TechTarget Scoops up Oceanos Marketing

TechTarget LogoTucked into the tail end of TechTarget’s earnings release last week was notice that they had acquired Oceanos Marketing, a contact data management company.  Both firms are based in the Boston suburbs.  Oceanos brings “data quality and data management expertise that will help us improve our offerings and deliver better results to our customers.”

Oceanos began as a list broker in 2002, but has since evolved into a B2B contact aggregator and data refinery.  The firm aggregates 97 million active US contact records (as of August 2017) and retains millions of inactive names and emails to assist with hygiene.  Data is aggregated from over a dozen vendors and includes social data from FullContact and Pipl.  Oceanos provides data enrichment, TAM analysis, net-new contacts, and a set of data specialists to assist with projects.

TechTarget manages a smaller set of 18 million subscriber profiles, 16 million of which are technology professionals.  The Oceanos acquisition should allow TechTarget to improve both the quality of their subscriber dataset and expand coverage into non-technology positions.  As technology purchase decision making has expanded beyond tech titles, Oceanos provides significant lift into other job functions.  Oceanos contacts are mapped to 12 Job Functions, 109 Sub-functions, and 7 Job Levels.

Oceanos President Brian P. Hession identified their differentiators as their unique blend of technology, professional services, and data quality. With data quality being critical to ABM sales and marketing initiatives, the inclusion of real world project fulfillment through their program specialists provides Oceanos with data quality insights that are used to continuously inform and enhance the data quality processes. “We apply both technology and real-world insights to ensure the highest quality of data before we are releasing it. We are incorporating a continuous stream of data quality insights into our code to address the many nuances that a program specialist encounters manually on a dataset,” said Hession last summer.  “The way that Oceanos is going to be successful in the future is if we can assemble an internal contact database that is of the highest quality in the industry.  So there’s been a lot of focus on putting models on top of our contact data.”

“Social data plays a role in our data hygiene process and serves as a ‘signal’ within both our Data Quality Score (DQS) and ABM Usability Score. The social information is sourced from reputable partners,” said Hession.  “Oceanos does not scrape contacts across LinkedIn or, in that vein, any social media site. All of our contact records originate from carefully selected third party data providers.”

The acquisition cost was not announced but was deemed “non-material.”  Oceanos 2017 revenue was around $5 million.

DiscoverOrg Releases Operations Dataset

The Operations Dataset includes headshots, bios, responsibilities, org charts, emails, direct dials, and social links.
The Operations Dataset includes headshots, bios, responsibilities, org charts, emails, direct dials, exec changes, and social links.

DiscoverOrg continues to build out its functional datasets to assist firms in targeting specific departments.  The newest dataset, Operations, joins functional coverage of IT, Product Management (TEDD), Sales, Marketing, HR, and Legal/Compliance.  The Legal/Compliance dataset was released in January.

The new dataset covers 250,000 operations professionals and is divided into twelve sub-functions: Operations (including COOs), Customer Service, Supply Chain, Facilities Management, Logistics, Corporate Strategy, Office/Store Management, Safety, Real Estate, Physical Security, Quality Management, and Construction.

“Operations teams are rapidly transforming; in response, there has been an explosion in technology and service providers serving their needs,” said DiscoverOrg CEO Henry Schuck. “Our new operations dataset makes it easy for these companies to find and connect to the right decision-maker, nail their pitch, and save hours of grind.”

DiscoverOrg projects that operations will be the next function transformed by technology.  “Operations, which has historically have had to rely on trickle-down budget from IT or other departments, now has a budget of its own,” said Justin Stanley, VP of Data and Research at DiscoverOrg.  “Historically, sales to the operations function has been based on long-standing vendor relationships, making it difficult for startups, newcomers, and disruptors to get a piece of the pie. The democratization of data has made it much easier to contact buyers directly (if you can find them) – and beat out older incumbent vendors.”

