LeadSpace Offers A No-Memory Approach to B2B Lead Scoring

My discussion last week of Infer, Mintigo, and Lattice Engines raised the question of what other B2B data vendors might be considered Customer Data Platforms. It’s easy to exclude companies that provide basic B2B lists (D&B, Data.com, Netprospex, ZoomInfo, etc.) since they’re clearly in a different business. But there’s another set of vendors that look very much like Mintigo, Infer, and Lattice Engines building detailed profiles by extracting data from Web sites, social networks, and other sources. This group includes InsideView, OneSource, SalesLoft and LeadSpace. So far as I know, none of them maintains a permanent copy of a client’s own customer file, which is the essence of being a Customer Data Platform. But if you’re a marketer needing to identify and score B2B prospects, you’d still want to give them a look.

I bring this up because a colleague suggested reconsider classifying LeadSpace as a CDP, which prompted me to learn more about them. Here’s what I found.

- LeadSpace, like the other vendors, scans Web sites, blogs, Twitter feeds, LinkedIn profiles, job hunting sites, and other sources to build a picture of a company’s business, managers, technologies, and similar attributes. Of course, every vendor argues it does this better than anyone else.  I  suspect there are indeed significant differences.  But I haven’t done any testing or seen anyone else’s test results – so all I can say is that wise buyers will test for themselves before making a choice.

- LeadSpace does build lead scores, something its Web site doesn’t reflect. This is one of the major points of differentiation among vendors in this space, so it’s worth understanding exactly what kind of scores each company provides. In LeadSpace’s case, the company builds “ideal buyer profiles” that measure how similar a lead is to a sample of existing customers provided by a client. Most clients have multiple profiles for different products or customer segments. Other companies in this group build different types of scores: say, for response to a specific campaign, or becoming a sales accepted lead, or having a high lifetime value. Some also estimate the incremental financial value of taking an action. It’s easy for buyers to gloss over these differences, but that would be a big mistake: they largely what kinds f applications a system can support. So be sure to explore them in detail (or read our explanations once we release the CDP Report itself.)

- LeadSpace doesn’t maintain its own permanent master database of all companies on the Internet. Rather, it conducts a fresh scan as each client requests research into its target audience.  This is another big difference from its competitors, who do run continuous scans and keep the results. LeadSpace argues that its approach avoids outdated information, saves the cost of storing and updating a persistent database, and lets the system collect precisely the right attributes for each situation – which can’t be known in advance. The company also points out that even a new scan will capture some history: the public Twitter feed goes back one year, as do job site listings. I have doubts about these arguments – I think older data can show important trends, am sure there’s plenty of outdated information on current Web pages, and suspect there’s the important attributes are pretty similar from one project to another.  Perhaps LeadSpace is really making the subtler argument that the incremental value of older information doesn’t justify the incremental cost of scanning and storing it, which is perfectly possible.  The company does store some old information, such as common job titles, to help analyze and classify inputs.

- LeadSpace doesn’t load a copy of its clients’ customer names, either. That’s essential for a CDP, which by definition has the potential of evolving into a primary marketing database. But it's not essential for LeadSpace's primary business of lead scoring, where even can be built on just a sample of a few hundred records. The arguments for and against the permanent master database also apply here, so I won’t repeat them. In addition, LeadSpace says its clients care more finding prospects with the right attributes, such as industry, company size, and technology fit, than trends in their behaviors or new job titles. Again, I’m not sure I agree, but should point out that LeadSpace mentioned combining their own scores with behavior data captured in marketing automation: so LeadSpace itself is at least implicitly acknowledging that behaviors are important.. LeadSpace's approach also means it can’t monitor a set of names and issue alerts when they do something interesting.  This is definitely something salespeople like to do. LeadSpace is closing that particular gap by developing a service, soon to enter beta testing, that will do a monthly scan of a client’s customer records.  It will feed the results back to the client's CRM or marketing automation, which themselves will highlight any changes.

