How AI Builds a Canvas for Customer Loyalty

2017, is the year where AI has finally become a mainstream business platform. Many of the services, apps and products, that we use on a daily basis are being powered by artificial intelligence and machine learning platforms.

AI is directly shaping how our future will look in the coming years. The 2 gadgets that we are heavily dependent on today, our computer and our phones have AI assistants and machine learning tech built in. People are buying AI assistant based product for their home automation systems like Google home, Amazon echo etc.  

Evidently, it was just a matter of time when Artificial intelligence became a household product. But before this happened, the AI and machine learning wave had already hit the business sector.

Accenture forecasted that the impact of AI technologies on business will increase productivity by up to 40 percent and enable people to make more efficient use of their time.

What general marketers forget is that, AI will eventually provide a canvas for improving customer loyalty too, by providing a seamless and customer centric experience.

How does AI improve customer Loyalty?

Here are 3 ways by which artificial intelligence would contribute to better customer loyalty and retention rates. Today, we will discuss each one in detail –

AI will make it easier for you to find flaws in your product

With the use of AI and Machine learning technologies, finding flaws in your own product became easier. AI can monitor customer behavior and engagement with every feature that your product has to offer. And it could provide you useful insights about your product’s features.

Using the data that AI will mine out for you, you can thoroughly understand what features of your product makes it a high-seller and which features make it a deal-breaker for users. By refining your product’s features and offerings, you can really make your product stand out and provide your users a customer-centric experience.

Hence preparing a canvas to improve customer loyalty by providing better iteration of your product.

AI will personalize customer experience on 1:1 level

Personalization and segmentation are every marketer’s nightmare. Before AI came into the picture, a lot of companies tried to emulate 1:1 personalization for customers and failed miserably.

As their user-base expanded, marketers found out that it’s nearly impossible to personalize user communication on a 1:1 basis. Instead, they come out with a make-do technique, which was named segmentation. Segmentation is a marketing tactic, where similar users are grouped together, and then the communication is tailored accordingly to the group’s trait.

In simple words, segmentation meant having a set of communication rules, based on the group of customers a user falls into. A One-to-many approach to user communication. Here is a detailed discussion of why personalization is a much better approach than segmentation for user engagement.

But with the combination of AI, machine learning, and automation, Personalization could be easily implemented. And there are several instances where personalization has helped brands retain customers. A 1:1 experience has always been one of the major factors when it comes to driving higher user engagement and optimizing conversion rates.

How you ask?

AI and machine learning product and platforms are integrated with your product in a tightly-knit environment. Once the integration is complete, AI engine starts monitoring all kinds of user activity and interaction on-site (website, mobile app, etc) and off-site (transactional emails, push notifications, promotional emails etc).  Utilizing the continuous stream of data, it starts optimizing your on-site and off-site messaging and makes a better recommendation on a personal level. This pushes out a better overall user experience, which is a key factor in boosting customer loyalty in the longer run.

Here is our story on how we worked with She Finds to personalize 30 million customer facing emails.

AI understands Omnichannel engagement

AI systems are smart enough to understand any user’s behavior. Using this data, AI will always target devices and channels where the user is most likely to engage with your brand.

Apart from that AI will also segregate users based on their liking, their activity time-frame, when they are most likely to buy from you, etc. Combined with multiple devices, this data would allow AI engines to push messages when your customers are most likely to open and read these message.  

You might also like – Omnichannel vs Multichannel marketing – which is better?

2 real-life examples of AI boosting customer loyalty

By now, you must have got the idea that AI increases customer loyalty by providing them useful information at the right time. We will show you 2 superb examples, where successful brand have used AI customization to increase their customer loyalty.

1. Spotify’s music recommendation engine – Spotify have built their own AI and machine learning engine, whose sole purpose is monitor a user’s listening preferences and tailor the whole product around it. In the first 2-3 weeks Spotify’s AI engine would have understood what you like, which artists are your favorite, what are the genre’s you are most interested in, to minute details like, when do you listen most often, your average listening period, etc. Using all these data, the AI engine will recommend music that you are most likely to favorite or save to your own collection. Apart from that, it will automatically send you communication about new releases from your favorite artists, how your favorite music charts are shaping up, etc. Streaming industry experts, credit Spotify’s AI engine for their massive growth in last 6 years and also how easily they have fended off bigger companies like Apple, Google, etc in the same industry to keep the top player title for themselves.


2. Under Armour’s Fitness App – Under Armour, the leading american brand for sports and Fitness have a highly successful fitness app. The best part about the app is AI engine that supports it. As a result each individual’s routine are informed by personal, physiological and behavioral factors. They integrate machine learning technology to understand everything about their users. The app analyses personal food, exercise and sleep data in combination with insights from other anonymized members of the community, providing real-time advice and motivation.

So these are the few ways in which brands can approach AI and machine learning and build a platform for improving customer loyalty.  Our mission at Boomtrain is to help brands excel at providing stellar user experience regardless of the nature of the users (whether the user is just a reader or the user is your customer). If you liked this article, be sure to check out our blog for more on AI, user engagement, and personalized marketing.