Sparklane €4m Funding Round

Sparklane Lead Scoring
Sparklane Lead Scoring

Sparklane, which describes itself as “a publisher of sales intelligence SAAS solutions,” announced that it received a €4m funding round from XAnge and Entrepreneur Venture Investment Fund.  The round raised its total funding to €7m.  XAnge also participated in Sparklane’s previous funding round.

“We were won over by Sparklane’s disruptive positioning and the impressive performance of its management team, prompting us to offer them our renewed support as we participate in this fundraising initiative alongside Entrepreneur Venture,” stated Guilhem de Vregille, Deputy Director of XAnge.

The round allows Sparklane to continue its European expansion.  The French company established itself in the UK in 2016 and is currently eyeing the German market.  The funding will also be directed towards expanding its artificial intelligence capabilities, and growth in their sales and R&D teams.

According to Chairman Frédéric Pichard, the funding round is a “real vote of confidence,” in the company.  “Our goal remains the same: to help marketing and sales people identify their future customers more quickly using Artificial Intelligence.”

Sparklane offers predictive lead scoring and prospecting tools for sales and marketing teams in the UK and France.  Their Predict platform processes client CRM data to define an Ideal Customer Profile (ICP), apply predictive lead scores, and identify look-a-like prospects.

Sparklane supports nearly 350 clients across banking, insurance, technology and business services.  The firm was listed in Deloitte’s 2016 EMEA Fast 500 list of technology companies with 265% revenue growth between 2012 and 2015 (three-year CAGR of 54%).

Marketing Malpractice

1328101865_Thumbs_downThe other day, I wanted to grab a screenshot of a B2B product I license so I googled the demo.  I was brought to a landing page where I had to fill out a web form to see a short video (Mistake 1 – Creating barriers to early information seekers).  Once I registered, I was taken to a page where the video was displayed in a small, non-expandable window (Mistake2).

A half hour later, I received an email which said my company was too small to speak with a rep, but that I could purchase it online (Mistake 3 – suggesting that I wasn’t worth the time of a sales rep implies that I also wasn’t going to be worth the time of trainers or support teams; Mistake 4 – they treated me as a prospect when I was a customer, a fact they easily could have checked based upon my email; Mistake 5 assuming that I would be ready to purchase based upon a three-minute demo).  When I replied to the email to let them know about these marketing mistakes, it bounced (Mistake 6 —  I missed that it was a no reply email, but since the note was addressed and signed by somebody, I didn’t look at the actual email address).

It was an incredible display of big company arrogance and incompetent marketing.  I’m not going to shame the company by naming it.  Instead I turned them into an object lesson.  There were so many errors in this process that it was clear that their own marketing teams don’t test out their automated processes.  The real shame is that this is a company that offers marketing services, but seemed not to care about checking its own marketing processes.

Sales 3.0 and the Growth Mindset

Sales 3.0 LogoThe Sales 2.0 shows, which have been held for almost a decade, were rebranded Sales 3.0.  As with Sales 2.0, the focus remains on people, process, and technology.  I am not convinced that there is actually a discrete break from 2.0 to 3.0.  For example, the conference site states, “B2B buyers are online, digitally empowered, and looking for salespeople who can articulate value,” but this has been true for the past decade.  One can argue that two other differences are more current, the rise of artificial intelligence and Account Based Marketing.  Both have risen to the forefront of sales and marketing intelligence over the past two years due to the maturation of technology.

The final Sales 3.0 difference focuses on coaching sales reps to “embrace the power of mindset [to] achieve peak sales performance.”  Mindset is a set of attitudes and beliefs that we begin assembling at birth and which shape behavior.  The pre-frontal cortex of the brain stores these mindsets as networks of “cognitive elements, memories, and associated feelings from past experiences.”

“When your mindset is functioning at optimum levels, you’re better able to excel in tough sales situations. That’s because – according to scientific research conducted by Professor Michael Bernard at the University of Melbourne, Australia – high achievers consciously create a belief system that helps them cope effectively with difficult situations at work,” says a Sales 3.0 Conference report.  “We all have the capacity to direct our minds to become powerful, positive, productive forces for ourselves.”