- LeadSpace provides both prospect lists (i.e., new names) as well as data enhancement (i.e., information on names provided by the client). Most of its competitors also do both, but some do only enhancement. Again like its competitors, LeadSpace provides an interface for sales people to view the details associated with an existing customer. This is where its on demand approach comes in handy, since the interface can present information in categories tailored to each client’s needs. The system also lets sales people rate each lead with a thumbs up or thumbs down, providing feedback to fine tune the scoring model. I haven’t seen that particular feature in competitive systems but it’s not something I’ve specifically researched.

LeadSpace was founded in 2007 as a prospecting tool that let salespeople enter a company name and receive a list of individuals and their associated information and social conversations. The evolutionary path from there to the current system , launched in 2012, is fairly obvious. The company currently has more than 50 clients, mostly large B2B technology vendors. Pricing is based on the number of records either enhanced or provided in prospect lists, and starts around $25,000 per year.

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Infer Keeps It Simple: B2B Lead Scores and Nothing Else

I’ve nearly finished gathering information from vendors for my new study on Customer Data Platform systems and have started to look for patterns in the results. One thing that has become clear is that the CDP vendors fall into several groups of systems that are similar to each other but quite different from the rest. This makes sense: most of the existing CDP systems were built to solve specific problems , not as general-purpose data platforms. Features will probably converge as vendors extend their products to attract more clients. But right now the groups are quite distinct.

One of these categories is systems for B2B lead scoring. I found three CDPs in this group: Lattice Engines (which I reviewed in April), Mintigo (reviewed in June), and Infer, which I'm reviewing right now.

Like the others, Infer builds a proprietary database of pretty much every company on the Internet by scanning Web sites, blogs, social media, government records, and other sources for company information and relevant events.  It then imports CRM and marketing automation data from its clients' systems, enhances the imported records with information from its big proprietary database, and builds predictive models that score companies and individuals on their likely win rate, conversion rate, deal size, and lifetime revenue.

The models are applied to new records as they enter a client’s system, creating scores that are returned to marketing automation and CRM to use as those systems see fit. The most typical application is deciding which leads should go to sales, be further nurtured by marketing automation,  or discarded entirely. But Infer customers also use the scores to prioritize leads for salespeople within CRM, to measure the quality of leads produced by a marketing program, assess salesperson performance based on the quality of leads they received, and even adjust paid search campaigns based on the quality of leads generated by each source and keyword.

Infer differs from its competitors in many subtle ways: the scope of its data sources, its matching processes to assemble company and individual data, the exact types of scores it produces, its modeling techniques, and reporting.  It also differs in one very obvious way: it returns only scores, while competitors return both scores and enhanced profiles on individual prospects.  Infer gathers the individual detail needed for such profiles, but has decided so far not to make them available. Its reasoning is that scores provide the major value from its system and profiles would detract from them – perhaps because sales people might ignore them scores in favor of profile data. Focusing on scores alone also makes Infer simpler to set up, operate, and understand.

Infer might be right, but it’s hard to imagine they'll will stick with this position once they start selling directly against competitors that offer scores plus profiles.  They will surely lose many deals for that reason alone.  On the other hand, Infer’s initial clients have been companies where free trials versions generate huge lead volumes, including Box, Tableau, NitroPDF, Zendesk, Jive and Yammer. Scores that accurately filter non-productive leads are more important to those companies than individual lead profiles.  Perhaps there are enough such firms for Infer to succeed by selling only to them.

Whether or not Infer expands its outputs, it faces another challenge: convincing buyers that its scores and data are better than its competitors. This might well be true: based on the information I’ve gathered, Infer seems to have a richer set of data sources and more sophisticated identity matching than at least some competitors. But my impressions may be wrong, and most buyers will won’t dig deeply enough to form an opinion.  Instead, their eyes will glaze over when the vendors start to get into the details, and they’ll simply assume that everybody’s data, matching, and modeling are roughly equivalent.

The only real way to measure relative quality is through competitive testing of which scores work better.  Each buyer needs to run her own tests since results may vary from business to business. How many buyers will take the time to do this, and which vendors will agree to cooperate, is a very open question.

That said, I did speak with some current Infer users, who were quite delighted with how easy it had been to deploy the system and with results to date. This is hardly a random sample – these were pioneer users (the system was only launched about a year ago) and hand-picked by the vendor. But their experience does confirm that performance is solid.

Infer pricing is based on the number of records processed and connected systems.  The vendor doesn’t reveal the actual rates but did say it is looking at options to make the system more affordable for smaller clients.

