Everything You Need to Know About AI-Enabled Personalization

Artificial Intelligence (AI) makes it possible to treat each of your contacts as a unique and valuable individual. Ever wonder how it works?  According to David Hahn, “The key ingredient to better content is separating the single from the stream.” In other words, the more you personalize, the better your results. In today’s world, this usually means some type of data-driven personalization is in play. With improvements in technology, we’re starting to see the use of AI-enabled personalization. You may not know exactly how this works. Have no fear — we’ll explain it in today’s post.

An Illustration of AI at Work

First, let’s look at a scenario that calls for intense personalization. Cast your mind back to your high school prom or any other social event that required you to dress up. Choosing an outfit was a big deal, right? Even if you weren’t fashion-obsessed, you didn’t want to wind up in a 20-year-old suit or dress. In this situation, imagine that a friend tells you they will give you some awesome clothes as per your liking for your event. That would truly be a personalized experience. But we can take it one step further. Suppose your friend gave you multiple choices and arranged to have your choice shipped to you the week before your event. That would be great! We can say that the second friend is an illustration of AI at work. Personalization can see a need and select a single product to fill it; AI-enabled hyper personalization can deliver tailored options and results on schedule. It’s taking things to the next level. At this point, though, let’s define what we mean when we say AI.

What Is AI?

AI is the science and engineering of making intelligent machines. Any science that enables us to make human-like decisions can be a part of AI. This includes such abstract and advanced concepts as logic, visualization, self-awareness, learning, emotional knowledge, planning, creativity, and problem-solving. AI is being used for a huge number of vastly different things. It can enhance one business’ marketing and another’s supply chain management; it can help us in the fields of medicine and sociology. People are using it to find the nearest gas station and to detect lung cancer — it’s becoming a ubiquitous technology. In the future, we can expect that the human-machine conversation aspect of AI to become more dominant. We’ll see an upsurge in the importance of voice, touch, and other really cool things. But right now, we are seeing AI in another new way: as a way to intensely personalize marketing communication.

How Does AI-Based Personalization Work?

Before jumping on the personalization bandwagon, it’s useful to understand how AI-enabled personalization works. Here are the broad steps:

1. Learning starts with historical data — a lot of it. Machine learning as a process is not very different than how a child learns. Both begin to differentiate between right and wrong through instruction and prior knowledge. On similar lines, we feed scenarios (historical data) into the machine and let it know what is correct. It needs to know why a customer responded to an offer, why they clicked on a specific email, etc. We are training the machine by showing it what has worked in the past. Later, we’ll be asking it to make connections between historical data patterns and its current inputs.

1. Individual technologies’ are integrated. Marketing requires the use of multiple technologies that, unfortunately, work in silos and rarely intercommunicate. The AI system needs to understand each technology’s input/output dynamics to improve their effectiveness. Also, AI needs to understand and adapt to advances in data science, and vice versa. This will make the entire system more effective.

1. The platform should be all-encompassing. Giving a decision option in a new situation is a major challenge for an AI system, as it must operate off past data. A machine that self learns can find similarities between new scenarios and previous ones. An AI system that works only for specific situations is not truly AI and will never scale well. The more situations the system can handle correctly, the better it will be.

1. Decisions are fine-tuned using a feedback loop. A crucial part of AI self-learning is the feedback loop, a process that provides continuous feedback on the decisions the system makes. The AI system needs to know if the historical decisions were right or wrong, and it needs to be smart enough to tweak its own algorithm and provide more accurate and robust results. It basically should self-learn.

The greatest effort in this type of system is collecting the data, streamlining the various processes, and feeding into the AI system. Organizations that successfully accomplish this are rewarded by more powerful, targeted, and effective hyper personalization. AI might seem like a new development in marketing, but in reality, it’s taking technologies and processes one step further.

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Authors:

• Rajat Narang, Associate Director, Absolutdata
• Abdurrehman Malekji, Manager, Absolutdata