The report noted that successful and positive individuals have a growth mindset which focuses on self-improvement.  “They believe that their talents and abilities can be developed through effort, instruction, and persistence. They don’t necessarily believe they can become geniuses, but they believe they can become more skilled and intelligent by working hard. People with a growth mindset tend to achieve higher levels of success.”

This year’s Sales 3.0 shows will be held in San Francisco (May 1-2), Las Vegas (September 18-19), and Philadelphia (December 4th).

Sales Intelligence Vendors Move Upstream

ZoomInfo Personas provide a multi-dimensional cluster analysis for identifying persona categories and prospecting against them.
ZoomInfo Personas provide a multi-dimensional cluster analysis for identifying persona categories and prospecting against them.

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

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

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

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

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

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

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

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

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

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

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

Demandbase DemandGraph
Demandbase DemandGraph

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

Things are just beginning to get interesting.

Data Strategy Must Support Both MAP and CRM

IDC Chart from "The Data Advantage for Marketing and Sales," June 2016 Research (N=200)
IDC Chart from “The Data Advantage for Marketing and Sales,” June 2016 Research (N=200)

A recent IDC survey of 200 sales and marketing professionals in North America found that the largest source of leads was the Direct Sales Force at 37% of organizations.  The remaining top sources were generated by the marketing department.  Direct Marketing was still the second most important source (21%) with digital ads (14%), corporate websites (10%), and trade events (7%) also generating significant leads.

Thus, any attempt to improve the quality of leads must include both sales and marketing departments.  A focus on only those leads generated by marketing and stored in the marketing automation platform (MAP) means that a high percentage of your leads are not being impacted by your data quality efforts.  Furthermore, even if the MAP is being regularly cleansed and enriched, once leads are sent to the CRM, they still need to be maintained.

The good news is that at firms which focus on sales rep lead identification, the percentage of bad leads (incomplete, inaccurate, duplicate) was only 22%.  Only trade event focused companies had a lower lead quality rate (20%).  So which programs generate a high percentage of bad leads?  Those which are led by social content (49%), off-line ads (42%), and direct marketing (33%).  In these cases, attribution issues and incomplete data are likely sources of errors and duplicates.

What is shocking is that four of every nine firms surveyed with at least one hundred employees have no data services strategy.  Of these, 38% see no need for a working with a data services provider.  34% were put off by cost, but fail to recognize the cost of bad data is felt in sales, marketing, and downstream platforms with a host of both direct and indirect costs.  What’s more, once bad data is propagated downstream, the remediation costs go up several fold.

There are a number of vendors that address data quality in both sales and marketing platforms.  These include ReachForce, D&B NetProspex, InsideView, Avention, and Zoominfo.

Digital Transformation and Sales Intelligence

Data Source: “The 2016 Guide To Digital Predators, Transformers, and Dinosaurs," Forrester Research, May 2016.
Data Source: “The 2016 Guide To Digital Predators, Transformers, and Dinosaurs,” Forrester Research, May 2016.

Forrester released a study titled “The 2016 Guide To Digital Predators, Transformers, and Dinosaurs” which argued that companies need to quickly transform themselves into digital businesses.  The study broke businesses into three digital categories: Predator, Transformer, and Dinosaur and evaluated the percent of business that are either digital services or sold online.

Predators are already generating over 80% of their business digitally and will grow their business to 90% by 2020.  For them, digital is a foundational element of their operations.

Likewise, transformers are quickly evolving into digital businesses while dinosaurs are plodding along.  In 2014, only one in six dollars was generated digitally at transformers, but by 2020, two of every three dollars will be digitally mediated at transformed businesses.

At the dinosaurs, only one in three dollars will be digitally generated in 2020.

Forrester found that transformers are customer-centric in their business strategy and processes.  Customer obsession is part of their corporate DNA:

While all companies profess to put customers first, it’s clear from the data that executives at digital Predators care more passionately about the customer across multiple dimensions: In every customer metric we measured, these executives rated the importance of the customer higher than peers in transformers and dinosaurs – in short, they are not just customer obsessed, they are really, really customer obsessed.

