TechTarget Priority Engine: Strong Q4 and Product Enhancements

Priority Engine combines Intent data with predictive analytics, technographics, and contacts.
Priority Engine combines Intent data with predictive analytics, technographics, and contacts.

Technology media company TechTarget announced strong Q4 growth for their Sales Intelligence Priority Engine service.  The firm added over 40 new Priority Engine and Deal Data customers in Q4 with revenues more than doubling year-over-year.  Priority Engine benefited from the addition of DiscoverOrg technographic and contact intelligence during the quarter.  The service combines intent, predictive, and contacts intelligence into a single solution.  Intent data is sourced from their 140 B2B media tech web sites containing 550,000 indexed content pages, many of which make the first page of Google technology searches.  Each day, the firm has one million buyer interactions tied to its 17 million members which it then tags to 10,000 technology topics.  The majority of members have technology titles, but TechTarget also supports five million non-IT members.

Content is available in English, Spanish, French, German, Portuguese, Chinese, and Japanese.

TechTarget claims that its hand-indexed, technology-focused editorial content results in a better indication of technology intent than machine-indexed intent files built across a broader set of B2B media sites.  Furthermore, because TechTarget has member ids associated with site activity, they know who at each company is researching specific topics, providing surge data tied to specific individuals.  Other intent vendors provide anonymous intent.

“Real purchase intent insight is actually made, not scraped from general-purpose websites.  It begins with relevant, useful content that provides critical value to professionals as they look to solve business challenges and make buying decisions. By observing and learning from their content consumption patterns as they happen, marketers can market and sellers can sell at the right time with greater relevance. Our ability to deliver real purchase intent starts with our extensive content footprint and the hyper-relevant audiences that we’ve built.”

  • TechTarget CMO John Steinert

Priority Engine identifies “vendors actively influencing this deal,” core and related topics, and products and vendors.  Installed product and vendor data is licensed from HG Data and viewable by category.  Users can also search installed technology at an account by product, vendor, and category.

Accounts are ranked on a weekly basis with the service providing “an early radar on who’s buying from your named account lists.”  TechTarget provides real-time analysis of the “most active accounts and named prospects conducting purchase research” and ranks those accounts by “likelihood to engage.”  Prospects are segmented by geography and hundreds of marketing segments.  The solution “creates a world-class ABM solution that combines breadth of reach, purchase power insights, and the ability to pinpoint and influence key prospects in one place.”

By combining DiscoverOrg contacts with member search data, Priority Engine provides “direct access” to the demand units of named active researchers and key influencers.  Joint customers will have full access to DiscoverOrg’s editorially verified decision makers alongside TechTarget contacts that are conducting active research.  The partnership displays the “Target Buying Team within a single dashboard.”  Priority Engine customers that have not licensed DiscoverOrg will be limited to ten names per account.

TechTarget announced a set of enhancements last month which includes weekly contact updates, Marketo integration, regional subscriptions (North America, EMEA, United Kingdom/Ireland, APAC, ASEAN and India), and integration with internal datasets such as sales territories and web site visitors.

“We’ve moved beyond company-level insights; Priority Engine gives you access to ranked accounts AND the actual buyers researching purchases at those accounts,” said TechTarget SVP of Products Andrew Briney. “The unique purchase intent insight available within Priority Engine helps marketers generate demand more efficiently, accelerate ABM effectiveness, and deliver a more substantive contribution to sales.”

Artesian CEO Andrew Yates: Technological Disruption, AI, and Data Insights

Arti responds to

Artesian CEO Andrew Yates recently discussed Artesian Solutions with Sudipto Ghosh as part of the MarTech Interview Series. Artesian was founded to help resolve the disparity between B2B buyer and seller tools. “We saw that businesses had transformed the way they buy, but that sellers had not adapted. This mismatch led us to create a vision of better B2B sales engagement that is customer-centric at its heart, and to develop the world’s most powerful customer intelligence application to support it.”

Yates described technology as “the biggest disruptive force in the world” and his entrepreneurship as “a desire to disrupt the status quo, solve problems, remove complexity and make a difference.” He sees Artesian Solutions as a “disruptive force for good in our sector, providing engagement smarts for companies and markets in the same way that LinkedIn has done for people insights.”

