LeadGenius Adds a Dash of Artificial Intelligence to Account Based Marketing

You may have noticed that I’m writing a little less about artificial intelligence than I had been. It may be that Skynet has imprisoned the real David Raab to block him from issuing dire warnings about its imminent threat to humanity and replaced him with a less alarmist simulation. You can’t actually prove that isn’t happening. But the David Raab, or Raab-bot, writing this will tell you it’s because he’s concluded that AI is destined to become so pervasive that it doesn’t make sense to treat it as a distinct topic. It will simply be embedded in everything and so should be evaluated as part of whatever it belongs to.

LeadGenius is a good example. The company is in the business of assembling B2B marketing lists – an industry dating back centuries to city directories and beyond. But LeadGenius was founded in 2011 to commercialize university research into combining AI with human inputs. It has since expanded from list gathering to all stages in the Account Based Marketing process, sprinkling in dashes of artificial intelligence at every step along the way.

Let’s look at those stages, using the four step structure of the Raab Guide to ABM Vendors.

1. Identify target accounts. This includes assembling data on potential accounts and selecting the right targets. Like many data gatherers, LeadGenius uses a combination of Web and other sources to build company and contact lists. Nearly every vendor who does this applies some form of natural language processing to extract information from unstructured sources. LeadGenius does this too. But it goes further by using artificial intelligence to identify records with questionably accurate information. It then sends these to humans for direct verification by telephone. The company guarantees 99% accuracy in its data, which is significantly better than most competitors can offer. AI's contribution here is to let LeadGenius call only the companies that need human contact, reducing over-all effort substantially. 

To find the right targets, LeadGenius loads a client's current CRM lists. It analyzes these for accuracy and completeness, providing users with reports that highlight problem areas. There’s probably some AI at work in that analysis. LeadGenius then identifies major file segments within the customer base and finds similar companies in the broader universe, estimating potential buyers and revenue by segment. Somewhat surprisingly , LeadGenius doesn’t create predictive lead scores, having found its more useful to prioritize prospects based on company attributes like size and industry. LeadGenius does use artificial intelligence, or at least its country cousin “fuzzy logic”, to map business titles into buyer roles, taking into account how different terms are used at different size companies to describe the same role.

2. Plan interactions. LeadGenius has a basic email campaign capability, including segment definition, email templates with personalization variables, and email sequences. There don’t seem to be any particular AI features here, although we’ll see in a moment that email does play a key role in LeadGenius’ AI utilization.

3. Execute interactions. LeadGenius sends emails through corporate or individual salespeople’s email accounts. It captures replies and uses AI-based natural language processing to classify them, distinguishing answers that indicate interest from out-of-office messages and clear rejections. Hot leads are pushed back to salespeople’s inboxes.  All response classifications are added to the database where they can be used in future selections. So AI does indirectly drive interaction flows. Response data can also be posted to Salesforce.com or Marketos, with additional integrations planned for the near future. Messages through other channels would have to be executed through marketing automation or CRM.

4. Analyze results. LeadGenius has the usual email and campaign reporting, enhanced with the AI-based response classifications.

As promised, you see a bit of AI magic at each of these process stages (assuming you count the AI-based email response as enabling the interaction planning). Certainly there’s room for more features and more AI use. But it’s already enough to illustrate how AI will add power throughout the ABM cycle.

LeadGenius is used primarily by large enterprises selling to small businesses. Those are the firms that can most benefit from its comprehensive data, market analyses, and prospect lists. Pricing is tailored to each client. The company has more than 150 B2B clients.

DemandBase Creeps Up the Value Chain

I had a nice little chat with DemandBase two weeks ago. I’d been aware of them since they were founded in 2006 but in their original incarnation as a data provider. That is, they take business data from sources including Hoovers, D&B, LexisNexis, AccuData, BusinessWatch Network, Jigsaw) and merge it into one big contact list that people can use for outbound promotions or to enhance their own files. It’s a perfectly reasonable business, but not one I find especially exciting.

But it turns out that DemandBase has been inching its way up the value chain. Some time ago they released a free widget, DemandBase Stream, that shows the companies visiting your Web site in a news ticker on your computer desktop. That’s somewhat entertaining and can be useful to salespeople who might notice and reach out to current clients or prospects. But the technology is nothing special: a page tag sends the visitor’s IP address to DemandBase, which looks up its owner in standard Internet registries. In any case, being free, it's really just a promotion for DemandBase.

Their new product, DemandBase Professional, is another matter. It also captures the visitor stream to a company Web site and uses the IP address to identify the company. But now it matches that company against the main DemandBase database to actually apply details such as location, company size, industry, and further finds contact names that marketing or salespeople can reach out to. That’s not much more entertaining, but a lot more salable.

DemandBase Professional actually goes further than simply looking up the information, by letting clients specify the industries, company sizes, geographic regions, search terms and number of page views they care about, and only returning information on visitors who fit those parameters. It can also import a client’s list of target accounts from Salesforce.com and issuing alerts when those companies visit. The good news is that clients only pay for alerts that meet their specified parameters, keeping both the cost and volume within reason. The company only charges for incremental prospect names, so you pay don't again if someone visits your Web site twice.

I was impressed by the sheer cleverness of all this, precisely because the underlying technology (page tags, IP owner lookup, name matching, simple filtering) is so straightforward. There’s no identification of actual visitors and no cookies.

Ok, some of the underlying database preparation and matching is actually pretty demanding. In fact, DemandBase told me that they can use only about 20% of the data they get from their partners because quality problems with the rest. But Rodney Dangerfield on a bad day got more respect than data hygiene experts.

One obvious question is how many useful new names can DemandBase actually provide. According to the company, it typically finds that 50-60% of the Web site visitors come through a generic Internet Service Provider connection and thus can’t be traced to a particular company. Of the remainder, 10-20% fall within the target company sizes, industries or regions. Thus, DemandBase might send information on 5-10% of total visitors.

This is still twice the 2-4% of visitors who DemandBase says typically identify themselves directly. DemandBase said they hadn’t made a formal study of the quality of those leads, but felt confident they were more than worth the cost.

DemandBase plans to continue adding value, possibly by pushing automated messages to selected visitors. But they don’t intend to become a lead management system. We discussed social media briefly; they aren’t using social data (e.g. blog, Facebook, Twitter posts) but are considering trying to find degrees of separation in social networks like Linked In. They didn’t mention it, but I could also see them providing input to Web site personalization systems, so the site itself would tailor its content to what DemandBase infers about the visitor.

The company said that about one thousand companies have set up its free widget and a couple hundred are testing DemandBase Professional. Pricing for Professional depends on volume and starts around $200-$300 per month.

I suppose I could just say this is a useful-sounding product and let it go at that. But if you’re looking for Some Larger Significance: it’s also an example of how the traditional distinction between sales and marketing is dissolving. DemandBase is mostly a salesperson’s tool, but it is identifying names much earlier than sales typically gets involved. Even more to the point, a particular name might go to either sales or marketing depending on the situation. This means that sales and marketing have to agree on rules for who does what—requiring considerably more cooperation than just throwing a lead over the wall once it's deemed “qualified”. I'd say that's significant.