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NitroMojo and Marketing Advocate Specialize in Marketing Automation for Channel Partners

As I noted in a post last year, there is a universe of specialized marketing automation systems for companies that sell through channel partners. These products address several interrelated challenges: distributing leads to partners without losing track of performance; distributing partner-customized versions of company-created content; and helping partners run their own marketing campaigns. Here are two more vendors with related offerings:

NitroMojo focuses primarily on lead distribution and tracking. Its particular strength comes from sending follow-up email surveys directly to leads to find out what happened: were they contacted by the channel partner? did they eventually buy? is there someone else at their company to talk to? is there something else they might purchase? This addresses one of the central dilemmas of selling through partners, which is losing contact with the leads and, as a result, not being able to measure effectiveness of corporate lead generation programs. NitroMojo says about 60% of leads reply to the surveys, giving enough information for meaningful analysis of program, partner, and salesperson performance.

The system also provides sales reps and sales managers with basic sales automation, including abilities to enter and rate new leads, review and prioritize existing leads, track call results, send materials from a central library, and schedule future calls. Corporate marketers can build campaigns with multiple events, create landing pages, capture revenues and costs, distribute leads with complex routing rules, score leads on behaviors and salesperson ratings, and measure performance.  Pricing starts around $3,000 per year plus $100 per user per month, which is usually less than the cost of marketing automation and sales automation systems that NitroMojo would replace. The current version of NitroMojo system was introduced about a year ago and had three global clients with more than 150 users when I spoke with the company in April.

Marketing Advocate is designed to help technology resellers who lack in-house marketing skills. It provides a resellers with a vendor-sponsored microsite that gives them access to marketing content, prospect lists, acquisition email campaigns, and automated nurture emails.  Resellers define their target prospects when they set up the system and then purchase suitable lists from suppliers including NetProspex, Jigsaw, and Harte-Hanks. These prospects, and other names uploaded by the reseller, receive standard campaign emails at three week intervals until they respond by visiting a landing page. The system then sends them personalized emails offering contents related to their behaviors. The leads are also scored and, when ready, can be passed to a telephone lead qualification service or directly to the vendor’s sales automation system. The sponsoring vendor doesn’t see the lead names until the reseller enters them into the system.

The point of all this is to minimize the effort that the resellers themselves must put into marketing. Marketing Advocate typically builds 25 to 30 prospecting campaigns tailored to different customer segments, and lets the resellers select the campaign and segments they want to pursue. The company also assembles and selects content to offer in the emails, has negotiated arrangements with the list providers, gives reports that analyze program response quantity and quality, and offers a concierge service to review results with resellers and discuss improvements. The system can also integrate with event management software and Google AdWords. Partner agencies are available for telephone lead qualification, search engine optimization, and paid search.

Marketing Advocate typically costs $500 to $700 per month per reseller, with some portion of the expense usually subsidized by the sponsoring vendor. Marketers pay $1 per name for prospects. The system is used by divisions at several major technology vendors including IBM, Microsoft, and HP.

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NICE Buys Causata to Extend Its Customer Experience Management Position

So, there I was around 7:30 Eastern time this morning, sending out reminder notices to vendors I need to interview for an upcoming report on Customer Data Platforms. I received an immediate response from the Kevin Nix of Causata, offering to talk that very morning. This seemed a bit odd – Causata is based in San Francisco, so it was 4:30 a.m. local time and most people need more notice to schedule a call. But I had Things To Do, so I didn't give it much thought. Then, at the end of another call, a participant casually mentioned that Causata had just been purchased by Israel-based NICE Systems.  At first I was struck by the coincidence, and then realized what had happened: Nix was up because he had been talking to the folks in Israel, and he replied because he wanted to discuss his acquisition, not my report. [Insert image of deflating self-importance].

Sure enough, when I did dial in, I was treated to a prepared briefing on why NICE had made the deal.

There’s really nothing wrong with that. NICE is little-known in marketing circles, although I had bumped into them previously when they bought decision management vendor eGlue in 2010. But NICE is a major player in contact center systems, with nearly $1 billion revenue and $2.5 billion stock market capitalization. So I was pleased to connect with them directly and learn a bit more.