Furthermore, the budget is “huge” and includes “smart” buildings, security, infrastructure, transportation, insurance, planning, and facilities management.

Stanley noted that operations buyers are focused on efficiency, digitization, automation, and efficiency. They also have a significant role in purchasing and implementing the Internet of Things (IoT) at their facilities.  Forbes sized process automation and digitization at $157 billion in 2016 growing to $457 billion by 2020.

But selling into this function is difficult.  “First, ‘operations’ is a pretty vague term. It doesn’t usually appear in an employee’s title, so it’s hard to identify exactly the role you’re looking for,” said Stanley.  “Second, Operations employees don’t often hold high-profile titles. These aren’t roles that are typically listed on a corporate website, and there aren’t a lot of operations ‘thought leaders’ on LinkedIn. So, they’re difficult to identify – and harder to find contact information for.”

A recent survey by BSG found that the two biggest problems for operations and facilities sales are prospecting and accessing the right decision makers.

“Customers and prospects repeatedly asked for it [an operations database],” said Senior VP of Data and Research Derek Smith.  “Over time, it became clear that plenty of people wanted to reach these types of contacts. But there was nowhere to get them.”

DiscoverOrg now covers over 3.6 million contacts across 140,000+ global companies.  Data is collected through direct research by their multi-lingual editorial team and refreshed every ninety days.  The dataset includes firmographics; contact details like direct dials and verified email addresses; org charts and reporting structures; installed technologies; and buying signals like planned projects, online research behavior, funding announcements and personnel moves.

“We are currently evaluating and prioritizing what our next dataset launch will be,” said Chief Growth Officer Katie Bullard.  The database will double in size again this year – some of that growth will be from new dataset launches and most from additional contacts in our existing datasets.”

SalesIntel Human-Verified Contacts

SalesIntel supports prospecting by Job Level, Department, Title, Company, Location, Size, Email, and Contact Name.
SalesIntel supports prospecting by Job Level, Department, Title, Company, Location, Size, Email, and Contact Name.

Manoj Ramnani, CEO of CircleBack, launched his next venture, SalesIntel, as a beta service this month. After spending a decade in the sales and marketing space, Ramnani realized that “high quality and affordable B2B contact data for sales professionals was missing, and that enterprises were looking for a better deal.”

Traditional contact files are around 80% accuracy, but SalesIntel claims 95%+ accuracy through human verification of their contact records. Once added to the database, SalesIntel contacts are subject to a 90-day reverification cycle to maintain accuracy. 95% pushes the limits of accuracy due to the 2 to 2 ½% natural decay rate of contacts based on ongoing executive changes.

SalesIntel currently covers one million U.S. contacts, but it is growing at 100,000 names per week. Ramnani projects that the SalesIntel database will double in size to two million contacts by September.

Every contact record contains an email address and 90% contain direct dial phone number and LinkedIn hyperlinks. SalesIntel also provides headquarter and branch location switchboard numbers.

This data acquisition model is similar to the editorial process implemented at DiscoverOrg which has built a high quality database of three million contacts subject to 90-day human reverification cycles.

Ramnani emphasized that contact quality is even more important in the era of ABM targeting and committee buying:

When they do start a conversation, sales reps lack the contact information to easily include and reach out to everyone involved at an account. Each business decision involves seven buyers on average, but at least info for two of those contacts is expected to be wrong on average. Inaccurate data doesn’t only cost the cost of acquiring the data. It costs your sales team time, profit, and can slow down deals.

  • SalesIntel CEO Manoj Ramnani

SalesIntel also supports ABM lookup of contacts at companies and broader list building. Screening covers basic location, employee, revenue, title, and name filters along with six job levels, nine departments, and industry codes (SIC and NAICS). Location screening is limited to State and ZIP codes. Up to 500 records may be downloaded at a time.

The basic service offers 50 view-only contacts per month for $50. The standard service provides 100 downloadable contacts per month for $100 and the Advanced service provides 250 contacts per month for $250. A Salesforce integration and technographic selects are coming later this month.

