How Hershey Uses AI for S'mores Season Strategy

Picture this. You have a seasonal window of just twelve weeks to hit aggressive revenue targets. Your operations team is drowning in manual spreadsheets, trying to guess which end-cap display will move the most product across a thousand different stores. Meanwhile, your biggest competitor just deployed an army of algorithms to analyze store layouts, adjust marketing mixes on the fly, and track consumer behavior before you even get your first sales report.

That is exactly what is happening in the snack aisle right now.

The end of guessing: Tracking the summer rush

Historically, planning for a massive seasonal push meant looking at last year’s data, shipping cardboard displays to retailers, and hoping for the best.

Not anymore.

According to recent reports from Modern Retail, Hershey fundamentally changed its approach to the s’mores season—a period that brings in up to $250 million in sales. They built a proprietary tool that uses computer vision and augmented reality to show sales teams exactly where a display should go to maximize visibility.

Instead of relying on paper guidelines, reps point their cameras, analyze the physical space, and let the algorithm dictate the optimal setup based on real-time consumer data. Add in a marketing-mix model driven by artificial intelligence, and they are adjusting strategies instantly rather than waiting for a post-mortem report in October. For brands looking to maximize peak moments, this is a masterclass in how to adapt your tag new season Amazon strategies directly into physical and omnichannel retail environments.

3x — greater total shareholder returns are delivered by consumer packaged goods (CPG) companies that lead in digital and AI adoption compared to their industry peers. Source: McKinsey 2025

The great generative myth

Here is where most brand managers get it completely wrong.

When you hear about brands using AI for advertising, the first thought usually jumps to generative text or flashy artificial images. People think this technology is just a cheaper copywriter or a shortcut for the design team.

That is a dangerous myth.

The real power of artificial intelligence for manufacturers and CPG leaders is operational efficiency and spatial data processing. It is about computer vision analyzing thousands of retail shelves to tell you why your chocolate bars aren’t selling in aisle four but fly off the shelves near the marshmallows. It is about connecting supply chain forecasting directly to your real-time marketing spend. If your team only uses these tools to write social media captions, you are driving a race car at ten miles per hour in a school zone. Your top talent is still bogged down with manual data entry. Eventually, they will leave for a company that gives them the infrastructure to do meaningful work.

Epinium data: Brands that integrate AI-driven real-time data into their omnichannel retail strategy reduce decision-making time by an estimated 40%, freeing up operations teams to focus on strategy rather than manual reporting.

What this means for your operations

You do not need to be a multi-billion dollar chocolate empire to apply these principles today.

The barrier to entry for computer vision and real-time analytics has dropped dramatically over the last year. Tools that required a massive in-house engineering team five years ago are now accessible via specialized SaaS platforms and consulting frameworks. What you actually need right now is a shift in mindset.

Start treating your physical displays and retail placements with the same analytical rigor as your digital ads. If you run a digital campaign, you track impressions, clicks, and conversions minute by minute. Physical retail is finally catching up. By adopting models to measure physical shelf performance and seasonal spikes, you iterate faster. You stop arguing over subjective opinions in board meetings and start executing based on hard mathematical probabilities.

Why is Hershey using AI for s’mores season?

They deployed AI tools featuring computer vision and augmented reality to determine the absolute best in-store placement for displays, maximizing visibility and sales during their peak summer season.

How does computer vision help retail brands?

It analyzes physical spaces through cameras, allowing algorithms to process shelf layouts, customer flow, and product positioning without requiring humans to manually measure and report back.

Is AI only useful for digital marketing?

Absolutely not. As recent case studies show, artificial intelligence is highly effective in optimizing physical operations, supply chain forecasting, and in-store visual merchandising.

What happens to brands that ignore these AI tools?

They will suffer from slower decision-making, higher operational costs, and ultimately lose market share to competitors who can adapt to consumer behavior in real time.

How can smaller manufacturers adopt these strategies?

You can start by auditing your current manual processes and partnering with AI consulting experts to implement accessible, off-the-shelf predictive analytics and computer vision tools.