Simon Spotlight: Exploring GenAI in CDPs with Simon Data's product designer

For over ten years, Simon Data has always been at the forefront of leveraging data and technology to empower marketers. With the rapid advancements in GenAI, our team wanted to take a thoughtful approach to understand its implications and how to use it appropriately within our platform to provide real value to our users. 

In this post, Simon’s content marketing team sat down with Simon Data product designer Hana Kurihara, who shared insights from our recent AI research and discussed Simon’s approach to integrating GenAI into our product strategy. 

Hana, can you tell us about Simon Data's recent exploration into GenAI?

Of course! We recently conducted interviews and surveys with our users to understand their needs better. What's interesting is that we intentionally avoided mentioning GenAI at first. We wanted an unbiased view of what marketers are struggling with and how they're using our platform.

‍That's an intriguing approach. What did you discover?

We found that the biggest challenge for our users is making the most out of their customer data when creating campaigns. It's fascinating because this aligns perfectly with Simon Data's core mission as a CDP and GenAI's strengths.

So how does this finding influence your approach to incorporating GenAI into Simon Data's platform?

It's really shaping our strategy. We're focusing on how GenAI can help marketers better understand and utilize their first-party data. We're first looking at areas like improving data cleanliness and aggregation, which are crucial for getting the most out of GenAI and any data-driven marketing efforts.

Can you give us an example of how GenAI might help?

Sure! Let's consider data cleanliness, for example. GenAI could help identify and standardize inconsistent data entries, like variations in address formats or product names. Aggregation could assist in creating more sophisticated customer lifetime value (LTV) models by identifying patterns in purchase history that humans might miss.

That sounds promising. What AI features are already available on Simon’s platform?

We’ve started integrating GenAI in a few key areas. We currently have a Jinja generator in our template editor. It’s a nifty little tool that helps you assemble Jinja code blocks for email templates to personalize emails. We also have a segment description generator that automatically generates a description for your segment as you build it. Essentially, it gives users a quick, easy way to know who is in the segment. These features are just the beginning, though. We're excited about the potential to do much more!

How do you see AI changing the game for B2C retail marketers specifically?

For retail marketers, I think GenAI will be a game-changer in personalization and campaign efficiency, such as having the ability to quickly generate highly tailored product recommendations or create dynamic content that adapts to individual customer preferences at scale. 

A huge plus is the ability to automate and streamline tasks, but we’re looking to go beyond that by using AI to uncover insights and opportunities that might be hidden in your customer data.

Are there any challenges you foresee in implementing AI?

Definitely. One of the biggest challenges is ensuring that the AI models can work effectively with each of our customer's unique data sets. Every retailer has its own product catalog, customer segments, and historical data. We need to make sure our GenAI solutions can adapt to these differences while maintaining accuracy and relevance.

Looking ahead, what excites you most about the future of AI in marketing?

What excites me most is the potential for GenAI to democratize data science for marketers. Not every team has a data scientist, but using GenAI, more marketers can leverage advanced analytics and insights. 

I'm also thrilled about our partnership with Snowflake and how it could allow us to process first-party data more efficiently, leading to faster, more personalized insights for our users.

Any final thoughts?

I'd encourage marketers to start thinking about how they can prepare their data for the GenAI revolution. Clean, well-structured data will be crucial for getting the most out of these tools. And stay curious! The field is evolving rapidly, and there will be many exciting developments to come.