CaliberMind Offers B2B Orchestration with a Twist

I spent quite a bit of time debating with myself how to classify CaliberMind. But instead of presenting my conclusion and defending it, I’ll just tell you what CaliberMind does. We’ll circle back to classification at the end.

Unify B2B data. CaliberMind ingests data from Salesforce Sales cloud and Marketo, Oracle Eloqua, Salesforce Pardot, and HubSpot marketing automation systems. It reports on missing data and fills in the blanks using data from external vendors. It also uses those vendors to find identifiers belonging to the same person (such as multiple email addresses or alternative company names) and to link contact and lead records to accounts. The system can accept feeds from major advertising systems (GoogleAdwords, Bing, Facebook Ads), from Web analytics (Google Analytics, Mixpanel), and various data stores (MySQL, Amazon Redshift and S3, MongoDB, Apache Hive, etc.). CaliberMind has embedded a third-party data load and transformation tool to manage such inputs. The system stores structured data in Redshift, semi-structured data in MongoDB, and unstructured data in S3.

Report on journeys. CaliberMind system builds an account-level journey visualization that shows different types of events (outbound contacts, inbound contacts, account created, opportunity created, deal won, etc.) on parallel time lines. It imports opportunity stages or account statuses from the source systems rather than creating its own journey stages. Attribution reports show the timing of different types of contacts relative to the date of the final sale, aggregated across multiple accounts. The system doesn’t explicitly report the impact of different contacts but it does consider their effects when recommending which messages to send next.

Create personas. Users can define a list of personas and then assign them profile attributes such as job titles or company sizes. More interesting, they can also submit texts related to each persona. These might be job descriptions, advertising copy, blog posts, video transcripts, email messages, or anything else written in English. (Other languages will be added in the future.) The system uses natural language processing to analyze these and build a profile of what they have in common. This can later be used to determine how closely other texts match each persona. The system can also classify new contacts by persona, based on their profile attributes and associated texts such as content consumed or emails written. The assignments can be adjusted over time as new information becomes available.

Match content to individuals. CaliberMind also uses the texts associated with each contact to build a personal profile. Because the language processor can understand things like level of interest, buyer role, and stage in the purchasing process, it can identify new and generate alerts about important events. The system can also pick up references to other individuals and infer their own roles and interests.

Push results to other systems. CaliberMind draws on its individual-level profiles to push personality insights, engagement tips, and content recommendations to sales people. These can be loaded into the CRM database or displayed in a window on the CRM desktop. CRM users can also see the account-level journey reports and revenue summaries including forecasts. Marketing automation systems could get the same details but usually take more general information, such as persona codes used in segmentation. User-created rules can pick records meeting specified criteria and send them to different marketing automation campaigns. A Salesforce app is pending approval on the App Exchange and Salesforce single sign-on is scheduled for later this year.

Expose detailed data. CaliberMind’s own interface lets users examine the data loaded into the system. Individual-level reports can display details down to the level of single emails or Web visits. These reports are used by marketing, enablement and sales operations teams, not sales people.

These facts should give you an idea why classifying CaliberMind is such a challenge. Its two most notable features are data unification and the personas and recommendations based on natural language processing. The unification and access features make it a Customer Data Platform, while the personas and recommendations make it a Sales Enablement tool. That’s an unusual combination because the marketing and sales domains usually remain separate. You might label CaliberMind an Account Based Marketing system, which also straddles those domains. But there are so many types of ABM systems that it's not a useful classification. CaliberMind itself calls the system an orchestration engine.  That's also accurate, since CaliberMind does indeed coordinate messages across channels. But orchestration is another vague term that if understates the main value of CaliberMind, which is less about coordinating messages than finding the best ones. So must best suggestion is to leave categories aside and consider CaliberMind on its own merits.

CaliberMind was released last summer and currently has eleven clients including a mix of mid-size and enterprise B2B companies. Pricing is based on number of contacts and data sources and starts at $2,000 per month.