Artesian is incorporating new AI technologies into its platform including the Arti chatbot based upon IBM Watson. As they are doing so, they are repositioning from Social Selling to “A.I.-powered sales intelligence.”

Yates warns that businesses look for CRM platforms to help customer facing departments build customer-centric businesses and a full customer view. Often, though, they become frustrated when CRMs do not provide the desired customer experience and engagement. But CRMs are only as good as the data entered into them and are subject to ongoing data decay. Further compounding this issue is

“the sheer volume of data businesses need to grapple with. Often unstructured, this data is increasingly hard to find, rationalize and interpret. Inaccurate or out-of-date data has several inevitable consequences. Take-up and enthusiasm for CRM input wanes as the volume of data increases, and time spent just keeping up-to-date with existing customer data impacts negatively on time spent researching and acquiring new ones. Opportunities to respond to real-time customer news and market insight are missed, and customers looking for instant action and results are left disappointed. Likewise, deals are lost through mistakes, and errors in messaging and targeting become more frequent. Forecasting accuracy diminishes as emerging trends go unnoticed.”

Yates recommends working with a data partner that provides a full view of customers and contacts, including contextualized customer insight; news, market trends and social media monitoring; real-time intelligence; and single sourced company and contact profiles with “social profiles, opinions, and expectations.”

Full Interview

Leadspace: Series C, AI, and ABM

LeadSpace Use Cases
LeadSpace Use Cases

Predictive Analytics and Audience Management vendor Leadspace completed its Series C.  The funding round was led by Arrowroot Capital and joined by JVP.  The $21 million round will be used “to grow our customer team in San Francisco and Denver, and our AI and data management product teams in Israel.”

The firm is assessing additional locations, including possible offices on the East Coast and Europe, “perhaps” London.

Arrowroot has taken a seat on Leadspace’s Board.  The firm wanted growth equity advisors instead of traditional VCs for Round C.  “At this point the investment is not just in the idea and the team, but also the underlying metrics and performance of the business,” said CEO Doug Bewsher.  “Once you have “Product/Market fit”, the kinds of questions investors ask are whether you are ready to scale; what are the opportunities for further growth; and apart from additional investment can we be an investment partner that can help you address these opportunities?”

Bewsher noted that marketing has been transformed over the past seven years since Leadspace was founded.  Firms are switching from tactical demand generation programs to targeted Account Based Marketing (ABM) communications.  “No longer is it OK to just send out blanket “nurture” emails to everyone and hope that will generate positive customer engagements. No longer can you rely on a single data source as the basis to know your customer. No longer is it enough for marketers to just think of leads — they need to market to accounts, and teams of people. Neither can marketers afford to ignore intelligence and information from external parties, and simply rely on the limited info they gather internally.”

Not only has the nature of B2B marketing been transformed, but “world class B2B sales and marketing organizations” need to become more like consumer companies with a deep understanding of the account at multiple levels.  Echoing Sirius Decisions, Bewsher said that B2B marketers need to “really know your customer at the account, demand unit and individual level, and then target and personalize your messaging to cut through the noise. And think customer-first.”

As an analytics company, Bewsher talks up the value of AI for sales and marketing as it begins to address specific problems and workflows:

AI is everywhere. While there is no doubt that it is going to change every corner of our life, both as private users and business people, I think we will start to move from the promise to the reality in 2018. In business-to-business sales and marketing in 2017, it was enough to say: “We have a ton of great data scientists who are working on new ways to better engage your customers.”

But in 2018 customers will look to see actual results — like the 90 percent increase in email connection rates we have seen from the deployment of AI to recommend the right way to engage a specific user. This will require a maniacal focus on specific use cases from the emerging area of AI.

One area where AI will improve revenue generation effectiveness is in ABM programs which has been limited by the human ability to consume information and the historical lack of data availability.  However, “AI is changing all this, with the ability to consume and understand unprecedented amounts of information and turn this into action at scale and in real time. So sales and marketing teams now have the opportunity to drive much more relevant and effective engagement programs for their entire potential target audience.”

According to Leadspace, they are trusted by over 130 B2B brands and seven of the top ten enterprise software companies.  Clients include Microsoft, Marketo, Oracle, and RingCentral.

 

Dreamforce Keynote: The Fourth Industrial Revolution

One of the key themes of Dreamforce 2017 was the ability of companies to customize the branding and content within Salesforce clouds via "clicks, not code."
One of the key themes of Dreamforce 2017 was the ability of companies to customize the branding and content within Salesforce clouds via “clicks, not code.”

