6Sense Finds B2B Prospects Using Web Site Activities

I mentioned 6Sense briefly in a recent post about vendors who help companies find prospects on the Web. Since then, I’ve had a more detailed briefing, which clarified that their scope extends well beyond prospect lists to predictive models applied across all stages of the purchase cycle. We also clarified that users can extract company-level profiles including attributes (industry, revenue, etc.) and key activities (Web site visits, topics researched) and scores at both company and individual levels.

The extraction features are important – at least to me – because they determine whether 6Sense qualifies as a “customer data platform” (CDP), a type of system I see as fundamental for future marketing. As a quick refresher, CDP is defined as “a marketer-controlled system that supports external marketing execution based on persistent, cross-channel customer data.” The part about “supports external marketing execution” is where data extraction comes in: it means that external systems can access data within the CDP for their own use. 6Sense wouldn't be a CDP if it merely displayed its data on a CRM screen without letting the CRM system import it.  If 6Sense exposed model scores but no other data, it would qualify as a CDP by the thinnest margin possible.

Of course, there are more important things about 6Sense than whether I consider it a CDP. Starting at the beginning, the system imports a list of each client’s customers and sales opportunities from CRM and marketing automation systems. Standard integrations are available for Salesforce.com, Oracle Eloqua and Marketo.  APIs can load data from other sources, potentially including other CRM marketing automation products, Web logs and tags, order processing, bookings, call centers, media impressions, and pretty much anything else.

The system standardizes and deduplicates this data at the individual and company levels. It then matches against company profiles that 6Sense itself has gathered from the usual Web sources – public social media, Web sites, job boards, directories, etc. – and from a network of third-party Web sites. The Web site network is unusual if not unique among B2B data providers; the most similar offerings I can think of are audience profiles from B2C site networks, from owners of large B2B sites, and based on other B2B activity such as email response. The advantage of Web site activity is it finds companies early in the buying cycle, when they are most open to considering new vendors. The system can map known individuals to individuals on partner Web sites, using hashing techniques to avoid passing personally identifiable information.  .

The result of all this is a database with deep company and individual profiles including both attributes and activities. 6Sense uses this to build company and individual-level predictive models.  Company models score each company’s likelihood to buy from the client.  Individual models predict the individual’s likelihood to be the best sales contact. Models are built by 6Sense staff using automated techniques and take about three weeks to complete.

The system can also estimate what product each company is most likely to purchase, when it will buy, and what stage it has reached in the buying process. Stages are defined in consultation with the client. Assignment rules might use purchase likelihood or a predictive model trained against a sample of companies in each buying stage.

Outputs from 6Sense can include lists of likely new prospect companies (not in the client’s existing database), contacts at those companies, current prospects organized by purchase stage and ranked by purchase likelihood, current contacts within each company, and key indicators that drive each company’s score. The key indicators can be very specific, such as searches for competitors’ names, visits to product detail pages, or activity by known leads.

Users can define segments based on these or other attributes and export their related data to CRM, marketing automation, ad targeting, or Web personalization systems via file transfers or API calls. 6Sense can also display the information on screen to help guide sales conversations and is now testing an extension to recommend specific talking points.  

Pricing for 6Sense starts at more than $100,000 and is based on factors including the number of models created and volume of new net contacts provided.  The company was founded in 2013 and released early versions of its product that same year. Formal release was in May 2014. It has ten current customers and more in the pipeline.

Lots of Vendors Can Help You Find Leads on the Web

Few people would suggest you learn salesmanship from the play Glengarry Glen Ross,* but its central message rings true: good leads are the lifeblood of a sales organization.** That’s why scanning the Internet to find new  prospects is such an exciting opportunity. At least a dozen firms are now following that path.

These firms scan company Web sites, social media, news sites, directories, and other sources to identify companies, extract attributes like revenue, growth rates, and technologies used, and flag events that might indicate a sales opportunity, such as opening a new office, launching a new product, or hiring new management. Of course, there are plenty of important differences which impact which might make sense for you.  Some of the more important ones include:

• Specific data sources, scanning techniques, and analytical methods. Evaluating these in the abstract is interesting, but what works well for one purpose in one industry might work poorly for something else. So buyers really need to run their own tests to see what works for them.

• Types of predictive models available.  Some vendors only rank leads while others build multiple models for different purposes.

• Use of the client's internal data for model scoring, and whether this extends to sources beyond CRM.

• Whether the vendor sells prospect lists or only enhance names provided by the client.

• Whether the vendor provides lists of individuals as well as companies.  Since Web scanning is usually at the company level, the individual names usually come from other sources.

• Coverage outside the United States

• Information returned beyond names and lead scores, such as recommended treatments and social profiles.

• Whether the company maintains a permanent database on all businesses or only scans when clients request information about specified businesses or segments.  The permanent database costs more to maintain but stores history and trend information that is otherwise unavailable.

Here are brief profiles of the vendors I’ve identified in or near this space. There are probably others.  I’ve grouped them based on how much information I have available.  This correlates to some degree with market presence.

Vendors I’ve Reviewed

• Mintigo both returns new prospects and applies scores to prospect lists provided by the client. It is currently stressing uses of predictive modeling beyond traditional lead scoring and making it easier for clients to set up new models on their own. I last reviewed them in June 2013.

• Lattice Engines runs different types of models against names provided by the client. It provides recommendations for customer treatments in addition to scores. I wrote about them in April 2013.

• Infer runs multiple models against leads provided by the client. It originally returned only lead scores, although they are now adding multiple applications that create different scores for different purposes. I wrote about them in August 2013.

• Fliptop returns scores and some summary data on names provided by the client. It stresses quick model building. I reviewed them in June 2014.

• LeadSpace scans for data on demand, rather than maintaining its own master database.  It can find new prospects in specified segments and enhance names provided by the client.  It returns individual names as well as companies. I wrote about them in June 2013.

Vendors I’ve Spoken with But Not Reviewed

• Growth Intelligence is a relatively recent UK-based startup that provides lists of companies and associated contacts that are likely to become customers.  It draws from Web information, government lists, and similarity to the client’s current customer base.

• Kemvi is just emerging from stealth and plans to launch formally late this year or early 2015. It expects to focus on finding trigger events and advising salespeople about the best ways to approach each prospect.

• 6Sense finds new prospects using behavioral data gathered from a network of "several thousand" Web publishers rather scanning public sources like others in this list. So it doesn’t quite belong here, but it’s interesting nevertheless.

• Radius finds small business prospects that resemble current customers and deploys them to Salesforce.com, along with key profile information and lead scores.


Vendors I’ve Only Seen on the Web

• Avention (formerly OneSource, now part of D&B Hoovers) scans an eclectic collection of data sources to find prospect companies based on attributes and signals. It can rank companies with scoring but the scoring formulas are built manually.

• Gagein sends alerts on trigger events in media, social or public Web sites. It can track companies named by the client or build prospects lists for client-specified segments. It’s primarily a sales tool, with other features such as social selling and apparently without any predictive modeling.

• RealSociable is another sales-oriented product that tracks social media for trigger events related to target accounts. It appears to let users decide which events are important without using predictive models.  But it seems to have some clever technology to extract the trigger events from unstructured social streams. That (presumed) semantic filtering is the only reason to include it on this list -- otherwise, the limit to social sources and lack of predictive models would rule it out.

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*and the one person who admitted to it now makes his living as an arts critic.

** Also, coffee really is for closers.