AI & Personalization for Brand Loyalty
The evolution of data-driven marketing
In today’s world, it’s becoming more and more clear that customer loyalty is an essential component of business success. With so many choices available to consumers, it’s critical for businesses to build strong relationships with their customers to keep them coming back.
At the same time, we’re seeing an explosion of innovation in the world of artificial intelligence — DALL-E blew our minds when it showed that it could create pictures from language prompts. ChatGPT took the world by storm, as it took text prompts to create news articles, students’ essays, speeches, and more. There’s no doubt that if emerging AI tools are used in the right way, they will radically change the world of marketing & customer loyalty.
One of the most effective ways to improve customer experiences will increasingly be by using AI. Let’s explore how marketers can use AI to deliver personalized experiences, anticipate customer needs, and build lasting relationships that drive customer loyalty.
One of the key benefits of AI in marketing is the ability to deliver personalized experiences. While data analysis is not a new concept, AI can analyze data and extract patterns and insights far better than humans can, diving deeper into individual customer preferences, behaviors, and needs.
This data can be used to create tailored marketing campaigns that are more likely to resonate with customers and drive engagement.
Traditionally, marketers analyzed data on aggregate, or through segmentation. After all, most brands don’t have the time or bandwidth to analyze the shopping behavior of every single customer. Customer segmentation is a shortcut.
However, AI does have the time and bandwidth to do this deeper analysis. It doesn’t sleep or take time off, and it works much faster than humans can.
One brand already using AI for personalization is Sephora with their Color IQ technology, which pulls from a dataset of thousands of skin tones to help shoppers and store workers identify the correct shade for a customer.
This example is just a transactional way AI can personalize marketing campaigns, but once integrated with a web3 loyalty program, we can also better understand how a customer likes to interact with the brand outside her visits to the store.
Maybe they engage most with Instagram posts or like to buy certain products on the website (as opposed to in-store). Web3 loyalty programs are interoperable, meaning that different customer touchpoints can be “stacked” together to create a unified view of a single customer. Customers carry a unique identifier (their membership token) across social media, points-of-sale, IRL events, or other branded channels.
No matter what it is, a holistic, unified picture of the customer through a web3 loyalty program provides more data points for AI to analyze and more opportunities for insights to be extracted that humans may have missed.
Anticipating Customer Needs
Another important use of AI in marketing is in predictive analytics. As we mentioned above, AI is significantly better at analyzing past customer behavior and identifying patterns. By looking at past behavior, AI can predict future behavior.
This information can be used to anticipate customer needs and deliver proactive, personalized experiences that build customer loyalty. In the same way that we distinguish between the individual and the aggregate levels of customer data, AI can identify patterns & trends between different customers on a granular scale.
Oftentimes, these patterns are not intuitive, so we can’t identify them. Because of the “black box” nature of AI, we have no understanding of how it works, and it “thinks” differently than humans might think.
Using AI to find trends across customer groups in past behavior allows us to find out things we would have normally missed, and therefore use those findings to offer the right products, to the right customers, and at the right times.
Real-Time Customer Service
Another important way to build customer loyalty is through real-time customer service. By leveraging chatbots and other AI-driven tools, brands can provide immediate support to customers in ways that are conversational and meaningful. While this use case might not necessarily apply to small businesses, it can be extremely effective as brands scale.
As an example of an apparel brand already using AI for customer service, Levi’s uses a virtual stylist to offer AI fashion advice via chatbot.
AI customer service tools trained on a company’s support docs and FAQs can help answer questions, resolve issues quickly and efficiently, and be responsive during off-hours. Responsiveness helps to build customer trust & satisfaction, crucial elements to successful loyalty programs.
As more brands develop an omnichannel presence (selling both online and offline), AI can help to bridge the gaps in customer behavior across multiple different channels & platforms. Whether it be social media accounts, advertising channels, email, SMS, online storefronts, or IRL points of sale, AI can do the heavy lifting of tying these pieces together to create a unified picture of a customer.
Currently, attribution is a nightmare for marketers. Tracking a single customer across an increasing number of touchpoints and gathering past data is already challenging enough, but predicting what customers will want in the future is even more difficult.
Fortunately, AI thrives under increasing complexity and can train on massive amounts of data to create better predictions of future customer behavior — where they will shop, what products they will buy that a brand offers, what other types of products they will want that the brand does not currently offer, and insight into other specific customer interests that might not have been intuitive.
We’ve talked before about how web3 loyalty programs are better than traditional ones due to the concept of interoperability. The next major step after having better first-party customer data is actually figuring out what to do with it. AI can deliver the insights from this unified customer view to help craft better and more personalized marketing campaigns.
Loyalty & Rewards
Lastly, AI can be used to enhance the rewards offerings in a loyalty program. By offering better rewards, brands can align incentives with their customers. This concept is not new.
What is new with AI is the ability to offer better rewards than were previously possible. “Better’ is subjective — it varies from person to person. As it was previously not feasible to offer the right rewards to each individual person, AI makes this possibility a reality.
As a fictional example, AI could tell us that Anna visits LA Grind (a coffee shop) on nearly every Tuesday, Thursday, and Saturday — and on Saturdays, she orders a turkey bacon and egg sandwich on gluten free bread with her coffee. Over time, it may notice other patterns, like how she orders different drinks, but always chooses the vanilla flavor. AI might notice that she never orders a product with dairy. It could take all of these insights to create personalized marketing campaigns — special offers on specific drinks she likes, offers on new products that fit her dietary preferences, and more.
And this is just a single customer! AI can replicate these deeper insights with all customers, without additional lift from a marketing team. Surprise & delight moments can happen more often for every customer because all of their rewards are relevant to their personal preferences and experiences.
The result? Deeper, more meaningful customer relationships, driving loyalty and increasing customer LTV.
With the power of web3 loyalty programs driven by AI technology to do the heavy lifting, it’s actually now feasible for brands to retain that personalization touch at scale.
To summarize, by leveraging the power of AI to deliver personalized experiences, anticipate customer needs, provide real-time customer service, and develop effective omnichannel marketing campaigns, brands will be equipped to build next-generation loyalty programs. Those who do so effectively will create far better customer relationships, keep them coming back, and increase customer lifetime value.
Higher LTV at lower costs will allow brands to accelerate growth while doing it sustainably — without sacrificing the quality service & customer relationships that got them there in the first place.
AI is only in its early stages, and many of its future possibilities have yet to unfold. However, marketers who get started now will be lightyears ahead of those who wait. Disrupt, or be disrupted, as they say.
At Hang, we’re using next generation technology to create better brand-customer relationships. Learn more here.