Personalization today, tomorrow and beyond

Let’s face it, the word “personalization” has been stretched thin. Companies are quickly launching tailored experiences that have a lot of promise for converting customers, but often fall short due to their execution. For many, it's their first time experimenting with this, and creating content at such a scale — so it makes sense that there is a learning curve. 

The best way to get around this curve is to take a beat, understand the state of personalization today (and into the future), and get strategic with your implementation. What should that strategy include? 

Allow Sara Sullivan, VP Solution Engineering, Contentful, and Dan Dicamillo, CTO, Code and Theory, to walk you through it. The pair recently joined Adweek and spent time exploring modern personalization and its roots, barriers to launching personalization, which technology is best suited for the job, and so much more. 

If you want the nitty-gritty details, here’s the full webinar recording (which you can watch on demand). If you’re short on time and just want the highlights, you’ve come to the right place. Continue reading for some of the best sound bites of their conversation and take what you learn with you as you build out your personalization strategy and a stronger relationship with your customers. 

How has personalization evolved over time?

Dan Dicamillo: I encountered personalization in the early 2000s, but back then, it was really just another name for A/B testing. We would try to figure out what the customer liked and then keep on serving it to them to facilitate their journey with the brand.

The expectation shift really came with the introduction of social media. Each time you log on, you get a dopamine hit, and some brand gets data about you from that interaction. From there, they get a better sense of who you are and what you want, and they can use this information to give you a better experience. 

We see it with Facebook, TikTok, Netflix, and verticals outside of media and entertainment like Uber — they know when you’re hungry and what you want to order. Customers are starting to catch on to this give-and-take. If a customer gives up their valuable data, it better be worth the effort.  

Sara Sullivan: These customers also want the personalization to be consistent across channels. Let’s say I’m on Instagram, I see an ad for a pair of trainers and click on it. It takes me to the product page, but then there is a pop-up. It suggests I download the mobile app for a better shopping experience, so I figure, why not? When I get into that app, I want to be served content based on the product I’m already interested in. I’m looking for the same personalized experience across channels — and that can be difficult when you have web, mobile, app, email, social, etc.

What are some modern barriers to launching personalized content?

Sara: Definitely, how much time and resources it takes to create that content if you don’t have the proper tools. If I look at the basic content management for my digital experience, there is already a lot to do. I need to create that first version of content, localize it, and then keep it up to date. Then, I’ll need to do it again and again as I enter new regions — it’s a lot. But wait… 

Personalization crashes the scene, multiplying the number of audience segments you have. Doing that at scale is really, really difficult.

Dan: That’s especially true when companies work with legacy technologies. You have all these tools that promise to address personalization but a lot of them aren’t as future-ready as they need to be. They have all these business rules that have to be authored in the back end and everything is forced into the UI rather than something that actually allows you to federate content freely via API layers and create business rules on the fly. This speed to market is especially important now that AI tools are allowing companies to generate new content faster than ever before.

Why are solutions like Contentful a good fit for most organizations as they begin personalization?

Sara: It's important to zero in on a technology that multiple areas of the business feel comfortable using, otherwise you become dependent on engineering and other teams to get things out the door (and sometimes there are multiple things in their queue that they need to address before they get around to yours). We really need to unburden marketers from having to run their work through different teams and technologies. We need to give them the tools to do their job better. It's a win-win because those teams' marketing relies on them wanting to do other work. 

Dan: At Code and Theory, we are firm believers in composability and having that sort of sense of separation between the presentation layer and all the tools needed to power it. You get the freedom to integrate different tools and even data sets to build a more bespoke user experience.

How do new generations discover brands? What is its effect on optimization best practices?

Sara: What my mind immediately goes to is GEO. SEO, to a certain degree, is yesterday’s problem. It’s important and you have to solve it, but the bigger focus needs to be on generative engine optimization (GEO) and how you’re producing content in a consistent, scalable structure for it. Ultimately, you’re going to train not one GPT tool, but thousands, if not millions. That's the future, and you have to start preparing for that future today.

Dan: It’s a different ball game for current and future generations. Gen Z isn’t going to Google to find things or ask questions. They’re going to ChatGPT. They’re going to Perplexity. AI-driven tools are more conversational and simpler to work with. The briefs we receive from clients interested in attracting this audience are amazing. They say that traditional SEO is missing these individuals. In fact, many startups are starting to prioritize optimization for crawlers of LLMs by approaching content in an atomic way so it’s easily understood by this technology. 

How can companies ensure brand consistency when using GenAI tools to create personalized experiences and other content?

Sara: We put this type of content in another category: “contextual AI.” To get LLMs to take on the voice of your company, you need to build or rearrange your style guide to be read by these technologies. In fact, many organizations are choosing generative tools that incorporate these things from the very start. They find that the output is of higher quality. 

Contentful can definitely help here, as content is broken into smaller pieces to fit within a content model. We even have a personalization and experimentation platform baked in (Contentful Personalization) — so everything is really easy to set up and use.

Wrapping up

Before ending their chat, Dan and Sara answered a few questions from the audience, including:

• How does personalization differ between B2B and B2C businesses?

• As personalization progresses, will we respond to user intent or end up subtly shaping it by curating the content they're exposed to?

To find out what advice the experts dished out, watch the full webinar recording. 

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