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Hershey's AI-Powered Media Mix Modelling: A Blueprint for NZ Marketers
Confectionery giant Hershey's is leveraging an advanced AI-enabled media mix modelling (MMM) system to refine its media investment strategies. This initiative signals a broader trend towards marketers owning and developing sophisticated AI tools for media optimisation, moving beyond traditional approaches.
What Happened
- •Hershey's has developed and implemented an AI-powered media mix modelling (MMM) system to guide its media spending decisions.
- •The company's programmatic lead, Vinny Rinaldi, emphasised the importance of brands owning their AI solutions rather than relying solely on third-party vendors.
- •This internal development allows for greater control, customisation, and deeper integration of AI into their media strategy.
- •Hershey's intends to expand its AI adoption beyond MMM, indicating a long-term commitment to AI-driven marketing.
- •The move reflects a strategic shift towards more data-driven and predictive media allocation.
- •Source: Digiday, 14 May 2026
Why It Matters for NZ Marketers
- •NZ marketers can learn from Hershey's proactive approach to developing proprietary AI solutions for media measurement.
- •It highlights the increasing need for local brands to invest in robust, in-house analytical capabilities to compete effectively.
- •Smaller NZ marketing teams may find inspiration to explore accessible AI tools or partnerships for similar MMM benefits.
- •This trend will likely accelerate the demand for data scientists and AI specialists within NZ marketing departments.
- •It challenges the reliance on agency-provided MMM, encouraging NZ brands to gain deeper insights into their media performance.
- •The focus on ownership ensures models are tailored to specific market nuances, crucial for NZ's unique consumer landscape.
Strategic Implications
- •Marketers should consider developing or significantly investing in proprietary AI tools for media optimisation and measurement.
- •Prioritise data integration and clean data pipelines as foundational elements for effective AI-driven MMM.
- •Foster cross-functional collaboration between marketing, data science, and IT teams to build internal AI capabilities.
- •Evaluate existing media measurement frameworks to identify opportunities for AI enhancement and predictive analytics.
- •Shift focus from simply collecting data to actively leveraging AI for actionable insights and strategic decision-making.
- •Budget for long-term AI development and talent acquisition, viewing it as a core strategic asset.
Future Trend Signals
- •Increased internalisation of advanced marketing technology and AI development by brands.
- •Greater emphasis on predictive analytics and real-time optimisation in media planning.
- •The rise of 'AI agents' or autonomous AI systems managing aspects of media buying.
- •A growing competitive advantage for brands that effectively own and deploy sophisticated AI for marketing.
Sources
Editorial note: This analysis is original, AI-assisted editorial content. All source material is attributed with links. No full articles are reproduced. Short excerpts are used under fair dealing principles.
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