The theme of this year’s Dreamforce was The Fourth Industrial Revolution.  Following after revolutions driven by steam, electricity, and information technology, the fourth industrial revolution blurs the “physical and digital worlds” creating a wave of “innovation in technology” which is transforming the economy, society, and lives while creating new jobs, industries, and opportunities.  This next wave is based upon intelligence.  Elements include IoT, 3D printing, biotech, robotics, autonomous vehicles, nanotechnology, and quantum computing.

“This is what we call the fourth industrial revolution,” said Salesforce CEO Marc Benioff. “There’s all these amazing new technologies, things like autonomous vehicles and artificial intelligence and nanotechnology and mobile computing and all these things are really hitting at once. And companies are really transforming themselves and bringing all these new technologies in really to connect with their customers in new ways.”

Thus, elevators loaded with sensors now communicate back to the manufacturer and predict failures, calling for service prior to trapping people.  Likewise, with tires, “if the tire blows, nobody knows; but in the future, if the [smart] tire blows, everybody knows.”  So, firms like Kone (elevators) and Michelin (tires) are now B2B2C companies.  In the future, if a tire is about to blow, it will communicate to the autonomous vehicle to pull over.

“Every company is getting closer to their customers.  We’ve been talking about this for years.  It doesn’t matter if you’re a B2B company or a B2C company, everybody’s becoming a B2B2C company.”

Salesforce and its customers are “delivering personalized one-to-one engagement at scale,” said Stephanie Buscemi, EVP of Product Marketing.  This is done “declaratively, with clicks and not code.”  Through the Salesforce Data Management Platform, ads are customized and delivered cross-device, allowing companies to redisplay ads or present new advertisements to their customers and prospects.

Benioff cited a series of companies providing customer service and support through Salesforce platforms including Louis Vuitton, Marriot, Coca-Cola, T-Mobile, Adidas, and Ducati Motorcycles.

“Behind all these things…behind everything is a customer.  And that’s what all of us do.  We are working to connect with our customers in an incredible new way.”

Simplified customization, development, and branding were emphasized during the keynote.  A set of customizable products provide a “smarter, more personalized Salesforce”:

  • MyTrailhead service supports custom branding, content, and learning paths that allows firms to onboard and train employees on desktops and phones.  Tools include quizzes, reference links, trails, and badges.  Salesforce Trailhead content is also available.
  • MyEinstein provides an artificial intelligence layer driven declaratively by “clicks, not code” supporting “smarter capabilities including bots.”
  • MyLightning customization provides an app builder with custom pages, a Lightning theming and design system, Lightning Flow, Components, and Bolts which operate automatically on both desktops and phones.  Designers will have access to dynamic components which are conditionally displayed.
  • MySalesforce branded “mobile apps without code” can be uploaded to the Google Play and App Store.
  • MyIoT supports native integration capturing real-time events, business rule automation, and low-code orchestration.

Based upon customer feedback, SFDC has shifted from IoT as a separate platform to an integrated feature of the CRM platform which also operates “declaratively without code.”

Benioff admitted that the Fourth Industrial Revolution is creating concerns and wondered whether it is “uniting us or dividing us.  Are we more connected or somehow less connected?”

He also asked whether there is more or less equality in the World.

“There is this stress being created by this fourth industrial revolution.  Yes, we have this promise of this new connected World.  But what is it doing to us? And what are other actors doing around the World using these technologies?  Are they changing our society?  Are they changing our elections?  What are they doing with this technology?”

Benioff is looking at the Trailblazers attending Dreamforce as the Customer Innovators, Technology Disruptors, and Global Shapers to ensure that the next wave is directed in a positive direction.  “You have all these new tools at your fingertips, these incredible new technologies, but you are doing some amazing things in the World.  You are changing your companies.  You are steering this technology in the right direction.  I’m so confident in who you are.  I’m so confident in what’s in your hearts and where we are all going.”

Benioff noted that most technology is generally neutral in it effect upon society.  It is therefore incumbent upon technologists, developers, and companies to deploy technology in a socially responsible manner which promotes greater equality.  Benioff called for companies to fight for equality through equal pay, investing in schools, and opposing discriminatory laws.  He also noted that it is the poor who are most hurt by environmental degradation and proudly stated, “we are a net zero cloud.”

