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.

Sparklane Predict 2.0

Predict builds Ideal Customer Profiles based upon Fit (Firmographics), Need (Sales Triggers), and Behavior (Marketing Automation behavioral data) allowing customers to identify both current best-fit accounts and net-new prospects.
Predict builds Ideal Customer Profiles based upon Fit (Firmographics), Need (Sales Triggers), and Behavior (Marketing Automation behavioral data) allowing customers to identify both current best-fit accounts and net-new prospects.

French predictive analytics firm Sparklane unveiled their version 2.0 Predict platform which employs artificial intelligence (AI) and active learning to score millions of companies and determine which prospects are most likely to become net-new customers.  The Predict platform is available for the UK and French markets with localized language and datasets.  A German edition is in development.

Sparklane ingests and enriches company data, matching it against firmographics and trigger events to score millions of companies.  The system then models the Ideal Customer Profile (ICP) and Total Addressable Market (TAM).  Sparklane also identifies “sparks” (hot prospects) based upon sales triggers and delivers real-time alerts, messaging, and contacts.

Models can be deployed for both new and existing business.  New business models can be constructed from historical data (e.g. CRM win / loss flags) or estimated and refined for new market entry.  Existing business data can also be deployed for churn models to help identify companies that are more likely to drop as well as upsell and cross-sell models.

CEO Frédéric Pichard said that employing artificial intelligence to identify your next best customers “is probably the most amazing promise B2B marketing and sales tools can fulfill” as it provides “a new way of working to help our customers be more efficient and successful.”

Sparklane users begin by importing datasets from CRMs or CSV files.  Logic is employed to determine both positive and negative sample records.  For example, a CRM Win / Loss flag could serve as such an indicator.  The file is then enriched and an ICP model is constructed.  The ICP contains three types of variables: Fit (firmographic), Need (Triggers), and Behavior (Marketing Automation prospect activity).  Marketers or Sales Operations are able to view the model and adjust weights.  This model is then employed for constructing a TAM with net-new accounts which can be saved as a fixed account list or dynamic model.

Sparklane onboarded file mapping.
Sparklane onboarded file mapping.

An accuracy score helps define how well the model distinguishes between good and bad prospects.  Thus, an 80% accuracy score indicates that 8 out of 10 companies in the seed file are properly predicted by the model.

An accelerated learning option is available for new market entry.  Thus, if a seed list of good and bad prospects is not available for a new product line or market, an initial set can be manually selected from Sparklane company lists and deployed as a first generation seed list.

An active learning option allows users to perform a qualification pass on a list to help expedite model construction.  While engaged in active learning, the user is shown company profiles which include account overviews, triggers, and family trees.   The marketer can then give a thumbs up or down to each proposed account.

During active learning, sparks can be added, dismissed, or decision postponed, allowing the platform to adjust the model.
During active learning, sparks can be added, dismissed, or decision postponed, allowing the platform to adjust the model.

As output, the platform provides a set of “sparks” which are high probability accounts or contacts.  The user sets the number of sparks displayed in a spark list.  Qualified prospects can be sent to a CRM as accounts or leads.

The French dataset covers three million firms and two million contacts.  The UK universe provides 200,000 companies and 300,000 contacts.  The UK dataset focuses on large companies with sales triggers.

The French file includes 600,000 emails while the UK file supports 100,000 emails.

The firm claims that Predict increases the opportunity conversion rate by 70% and shortens the sales cycle by 30%.

Sparklane employs sixty headcount in Paris, London, and Nantes.  It invests over 20% of its turnover in R&D and has nearly 200 customers in Europe.

2016 North American Market Size

2016 North American Sales Intelligence Market Sizing Model (Excel)

The Market Size of North American Sales Intelligence Vendors. Includes vendor product features, market share, and notes. GZ Consulting Copyright 2017.

$500.00

Price Reduced ($750 ⇒ $500)

For the past few years, I have been sizing the North American Sales Intelligence Market.  This is the largest of the markets as Europe and AsiaPac are more fragmented (the UK is the only other mature market with Bureau van Dijk, Avention UK, Artesian Solutions, and DueDil offering full solutions).

