intelligence, Synthio (FKA Social123), and Dun & Bradstreet. Additional vendors are in the final certification stages. Openprise claims that new data providers can be setup in minutes.
Customers can extend pre-existing vendor contracts or take advantage of pre-negotiated discounts.
“Earlier this year, we surveyed 175 marketing professionals to identify data marketplace trends and published our findings in the B2B Data Market Industry Report,” said CEO Ed King. “We found that companies that worked with multiple data providers were much more likely to be satisfied with their third-party data, but those same companies expressed how much they struggled with pulling multiple providers’ data into their marketing and sales system of record while maintaining a consistent set of standards. Openprise Data Marketplaces solves this problem.”
The B2B Data Market Industry Report also asked which vendors were being deployed. The survey of 175 B2B marketers at firms with at least 200 employees found the top three vendors were Zoominfo (40%), InfoUSA (36%), and Data.com (35%). Surprisingly Sales Genie matched D&B/Hoovers amongst all of the surveyed marketers and exceeded it amongst enterprises. InfoUSA rates were likely higher than the other firms as it offers both business and consumer data while Dun & Bradstreet/Hoovers and many of the other vendors offer strictly B2B data.
The most common use case for B2B data vendors is identifying additional contacts at target companies (62%). Marketers also looked to B2B companies to identify additional target accounts (52%) and append missing fields (50%). Only 37% were looking to B2B data vendors to cleanse their database.
The survey participants were well distributed across B2B industries with an over weighting to advertising / marketing.
2016 North American Sales Intelligence Market Sizing Model (Excel)
The Market Size of North American Sales Intelligence Vendors. Includes vendor product features, market share, and notes. GZ Consulting Copyright 2017.
For the past few years, I have been sizing the North American Sales Intelligence Market. This is the largest of the markets as Europe and AsiaPac are more fragmented (the UK is the only other mature market with Bureau van Dijk, Avention UK, Artesian Solutions, and DueDil offering full solutions).
In 2016, I estimated the market at $770 million with LinkedIn Sales Navigator as the top vendor. While new firms continue to enter, the top ten firms (now eight following the 2017 acquisitions of Avention and RainKing) earn seven of every eight dollars in the industry.
I am making my market model available for license (See PayPal button at top) as an Excel spreadsheet. It includes revenue numbers by company along with market share, key features, and notes.
I have also broken out two sub-categories: Predictive Analytics and Tech Sales Intelligence. Predictive Analytics vendors continue to scuffle in the marketplace. Last September, Gartner sized the global market at between $100 and $150 million. I have gone back and forth on whether to include them in the larger sales intelligence space, but several of the sales intelligence vendors have added light predictive tools (e.g. Avention, DiscoverOrg, RainKing) while the predictive analytics companies have moved to add enrichment and provide more insights to sales reps. As such, I see the two product categories moving towards each other so chose to include Lattice Engines, Leadspace, and similar firms.
The Tech Sales Intelligence category (e.g. DiscoverOrg, RainKing, Aberdeen, Corporate360) continues to show strong growth and makes up just over 15% of the market. Both DiscoverOrg and RainKing have posted remarkable growth over the past few years and merged their efforts last month. Post acquisition, they are the number three vendor in the space and may hit $120 million in 2017 revenue. The new powerhouse has 4,000 customers and is looking to expand beyond technology sales to become a general purpose sales intelligence solution.
Acquiring RainKing should move DiscoverOrg well past Data.com (Salesforce) which will likely see declining 2017 revenue. Salesforce has dropped the ball on Data.com. They overpromised and under-delivered for years, relying on their ability to bundle the offering with other SFDC products. As of last month, they are no longer able to deliver Dun & Bradstreet content (D&B WorldBase, Hoovers, and First Research) to new customers (legacy customers retain access). Unless Data.com has a major content partner announcement at Dreamforce, it is likely to see significant revenue declines in 2017 and 2018 as customers switch to D&B Hoovers for Salesforce and other offerings.