IDC CRM Market Share (Courtesy: Salesforce 2017)
IDC CRM Market Share (Courtesy: Salesforce 2017)

Benioff was also proud to have founded and led the leading CRM with an 18.1% market share (2016 IDC) nearly double that of Oracle (9.4%).  Salesforce has the top solutions for sales (34.2%), service (33.7%), marketing (9.9%), and Platform-as-a-Service.  Within the marketing cloud, Salesforce claims to offer the leading Data Management Platform and commerce Platform.

What’s more, the firm is on track to be the fastest enterprise software company to hit $12.5 billion in revenue.  They hit $10 billion this year and have FY19 guidance of $12.5 billion in year 20.

One of the issues facing businesses and policymakers is an increasing skills gap.  Benioff proposed MyTrailhead as one of the tools to help address the problem of workers across many industries and skill levels.  MyTrailhead provides a customized, branded training platform.

TechCrunch complained that this year’s Dreamforce lacked drama as it lacked new initiatives such as the social enterprise, artificial intelligence, and IoT.  “They are a company that embraces the cutting edge, but this year lacked that kind of big announcement,” complained enterprise reporter Ron Miller.  To be fair, though, the company has rolled out a series of new platforms, clouds, and acquisitions over the past few years.  A year with few fireworks is not necessarily a year without forward progress for Lightning, Quip, Einstein, Trailhead, and platform customization.

The conference remains a monster with 170,000 registered participants joining in San Francisco and millions of online views.


This was the beginning of my weekly newsletter coverage on Dreamforce.  Please contact me if you’d like a free trial subscription.

Ignite Technologies acquires Infer

Infer Account Based Behavior Score
Infer Account Based Behavior Score

ESW Capital completed the acquisition of predictive analytics vendor Infer and will be rolling it into Ignite Technologies. Infer offers predictive lead and account scoring. Use cases include TAM identification, segmentation, account selection, demand generation, lead scoring, opportunity scoring, and upsell/cross-sell. In a September 2016 report, Gartner said that Infer pricing starts at $30,000 and increases based on the number of models. There are also charges for net-new contacts.

This summer, ESW also acquired company intelligence vendor FirstRain and rolled it into Ignite as well.

The Ignite Prime program offers clients access to additional enterprise technology once they have signed a contract for one of the Ignite Technology solutions. For example, Infer customers would have access to additional enterprise software solutions such as First Rain, ThinkVine, and Placeable equal to the value of their Infer contracts.

“We’ve been continually impressed by Ignite throughout this acquisition process. They have a strong leadership team and the right strategy that’s in line with where the future of sales and marketing solutions are going, where there’s a need to converge multiple products into a cohesive platform to drive true, full-circle customer intelligence. We’re confident this is the platform that our amazing customers will want to build on and grow, and are excited for the Infer solutions to be a part of Ignite’s Prime Program which will help customers drive 2x ROI.”

  • Vik Singh, Infer’s CEO

Infer was founded in 2010 and is headquartered in Mountain View, California. Infer focuses on predictive solutions for the technology sector and lists AdRoll, Cloudera, New Relic, Tableau, Xactly and Zendesk as clients. As of Q3 last year, Infer reported over 140 customers. Deal size was not disclosed.

Lattice Engines: Predictive Model Building

The Lattice Data Cloud Explorer highlights the top fields by category and helps admins determine which fields should be exported to other platforms.
The Lattice Data Cloud Explorer highlights the top fields by category and helps admins determine which fields should be exported to other platforms.

Lattice Engines has taken the pole position in the emerging Predictive Analytics space.  In yesterday’s blog, I covered its pricing, value proposition, content, and integrations.  Part two covers model building.

When first launched, Lattice Engines and its peers had long deployments and black-boxed models that required data science expertise.  The firm now offers 24-hour deployments, simplified model building, and greater transparency around models and recommendations.  Furthermore, the system allows marketers to either build their own models or import industry standard PMML files constructed by their data science teams.

Predictive models are built by importing training files which are matched against the Lattice Data Cloud using D&B DUNSMatch logic and Lattice proprietary techniques.  Training models contain examples of both positive and negative outcomes (e.g. win / lose, renew / drop).  A model is typically available within thirty minutes of the training file upload.

