Table of contents for Marketing Decision Management Solutions
- Decision Management and Marketing – a Blog Series
- Marketing Decision Management: Critical Elements in a Solution
- First Look: IBM Real-time Interaction Management
- First Look: FICO Marketing Products
- First Look: SAP Real-Time Offer Management
- First Look: SAS Real-time Decision Manager
- First Look – Pitney Bowes Software update
- First Look: Idio
- First Look: Experian Marketing Solutions
- Listening, learning and acting in multi-channel marketing
- First Look: 7
- First Look: Teradata Integrated Marketing Management
- First Look: Lattice Engines
- First Look: NICE
- First Look: Provenir Big Data Listening and Engagement Platform
- First Look: Granata Decision Systems
As we start the series let’s begin with a set of what I consider to be critical elements in a Marketing Decision Management solution. These are not a complete set of everything a solution might do but a set of critical elements from my (decision management) perspective.
A suitable marketing solution is:
- Multi-channel, supporting inbound and outbound, interactive and passive channels. Part of the critical value of a Decision Management solution is its ability to sit behind many channel-specific environments and deliver consistent decisions based on data gathered from ALL those channels.
- Able to build customer dialogues over time and across channels, moving customers along journeys that increase their value. Each interaction, each decision, matters but it must be possible to string these together as a set.
- Able to arbitrate between and optimize across multiple potential offers and actions. The reality of a modern company is that it has lots of potential offers to make, lots of non-offer marketing actions it could take and it must be able to manage across this portfolio.
- Using predictive analytics based on a rich set of customer data from multiple sources. There is simply too much data, and too little time to act, for reporting or dashboards to cut it. The solution needs to embed predictive analytics into decision-making.
- Able to learn what works and what does not, both automatically with adaptive analytic models that learn for themselves and by supporting A/B and Champion/Challenger testing.
Another way to see the solution is shown below. Data mining determines significant customer segments, based on behavior. Predictive Analytics predict which products, offers or actions will be attractive to these segments. Business Rules enforce policies or regulations, determine pricing, manage preferences, etc. All packaged up into a Decision Service that takes in context information and returns a recommendation or set of recommendations.
Why not take a look at your marketing systems. Are they managing decisions? Are they using analytics to drive better decisions? Are they agile and transparent so they can be changed easily, and adaptive to changing circumstances? If not, perhaps you should be thinking about building or buying a Marketing Decision Management System.