This year at IBM Think, I had the opportunity to speak about 'How the big industry players with large databases personalize their marketing'. By using AI, gaining insight with external behavioral data sources, and leveraging new platforms, the leaders are focused on having a more customized relationship with customers.
Here are the key themes from this year’s event:
We are now in a world which data breaches are all too common. Encrypting data while in motion and at rest are now the standard, but with all this security in place, data breaches may still occur. Building customer trust is going beyond to ensure customer data is secure. The first step to customer trust is being relevant to customer and listening to them. Responding to the customer needs, anticipating what they want via model scoring is the next step, but you’ll want to avoid creepy marketing. Doing this can adhere to customers that we are listening to their needs/asks without violating their trust without being creepy. With the information about a customer from first-party (e.g., IBM Interact) and third-party (DMP) data is how you gain the right understanding to be relevant. Divulging too much information/knowledge about the customer can impact trust with the brand. “Chance favors the prepared mind” comes to mind in that we may not have the answers to all the customer data which we ingest, but if there is a solid foundation, then we can easily pivot to a new view of data without boiling the ocean.
Marketers now have access to an enormous amount of data which can be overwhelming. In an ideal world, marketers should have access to the raw data within their own ‘data mart’ in addition to the data in a centralized data platform. Marketers are now being granted access to data lakes, which hold this vast amount of data. Unfortunately, having all this data, but not having any structure to it often makes it seem like a data swamp instead of a lake. By integrating with a CRM tool like IBM Campaign, marketers can consolidate all data inputs (consolidation layer) and then expose views to the CRM tool which have some business rules included within them. We typically refer to this as the consumption layer. This allows marketers to access the data from the data lake in a structured manner.
The initial step to being smarter with marketing is to be relevant to the audience that you are targeting. Without relevant messaging for customers, using AI will not help with engagement. It’s important to listen to the customer, gather end user information, which is available real-time interaction, and then provide this as input to determine the next best action from a real-time personalization tool (e.g., IBM Interact). Being relevant across all your channels is making sure that messages reflect both your brand and individual targeting. Then, you can include AI to enhance the relevant to gather/understand tone and or intent using tools like IBM Watson APIs. The Watson API’s use the AI capability to analyze the unstructured aspect of human speech and provide structured data (happy, sad, angry, joy) back to the real-time personalization tool. AI can be considered an electricity to help marketers to gains access to data in faster manner.
It is not so much as only looking at offline (e.g., direct mail) and online (digital), but it is also significant to consider human-facing channels as well. Looking across all channels or touchpoints with a customer is why having a central decision hub is key. Using a single brain that runs at level below all your channels, taking in all your data, models, machine learning, past interaction data from every channel, to determine that one next best action regardless of channel. It’s important to look past the aspect of digital, human, and offline channels, however from a single perspective. That being that the customer is interacting with you as a single brand as opposed to multiple, separate channels. The channel in you communicate is not becoming less important, but you need to ensure that the experience is consistent regardless of the channel.