TechTarget, which offers both IT media sites and technology sales and marketing intelligence, posted $31.5 million in Q2 earnings, up 18% year-over-year. Growth was driven by their Priority Engine Technology Sales Intelligence service which grew revenues 60% year-over-year. The firm noted that “revenue growth continues to be driven by our leadership position in purchase intent data and our customers’ transition to becoming data driven sales and marketing organizations.”
IT Deal Alerts revenue was up 21% to $14 million as the customer base grew from 500 to 600 clients. The firm also signed more than 40 new Priority Engine clients in the quarter (to approximately 250).
The new Priority Engine enhancements, which were released in early May, have been “well received in the market place.” New features included improvements to the user experience, a new Salesforce widget, persistent URLs, list assignments, user roles, and improved topic filtering.
Furthermore, Priority Engine is shifting the firm to a recurring revenue model with 34% of revenue now attributable to longer-term contracts. Approximately 80% of subscription revenue comes from medium and large firms and 20% from smaller firms, “typically VC-backed start-ups.” The revenue renewal rate for medium and large customers is “well over 100%,” said the firm in its earnings press release. “Those customers are finding great value in our purchase intent data and are renewing and buying more from us at high rates.”
However, TechTarget has a higher churn rate on smaller customers due to common issues inherent to smaller firms such as “changing go-to-market priorities, budget or funding reductions, personnel turnover, etc.” The issue of small customer churn exists for both their core services and longer-term contracts. To reduce churn, the firm is taking three steps: improving the ease of use of products; expanding their Customer Success team which owns customer on-boarding, training and monitoring; and building a dedicated sales team responsible for renewing and upselling. Splitting sales into hunters and farmers will allow the “existing sales team to hunt for new opportunities.”
Bombora partnered with Marketo to natively integrate its intent file into the Marketo Engagement Platform. Bombora collects anonymous company-level activity from B2B media sites and determines intent as a company surge score across 4,100 B2B topics and 2.8 million companies. The surge score indicates an uptick in baseline interest in customer-specific B2B topics.
The intent scores help identify and prioritize sales and marketing activities around prospects with active purchasing research programs. Firms with high surge scores can then be targeted for programmatic marketing, digital messaging, and sales outreach. Surge data also flag dormant accounts which are re-entering the purchasing cycle, assist with messaging around key topics, and inform lead scoring and routing decisions.
According to Bombora, only fifteen to twenty percent of companies in a target list are engaged in an active purchase cycle. Thus, understanding which companies are in market is critical to marketing effectiveness. “It arms you with insight into which of your target companies are more actively researching your products or services compared to historic baselines – indicating intent to take action,” said Bombora.
“With the Marketo Engagement Platform acting as the hub to make this understanding more actionable, there is exponential value to how Bombora’s intent data can be leveraged across an organization,” stated Bombora CEO Erik Matlick.
“As a marketer, the best buyers to engage with are the ones that are already actively researching,” said Marketo SVP of Strategy and Alliances TK Kader. “Providing intent data from Bombora to our customers creates an opportunity for them to engage with buyers who have a high propensity to buy, ultimately delivering better pipeline to sales and increasing the velocity of the sales process.”
Marketo is also offering best practices and campaign setup advice.
Predictive Analytics company Mintigo unveiled its new MintigoAI service. Mintigo describes their solution suite as “a comprehensive intelligent customer engagement platform powered by AI” for mid-size and enterprise companies to “drive greater pipeline and revenue.” The “customer lifecycle solution” includes CRM and MAP connectors, ABM targeting tools, inbound lead enrichment and prioritization, upsell / cross-sell recommendations, and a new Buying Stages capability.
Buying Stages determines where accounts and leads are in their buyers’ journey. The solution assesses lead enrichment, fit, intent, and behavior data to determine customer intent and stage. Data is sourced from 1.7 billion user interactions per day spanning 13 million global companies. Buying Stages tags accounts into three categories: Target (based on fit), Awareness (based on intent), and Consideration (based on behavior). Buying Stages evaluates the “aggregate actions of leads” and weighs both anonymous web traffic and site visit activity. Mintigo also factors in firmographic, technographic, and social intelligence.