  • Nigel Fenwick, Forrester VP and Principal Analyst

Overall, Forrester found that 29% of current total sales are influenced by digital, but that 47% would be digitally influenced by 2020.  Thus, any business that wishes to remain competitive must have a digital strategy which encompasses sales, marketing, credit decisioning, contracting, and all of the elements across your sales funnel.

My blog focuses on sales intelligence (with some discussion of marketing intelligence and DaaS), so I’m covering a subset of this transformation.  But sales intelligence is a key element of the digital transformation of sales and marketing.  Its goal is to make sales reps more efficient and effective at generating revenue through

  • Improved understanding of customers and prospects.  Whether the company is employing ABM, ABSD, social selling, trigger selling, or other techniques, customer-centricity begins with an understanding of the customer at the contact, company, and industry level.  Sales intelligence vendors go beyond firmographics and contact data to deliver business descriptions, SWOTs, biographies, social posts, industry research, financials, analyst reports, technology platforms, etc.
  • Current Awareness. Improved awareness of changes at customers and prospects helps to improve account planning, messaging, and forecasting.  Where once this intelligence was delivered as generic company news, the sales intelligence vendors have refined their tagging and now provide high precision sales triggers which are accurate at both the company and business topic level.  Some have even begun to integrate sales triggers into their prospecting engines.
  • Reduced busywork + improved data quality.  Sales intelligence vendors cut the time wasted on busywork through the implementation of DaaS enrichment of accounts, contacts, and leads.  Enrichment provides more accurate firmographics, corporate linkage, and contact information which is then propagated to downstream systems.  It also reduces the keying done by prospects on web forms and sales reps in CRMs.  Furthermore, targeting, segmentation, and messaging are much more accurate when the ongoing maintenance of account intelligence is managed by a third party.

Over the past decade, sales intelligence firms have grown from standalone web information portals to integrated workflow services that deliver a broad set of account intelligence to CRMs, marketing automation platforms, sales acceleration (ABSD) services, Google Chrome, web forms, and mobile devices.  Thus, sales intelligence is now becoming available to sales, marketing, and service departments across a broad set of platforms and devices.

If you would like to read more on my thoughts concerning the digital transformation of sales and marketing, I have also discussed the topic on Sparklane and Avention’s blogs.

SFDC Einstein: Once Again We’re Discussing AI

einstein-artificial-intelligence-in-business

In the late 1980’s, when my career was first beginning, I worked on a technology helpdesk for an insurance agency automation system (Aetna’s Gemini platform).  Many of the calls were routine with an easily road mapped set of resolution steps.  So the firm decided to invest in artificial intelligence (AI) and began interviewing its most seasoned experts to identify the problem resolution path.

After several months of development, an AI module would be unveiled that walked the user through problem resolution.  It was basically a set of if-then-else and case statements providing pre-coded branching logic.  Support reps started with a category and were walked through a set of questions to ask and resolution steps to convey over the phone.

The solution was expensive and lacked the ability to learn.  Thus, if new problems arose or the problem resolution changed due to new hardware or software being introduced, the rules no longer applied.

It was far from intelligent.  Heck, I’d coded a twenty-questions game in a first semester programming class that was more intelligent than the service.  At least my Q&A game had the ability to learn new questions to ask without requiring an expensive consultant.

Finally, it was only used by new hires as much of the routine steps were just that — routine.

Solutions like this quickly proved that Artificial Intelligence wasn’t intelligent and after a few years, the term AI fell from favor and returned to the realm of sci-fi killer robots.

Nearly three decades later, the term AI is once again being rolled out.  But now it does convey an impressive level of intelligence which makes our devices feel smart.  It’s why we call them smartphones.  They are able to leverage vast amounts of data and make decisions in the blink of an eye.  Whether it is asking Siri a question or having Google map the best route to a location subject to current traffic patterns and transportation mode, we expect our devices to be intelligent.

AI represents a massive change in technology. You might call it a “paradigm shift” or “disruption” or we could just stick with “massive change.” What we’re trying to say is, AI is kind of a big deal. And just like the arrival of the personal computer, cloud computing, and the mobile smartphone, AI is going to fundamentally change the way things work, forever.

AI is not killer robots. It’s killer technology.

