Getting the smart lighting system or home camera your company developed on the shelves at a major retailer is part science, part sales, and increasingly, part artificial intelligence.

Brands developing smart-home devices know that AI can do far more than automate their products: it’s quietly revolutionizing how these companies win and grow new retail deals.

Let’s break down how device makers are weaving AI into their retail strategy, all the way from demand forecasting to those first in-store demos.

Using AI to Size Demand and Map Retail Fit

Every product launch starts with a question: will shoppers actually want this? AI helps speed up decision making by helping device makers analyze purchase trends, competitor inventory, seasonal spikes, and even social media chatter to project where and when a product might hit the jackpot. These tools can help you sift through messy datasets that a human team would take weeks to process and return actionable insights overnight.

But it’s not just about identifying demand. AI pinpoints which retailers are actually the best fit for each product. For instance, for a high-end smart thermostat, the ideal partner might be a specialty store with an audience of tech enthusiasts, while budget-friendly sensors may fit a big-box retail chain.

By crunching sales history, customer demographics, and product affinities, AI lets brands match their inventory with the retailers most likely to say yes.

Identifying Buyer Contacts and Accelerating Outreach

Identifying Buyer Contacts and Accelerating Outreach GearBrain

Knowing which retailers to target is only half the battle. The next hurdle? Finding the actual decision-makers and getting your pitch in front of them before someone else does.

Here’s where AI-driven prospecting shines. With access to rich company data and public records, AI agents can automatically identify buyer contacts at national and regional chains, scanning for recent job changes, new buying cycles, or past deal activity. What once took sales teams hours of research is now handled in minutes.

For example, teams can deploy tools like GTM AI to automate prospecting and streamline their outreach. By integrating this technology, go-to-market teams get a living database of buyers and merchants, complete with up-to-date contact info and insights on when to pitch a new range or suggest a store visit. These AI agents also help personalize the initial approach, increasing the odds of getting a real conversation.

Generating Store-Ready Bundles and Sell-Through Materials

Once a retailer gives the nod, device makers still have plenty of work to do. AI steps in to craft product bundles that fit a specific store’s local demand. For example, if cameras, sensors, and smart plugs tend to sell together in suburban locations, the AI can recommend a tailored “starter kit” for that demographic.

When it comes to marketing, AI tools can help create store-ready assets like shelf talkers, digital displays, and QR codes that link to product videos. What’s impressive is how AI can quickly tweak these materials to suit each retailer’s brand guidelines or seasonal promotions, reducing the guesswork and back-and-forth that may come from manually creating these materials.

Forecasting Returns and Preventing Overstock

No retailer wants a slow-moving product closing off space on key shelves! Fortunately, you can be a step ahead of the game with the right tools. For instance, you can use AI to forecast not just initial demand, but also likely return rates by region or store. These models account for historical return data, local climate, and even neighborhood tech savviness. The result? Companies can limit overstock risk and negotiate smarter return agreements with their partners.

A better handle on returns and overstock also improves sustainability: fewer wasted units and costly returns means less strain on the environment and the bottom line. A win-win!

Scheduling In-Store Demos and Training

Scheduling In-Store Demos and TrainingGoogle

A product demo in the right store, at the right time, can make all the difference for connected-home devices that aren’t easy to understand just from reading the box. AI-powered platforms help coordinate demo scheduling, ensuring product specialists show up when foot traffic is highest or during local events with the biggest sales potential.

AI can even analyze past demo data (like which day of the week saw the most bundle sales) so future demos get the timing and format just right.

What’s in It for Shoppers?

All this behind-the-scenes AI activity isn’t just about making things easier for brands and retailers. In the end, it means shoppers are more likely to find the latest gadgets actually in stock, see clear comparisons and reviews on the shelf, and get hands-on help right when they’re interested. Simply put, with a smooth and efficient retail process, everyone gets more value for their dollar and their time.

The AI-Driven Retail Advantage

AI can help device makers cut down on guesswork and make smart, data-driven choices about who to pitch, when to launch, and how to win at retail. It’s a major shift that takes much of the frantic unpredictability out of go-to-market efforts, and it’s only going to get smarter from here.

Curious to learn more about how AI is shaping the future of connected home retail? Dive into our latest guides for a closer look at the strategies and partnerships changing the way innovative devices reach the market.