“My team and I started this journey six months ago with the mission to make sales professionals’ lives easier,” Ramnani said. “We realize that salespeople shoulder the most important responsibility for the existence and growth of their organizations, namely, revenue growth. Our goal is to use the power of machine gathering and human verification to make their lives easier by providing them with the highest quality data on the market.”

InsideView Marketing Suite for Microsoft 365

Sales and Marketing Intelligence vendor InsideView rolled out a Marketing Suite for Microsoft 365 which packages add-on prospecting and enrichment capabilities for the Microsoft 365 InsideView service. The new suite helps “modern marketers grow and improve the quality of their pipeline, prioritize leads, find and engage ideal prospects and customers, and support account-based marketing (ABM) programs.”

The Marketing Suite bundles InsideView Enrich (lead and webform enrichment), InsideView Target (list building), and InsideView Refresh (Batch Account updates). InsideView is offering special “Suite Deal” pricing.

InsideView has long provided a natively embedded free Insights service for North American sales reps within Dynamics.

InsideView Refresh Match Analytics.
InsideView Refresh Match Analytics.

InsideView Apex, their recently launched go-to-market decision engine, is a further option for the Marketing Suite.

“Today, as more B2B marketers use targeted strategies like account-based marketing to expand customer relationships and win new ones, they need a marketing automation solution that helps them identify and engage with the best opportunities,” said Joe Andrews, InsideView VP of product and solution marketing. “The InsideView Marketing Suite builds on the foundation of Microsoft Dynamics 365 for Marketing so marketers can tap into our Targeting Intelligence to get higher quality data, make better marketing decisions, and execute more successful targeted marketing programs. As a Microsoft OEM partner, InsideView is always looking for ways to extend the value we can offer their customers.”

D&B Optimizer for Marketing

DNB Optimizer for Marketing -- Key Features
DNB Optimizer for Marketing — Key Features

Dun & Bradstreet rebranded D&B Workbench Data Optimizer as D&B Optimizer for Marketing and announced a set of enhancements to the platform.  The Workbench name, now dropped, went back to the product’s origins as NetProspex Workbench, one of the first DaaS Hygiene / Enrichment / Prospecting platforms.  The rebranded product includes a series of new features including an Analyze module, Salesforce Contact Optimization, custom email deliverability targets, and NAICS industry code support.

“This new name reflects Dun & Bradstreet’s commitment to deliver the very best in data optimization services,” the firm wrote its clients.  The new name is also consistent with its other Optimizer solutions: D&B Optimizer for Salesforce and D&B Optimizer for Microsoft.

The new Analyze module delivers profiling and market opportunity analysis “utilizing D&B Master Data and proprietary machine-made analytics.”  Features include dynamic dashboards which help marketers visualize their primary profile by revenue, employee size, and industry.  The service also provides look-a-like opportunities to assist with ABM expansion and pipeline growth.

The new Salesforce Integration for Contact optimization supports contact cleansing and enrichment at a frequency determined by the customer.  Dun & Bradstreet claims that the Salesforce integration may be setup in fewer than twenty minutes.

Custom Email Deliverability Levels allow marketers to dip deeper into Dun & Bradstreet’s pool of emails and select contacts with lower reliability scores.  The default level is 90% deliverability, but highly targeted selects may require using contacts that are below the 90% deliverability threshold.  Dun & Bradstreet called the 90% threshold “our recommended level for most email campaigns.”

Finally, D&B Optimizer for Marketing added NAICS industry code selects.  The product already supports the older US SIC industry taxonomy.

Other D&B Optimizer for Marketing features include data validation and standardization (email, phone, address), duplicate flagging, data hygiene reports, lead prospecting, segmentation analysis, and data enrichment (firmographics, D-U-N-S Numbers, corporate linkages, technographics, biographics).

