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Three Ways AI Can Boost Customer-Centricity

Reflection of computer data on a woman.

While we may not be entirely out of the woods yet, we have grown familiar enough with ongoing disruption to be able to move forward and begin focusing on growth rather than simply staying afloat. For many businesses, the focus will shift to becoming more customer-centric.

While true customer-centricity must emanate from every level and department of the organization, the task of creating and delivering these types of experiences rests with sales and marketing. Artificial Intelligence (AI) can help facilitate this and enable organizations to reach this goal more easily and effectively. Let’s explore how.

Better Insights

In order to be truly customer-centric, you need to really know and understand your customer. What drives them? What really matters to them? What influences them to choose your product or service over your competitors? This is the marketer’s raison d'être. It is also one of their biggest challenges, as habits and attitudes change swiftly and often. Historically, marketers had to conduct detailed research to uncover customer requirements. But thanks to our increasingly digital behaviors, this information is now much easier to attain.

Whether we like it or not, every activity we do creates data. If we visit a website, make a purchase in a store, or interact on social platforms, we contribute to our data footprint. This information helps to paint a picture of who the customer is, what motivates them, and what their interests, attitudes and habits are. This is incredibly valuable for businesses, yet many are simply unaware as to how they can exploit the data.

Increasingly, AI has the answer. AI tools have the capability to collect, organize and categorize this data, making it more easily accessible for marketers and salespeople. Beyond cleaning up unstructured data, AI can help make sense of it. AI is able to analyze large volumes of information, detect patterns and trends, generate insights and even make recommendations. This usually happens continuously in real time, making it possible to gain the most up-to-date snapshot of the marketplace when it is needed. No human employee could possibly replicate this speed or analyze such a large volume of data in that much depth. By allowing AI to do this part of the job, the human staff is then freed up to focus on turning these insights into action through the more creative and strategic types of thinking that AI cannot yet replicate.

In my book AI Strategy for Sales and Marketing, I include some case studies of various platforms that help marketers accomplish this. For example, Brandwatch is a social listening tool that monitors the ongoing online conversation about a brand across all platforms, ranging from social to review aggregators to news sites. The platform tracks this activity looks for trends and can even assess the sentiment behind this discourse. Are your customers saying great things about your brand, or are they fed up? The tool is able to alert the marketer to potential problems and opportunities so that they can be handled accordingly. That makes the marketer more effective and helps contribute to a better brand experience for the customer.

Personalization at Scale

The insights AI can provide about the type of experiences customers desire is invaluable, but its ability to deliver those experiences is another real asset for marketers. Today’s consumers are aware of the fact that they are generating data, but that has created an expectation that this data will be used to enhance their experience. We are witnessing a rise in consumer demand for more tailored personalized experiences.

Normally, marketers segment their audiences and then target these groups. This usually involves some generalization, because catering to each audience member would typically be expensive and time-consuming. But astoundingly, AI makes it achievable. Many organizations across all industries are using intelligent tools in order to help tailor their customers’ experiences at scale with little to no human interaction. The use cases range from more complex activities such as providing each user with a different website experience, while others have become so commonplace that we don’t even think twice about them.

A prime example of the latter is Spotify’s selection of personalized playlists. The Spotify app interface itself looks the same for every user and every Spotify customer uses the app for the same fundamental purpose: to listen to music and/or podcasts. However, your Spotify experience will likely be completely different from that of your partner, friends, family, or colleagues who use the service. That is because the platform is highly successful at using customers’ data effectively to create totally tailored experiences. Spotify’s algorithms learn from your listening history in order to make recommendations and generate playlists of other music or artists you might enjoy. The entire streaming experience feels customized, even though at its core, the basic functions are universal.

Reinserting the Human Touch

It may seem counterintuitive but using AI can help us to reinsert human elements back into marketing, sales and other functions. As we are learning, AI is an incredible technology, but it has its limits. These tools can generate incredible insights and inform you about your customer and your business, but this is worthless without a human to put it all into perspective. Your customers are not just data; you need to be able to take the information they produce and turn it into actions and initiatives that will deliver value for them and for your business. Artificial intelligence helps to paint the picture, but human intelligence tells the story. When the two marry, the customer wins, which means you benefit too.