Dun & Bradstreet re-established itself as the #2 vendor in the space with the January 2017 acquisition of Avention and the rebranding of Avention OneSource as D&B Hoovers. Both companies have struggled to grow revenue with Avention growing slowly over the past few years and Hoovers declining. However, infusing Avention products with Dun & Bradstreet content both reduces the underlying cost structure of Avention offerings and improves the depth and quality of the content. Furthermore, Dun & Bradstreet has a much larger sales force which previously has lacked a credible global sales intelligence offering. Hoovers classic generated nearly all of its revenue in the United States. Over the next two years, expect to see significant revenue shift from Hoovers Classic to D&B Hoovers.
Finally, LinkedIn Sales Navigator has established itself as the clear number one vendor in market revenue. The product didn’t exist five years ago and its competitors still tend to dismiss this gorilla in their midst. How can they be missing the #1 vendor in the space? Easy — the gorilla is well camouflaged and appears to be more of a three-toed sloth sleeping in the forest canopy. Sales reps all use the freemium version of LinkedIn so give little thought to delve further when they ask “how are you obtaining your account intelligence today?” and the response is LinkedIn. Thus, they enter LinkedIn as the competitor into their CRM, not Sales Navigator. A few months later when they lose the opportunity, the rep then enters “no decision” into the CRM instead of recognizing a competitive loss. I have been warning vendors in the space for years about this phenomenon, but they have failed to understand the threat of a gorilla that looks like a three-toed sloth.
N.B. Three-toed sloths inhabit Central and South America and gorillas Central Africa. This is a metaphor.
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.
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.
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.
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:
Contact Records Company Type (emails)
Contact Records Campaign Type (emails and phones)
Company Records Firmographics
Cookies and Mobile ID’s for programmatic and mobile targeting
Emails have a 90% confidence rate for deliverability.
Dun & Bradstreet unveiled a new Beneficial Ownership product to assist with client onboarding and back-book remediation of current customers. The service helps determine who are the ultimate benefactors of each transaction. Beneficial Ownership assists with legal compliance including Know Your Customer (KYC), Anti-Money Laundering, Politically Exposed Persons (PEP), and sanctions lists monitoring. Overall, there are around a dozen relevant regulations concerning beneficial ownership with different thresholds for research. By automating these checks, which have historically required manual research teams, Dun & Bradstreet is reducing time, expense, and risk (e.g. credit, supplier, reputational) while expediting the client onboarding process.
“Compliance teams are challenged to manage third-party due diligence, Anti-Money Laundering, Know Your Customer and tax compliance regulations through manual processes that can be costly and inefficient,” said Brian Alster, Dun & Bradstreet’s Global Head of Supply and Compliance. “By harnessing Dun & Bradstreet’s verified data with D&B Beneficial Ownership, the process can be easily automated to fast-track standard onboarding, helping companies relieve compliance burdens, and get back to driving growth.”
While family trees focus on controlling interest there are numerous legal reasons to look beyond controlling interest. These include onboarding and ongoing compliance (e.g. KYC, AML, PEP, sanctions) as well as company research relevant to conflicts of interest, supply chain risk, and vetting customers, partners, service providers, and resellers.
The new offering, which draws from the D&B WorldBase file of 265 million active and inactive company records, spans 62 countries and 71 million shareholders. D&B Beneficial Ownership is available through batch, real-time, and online access via the D&B Direct API or D&B Onboard. The service also delivers ownership change alerts and a visualization layer which displays a spider-web view of branches and loops of business structures. To assist with varying global requirements, users can query at different ownership thresholds. Both corporate and individual beneficial owners are assessed across 100 million plus connections.
With D&B Direct 2.0, API clients pass the company name which is DUNS Matched. The API then returns a detailed list of shareholders to the desired threshold including percent of ownership and loops (i.e. cross-ownerships).
Dun & Bradstreet collects shareholdings data from registered filings (mostly in Europe), direct research teams, and licensed data. Ownership data goes down to 0.1% ownership levels. Other compliance data includes PEP flags, sanctions lists (e.g. OFAC), and adverse media searches.
Beneficial Ownership intelligence is also important for companies with deep supply chains looking to prevent reputational risk and ensure a minimal level of ethical behavior amongst their subcontractors. Last May, Dun & Bradstreet launched a Human Trafficking Risk Index tool which helps firms avoid dodgy suppliers that may be using slave labor. The Human Trafficking Risk Index is the first in a series of “Responsible Business Analytics” products in their pipeline.