CartHappy Blog
Our Story
ADstruc was an important part of our journey and helped lead us to where we are today. We pioneered the use of data, accessibility, and automation in a way that fundamentally reshaped the OOH industry. After stepping back from ADstruc/Project X in 2022, Josh and I finally got the chance to slow down to spend time with our families and think about what may be next. On a long walk through NYC, we realized two things, 1) we weren’t done building, and 2) whatever came next, we wanted to build it together again.
We’d been building toward this idea for a while, long before we understood what it would become…Back at ADstruc, we watched billions of dollars get spent trying to understand what consumers might do based on intent signals. But the real breakthrough happens when you understand what consumers actually do — what they buy, when, and why. And when we started looking at purchase-history data, one category kept standing out: the one that’s most structured, most repeatable, and most price-sensitive — grocery.
And the early signals inside our platform have been really strong. We’re seeing just how volatile groceries actually are. This week, I was looking at a shopping cart where someone could save five dollars on a 12-pack of Coke just by going to the grocery store across the street. Multiply that insight across a full cart and a full year, and it can save you thousands.
The data shoppers already generate — without doing anything extra — can genuinely reshape how people spend, save, and make everyday decisions. And that’s the core of what we’re building. It’s not “another shopping app.” It’s an evolution of something we’ve believed in since the ADstruc days: when people have the right information, the whole experience gets better.
So from there, the question became: what happens when you connect someone’s actual grocery purchase history with real-time prices at the stores around them? Over the last three years, as we dug into that question, it became obvious that you could genuinely reshape how people buy groceries — and how much they spend doing it.
Our mission now is simple: To turn everyday shopping into everyday opportunity — empowering people to save more on the essentials that matter most.
The Problem
The truth is, most Americans have been forced to shop with convenience over value. But the real challenge isn’t getting groceries — it’s knowing what to buy, where to buy it, and whether you’re overpaying.
The next big shift in grocery isn’t faster delivery — it’s intelligence. Delivery changed how food moves; data will change how we decide what and where to buy.
Grocery is volatile, prices swing constantly, and it’s a major weekly source of financial pressure for most households. “From 2020 to 2024, food prices rose 23.6 percent” and “86% of Americans say the cost of groceries is at least a minor source of stress, with 53% calling it a major source of anxiety in their lives” U.S. News & World Report, according to an August 2025 AP-NORC poll.
Millions of people are making decisions completely blind — they don’t see price swings, don’t know which store is cheaper today, and have no idea how much they’re overpaying. Yet every week, millions of people start from scratch because the information that could actually help them is buried across different retailers and systems.
People don’t need more places to shop. They need help shopping better — to stop worrying and feel confident they’re getting what they need at the best price, without all the mental math.
And this moment matters — rising prices, data portability, and AI have created the perfect inflection point.
Here’s how the pieces come together:
Data + Personalization = Agentic Commerce
- What we know: Agentic commerce works best on structured, repeatable, and price-sensitive datasets - and no purchase is more frequent or predictable than groceries.
Let’s start with the data - there’s two types: consumer purchase data and retailer data. When you put those together, the whole model comes to life. Let me explain:
For consumers
- We give users a Chrome extension so they can pull their purchase history straight from their retailer accounts into our system.
- From there, we run the data through an LLM which identifies purchase patterns — what they buy, when, where, how much they paid, coupon activity — and can even infer dietary patterns or restrictions.
Next, we connect this to our retailer-side data.
- Through APIs and data pulls, we bring in real-time pricing and inventory. That lets us link a user’s buying behavior with the products they purchase and automatically build and optimize carts across multiple stores based on their preferences — price, value, delivery, pickup, convenience, and more.
- What’s really important on the retailer side is this: with a single click, CartHappy loads those ready-to-buy carts directly on the retailer’s site for the user to check out. Everything happens within the retailer’s four walls > keeping full ownership of their customer relationship.
We see CartHappy as the beginning of a future where your groceries plan themselves through your own data finally working for you.