In 2016, I estimated the market at $770 million with LinkedIn Sales Navigator as the top vendor.  While new firms continue to enter, the top ten firms (now eight following the 2017 acquisitions of Avention and RainKing) earn seven of every eight dollars in the industry.

I am making my market model available for license (See PayPal button at top) as an Excel spreadsheet.  It includes revenue numbers by company along with market share, key features, and notes.

The LinkedIn Market Share Section of the 2016 North American Sales Intelligence Market Sizing
The LinkedIn Market Share Section of the 2016 North American Sales Intelligence Market Sizing

I have also broken out two sub-categories: Predictive Analytics and Tech Sales Intelligence.  Predictive Analytics vendors continue to scuffle in the marketplace.  Last September, Gartner sized the global market at between $100 and $150 million.  I have gone back and forth on whether to include them in the larger sales intelligence space, but several of the sales intelligence vendors have added light predictive tools (e.g. Avention, DiscoverOrg, RainKing) while the predictive analytics companies have moved to add enrichment and provide more insights to sales reps.  As such, I see the two product categories moving towards each other so chose to include Lattice Engines, Leadspace, and similar firms.

The Tech Sales Intelligence category (e.g. DiscoverOrg, RainKing, Aberdeen, Corporate360) continues to show strong growth and makes up just over 15% of the market.  Both DiscoverOrg and RainKing have posted remarkable growth over the past few years and merged their efforts last month.  Post acquisition, they are the number three vendor in the space and may hit $120 million in 2017 revenue.  The new powerhouse has 4,000 customers and is looking to expand beyond technology sales to become a general purpose sales intelligence solution.

Acquiring RainKing should move DiscoverOrg well past Data.com (Salesforce) which will likely see declining 2017 revenue.  Salesforce has dropped the ball on Data.com.  They overpromised and under-delivered for years, relying on their ability to bundle the offering with other SFDC products.  As of last month, they are no longer able to deliver Dun & Bradstreet content (D&B WorldBase, Hoovers, and First Research) to new customers (legacy customers retain access).  Unless Data.com has a major content partner announcement at Dreamforce, it is likely to see significant revenue declines in 2017 and 2018 as customers switch to D&B Hoovers for Salesforce and other offerings.

Dun & Bradstreet re-established itself as the #2 vendor in the space with the January 2017 acquisition of Avention and the rebranding of Avention OneSource as D&B Hoovers.  Both companies have struggled to grow revenue with Avention growing slowly over the past few years and Hoovers declining.  However, infusing Avention products with Dun & Bradstreet content both reduces the underlying cost structure of Avention offerings and improves the depth and quality of the content.  Furthermore, Dun & Bradstreet has a much larger sales force which previously has lacked a credible global sales intelligence offering.  Hoovers classic generated nearly all of its revenue in the United States.  Over the next two years, expect to see significant revenue shift from Hoovers Classic to D&B Hoovers.

Three-Toed Sloth By Stefan Laube (Tauchgurke) - Public Domain.
Three-Toed Sloth By Stefan Laube (Tauchgurke) – Public Domain.

Finally, LinkedIn Sales Navigator has established itself as the clear number one vendor in market revenue.  The product didn’t exist five years ago and its competitors still tend to dismiss this gorilla in their midst.  How can they be missing the #1 vendor in the space?  Easy — the gorilla is well camouflaged and appears to be more of a three-toed sloth sleeping in the forest canopy.  Sales reps all use the freemium version of LinkedIn so give little thought to delve further when they ask “how are you obtaining your account intelligence today?” and the response is LinkedIn.  Thus, they enter LinkedIn as the competitor into their CRM, not Sales Navigator.  A few months later when they lose the opportunity, the rep then enters “no decision” into the CRM instead of recognizing a competitive loss.  I have been warning vendors in the space for years about this phenomenon, but they have failed to understand the threat of a gorilla that looks like a three-toed sloth.


N.B. Three-toed sloths inhabit Central and South America and gorillas Central Africa.  This is a metaphor.

<br />
<img height=”1″ width=”1″ style=”display:none;” alt=”” src=”https://dc.ads.linkedin.com/collect/?pid=207554&fmt=gif” /><br />