“To plan, strategize and execute B2B marketing effectively in today’s world, marketers need a high-definition view of their customers,” blogged CEO Jacob Sharma. “Using AI and predictive analytics, we built MintigoAI to mine billions of data points and identify the set of insights that make a company’s actual customers unique. These insights range from hiring patterns to technology installs to firmographic data, and much more. The result of this process is the ICP, which MintigoAI uses to identify right targets within existing marketing databases and proactively discover new high-propensity targets that display the ICP characteristics.”
Lattice Enginesannounced commencement of a private beta for its Atlas Customer Data Platform (CDP). Lattice Atlas matches internal and Lattice Engines data sources, provides a single view of the customer, and supports a centralized audience platform for cross-channel creation and measurement. The formal launch is planned for the end of the year.
According to Lattice Engines, “Marketing organizations struggle to scale their Account-Based Marketing (ABM) programs because each application they deploy has its own data, segmentation, activation and measurement modules. This has led to a fractured buyer journey because banner ads, social ads, emails and sales calls communicate different messages, which creates confusion. Lattice Atlas solves this problem directly by integrating all the application data into a single place and providing the ability to manage this data, segment on it, and activate it through open APIs.”
“A CDP connects existing systems to create a unified customer view that makes ABM possible. In a world that never stops changing, the power and flexibility of a CDP will help marketers deliver on the promise of ABM. The features you need in a Customer Data Platform (CDP) will depend on your business, existing systems, and intended use. There are a few key considerations when evaluating CDP solutions for executing ABM programs, including a unification of all data sources, segment creation, campaign execution and predictions.”
David Raab, founder of the CDP Institute
Lattice contends that ABM at scale requires a CDP supporting four key attributes:
Unified Customer Data: After aggregating and consolidating customer data, a CDP must link identity, behavior, purchase history, and firmographics.
AI-driven Audiences: The CDP must not only score accounts and contacts, but identify buying committees, assess buying stage, and recommend the next-best offer.
Omnichannel Activation and Personalization: The CDP suggests highly personalized campaigns across relevant channels. The messaging must remain consistent across all of the channels.
Enterprise Grade Governance: The CDP maintains data security and privacy while complying with relevant laws such as GDPR.
Lattice Atlas aggregates client data across platforms and appends it with data from the Lattice Data Cloud. First-party content is gathered from CRM, marketing automation, web visitor logs, transaction histories, product usage details, etc. The Lattice Data Cloud enriches the customer view with firmographics, intent data, and technographics. Lattice also maintains an ABM Identity Graph which organizes customer data by account, buying center, and contact.
“Lattice Atlas was a natural evolution of our platform,” blogged VP of Products Chitrang Shah. “Since day 1, our approach has focused on being deeply integrated with each execution application and managing all data under one platform. Because of this we not only capture the largest amount of data, but also all that relevant metadata that describes it. Lattice Atlas is built on our understanding of these applications and their data to create the first CDP for enabling ABM at scale.”
Audience creation tools predict conversion likelihood, purchase window, and likely spend. Atlas also supports next-best targets and next-best actions.
Lattice Atlas connectors support Marketo, Eloqua, Salesforce, and a set of REST APIs.
Other features include GDPR opt out for campaigns and all marketing communications, engagement thresholds to prevent marketing fatigue, and lead-to-account mapping.
The initial Atlas application will be Playmaker which offers prescriptive recommendations to sales teams. “Playmaker lets them quickly identify top products to sell across all audiences and programmatically deliver those recommendations to the sales teams,” said Shah. “It also has built-in interactive dashboard to track the engagements (or lack of it) and its impact on the pipeline, enabling out-of-the-box visibility into play ROI measurements and the ways to improve it.”
“The holy grail of B2B marketing is creating 1-to-1 experiences across the entire buyer’s journey. This is why the B2B world is so interested in ABM these days. In order to craft personalized experiences at scale, our customers need a data foundation to better understand their target audiences, and an execution platform to engage those audiences in meaningful ways. With Lattice Atlas, we now enable companies to engage their buyers with 1-to-1 omnichannel experiences, making B2B marketing as personalized as B2C marketing,” said Lattice Engines CEO Shashi Upadhyay.
Lattice has over 200 customers including PayPal, Adobe, Dell, and SunTrust Bank.
