Alice Bedwell
Alice Bedwell
Posted 31 October 2023

How Martech Companies Leverage AI

Breaking Down the Podcast with Wunderkind and Ometria

Djalal Lougouev, President & Co-Founder of Ometria, joined Vern Tremble, Senior Director of Marketing and Communications at Wunderkind for an episode of Wunderkind’s Individuality Unleashed. To watch Djalal and Vern in action, check out the podcast here. Or if you’re more of a reader, here are the key takeaways from the session with Djalal and Vern.

About Ometria

For those who aren’t familiar with Ometria, Djalal starts the podcast by revealing how he joined forces with Ometria CEO and Co-Founder, Ivan Mazour, to create Ometria and evolve the Customer Data and Experience platform to deliver on its foundational mission: helping retail brands create marketing experiences their customers love.

This mission could only ever begin with data at the heart of customer experience. Through leveraging Ometria’s 30 billion retail data points, retailers can understand how to execute the right experience for individual customers at scale.

About Wunderkind

Wunderkind is a performance marketing solution that helps brands reach new customers at unprecedented scale through their owned channels without relying on third-party cookies through proprietary identity management technology purpose-built for web, email, and text. By expertly tailoring, automating, and scaling brand-forward, one-to-one experiences Wunderkind helps brands acquire new customers at scale and keep them loyal for life.

Answering the tough questions

How do marketers actually go about leveraging the data they have to create efficiencies that benefit their marketing strategies?

According to Djalal, the first thing the marketer should ask themselves and their business is: “what are they trying to solve?” Understanding the ultimate objective, whether it’s to drive revenue, customer lifetime value, repeat rate or average order value, is where teams should start, prioritising the challenge they’re facing in order to find a solution. In terms of leveraging AI helping to provide that solution, it’s important to look at three main categories:

  • Predictive analytics: leveraging customer data to predict their behaviour and next move to be a step ahead, surfacing relevant content. 

  • Workflow automation: creating efficiencies from otherwise timely and manual work 

  • Personalization: using the data to create the 1:1 messaging effect


How do marketers go about vetting tools to enhance these three areas?

Find the biggest gaps in your stack

Finding technology and solutions in an abundant market is difficult as Djalal tells the audience there are over 10,000 different providers all with their own category and their own acronym. But problems arise when brands find a vendor that they need to retro-fit instead of aligning their mission with their technology from the get-go. 

Mapping out your own technological-ecosystem, then, should be your starting point. It’s imperative to look for a vendor that fits into and integrates well within this ecosystem. As Djalal put forward: find the vendor with the least path of resistance to your current stack.

What should marketers be wary of when it comes to AI?

Data Privacy

No matter what AI solution you’re using, be wary of data sharing. As with any due diligence, try to get an understanding from the offset about how data is processed and what would be done to enrich the data you already own. Asking these questions early can help you in the long run.


AI is there to spark creativity and innovation instead of being there to simply replace what humans are doing today. If you look at AI through the lens of advancing creativity to obtain a higher quality, embracing AI will become second nature. This will also allow you to achieve things you couldn’t prior to having that technology. Instead of replacing you, it’s about advancing you. 

An excess of automation

Once you start to automate multiple tasks, you can, in some occasions, put yourself at risk for losing the personal touch. The objective for many retail brands out there is to replicate the in-store experience so if you have AI that isn’t trained on the right data set, you’re at risk of creating messaging that doesn’t cut through the noise, but instead blends in. 

Lacking transparency

Make sure you know principles and parameters around how the algorithms you’re using work before you start using them in ways that won’t elevate your strategy. Make sure these principles align with your metrics of success.

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Where can you find additional resources that can help you to make the right decisions on AI?

Djalal suggests getting to grips with Chat GPT and Bart but warns that while it’s tempting to interact with bots in a very one-sided way where humans are simply asking for answers, we can receive a lot of value when we pass information back their way.

Talking to AI as if they are human and adhering to principles that human- to-human interaction dictates, can lead us to surprisingly profound responses. Djalal also suggested for listeners to read analyst reports with recommendations of Mckinsey, Forrester, Gartner while also checking out Wunderkind’s great content including whitepapers.

More specifically, Djalal referenced Ometria’s CDXP Buyer’s Guide that takes buyers through the martech-landscape, offering analyst recommendations and a full decision checklist to take into their vendor processes. You can get the guide here.

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