HG Connect for Salesforce and HG Audience

HG Data Vendor and Product Intelligence
HG Data Vendor and Product Intelligence

Last month, technographics vendor HG Data rolled out two new services: HG Connect, a Salesforce Data Exchange connector, and HG Audience for digital targeting.  HG Connect supports competitive and complementary targeting of prospects based upon installed hardware and software.  HG Connect use cases include sales intelligence, lead qualification, and demand generation.  Account records are enriched in near-real time via the Data Exchange and updated on a monthly basis.  Matching is done via corporate URLs.

“It is our mission to help companies achieve extraordinary results in their marketing and sales outreach through the use of accurate and comprehensive technographic data,” said Barbara Winters, VP of marketing at HG Data. “With HG Connect, customers don’t even have to think about how to integrate technographic data into their workflows, it’s already there, ready for them to use, so that they can begin creating targeted segments for their campaigns immediately without needing to work with an IT or operations person to integrate the data.”

The HG connector is Lightning enabled, delivering HG Data’s technographics to mobile devices, reports, and dashboards.  The data is also available for triggers and workflow.  Along with Vendor and Product data, HG Data publishes Confidence and Intensity Scores (accuracy and frequency of uniquely dated documents).

Sample HG Data Connect Lightning-enabled dashboard
Sample HG Data Connect Lightning-enabled dashboard

Data enrichment is limited to Account records with plans to enrich Lead records in the future.

Customers license access to HG Data segments which is enabled via a Salesforce Data Integration rule (formerly called a Clean rule).  HG Data tracks 13 million global companies and 88 million technology installations. Their taxonomy spans 3,800 vendors and 7,500 products.

The Data Exchange is a Salesforce enrichment service associated with Data.com.  The Data Exchange does not yet support prospecting.

HG Data also launched HG Audience for programmatic advertising on platforms including Krux, Lotame, Adobe Marketing  Cloud, DataXu, MediaMath, and TheTradeDesk.  Marketers will be able to target audiences based upon technographic variables, firmographics (e.g. sector, revenue, employees), job function, and job level.

HG Data Audience Solutions
HG Data Audience Solutions

“HG Audience allows companies to modernize their digital advertising targeting strategy in a profound way,” said John Connell, Vice President of Digital for HG Data. “Instead of deploying digital ads based on just traditional firmographics or Internet content consumption, companies can now use our precise custom segments to apply ABM-style focus to traditionally broader-reach display media tactics.  With HG Audience, we’re giving our customers access to the influencers and decision makers at the companies that matter to them, leading to better engagement, greater efficiency and much better ROI on their advertising dollars.”

Over the past few years, a number of content vendors have released programmatic products.  These include Infogroup (B2B and B2C selects), Dun & Bradstreet (B2B), HG Data, Bombora (B2B Intent), and LinkedIn (Member targeting).

“In the last year to 18 months, there’s been a shift with B2B companies doing more programmatic media buying,” says Ashu Garg, general partner at Foundation Capital, a venture capital firm that has invested in the ad tech space. “What’s behind the change is the greater ability to connect anonymous data with PII (personally identifiable information) data. Secondly is the ability to get much more precise targeting from niche segments and audiences across platforms, whether that be social, display or video platforms.”

An AdWeek BrandShare study commissioned by Dun & Bradstreet in September 2016 found that 65% of B2B marketers were deploying programmatic campaigns, a ten percent jump from 2015.

Quora: How do I do marketing using LinkedIn?

Here is how I answered the following question on Quora: “How do I do marketing using LinkedIn?”

I would use LinkedIn in the following ways to promote my company:

  • LinkedIn has a set of marketing services which allow you to build targeted campaigns by both firmographic (size, industry, location) and biographic variables. This is probably the most granular B2B advertising tool out there. The Campaign Manager also provides a set of analytics around viewing and impressions. Pricing is either CPC or CPM (impressions or clicks). Here is a quick description of their advertising formats: 
LinkedIn Marketing Formats
LinkedIn Marketing Formats
  • LinkedIn can be used to promote your own content as posts, whether it be white papers, product descriptions, case studies, blogs, or articles. If you mention a partner or customer, make sure to link to them and have their marketing departments like the content. Where possible, include some copy from the content or description of the content along with a visual (LinkedIn will grab a visual from the source if there is one available).

    Do not overly self-promote. Your content should lean towards thought leadership not corporate promotion. Of course, if you launch a new product, write about it. But LinkedIn is not the place for deep feature dives or long discussions of your value proposition. And please, not another What does [this character from Game of Thrones] teach us about [some aspect of business]. This type of coattail riding is generally full of clichés and stretched analogies. Originality, Professionalism, and Readability are key on LinkedIn (a good graphic and headline don’t hurt).

  • LinkedIn supports its own set of articles, but I’ve had more luck blogging on my site and then writing posts that link to my blog. You should test both approaches to determine whether LinkedIn articles work for your company.

