Fliptop: A Customer Data Platform for Predictive Lead Scoring, Pure and Simple

It’s been a while since I wrote about Customer Data Platforms, but only because I’ve been distracted by other topics. The CDP industry has been moving along nicely without my attention: new CDPs keep emerging and the existing vendors are growing.

Fliptop wasn’t on my original list of CDPs, having launched its relevant product just after the initial CDP report was published. But it fits perfectly into the “data enhancement” category, joining Infer, Lattice Engines, Mintigo, Growth Intelligence (which I’ve also yet to review) and ReachForce. Like all the others except ReachForce, the company builds a master database of information about businesses and individuals by scanning the social networks, company Web pages, job sites, paid search spend, search engine page rank, and other sources. When it gets a new client, it loads that company’s own customer list and sales from its CRM system, finds those companies and individuals in the Fliptop database, enhances their records with Fliptop data, and uses the combined information to build a predictive model that identifies the likelihood of someone making a purchase. This model can score new leads and classify existing opportunities in the sales pipeline.

So what makes Fliptop different from its competitors? The one objective distinction is that Fliptop is publicly listed on the Salesforce.com App Exchange, meaning it has passed the Salesforce.com security reviews. Not surprisingly, the company’s Salesforce connector is very efficient, automatically pulling down leads, contacts, accounts, and opportunities through the Salesforce API and feeding them into the modeling system. New clients who import only Salesforce data can have a model ready within 24 hours, which is faster than most competitors. But data from other sources may require custom connectors, slowing the process.  Fliptop is also able to model quickly because it defaults to predicting revenue: in other systems, part of the set-up time is devoted to deciding what to model against.

Once the model is built, Fliptop scores the client’s entire database and assigns contacts, accounts, and opportunities into classes based on expected results. A typical scheme would create A, B, C, and D lead classes, where A leads are best. Reports show the percentage of records in each group and the expected win rate, which in turn relates to expected revenue. A typical result might find that the top 10% of contacts account for 40% of the expected revenue or that the top 40% of contacts account for 95% of the revenue. Clients can adjust the breakpoints to create custom performance ranges. Reports also show which categories of data are contributing the most to the scoring models: this is more information than some systems provide and is presented quite understandably.  (Incidentally, Fliptop reports it has generally found that "fit" data, such as company size and industry, is more powerful than behavioral data such as email clicks and content downloads.)

Fliptop scores are loaded into a CRM or marketing automation system where they can be used to prioritize sales efforts and guide campaign segmentation. There are existing connectors for Salesforce.com, Marketo, and Eloqua and it’s fairly easy to connect with others. New leads can be scored in under one minute or in a few seconds if the system is directly connected to a lead capture form. Clients can build separate models for different products or segments and receive a score for each model. The system automatically checks for new sales results at regular intervals and adjusts the models when needed.

At present, Fliptop only sends scores to other systems. (Infer takes a similar approach.) The next release of its Salesforce.com integration is expected to add top positive and negative factors on individual records.  The company is considering future applications including campaign optimization, pipeline forecasting, and account-level targeting. But it does not plan to match competitors who offer treatment recommendations, sell lists of new prospects, or provide their own behavior tracking pixels.

Pricing for Fliptop is based on data volume and starts at $2,500 per month. The company offers a free 30 day trial – unusual in this segment and possible because set-up is so automated. After the trial, clients are required to sign a one-year contract. The system currently has about three dozen paying clients and a larger number of active trials.

Bottom line: Fliptop does a very good job with predictive lead scoring. Marketers looking for a broader range of applications may find other CDPs are a better fit.