Ideal Buyer Profile scores (Lattice’s term which is similar to Ideal Customer Profile scores) are available to sales and marketing and include both scores and recommendations.  Marketing can view the model via a graphical Data Cloud Explorer which highlights the key signals and variables in the model and makes the data available for export to other platforms.

To make the data more actionable for sales reps, Lattice provides Salesforce Talking Points which display recommendations and explanations that include Lattice data, transactional history, and buyer behavior.  A Lattice Buyer Insights CRM I-frame contains Lattice recommendations, talking points, company profiles, company fit, engaged contacts, engagement activity, intent analysis (surging topics), web activity, and purchase history tabs.

Lattice Recommendations with related scores. Sales reps can explore any of the recommendations by clicking on them.
Lattice Recommendations with related scores. Sales reps can explore any of the recommendations by clicking on them.

Future plans include a user interface for segmentation analysis and simplifying intent scoring to high/medium/low.


Part 1: Lattice Engines Overview.

Lattice Engines: Leader in B2B Predictive Analytics

Lattice Scores and Enriched Data are available within the Eloqua Canvas campaign builder.
Lattice Scores and Enriched Data are available within the Eloqua Canvas campaign builder.

In a 2016 survey of predictive analytics companies, Gartner sized the global market at between $100 and $150 million. Although Gartner remains bullish on the sector, the size must be disappointing to both the firms in the space and their investors. One of the early companies in the space, Lattice Engines, continues as a market leader with over 200 global deployments.

Lattice Engines supports both enterprise clients and high-growth companies with deployments beginning around $75,000. Pricing is based upon the number of managed leads or contacts in the instance along with the number of users. With revenue between $25 and $50 million (GZ Consulting estimate), the firm has a strong position in the nascent market.

Lattice Engines combines first and third-party data to build predictive models. External content includes firmographics, intent data, technographics, social data, and web crawled business signals. Content is licensed from leading vendors such as Dun & Bradstreet (WorldBase global company file), Bombora (intent captured from over 3,000 B2B media sites), and HG Data (technographics). The Lattice Data Cloud covers over 200 million global companies, 21,000 buying signals, 100 million tracked domains, and over one billion daily interactions. Internal content spans transactions, CRM, marketing behavioral data, usage data, and support services.

“Predictive analytics is one of the few types of marketing technology that has the ability to solve issues at every step of the funnel, because it aligns sales and marketing against the right targets, and provides them with the right data to create targeted campaigns.  By infusing fit and intent data into our models we enable teams to have a complete understanding of their ideal customer profile, which enhances the programs teams orchestrate against their targets.”

  • Director of Corporate Marketing Caitlin Ridge.

Firms can build multiple models to support various geographies, product lines, and scenarios (e.g. win/loss, upsell/cross-sell, renew/churn). Lattice scores and modeled data are integrated with many of the key SalesTech and MarTech platforms:

  • Ads/Web: DemandBase, Oracle Data Cloud, doubleclick (Google), AdRoll, Facebook
  • MAP: Marketo, Oracle Marketing Cloud (Eloqua), Pardot (Salesforce)
  • CRM: Salesforce, MS Dynamics, Oracle Sales Cloud, SAP

This platform coverage enables Omni-channel ABM campaigns across programmatic platforms, email, direct mail, and field marketing.  Scores, insights, and recommendations are provided to sales reps within CRM i-frames.

“Lattice remains the most visible “face” of the market,” said Gartner analyst Todd Berkowitz in September 2016. “With its focus on security, level of integrations and ETL tools, the company is a fit for enterprise clients (both in high-tech and other industries) and/or companies planning to deploy in multiple regions. Gartner clients report that the company’s go-to-market approach is unique in the way it addresses complex problems and help customers operationalize the insights from the models. Lattice is one of the few vendors that can recommend key plays at both the lead and account level across the entire funnel.”

According to Lattice, customers enjoy a broad set of improved metrics:

  • 2X Higher Conversion
  • 3X Greater Pipeline
  • 35% Higher Deal Sizes
  • 6% Increase in Quota Attainment
  • 85% Rise in Revenue per Customer
  • 20% Reduction in Customer Churn

The firm sells broadly across B2B sectors.  Customers include Amazon, Dell, PayPal, Staples, and SunTrust Bank.


Tomorrow’s blog will cover core Lattice Engines model building and recommendations.