  • Have your employees like content so that it is seen by your prospects and customers in their feed. 
  • Fill out your company profile. Many vendors rehash their website and Facebook profiles, but I would try to differentiate the copy between these three sites. For B2B companies, the website should be corporate, Facebook a bit cheeky, and LinkedIn professional, but lighter than your website. Keep in mind that LinkedIn is used by both prospective employees and customers so you want to be speaking to multiple readers. 
  • Evaluate Sales Navigator for your sales reps. This service does not allow you to download lists of companies and contacts, but it allows you to build and maintain lists of accounts and leads which are stored in Navigator (these lists can be built individually, via prospecting, or via CRM downloads). Sales Navigator also supports CRM viewing of company and contact profiles, InMails (direct messages with prospects outside of your current connections) and PointDrive, a custom website link that allows sales reps to forward attachments (collateral, price documents, videos, PowerPoints) as embedded content with descriptions. PointDrive provides analytics on what content has been consumed and tracks whether the document has been forwarded to others. 

Keep in mind that LinkedIn’s audience skews older and more professional than Twitter and Facebook.

 

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 and The Big Willow 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.”

 

 

 

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.

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.

DiscoverOrg AccountView ICP Tool

Intelligence vendor DiscoverOrg announced a new Account Based Marketing (ABM) tool called AccountView which helps marketers identify the attributes of their Ideal Customer Profile (ICP).  The new feature analyzes an account file which it calls a portfolio, enriches it with firmographics and technographics, and then provides a portfolio visualization dashboard of the accounts.  The service also identifies similar companies to the top accounts, prioritizes them, and identifies best fit decision-makers at the net-new accounts.

The AccountView Dashboard provides firmographic and technographic segmentation analysis.
The AccountView Dashboard provides firmographic and technographic segmentation analysis.

The portfolio segmentation dashboard tiles include

  • Size: Revenue and Employee Bar Charts
  • Industry: Primary Industry Pie Chart; SIC and NAICS top frequency lists
  • Technology: Technology lists
  • Ownership: Ownership Structure Pie Chart
  • Companies: Portfolio companies with employee and revenue data.  Company names are hyperlinked to their DiscoverOrg profiles.

Although geographic segmentation is not yet available, it is on the product roadmap.

Within the list tiles, users can search for specific elements (i.e. SIC, NAICS, technology, or company name).

Proposed contacts are shown within org charts with direct dial phones and emails to assist with organizational context and reach out.  DiscoverOrg also provides detailed platform information and a set of sales triggers.

Marketing and sales teams can drill into specific bars or wedges to further research segments.  To quickly refine models, customers can remove outliers to focus the ICP around high frequency variables.

Company Lists include DealPredict Scores and Lightning Bolt Alert Flags.
Company Lists include DealPredict Scores and Lightning Bolt Alert Flags.

Portfolios may be uploaded as CSV files, bulk matched within DiscoverOrg, or generated via DiscoverOrg prospecting.  Result lists may be saved as lists, viewed as searches, or exported to CSV files.  Models may also be loaded into DealPredict where company lists are displayed with Deal Predict scores of zero to five stars.  Next to DealPredict scores, DiscoverOrg displays a lightning bolt icon if the company has a Sales Trigger or OppAlerts in the past sixty days.  OppAlerts are intent based triggers which have been researched by DiscoverOrg editors or gathered through B2B publishers’ online content consumption data.  By clicking on the lightning bolt, reps are shown the related events.

Within DealPredict, company lists are dynamically maintained to reflect the current firmographic and technographic lists of companies.  If there is a change in company size or implemented technology, the DealPredict scores are automatically updated every time a search is conducted.  Likewise, companies which are added to the DiscoverOrg database are automatically scored.

The very foundation of successful sales and marketing is figuring out who your best customers are, understanding why they are the best, and finding more prospects just like them.  What could be a painful analytical exercise is made simple and straightforward with DiscoverOrg’s account-based marketing features, and the result is faster growth for customers who can more effectively identify, understand, and engage with their ideal buyer.

  • DiscoverOrg CEO Henry Schuck

DiscoverOrg suggests a number of account list categories that can be analyzed including the full customer list, high or low spend customers, renewing or non-renewing customers, high or low profitability customers, competitor customer lists, and prospect accounts.  For example, running a competitor’s customer profile through AccountView helps you “determine ways to improve your product, messaging, or positioning.  Likewise, running the non-renewed customer list through AccountView will help identify high-churn candidates for special programs.

Although DiscoverOrg recommends sets of strong and weak account lists, AccountView does not have the ability to discriminate between the two categories.  Thus, marketers would need to separately run the paired lists, compare the portfolio results, and adjust the models for overlapping variables.  For example, knowing that Microsoft Office is heavily used by both strong and weak accounts would indicate that MS Office is a frequently occurring, but non-predictive variable.

Future features include support for multiple models, grouping tech functions by category, sharing models across all users, geographic segmentation reports, and uploading contact information to assist with defining job functions and levels.

