BlueConic Selects Targeted Messages Using a Cross-Channel Marketing Database


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This blog has mentioned BlueConic in passing a couple of times but never quite gotten around to reviewing it in detail. Until now.

The delay may seem surprising, since BlueConic qualifies as a Customer Data Platform, a type of system I’ve been arguing will play an increasingly central role in marketers’ futures. For those of you who haven’t been paying close attention, a CDP is defined as a

• marketer-controlled system that
• supports external marketing execution based on
• persistent, cross-channel customer data.

This definition distinguishes CDPs from traditional marketing automation products, which do their own execution, and from real-time interaction managers, which lack persistent data stores. CDPs are important because few marketers have been able to build adequate cross-channel databases and because connecting those databases with execution systems has been difficult. The databases and connections are needed because today's customers expect personalized, coordinated treatments across all channels.  Call it the “Amazon fallacy”: customers believe that since can give them highly personalized treatments, so can everyone else.

Anyway, back to BlueConic. The system has two main capabilities, which are to maintain customer profiles and to deliver targeted messages. The profiles can be based on data imported from other systems via batch processes or APIs or captured by BlueConic itself.  It does this with “listeners” that can read data from forms or monitor behaviors via Javascript tags on Web pages, emails, and other media. “Listeners” can also create interest rankings and scores based on user behavior. All of these become available as attributes on the customer profile, which in turn can create customer segments and drive targeted messages.

The messages are delivered by what BlueConic calls “dialogues”, each of which sends a single message to a single location (email, text message, section on a Web page, etc.) to a specified customer segment. The message can include a recommendation that is tailored to customer interests and scores, but presenting a sequence of messages would require a set of dialogues that are delivered in sequence.  If a customer is eligible for several dialogues at once, the system currently relies on an optimizer to pick best-responding option and will soon let users create rules to further guide the results. There is no built-in predictive modeling but the optimizer can continuously test alternative messages within a dialogue and automatically deploy the winner. Users can also apply a frequency cap to dialogues to limit the number of times any customer sees the same message.

BlueConic’s integration features are more extensive than its decision management. The system can capture data entered into forms even if the form ise not submitted. Users can insert message contains into an existing Web page without writing HTML code. Profiles capture  customer identifiers provided by other systems and are automatically merged when two profiles are linked to the same external ID.  Data is exchanged with other sources and execution systems via REST APIs. There are standard integrations with Twitter, Facebook, and, as well as a system development kit for integration with mobile apps. The underlying data store is Apache Cassandra running on Amazon Web Services, which is highly flexible and scalable at moderate cost.

Integration and data management are what make BlueConic most interesting from a CDP perspective, since those are the core CDP functions. A “pure" CDP would provide only those services while leaving decision management and message delivery to other systems. I expect “pure” CDPs to appear, but most marketers prefer a broader solution, like BlueConic, to assembling the components for themselves. Pure CDPs will become more attractive as integration becomes easier through more standard APIs and connectors, a promise that cloud-based systems often make but are just starting to deliver.

BlueConic’s pricing is already data-centric: fees are based on numbers of profile and channels, not interactions or messages. Prices start around $1,000 per month although most clients pay more. Current implementations are mid-size and enterprise firms in B2C industries including retail, publishing, financial services, utilities, telecommunications, sports and travel. The system has about 70 current customers and is sold both directly and to partners such as ad agencies, other software vendors, and marketing service providers.

Republished with author's permission from original post.


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