Portrait itself brought an agglomeration of previous acquisitions, having expanded its original customer relationship management system by purchasing Quadstone analytics in 2005 and Million Handshakes marketing automation in 2008. Their descendants are now modules within integrated Portrait suite, including Portrait Explorer (visualization), Miner (predictive modeling), Uplift (model-based treatment selection), Foundation (data access and integration), Dialogue (multi-step outbound campaigns), and Interaction Optimizer (real-time decisions).
Dialogue and Interaction Optimizer are closely linked, sharing a user interface for campaign definition and both using Foundation to connect with external systems. The interface, called HQ, lets marketers define a hierarchy of campaigns linked to multiple marketing activities, which in turn contain multiple channels and offers. Offers are linked to products, which have customer-level eligibility criteria.
Marketing activities have budgets and response forecasts, which can be set for the activity as a whole or for each channel / message combination (called a treatment). An activity can be assigned an activity type, priority, and scoring rule, which are used to prioritize recommendations during inbound interactions. Activities can also be associated with tasks assigned to the user or others.
HQ provides dashboards showing a campaign calendar, personal and delegated tasks, and results by campaign, offer, and channel. The dashboard can be extended to include external data.
Recommendations in IO are based on marketing activities. Each recommendation has audience and message definitions. The audience can be defined by any combination of static lists, dynamic selections, and scoring rules. Messages belong to a single channel and provide content in a channel-specific format. The content may be an actual message or a pointer interpreted by the touchpoint. IO provides a HTML generator to create messages. These can be personalized with data from the customer record. Messages can be linked to offers, although this is optional.
When IO receives a recommendation request, it checks against the audience and offer definitions of all active recommendations to identify those that are available to the current customer in the current situation. It sorts the options based on activity type, priority, and scoring results, which can be applied in whatever sequence the user defined during campaign setup. More advanced prioritization could be built into the scoring rules but requires a modeling specialist. After the recommendation is selected, it is sent back to the touchpoint for delivery.
Scoring models can be created and automatically updated within IO or imported from external systems. The self-updating models are less accurate than batch built models but make sense where conditions change quickly or very large numbers of models are needed. External models can be created in Portrait’s own modeling tools or with third party software. Scores are calculated within IO using current data.
IO recommendations are generally called by an external touchpoint but can also be embedded within a Dialogue campaign flow, used to generate outbound campaigns. Dialogue provides a drag-and-drop flow builder with a broad range of capabilities to manage data, direct data flows, send messages, and access social media. Campaigns can execute as batch processes or events triggered by database stored procedures. Other Pitney Bowes product offer additional features for database management, data quality, and message creation.
Both IO and Dialogue are available as on-premise software or hosted by Pitney Bowes. Pricing of IO is based on the database size and number of channels supported. It starts around $75,000 for a 100,000 row database for one channel for a perpetual on-premise license. The system has fewer than 50 installations.
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