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.

HiveFire Curata Cuts the Work in Content Aggregation

Summary: HiveFire Curata makes it easy to assemble and republish content on specialized topics, attracting visitors to your company’s Web site.

Here’s an irony for you: the world is awash with content, but marketers struggle to find enough of it. It’s like a sailor dying of thirst.

Of course, sailors really do die of thirst. It happens when they’re surrounded by salt water they can’t drink. Marketers have the same problem: they can’t use most of the content that’s available.

HiveFire Curata aims to solve this problem by making it easier for marketers to extract usable content from the surrounding ocean. In fact, Curata provides a complete system to not just locate the right content but also to organize and present it to the marketer’s target audience. The goal is to make finding and repurposing existing content easier than creating new content on your own.

More specifically, Curata lets marketers build Web sites that republish content on selected topics, such as news of a particular industry. This attracts the marketer’s target customers and positions the marketer’s firm as an authority in the field. Once the audience is assembled, the site can also deliver the company’s own content and advertisements.

The trick to making this work is efficiency. You don’t need a special tool to scan the Internet: a simple Google Alert or Twitter search will do that for free. But you’d still need to read each article, tag it with keywords, and post it to your site. The work adds up so quickly that most marketers can’t afford to do it.

Curata reduces this effort by using natural language processing to automatically identify, classify and tag potential articles. It then presents them for manual review before being posted to a Curata Web site, which automatically adds them to appropriate indexes for future reference. The result is an organized archive that offers real value to someone interested in a topic. Because the search and tagging are highly automated, Curata says a typical client processes 40 to 80 articles each day in about 20 minutes.

Setting up a Curata site requires little technical skill. Users choose a format and then use a page designer to place widgets for articles, blog posts, lists of articles by category, author or entity, news streams, site search, media galleries, subscriptions and user registration. They also define the sources and search terms and exclusions the system will use to find content. Sources can include social media, news feeds, patent registrations and RSS subscriptions. Content on the Web site can also be published through RSS subscriptions, email newsletters, Twitter, Facebook and LinkedIn.

Because the system is hosted by Curata, it can be set up and maintained without help from the corporate IT department or Web team. This is a critical advantage for many marketers who lack priority access to those resources.

This is all good, and many companies should find Curata well worth the $1,500 per month ($1,200 with an annual contract). But I did see a number of features I’d like added. These include:

- screening the selected articles. Currently the system presents the articles in the sequence they are found, without identifying redundancies or even removing exact duplicates. Intelligent screening could remove some articles and present similar ones together, saving considerable labor when large volumes are involved.

- ranking the selected articles. The system currently reports the traffic attracted by each article, but it doesn’t use this to predict the popularity of new articles. Such predictions should be well within the capabilities of the natural language engine. Nor does the system rank articles on other criteria such as the authority of the source. Ranking could let editors review the most important articles first and discard the others once they had reached their daily quota.

- more subscriber information. Visitors register with the system to post comments and subscribe the email newsletters. But the profile cannot be extended beyond name, password and email address. This is missing an obvious opportunity to capture more information about potential leads.

- subscriber behavior tracking. Curata doesn’t report on the behavior of individual visitors, such as which items they view or how often they visit. This is another bundle of information that marketers and salespeople could use to understand visitor interests and to identify hot prospects.

HiveFire was open to these ideas when we discussed them, so I’d expect to see some appear in the future. But it's worth noting that Curata already has about 40 clients, who are presumably satisfied enough the existing features to pay for them. So even in its current state, Curata is worth a look if you want to sail the seas of content aggregation.