Speakers identified a range of use cases from building analytics queries with natural language, to interpreting charts with AI

Mixpanel, the event analytics* pioneer, recently hosted its annual EMEA Customer Forum in London, where more than 100 product and analytics leaders from the world’s most exciting digital innovators gathered to exchange ideas, share best practice, and hear from peers that have used event analytics to build outstanding digital products.

A key theme of the forum was the role that generative AI will play in product analytics, with speakers from companies including telecoms giant AT&T, fintech leader Wise, trading platform eToro, video game innovator Superplay and gambling software firm Playtech, touching on the potential of generative AI for analytics.

Rather than having to prepare queries, analytics leaders anticipate being able to chat with AI using natural language to get fast answers from their product data. For example, instead of writing a Structured Query Language (SQL) query to extract specific insights from a dataset, or using more modern and intuitive workflows like Mixpanel, the leaders saw potential in simply asking a question of generative AI linked to their analytics tool, like, “At what stage of the sign up process are we seeing the most drop offs?”. AI chat could be used in this way to create meaningful visual representations of data, such as charts and dashboards, removing the need to build queries manually.

Hazal Muhtar, Head of Global Product Analytics at fintech leader Wise said, “We’re using Mixpanel to better understand what our customers want from their Wise product experience, particularly our newer SME customers. My team guides our colleagues but we put Mixpanel directly in their hands too. In the most effective digital companies, analyzing and interpreting data extends beyond data scientists. I look forward to seeing how generative AI will enable people without a data background to begin asking questions.”

The experts also saw generative AI being used to identify anomalies and blind spots in datasets that may be challenging to detect using manual methods. By identifying emerging anomalies at an early stage, proactive measures can be taken to address them, enabling more efficient and accurate analysis.

“Generative AI has the potential to transform product analytics,” said Natalie Kouzeleas, VP EMEA & LATAM at Mixpanel. “We heard from some of the industry’s foremost practitioners at this year’s customer forum on a range of topics, but generative AI kept on popping up. Those working with customer data to build better product experiences know it can help them do more and empower a greater number of people to ask questions of data that aid decision making.”

Integrating generative AI into analytics tools can make data insights more readily available to all team members, creating an environment where insights become an integral part of more discussions, problem-solving, and decision-making processes. Team members who may previously have been reluctant to attempt data analysis become more comfortable using data, interpreting it, and drawing insights. Indeed many of the speakers explained how they were already making significant progress with Mixpanel’s existing user interface.

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Vasileios Papageorgiou, Lead Analyst at gambling software firm Playtech said: “We’re making it possible for hundreds of gambling brands that license our casino, sports, and retail betting games to easily visualise and ask questions of their user data with Mixpanel. For example, pop-up messages can provide valuable information and resources to players, such as reminders to take breaks, set limits on their gambling activity or access self-assessment tools. By integrating these messages into the online gambling experience, brands can help to encourage responsible behavior and reduce the risk of problem gambling.”

Leon Sucharov, Chief Technical Innovation Officer at gambling software giant Playtech said: “We’re making it possible for hundreds of gambling brands that license our casino, sports and retail betting games to easily visualize and ask questions of their user data with Mixpanel. Previously they couldn’t see things from the player’s perspective, now they can easily see what is and isn’t working for users, and make continual improvements.”

Guy Barkat, Product Analytics Leader at trading app eToro added: “Before Mixpanel we used BI and it took weeks to code SQL queries, tabulate the data and eventually publish a dashboard. Now we have 300 Mixpanel users asking questions of our data in minutes or even seconds. We still have BI capabilities but our senior leaders often bypass the process and jump straight to Mixpanel. Adding AI chat into the mix will make it easier, so more conversations and decisions can be grounded in the data.”

Engaging in this shift and taking advantage of new innovations in the coming months will prove essential for businesses wishing to make data insights available to more teams and colleagues.

But Paolo Sabatinelli, Chief Product Officer at Italy’s leading digital property portal, Immobiliare.it, explained that a degree of caution is needed: “I do have reservations about making analytics too easy. We need to ensure there are checks and balances so that people who aren’t experienced at working with data don’t make unintentional mistakes. We know AI isn’t always accurate, so there needs to be a data savvy person in the process, and a way to double check the AI’s work.”

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