AccountView is the latest capability within DiscoverOrg’s ABM Toolkit.  Other features include DiscoverOrg’s DealPredict predictive rankings for companies and contacts, OppAlerts intent-based opportunities, and sales triggers.

DealPredict provides predictive scores similar to those provided by predictive analytics companies.  DiscoverOrg CMO Katie Bullard noted that unlike some black-box predictive platforms, AccountView analysis and DealPredict models are fully visible to sales and marketing users.

The AccountView analytics and net-new account service is included as part of the DiscoverOrg service.  Firms license access to specific DiscoverOrg datasets and a set number of seats.  Licensed users then have unlimited access to the licensed content for viewing, uploading, or downloading.

Other sales intelligence companies that have developed AccountView-like functionality include Dun & Bradstreet (Workbench), Avention (DataVision), and Zoominfo (Growth Acceleration Platform).

DiscoverOrg, which hit $71 million in Annual Recurring Revenue (ARR) at the end of 2016, has expanded its customer base beyond technology companies.  Over 15% of revenues now come from marketing agencies, staffing firms, and consultancies.

DiscoverOrg is one of fourteen vendors covered in my “2017 Field Guide to Sales Intelligence Vendors“.

Sales Intelligence Vendors Move Upstream

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.

Five years ago, Sales Intelligence vendors avoided selling into the marketing  department.  While there were a few enrichment projects for CRMs, these were driven by Sales Ops, not marketing departments.  Furthermore, SalesTech products are sold on a per seat basis for sales reps while marketing revenue is generally volume based (e.g. number of prospecting records sold or records enriched).  This made pricing of services difficult.

But MarTech was receiving heavy investments and several firms shifted their focus from sales to marketing.  Zoominfo began discussing Sales and Marketing Alignment and developed a set of marketing tools.  The firm, which had been struggling to grow revenue for several years, is again on a growth trajectory and made the two most recent Inc. 5000 lists.

InsideView also began developing marketing functionality and now treats the two departments equally.  Most of InsideView’s recent investment has been in building out marketing solutions or expanding their company and contact coverage (which benefits sales and marketing equally).

At the beginning of 2015, Dun & Bradstreet acquired NetProspex for its contact database and Workbench hygiene platform.  The firm also used NetProspex as the basis for their Audience Solutions programmatic marketing service which was launched in 2015.

In 2016, the Sales Intelligence vendors continued to move upstream into marketing intelligence and hygiene.  InsideView continues to enhance its Target, Enrich, and Refresh marketing tools while Avention launched OneSource DataVision for web form enrichment, continuous enrichment, segmentation, look-a-like prospecting, and TAM analysis.  Avention also launched Marketo and Eloqua connectors for their OneSource service.

“OneSource DataVision naturally extends the sales and marketing benefits our customers can gain from OneSource Solutions by being even more targeted with campaigns and programmes – including account-based,” said Avention SVP of Product Lauren Bakewell. “Better qualified leads and more targeted account-based approaches should bring better sales results, which should in turn strengthen sales and marketing alignment; we feel alignment happens best when sales forecasts are being met and exceeded!”

Zoominfo has repositioned itself as a MarTech company with a rebranding of their platform as the Zoominfo Growth Acceleration Platform.  While sales reps are still supported, the emphasis is on data enrichment, segmentation analysis, cluster analysis, and look-a-like prospecting against clusters.

DiscoverOrg and RainKing also placed greater emphasis upon marketing and ABM capabilities.  Both services support predictive rankings of accounts and contacts, MAP and CRM enrichment, and new opportunities (Inside Scoops from RainKing and OppAlerts and sales triggers from DiscoverOrg).

In 2017 and 2018, expect the walls between SalesTech and MarTech to crumble.  The opportunity to offer a solution for both departments via a shared reference database will continue to drive strategy at these firms.  As MarTech begins to consolidate, expect M&A activity within the sector and vertically with SalesTech vendors.

Sales Intelligence vendors have key assets that benefit marketing departments including large company and contact datasets for prospecting and enrichment; firmographic data for lead scoring, targeting, segmentation, and routing; and the growing ability to tie leads to accounts in real-time.  They are also well positioned to support ABM functionality with profiling, analytics (segmentation, Total Addressable Market analysis), and look-a-like prospecting.

Of course, MarTech is also beginning to eye SalesTech.  Last spring, Demandbase acquired Spiderbook and leveraged its capabilities to launch their DemandGraph relationship dataset.  The expanded content set employs semantic mining and machine learning to assemble the “entire business network of a company” which helps  “identify which companies and buying committees are in-market for particular solutions.”  The DemandGraph helps users target in-market accounts, identify key buyers, uncover meaningful insights, and deliver personalized content.  While they have not announced specific predictive tools or capabilities, they are hinting at such tools.

Demandbase DemandGraph
Demandbase DemandGraph

Meanwhile, the predictive analytics companies, which originally focused on lead scoring, are now building sales functionality including net-new contacts at accounts, account prioritization, flagging churn candidates,  and providing recommendations for sales reps.

Things are just beginning to get interesting.