The following articles are from a white paper that I wrote for Merkle. You can find the original white paper on the Merkle website. I will post the white paper in 4 parts. This is part 4 of 4.
Once we solve for the rationalization of the individual across the offline and online world, we are still left with the challenge of how they interact with our brands today. Consumers expect relevance and context in our marketing messages. And the determination of relevance and context must happen in fractions of a second in the interactive channels. Part of the key to context is in understanding how the consumer has interacted in all of the other channels.
Each of the channels has a highly complex set of capabilities that allows brands to interact with consumers in those channels. Figure X below gives you a view of that complexity in only three of the channels. As your efforts span more channels, the complexity grows exponentially.
To solve for this complexity issue, we need a common way to provide data and insights to each of these channels, but do it in a way that we do not attempt to resolve the complexity in the channel. This can be achieved by developing a layer of abstraction from the channel complexity. The abstraction will take the form of a decision services layer. The decision services layer has a few key pieces: model execution, business rules evaluation, and machine learning. These components will manifest in slightly different fashions depending on the organization. There will also be data access services and workflow management services associated with this layer. Each component must be able to receive and act on the data that is created during the current session with the consumer.
The model execution component provides insights into the channel based on the intelligence developed by the marketing sciences group. This component informs the channels of the value and the likelihood of events. It also provides insights into recommendations and offers for that specific consumer.
Business Rule Evaluation
In the offline world we have a similar component in place with many of our CRM solutions. The marketing rules around how we communicate with consumers are typically found inside our campaign management systems. These are the same rules that will need to be evaluated in the decision services layer. The rules will consider consumer preferences, offer, creative, event history, and other parts of our consumer engagement strategy.
The machine learning component becomes critical to our ability to derive new insights in the fast moving digital experience. Through the application of advanced marketing sciences in the machine learning component, we will be able to fine tune our insights based the new data being introduced with every consumer interaction. Even in light of the importance of this component, we should be solving for the other areas of the decision service layer first.
Many of the key ingredients of our traditional marketing solutions are present in today’s marketing solution. We have not left one world and ventured into a completely new world. We are just in place where we must be able to react to larger data volumes, anonymous identities, and immediate interactions. The rules of marketing have not changed. Marketing must be measurable and relevant. If anything, I would argue that we are now in a place where we can do this more successfully than in the past. What has changed is the technology we use to enable our marketing efforts. This is why, as marketers, we must be more technologically savvy. Today when someone asks the question, “Who in this room is a technologist?” every marketer should raise their hand.