Hi! I'm Nathan, Co-founder and CEO of Raleon. We are thrilled to have you here with us! Before getting into all the fun product, configuration, and branding details available here in our product docs, I wanted to take just a few minutes to share why we believe so deeply in the power of personalization.

I won't bury the lede. We believe that personalization at scale is no longer a choice. . Let me explain with a short example from the TikTok hive mind from August 2023.

Treat Your Customers Like They're the Main Character

In August 2023, a creator named Kara posted a bean soup recipe on TikTok, noting its high Iron content for women on their periods. In classic social media fashion, another TikToker named Sarah replied with her own viral video geared towards the original video's onslaught of commenters, many of whom had questioned if it was possible to substitute anything else for the soup's main ingredient, beans.

Sarah's rebuttal sparked a fascinating debate over the "What About Me?" effect. This exceedingly 2023 phenomenon reinforces to us (brand leaders, marketers, and product designers) that speaking your audience's language has never been more imperative.

The viral discourse over bean soup on TikTok wasn’t really about beans or soup; the main ingredient was the basic human yearning to be deeply understood. Treating your customers as they want to see themselves - as the "main characters” in their own story is a must; here, they control the narrative and have ownership over how their character is perceived.

And while it's become self-evident that the key to creating truly loyal customers is personalization to product, the real challenge is only just heating up. For businesses it’s no longer about deciding whether or not to personalize, it is about determining the extent and cost of achieving personalization at scale.

Buckle up, because it’s time to upgrade your loyalty system with AI.

A primer on what not to do

A few years ago, I found myself eating lunch at a local deli twice a week or more for the better part of two years. As soon as I walked in, the employees greeted me by name, took me to my normal spot at the counter, sat my routine drink on the table, and asked me (confirmed, really) if I wanted the usual.

The staff at this deli took all the data they’d observed about me – my food and drink orders, my seating preferences, even something as simple as my name – and applied that to a personalized, one-of-one experience that kept me coming back over and over.

They knew me, they knew what I liked, and I trusted them to take care of me.

Contrast this with my experience at a well-known national chain. Thanks to my membership in their loyalty program, this chain knew my order history, my menu preferences, the time of day that I visited, and so on. They have far more data, far more resources, and far more people focused on this loyalty program’s administration than my deli.

And yet, after going there for months at breakfast and never once ordering a coffee, they continue to email me discounts on coffee. They can send me as many high quality emails as they want, I’m just not interested in getting caffeinated.

I tell this story to illustrate a specific point - just collecting data at scale is not enough - it’s what you do with it that counts.

A case study on scale

The world’s most popular services like YouTube, Instagram, TikTok, Spotify, Netflix, and Amazon personalize every. last. thing. In this new age, a broken personal recommendation algorithm is grounds for immediate service switching. Imagine being a die-hard romcom fan and constantly getting horror recommendations. Game over.

This scalable personalized “algorithm” is the true moat for these products and businesses. They thrive not just for their unique content offerings but for the way they offer it up - customizing their algorithms to understand their users makes their products more interesting, sticky, and relevant. The same moat can be built for brands who want to leverage AI to make every one of their customers feel like their own main characters.

A word on The Giants

It’s easy to overlook that two of the most influential companies in the world, Meta and Google, got that way because of their ability to personalize everything. Without getting too far into the weeds, part of their explosive growth came from an earlier AI innovation around “Alex Net”, what’s now more commonly referred to as Convolutional Neural Networks (CNN) and Recursive Neural Networks (RNN).

These companies built AI powerhouses on this technology, which spurred the growth of the feeds and search results we know and use today, along with the very effective advertising methods we’ve come to rely on. They funneled all that intelligence into algorithms so they could be more personalized, and even eerily human.

These aforementioned platforms are obviously years into their algo-building - so the question becomes: How can you and your team begin to do this for your own companies at scale?

AI and your ads

Optimization at the ad level isn’t new. But now, Generative AI tools and Large Language Models (LLMs) like GPT4 allow consumer-friendly chatbots like ChatGPT to understand and articulate massive data sets. This enables them to complete complex tasks such as image classification and object detection in order to satisfy a wide variety of natural language prompts (read, questions from humans) at scale.

Thanks to machine learning, any enterprise can now leverage AI to create and optimize ads targeting for very specific user segments based on interest, behaviors, and intent. It’s a revolution for every brand in digital advertising – AI generated copy and content on top of machine learning optimized targeting.

The AI cycle of life

Performance marketing has never been more effective (albeit noisier). But personalization’s effectiveness isn’t limited to the top of the funnel. It can be a game-changer for your entire customer lifecycle.

Delivering personalization at every interaction with a customer is a daunting task, and can be an expensive one if not tackled properly. The goal, after all, is not just to deliver a better “I’m-the-main character” experience to the customer, but one that provides a meaningful return on investment.

We’re talking about a lot more than just better product recommendations here. As AI continues to evolve over the next few years, the ways we can personalize customer experiences will become more sophisticated. For example, imagine sending a personalized video to a customer, using their name and some details, thanking them for their first purchase with you, and sharing ways they can use that new cooking spice. Sounds crazy? It's here, it’s real, and brands on the cutting edge are already rolling these capabilities out in their growth and retention campaigns.

Your tools have already arrived

AI has already shifted the landscape for marketers, advertisers, and brands — and there’s now countless ways to use this technology to your advantage to make your customers feel like you know them better than they know themselves. Investing in and leveraging this technology (or at the very least understanding it) will enable your brand’s every customer interaction to have personalization baked into it by default.

Think this level of attention to your customers’ needs, preferences, and desires is unwarranted? I’ve got two words for you: bean soup.

Loyalty will never look the same again.