On Monday, Radius Intelligence and Leadspace announced their merger and plans to become the “leader in B2B data intelligence.” The firm, which will continue under the Radius brand, is no longer emphasizing predictive analytics.
The predictive analytics market has failed to develop as a standalone segment. According to Radius Chairman Darian Shirazi, the total investment in the space was over $600 million. However, Gartner sized the market at $100 million to $150 million in 2016 revenue, suggesting that the promise of predictive analytics was developing slowly.
In his just released 2018 MarTech Landscape, Scott Brinker removed Predictive Analytics as a segment as machine learning is being integrated broadly across marketing products.
For B2B predictive tools to work, they require high quality reference data sets for initial and ongoing enrichment, but the predictive analytics companies black-boxed their data sourcing. Radius was one of the few exception to this opacity as they were transparent about their data acquisition model (web crawling combined with a customer contributed data model), but most of the other firms have been vague about their data models.
The predictive analytics companies were also slow to offer ABM tools and similar company and contact recommendations. These features are now commonly offered by both predictive analytics companies and sales and marketing intelligence firms such as D&B Hoovers, InsideView, DiscoverOrg, and Zoominfo. What’s more, the sales and marketing intelligence firms have all developed light predictive scoring or ranking tools. While none of these firms approaches Radius or Leadspace in predictive capabilities, they all provide company and contact insights for sales reps, ABM tools for sales and marketing, and integrated data enrichment processes.
The predictive analytics firms also initially black boxed their models, preferring to hide complexity. They have since become more transparent and begun displaying the top reasons for recommendations. However, Salesforce Einstein has provided similar functionality with predictive scores and insights.
Todd Berkowitz of Gartner summed up the situation well.
I’ve been covering the market for B2B predictive marketing analytics for almost four years. A few years ago, predictive lead scoring was all the rage. Then it became about fit and intent models for demand generation and prospecting. Then these tools were used for selecting accounts for large-scale ABM programs. But in the end, the standalone market for these applications never fully reached its potential. Many of the original vendors got acquired for their technology (Fliptop, SalesPredict, Infer and others) and predictive scoring became a standard feature of marketing automation and SFA systems.
Just because the standalone market went away, doesn’t mean there isn’t a lot of value here. In fact, the solutions have essentially moved into two other markets (and you’ll see this reflected in our upcoming Hype Cycle reports). On one end, you have the Data Intelligence for Sales market where predictive and AI-driven solutions are competing with traditional data vendors for demand gen, prospecting, and segmentation use cases. On the other end, you have the broader ABM solutions market where these applications not only help with account selection and planning, but are moving towards engagement and orchestration.
Berkowitz predicted that one or two of the remaining predictive analytics vendors will be acquired in the next six months.
With over 6,000 MarTech companies, the market is quite fragmented. Although the MarTech sector continues to expand, there is already momentum towards consolidation as clients look for broad, integrated functionality instead of many point solutions. For example, marketing and sales departments adopting ABM need a broad set of functionality which includes
AI scoring and recommendations
Real-time, batch, and continuous company and contact enrichment
Data hygiene (e.g. de-duplication, data standardization, and verification services)
Third-party verticalized data enrichment
Website visitor id
Look-a-like company and contact prospecting
Segmentation, TAM, and pipeline analysis
CRM, MAP, and sales engagement connectors
Account social media monitoring
Company and contact intelligence
At this point, nobody offers a full suite of these ABM capabilities for sales and marketing departments.
On Monday, Leadspace and Radius Intelligence announced their merger. The two firms were early entrants into the predictive analytics space, but the market for standalone predictive intelligence services has not developed as predicted. Thus, VCs and private equity companies are sitting on large bets that have yet to pay out.
The merged company will continue under the Radius brand as the “leader in B2B data intelligence.” Leadspace CEO Doug Bewsher will take over as the CEO of the merged firm while Radius founder Darian Shirazi will assume the role of Chairman. The two positioned the merger as a coming together of firms with complementary assets across company (Radius) and people (Leadspace) intelligence.
“Radius and Leadspace as one company will deliver a standout go-to-market platform with the best data, artificial intelligence and integrations at its core… What’s truly exciting is that our mission remains the same. Radius will be the nucleus that powers data and intelligence across all B2B applications, channels, and users — now built on The Global Network of Record.”