So it was with a smile that I saw the term AI being used by Salesforce in positioning their new Einstein service.  Each year at Dreamforce, CEO Marc Benioff discusses a new underlying technology or cloud.  Most recently it has been Lighting (UI and workflows), Wave (analytics), and the Internet of Things Cloud.  At Dreamforce 2016, it is Einstein, their artificial intelligence platform to assist with sales, marketing, and service.

Salesforce presents AI simply as

Lots of data + cloud computing + good data models = smarter machines

So while much of this technology has been provided as consumer applications for over a decade, businesses have been lagging behind when the scope goes beyond a mobile app or e-commerce portal.

Shouldn’t the full transactional and service history be available to help understand past purchases, preferences, and potential cross-sell and upsell opportunities?

Wouldn’t we want it delivered no matter the touch point?

That is the type of intelligence that Einstein is looking to bring to Salesforce customers.  Einstein is “the world’s first comprehensive artificial intelligence platform for CRM. I’ve never been more excited about the innovation happening at Salesforce,”  said Benioff.

Einstein is available both programmatically (for developers) and “declaratively for non-coders,” said Benioff.  It is integrated directly into the SFDC platform and available across all of the clouds.  For example, an Einstein widget displays a set of insights identifying competitor news, recommended actions, and account intelligence.

Einstein Insights Widgets provide intelligence both programmatically for developers and data scientists and declaratively for end users.
Einstein Insights alerts widget.

 

Einstein can surface competitor mentions even if the end user hasn't trained it to do so.
Einstein Insights surfaces insights both programmatically for developers and data scientists and declaratively for end users.  It can even infer competitors from emails and deliver alerts within SFDC widgets.

 

 

 

 

 

 

Einstein builds models with no coding or initial training by users.  For example, the system is able to determine which trigger events are important to sales reps and surface news about competitors without asking “who are your competitors?”  The system also can make recommendations concerning high-scoring leads based upon both fit (firmographics, biographics) and behavior (e.g. recent viewing of a demo).

Einstein recommends actions to sales reps. In this case, it is suggesting an email requesting a meeting be setup with the VP of Sales at a high-scoring account.
Einstein recommends actions to sales reps. In this case, it is suggesting an email requesting a meeting with the VP of Sales at a high scoring lead who recently viewed a product demo on the website.

Not only does the system recommend activity, but it then offers recommended email copy including a proposed call time.

The platform is built on a series of recent acquisitions including RelateIQ (rebranded SaleforceIQ), MetaMind, Implisit, PreductionIO, and TempoAI.  The firm now has a team of 175 data scientists “stitching together this amazing platform,” said Benioff.

“The new platform will “democratize artificial intelligence” and “make every company and every employee smarter, faster and more productive,” continued Benioff.  “This is going to be a huge differentiator and growth driver going forward as it puts us well ahead of our CRM competition once again.”

The new platform infuses their sales, cloud, and marketing platforms with AI capabilities for “anyone” regardless of their role or industry.  According to Salesforce, Einstein lets employees “use clicks or code to build AI-powered apps that get smarter with every interaction.”

Einstein is positioned as having your own data scientist focused on applying AI to customer relationships.  Einstein has access to a broad set of intelligence including CRM data, email, calendar, social, ERP, and IoT to “deliver predictions and recommendations in context of what you’re trying to do. In some cases, it even automates tasks for you. So you can make smarter decisions with confidence and focus more attention on your customers at every touch point.”

Several predictive analytics companies used the launch to shout, “hey wait, we’ve already mastered AI for sales and marketing.”  LeadSpace CEO and former Salesforce CMO Doug Bewsher stated, “B2B marketers need a complete solution that works across multiple channels, in their existing marketing stack.”

“Bad data is the Achilles heel of AI,” continued Bewsher. “AI is only as good as the data available to it. Marketers who want to get the full benefit of AI need to address their data problems first, or they’ll see the same diminishing returns as with traditional marketing automation.”

Shashi Upadhyay, CEO at Lattice Engines was a bit more diplomatic in welcoming Einstein.  “After having led the market for several years, we are really excited to see the mainstream attention shifting towards AI-based solutions for marketing and sales.  The Einstein announcement from Salesforce is a great step forward, as it will serve to educate the market and signal that predictive solutions are here to stay.”

Image Credit: Salesforce.com