TechTarget Priority Engine Q2 Release

 

 

Priority Engine account profiles combine TechTarget intent signals with HG Data platform insights and DiscoverOrg executives
Priority Engine account profiles combine TechTarget intent signals with HG Data platform insights and DiscoverOrg executives

Technology media and intent purchasing firm TechTarget announced a set of enhancements to its Priority Engine service “that vastly improve ABM performance, increase sales productivity and maximize demand generation success for enterprise B2B technology organizations.” Amongst the enhancements are improvements to the user experience, a new Salesforce widget, persistent URLs, list assignments, user roles, and improved topic filtering.

Priority Engine combines executive intelligence with purchaser specific demand signals spanning 10,000 IT Topics across its technology research sites.  The service marries HG Data technology intent intelligence with DiscoverOrg contacts, Owler firmographics, and TechTarget intent data and prospects.  Priority Engine assists sales and marketing professionals by “expanding access to total buying teams at active accounts and showcasing rich purchase details such as installed technologies, vendor shortlists and specific, relevant topical interests.”

Priority Engine is GDPR compliant across its 18 million professional profiles who have opted into TechTarget partner marketing programs.  Furthermore, because TechTarget has opted-in user profiles, it is able to provide intent data at the individual level.  This contrasts with other intent networks which gather anonymous intent information at the company level.

User Experience enhancements include a left-side navigation menu and search bar.  The navigation bar provides account list management, export functionality, and export monitoring.  The search bar provides a type-ahead company list to expedite account searching.

Account profiles contain Owler headquarters information along with a business description, logo, sizing data, and social media links.  Also displayed in the business summary are an account interest gauge, Buying Team counts, Vendor Interests based upon downloaded vendor content, and Top Interests.  The account Interest gauge evaluates site readership (number of readers, type of content, scope of vendor interest) to determine whether the prospect is Evaluating Vendors, Ramping Up, or Not Active in the segment.

TechTarget also offers a set of intent signals based upon readership patterns: Widespread, Sustained, Late Stage, Stakeholder, and Cross-Vendor.  According to the firm, “the more blue dots that are lit up, the more focus sales should commit to the account.”

TechTarget Priority Engine Intent Signals
TechTarget Priority Engine Intent Signals

At the top of each Account Profile are the licensed segments.  Sales reps can click on any of the segments and the profile is filtered for the segment across TechTarget Buying Teams, DiscoverOrg Contacts, HG Data products, and the business summary.  TechTarget offers 300 technology market segments with over 200 available for North America.

Priority Engine users are now assigned to one of three roles: Administrators, List Builders, and Read-Only.  Administrators have full system functionality along with account management responsibilities.  Both Administrators and List Builders can build and assign account lists to other users.  Only Administrators can export records.  Priority Engine suggests that Administrators are usually marketers and that List Builders are typically Sales Managers.  View only users would be inside sales reps that would be working account lists but not building them.

Account List Building was redesigned with reorganized and expanded filters displayed on a single page.  Filters have been separated into common and advanced screens with common filters spanning firmographic, technographic, and intent variables.  Advanced filters include Last Touch, Purchase Signals, and HQ location.  Within any filter, users may select Includes Any (OR), Include All (AND), and Exclude (NOT) Boolean logic.

Users can also rank results by market segment.  Most Priority Engine subscribers have between one and five licensed segments.  Except for the largest technology firms that operate in many segments, the firm contends that focusing on key segments provides better results than including adjacent technology segments.

Previously defined lists are available for both suppression or sub-list targeting.

TechTarget Priority Engine List Building
TechTarget Priority Engine List Building

Lists are ranked according to intent signal strength for a market segment.  Clicking on a different segment results in a different set of priorities.

The new Ranked Accounts list view includes the navigation bar along with company logos, the top areas of interest, and the company most influencing the account over the past 90 days (based upon TechTarget content viewing patterns).  Clicking on any account takes the user to the account profile.