Radius Intelligence Statement to Customers
Both Leadspace and Radius have edged closer to prospecting and data enrichment than other predictive vendors. Leadspace has long offered contact enrichment and prospecting, even appearing in a 2015 SiriusDecisions report on Contact Data Management. Meanwhile, Radius has built its own database of US company and contact data which it named “The Network of Record” and positioned as the “single source of truth for account data.” The Radius database spans 18 million US companies and 25 million contacts with verified emails and direct dials. Radius also offers digital ad targeting.
Radius is positioning itself as being at the center of B2B predictive analytics, B2B Audience Management, and B2B data management. However, several of the data solution vendors also offer advertising solutions including Infogroup and Dun & Bradstreet. (Source: Radius Intelligence)
The new Radius will help sales and marketing teams “find the right data on the right buyers, and reach those buyers across any channel.” Revenue teams will have access to the “industry’s most comprehensive data intelligence solution.” Features include account and people targeting, data management, ABM execution, and integrations with Salesforce, Microsoft Dynamics, Marketo, Eloqua (Oracle Marketing), and Pardot (Salesforce).
Shirazi is positioning the company as an Einstein competitor with expanded assets to compete against Salesforce. “We’re excited about this because it will create the largest number of customers, largest revenue base and really provide a company that is at scale in B2B data and intelligence,” said Shirazi. “The only other major player in this space we believe is Salesforce Einstein, and we’re excited to really give them a run for their money.”
Shirazi provided the following list of planned enhancements to be rolled out over the next year:
Master Data. Master Growth
Extend reach and accuracy as The Network of Record unites with Leadspace’s proprietary, real-time virtual database sourcing
Take complete control of data governance with added data dashboard functionality
Enhance data matching and append for contacts, as well as lead-to-account matching features
Real Intelligence. Real Buyers
Strengthen targeting on individual decision makers in both the U.S. and international markets
Access enhanced segmentation, scoring, and insights on contacts
Leverage features from two effective sales intelligence tools
Scale Channels. Scale Revenue
Expand audience reach with the largest deterministic reach of any platform
Source more contacts with even higher accuracy and contactability rates
Connect more channels with more seamless integrations and partners
Shirazi describes Radius as the next “backbone go-to-market platform.” The combined assets “will enable marketing, sales, revenue ops, and customer insights teams to finally address their data gaps and conquer their targeting challenges. We will create a standout solution in a crowded, fragmented space of point-solutions where customers are forced to stitch together multiple products or change vendors every year.”
Back in 2015, Radius Intelligence had a market value of $500 million and funding of $107.6 million. Leadspace never disclosed a valuation, but it received $59 million in funding with a $21 million Series C in December.
LinkedIn lists 100 Leadspace employees and 160 Radius employees.
The merged company has over 200 customers including Sam’s Club, Hewlett Packard, Microsoft, Comcast, MetLife, and American Express. Both firms maintain “innovation centers” in San Francisco and Israel.
Sales Engagement vendor Outreach is teasing a new predictive analytics capability called Amplify which leverages the history of a firm’s sequences and workflows. The firm will not be employing a black-box AI strategy but providing recommendations with explanations.
CEO Manny Medina faults deep learning strategies which lack “the ability to make inferences, such as the ability to figure out why things work” and require users to trust the recommendations without providing a basis for the suggestions.
“We believe we need to tackle this problem following general scientific principles. Hypotheses need to be testable, data should be very carefully examined to verify the quality of the data.”
Yifei Huang, Machine Learning Lead, Outreach
“When we built Amplify, we built it with the core belief in mind that, the human needs to understand why things work so that machine can understand why things work so that the machine can get better at helping the human,” said Medina.
For example, Amplify deploys natural language processing (NLP) around email responses to help identify whether responses are unsubscribes, objections, or positive. Outreach claims that their NLP classification is 92% accurate, only three points behind manual classification.
NLP will also be used to assess objection handling to identify reps who handle objections well and which ones need improvement. This feedback is then available to managers to assist with coaching.
Amplify addresses two key managerial questions: “Is my team adopting the new technology? Is the new technology delivering a measurable lift?”
Amplify will be unveiled at their May Unleash conference.
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 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.”
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.