AI and Machine Learning in Database Marketing

Artificial intelligence (AI) is where the computer then uses the best result and makes a decision. In short, it takes action in part due to that result without any human involvement.

Combining ML and AI makes marketing more sophisticated, allowing us to interact with people on a more personal basis, treating them as an individual rather than part of a larger segment.

I am quite lucky in that Euler is partnered with several technologies that have embedded ML and AI into their tools, which make my job easier and very exciting. Two partnerships I work particularly closely with is the Apteco Marketing Suite and Sisense.

The Apteco Marketing Suite is a campaign selection and analytics platform, where I can perform exploratory analysis on datasets to use in predictive models. Through recent developments in the FastStats tool, I can identify from transactional data, what behaviours are important and help classify those transactions into meaningful groups by a few clicks of a button. In other tools, this usually requires a lot of code writing or time developing tests.

Combining the analytic power of FastStats with another Apteco product, PeopleStage, audience parameters can be used to make decisions on which model is best for that individual, indicating which journey the individual should take and creating a truly personalised interaction.  

But where this becomes really exciting is Sisense’s use of AI in their Natural Language Querying ‘ask me anything’ button, which allows you to write a question as if you were talking to a human being and Sisense will go and explore the data model and present you the answer. It’s like “Ask Jeeves” has been reincarnated but for insight! 

Where is the AI you are asking here? Well if you look under the hood, you will see that the Natural Language Query algorithms are building a library of terminology and mapping them to the fields within your data model, continuously learning which is the most appropriate mapping to the data. Different departments and people often use their own terminology. Over time, the NLQ learns and builds that library for you. 

There is AI and ML embedded in a lot of tools today, but people are either scared of using it thinking it will replace them one day, they don’t know how to use a particular module or tool, or they are not even aware that the functionality exists.