Machine learning, artificial Intelligence (AI), cognitive computing, and decision engines. These are all buzz words or phrases that are trending in 2017. We need them to scale our customer experience, but let's not forget that personalization is about being personal. We know that data and technology are growing and developing at an incredible rate, but customer expectations are rising at an even faster velocity. We need to use automation effectively within our marketing platforms to keep up with these expectations. Choose technologies that will help you drive production line responses that not only add value, but also open opportunities for deeper ad-hoc communications and relationships.
The thing about personalization is that it's not just what you know about me; it's also about the context and even my state of mind. Things about me, such as my routine, my mood, or my surrounding environment, can make a big difference in how I want to be engaged. It's important that any decisioning engines factor this in.
In the commercial world, Lego is a great example of personalization. Not because of its website or its clever go-to-market combination of film and product, but because of the way children and adults use the product; the options that Lego gives you at the time you need it. It's fairly similar to the principle of Google. Google gives me answers to the question that I need answering, at the exact moment that I want the answer. With Lego, I may start playing with the knowledge of exactly what I want to build, or I may have no idea at all. With each new piece, my journey and my options move forward and change until I eventually get closer and closer to my end goal, which I may or may not have known from the start. And even if I had a vision, it may have a completely different outcome than I originally intended. The principle driver of creating an adaptable customer experience around customers is understanding how personalization can drive long-term relationships and better business results. Merkle’s 2017 Marketing Imperatives explore in-depth how to create personalized experiences.
I was in a meeting with a technology executive recently who raised a great point; "When we make recommendations to call center agents using technology, this is based on what we know. If the customer tells the agent something different, or they read that the call is going in a different direction, we tell them to change direction with it." This is a great example of how to blend automation with human context. You can see this approach being used in other AI technologies, such as virtual agents like Nuance Nina or IP Soft Amelia, or virtual EAs like Claralabs. We need to understand when automation works and when you should “hand off” the decisioning to a real person. Understanding this mix is the first step in obtaining truly personalized customer experiences at scale.