The briefing itself was interesting too. It turns out that while NICE still sells primarily to contact center managers, it is working hard to expand to clients in marketing, sales, compliance (it bought Actimize in 2007) and other areas related to customer experience. Its interest in Causata related to all  that, and in particular to that fact that Causata can capture Web interactions in real time and present them with related recommendations to contact center agents and other systems. This pumped me back up a bit, since it can be read as validation of the Customer Data Platform concept that I’ve been developing, which is about exactly this need to make customer data easily available across platforms. In fact, Causata was the original example I used to introduce the idea.

But enough about me, at least for the moment. The idea of NICE expanding to become an all-channel, all-department customer experience vendor immediately raises the question of how they’ll compete with all those other omni-everythings approaching from digital marketing (Adobe), B2B CRM (Salesforce.com), and general enterprise systems (Oracle, SAP, IBM). The contact center world has actually been a font of decision management systems, most notably Chordiant (now part of Pegasystems) and Infor Epiphany. So it’s certainly possible that they will be another source of competitors converging on the market for integrated customer experience management solutions. Like the CRM and Web content management vendors, the contact center firms start from a strong customer and financial base, making them formidable contenderss in what will surely be a long battle for high stakes.

I haven’t formed a solid opinion yet on how NICE in particular or contact center vendors in general are likely to fare in this new arena. But they are definitely something to factor into future assessments.

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How RightWave Solves the Marketing Automation Skill Shortage

One of the main reasons that marketing automation has not been adopted more quickly is that too few marketers know how to fully use it. For example, a recent Gleanster report found that 73% of top performers listed lack of skilled staff as one of the top challenges to success. Marketing automation vendors have adopted different strategies to deal with their problem, including making their systems easier to use, offering extensive training, and providing services to run the systems for their clients.

RightWave has taken that final option to an extreme: it doesn’t even give clients the option of running the system for themselves. Instead, RightWave offers what it calls “marketing automation as a service,” gives each client access to staff members who will set up and execute campaigns for them.  There’s nothing especially new about marketing service providers offering this type of service, but  RightWave does it at a price point – starting as low as $60,000 per year – that is comparable to what a good-sized company would pay for most marketing automation systems alone. Because RightWave charges are based on staff resources -- $5,000 per month buys one-half a full time equivalent person, and $8,000 buyers one full time equivalent, fees don't rise for bigger databases or higher message volume.  This means it could actually be cheaper than a self-service system for big companies.

It’s a little hard to review software that isn’t used by its buyers.  Still, the vendor comparison in our VEST report shows that RightWave’s core functionality – for lead generation, campaign management, scoring and distribution, and reporting – is on par with mid-tier leaders Pardot and Marketo.  Where it loses are usability and pricing, but only because it doesn't fit the scoring model: usability suffers from lack of training services which RightWave clients don’t need, and pricing is penalized by the high starting cost which doesn't take into account the lower cost at high volumes.

In other words, RightWave has the features to support pretty much any program marketers might want. More important, RightWave clients are more likely to actually run sophisticated programs because the RightWave staff will build them without the clients needing to learn how. RightWave staff also helps with data quality and analytics, two other areas where many marketing departments lack expertise.


RightWave actually does let marketers import files, create segmentations, and build emails, although few clients do these for themselves.  What clients do use are extensive reporting tools that show marketing calendars, campaign results, customer profiles, Web tracking reports, funnel analysis, return on investment, and other information. The system also gives sales users reports on new leads, activities of existing leads, and visits from target accounts.  Most of the sales information is presented within the Salesforce.com interface, although users can drill down into details held with RightWave.

The details of RightWave functionality are less important than the appeal of its fundamental business model. After seven years of development, the company has about twenty clients.  This sounds considerably short of setting the world on fire, but it really reflects intentionally slow growth as the product matured. Company founder Anurag Khemka, who also started an earlier generation B2C marketing automation system MarketFirst in 1996, said he’s found it relatively easy to sell the system to senior managers, but sometimes run into resistance from lower level staff who want to gain hands-on experience. The company is now starting to ramp up its sales efforts, so the true scope of its appeal will soon be clear. I’ll be watching with great interest.

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