As part of our ongoing series on Marketing Decision Management solutions I recently got a briefing on some of IBM’s Marketing Solutions – specifically IBM Real-time Interaction Management. IBM’s Real-time Interaction Management offering is part of IBM’s Enterprise Marketing Management suite. This has been a real focus area for IBM in the last few years with a broader and more integrated range of solutions. In particular IBM sees three imperatives for marketers within the broad remit of smarter marketing:
- Understand each customer as an individual
Marketers have always been responsible for knowing the customer.
- Create a system of engagement to maximize value creation at every touch
Marketers have always been responsible for defining what to market and how.
- Designing a culture and brand that are authentic
Marketers have always “owned” the brand.
The Real-time Interaction Management system is most focused on the system of engagement, though it is driven of course by analytics based on customer understanding.
IBM sees a number of use cases relevant to RTIM:
- Real-time means driving more cart and content usage – drive recommendations in real-time to get more content read, more purchases in the cart.
- Real-time means personalizing digital properties and experiences.
- Real-time can mean cross-channel marketing as it expands into real-time and interactive marketing.
- Finally real-time can mean cross-functional customer experience management, next best action not just next best offer, bringing service and other actions into the picture beyond just marketing.
Each of these increases the range of activities being considered and the number of channels across which they have to be managed. IBM offers several solutions with an increasing degree of connection between them so that each use case can be supported while building into a coherent whole.
IBM Digital Recommendations
This is for managing content and products to drive cart cross-sell/up-sell and content recommendation. It consists of two distinct products that use the same recommendation engine – one focused on content recommendations and one based on product recommendations. These use personalization (facts about the current user) as well as what others think (wisdom of crowds) to drive the recommendations. A/B testing and rules-based control are included.
Recent enhancements include mapping user activity across devices, focusing on value not just recency and using categories to drive recommendations not just specific content or products. This is primarily driven by interaction data though offline data can be brought in for reporting and analysis purposes.
IBM Marketing Center
This product supports the broader digital personalization scenario and is a cloud-based digital marketing solution handling email marketing, site personalization, list targeting, A/B testing, mobile ads, etc. Designed to automate and track marketing activities and campaign management, it builds on the Digital Recommendation product, though it also works with other products. It can integrate offline data to drive better online profiles and is mostly driven by rules and configuration rather than analytics.
This is the core legacy Unica product that drives marketing across all channels. Interact is triggered when there is some interaction (any channel) that provides a context. This context is combined with the user/customer profile being managed by Interact and a real-time decision is made by blending segmentation, rules, algorithms and event pattern recognition. Finally the result, an offer or a message, is returned to the calling channel.
Key elements include coordination with pre-calculated batch campaign decisions, management of suppression rules, arbitration and self-learning loops, and the ability to use a range of decision types and external calls. Interact is being used on websites, call center agents, in-store POS, at ATMs or Kiosks, etc.
Interact has a role-based UI designed for marketers, a stepwise approach to improving control, offer flexibility to allow for different audiences, analytics and business rules in combination, and inbound/outbound coordination to build ongoing dialogues. In addition, Interact is easy to supplement with predictive analytic models built outside (using SPSS modeler for instance) and calls to other decisioning engines like SPSS Decision Management.
IBM Signature Solution: Next Best Action
All of these pieces, plus IBM SPSS Decision Management and the Next Best Action Optimizer, can be pulled together to deliver the full cross-functional customer experience in IBM’s Signature Solution for Next Best Action. In general this kind of more complex solution is more tailored, often combining other IBM products like the Decision Management stack as well as the IBM Big Data Platform as well as other elements of information management. For instance a Decision Service might be integrated to combine both the marketing decisions from Interact as well as other decisions from elsewhere in the organization.
Overall IBM offers a wide range of components that support real-time data access to a wide range of data sources, that can drive decision-making using a blend of business rules and analytics (both built and adaptive analytics) defined using a role-based UI, deliver those decisions to a very wide range of channels through a flexible set of connection options, coordinating both inbound and outbound.
You can get more information here.