The persistent URL provides a direct link between sales and marketing platforms to the Priority Engine Dashboard.  “The sales-to-marketing handoff can be one of the most challenging aspects of implementing modern marketing strategies, especially ABM. To properly inform and empower salespeople, you must be able to pass along valuable account-level insights with each lead — and few systems or workflows support this,” said Michael Cotoia, CEO, TechTarget. “Priority Engine addresses this challenge by providing a persistent and portable account link that can be embedded within any existing sales or marketing systems.”


Please continue to Part II which discusses the Priority Engine Salesforce connector, product repackaging, and market momentum.

E-Mail Guessing Strategies Work Poorly

I’ve long suspected that email guessing strategies based upon corporate email templates are risky.  If the hit rate is low, you can quickly undermine your sender score and hurt your firm’s ability to communicate with customers and prospects.

Almost every sales rep does it as a quick workaround.  Hell, I’ve done it.  But, as a strategy for building marketing datasets, it is a dead end.  When sales reps do it, there is a high probability that their well drafted email will bounce.  When marketing does it, they will kill their email deliverability.

Two companies provide evidence to the failure of this strategy — DiscoverOrg and SalesLoft.

SalesLoft offered the Prospector service in 2014. It was a gerry-rigged Google search of LinkedIn that employed an email guessing strategy. The service was discontinued when CEO Kyle Porter decided to focus on Sales Engagement.
SalesLoft offered the Prospector service in 2014. It was a jerry-rigged Google search of LinkedIn that employed an email guessing strategy. The service was discontinued when CEO Kyle Porter decided to focus on Sales Engagement.

SalesLoft began as a LinkedIn scraping service that employed Google to build lists and then utilized email guessing to enrich the lists with dubious quality emails.  SalesLoft Prospector grew into a multi-million dollar business, but CEO Kyle Porter saw the business as unsustainable.   Instead, Porter used revenues from Prospector as a financial bridge for building out a sales engagement Cadence service which has grown rapidly.  Porter describes their service as “sincerity at scale.”

Yesterday, they announced the acquisition of partner SalesNinja which provides integrated meeting analytics for their sales engagement platform.   The tool transcribes and tags meetings for sales coaching, new hire training, and meeting note searching.  The goal is to improve sales efficiency and efficacy while identifying best practices.  Instead of dubious lists, the firm is looking to build quality conversations between sales and prospects.

SalesLoft’s mission is to “enable salespeople to sell with true intent and sincerity,” said Porter several years ago.  “The concept of getting a good prospect list and pounding it to death is old, trite and has become a terrible strategy and drag on our customer’s brands. We have never intended to participate in that process. SalesLoft Cadence is a different process, creates a different relationship, much different results and is executed by professionals with professional solutions.”

DiscoverOrg was never tempted by such strategies and employs a large editorial team to research and maintain executive profiles.  In a recent test of 2,700 editorially gathered emails that were also SMTP verified, DiscoverOrg found that basic template guessing was only 62.4% accurate.  When nickname substitution was employed, the rate only rose to 66%.  When they analyzed the incorrect guesses, they came up with multiple reasons for failure:

  • Large companies have multiple email formulas
  • Brands and subsidiaries create complications
  • Subdomains are becoming more popular in email addresses
  • Some companies use multiple email domains for different roles
  • Nicknames are very common
  • Middle initials and middle names
  • Duplicate names
  • Foreign names
  • Secretive email formulas

“A lot of data providers offer ‘confidence levels’ or likelihoods that a specific email is good,” blogged DiscoverOrg SVP of Data and Research Derek Smith.  “They’re just peddling their own guesses. Anybody can pass along their best guess at an email. Real sales intelligence gives you accurate, actionable data that won’t result in a bounce of your carefully crafted prospecting message.”

In the end, prospecting shortcuts are problematic.  The best sales and marketing professionals employ accurate data and insights for their messaging.  Furthermore, in the era of GDPR (three days from now), you can’t have explicit consent to communicate with an EU citizen when you are guessing at how to contact her.


DiscoverOrg Study