[00:00:15] Phillip: Hello and welcome to Future Commerce, the podcast at the intersection of culture and commerce. I'm Phillip.

[00:00:19] Brian: I'm Brian.

[00:00:20] Phillip: And today we are talking commerce readiness. And according to our next guest, being ready for 2026 isn't about flashy campaigns. It's not about more catalogs. It's not even necessarily about that next piece of channel expansion, despite all of the expos and conferences you're going to go to where you're probably going to see this guy. But it actually depends on your ability to be agile. And so we're going to talk about that today. Joining us to give us a little bit of depth on that, and hopefully a little bit of breadth too, he is Director of Product Management at Rithum. And he's going to give us his take on this. It's Louis Camassa. Welcome to the show.

[00:01:18] Louis Camassa: Thanks, Phillip. Brian, thanks for having me. Excited to chat with you today.

[00:01:21] Phillip: Lou, what does it mean to be agile? We're going into this 2026 Commerce Readiness Index. It is a report that you guys put out; we will link it in the show notes below. So if you want to go get it, it's easy to click. But it's a survey of 200 commerce executives across the US and UK. Tell me a little bit about the top line here and what you guys discovered.

[00:01:45] Louis Camassa: Absolutely. This is pretty exciting. A big part of my job is going out and talking to folks—interviewing prospects, clients, and learning what's working in their business and what's not working. And this survey is more of a quantitative approach. I'm getting that data where we can't go one-on-one and interview everyone. We did this survey to learn more about what the common problems and challenges are that our clients or prospects are experiencing in the industry as a whole, and then how we can help them solve that.

So it's across a marketing perspective or product perspective; it helps inform our engineering. And we're constantly using this type of insight to discover how we can better serve our clients. And this one—there are some insights in there that are interesting—but the one that stood out to me, the one that maybe validated everything I've thought, is that most companies, whether you're a retailer or a brand, are moving at spreadsheet speed. You've got Google Sheets or Excel, and you're manipulating data within that on a line-by-line basis. Maybe you have a macro set up, and you have two monitors going—comparing and looking at this data—and that's just not the way of the future. That's the old way of doing things.

How do we move into a more automated, streamlined approach? And this really set itself up in my head and framed it in a way where, when I'm sitting down with a client and doing this interview one-on-one, I'm looking at the two screens they have open. They have one screen—a spreadsheet of all their products. They have thousands of products: titles, descriptions, attributes, price. And then on the other screen, they have a list of all the categories approved by the marketplace they're trying to sell on. So what they have to do is reconcile their product catalog category to the marketplace they were selling on. They go line by line manually to do that.

And that survey really helped us understand that this is still a problem in today's day and age. Even though we have automation and AI to help us speed and streamline these processes, people are still stuck at that spreadsheet speed. So I think when you look at that survey, the bottom line is data readiness. How do I get my product data in a format that can get cross-posted across all these different sales channels? And now, of course, we'll talk—I'm sure—a little bit today about LLMs and agentic commerce.

[00:03:55] Phillip: I think that's something that you guys obviously are going deep on. From your vantage point, what are those key agility points? What do you know about channel profitability over there at Rithum?

[00:04:05] Louis Camassa: Yeah. So if we back up a bit, most people may not have heard of Rithum. This is a new brand we deployed a couple of years ago where two brands came together that are leaders in the commerce space—two of the largest brands in the commerce space over the last, you know, about twenty years. So CommerceHub is one of the brands that made up Rithum, and CommerceHub really pioneered the dropship space about, you know, over twenty-five, almost thirty years ago.

And what we do there is, if you're a major retailer or marketplace—if you're a Lowe's, a Home Depot, a Costco—and you're trying to increase the number of products you're selling on your website or your web presence, we provide you with the suppliers to help create that endless aisle. So we all know if you're a retailer and you're trying to increase the number of products in your store, you only have so much budget to buy and then store those products. What we're doing is giving you the capabilities to increase the number of products and assortments sold so you can expand your assortment online to get more customers into the products they're looking for. We pioneered that almost thirty years ago.

The other side of the business focuses on how we unlock brands and retailers to sell across all these different channels. So if I'm an apparel company and I have, let's say, 100,000 or even a million different products, how do I make it easy for that brand to sell on Walmart, Home Depot, Lowe's, Nordstrom? How do I manage the products? How do I manage the orders coming back through? How do I make that efficient and easy? Those are some of the areas we focus on.

[00:05:36] Louis Camassa: And with that comes insight. Like you said—this commerce survey—what are some of the areas we should be focused on, and how do we create agility? How do we create streamlined and efficient operations? Profitability is really the differentiator. You can go on and post products individually to every one of these marketplaces. You can have teams that do that and know the nuances of each marketplace—know how much ad spend to put in, know how to manage the orders on the way back down.

But if you have to scale team size every time you add a new channel—so you go from Amazon to eBay to Walmart to ChatGPT to Perplexity—now you have five or ten teams. That's a lot of people, a lot of overhead, and a lot of tribal knowledge being shared. What if you just had one platform that gave you access to all of it? Think of it like a Roku. If I'm trying to get on Disney, Netflix, Amazon Prime, I have one device that does that.

[00:06:26] Phillip: Totally.

[00:06:26] Louis Camassa: That's what we do in the sales channel world.

[00:06:29] Brian: It's incredible. Yeah. It's such a needed thing, and I love how you've brought those two different capabilities together—the ability to access the products and assortment you need, and the ability to take that data and put it out into the right places in the right ways at the speed of light. I think this is essential in this particular environment.

Phillip was at Adweek recently, and he came back saying the report was all about the speed of culture. The speed of culture was mentioned, like, a million times. It was a game.

[00:07:01] Phillip: It was like a good-bad-bad drinking game, because I think people would have been dead, actually.

[00:07:05] Brian: Exactly. Yeah. They'd have to switch to beer. It's a take-a-sip—not a shot—a sip. And I think speed is the name of the game: agility, responsiveness, being able to get in there and capture the moment of the weekend.

With a lot of this marketplace selling, algorithms are picking up new trends all the time in the way shoppers are getting after certain products. So being able to take what you're seeing in one channel and then make adjustments for all your other channels gives you the ability to capitalize on moments you wouldn't have been able to capitalize on before. And this is never more true than right now with the emerging channel of agentic commerce.

So you've launched AI products at Rithum, and you've written about this quite a bit—AI shopping agents, algorithmic visibility. How is Rithum taking these things you've built and helping companies adapt to agentic commerce?

[00:08:14] Louis Camassa: Yeah. If you go back twenty or twenty-five years ago, we've always been driven by algorithms. When Google Search came out, their algorithm was about how you get your product pages listed higher than your competitors. That was search engine results pages, and PageRank was involved—measuring your page and how effective it was in getting listed.

There were all these ways you could game the algorithm: stuffing keywords into your page, meta fields, descriptions, titles, content to get higher rankings. That worked for a while, and then people got smart. Google updated their algorithms. It became more challenging to game the system.

With AI, we're seeing a resurgence of that. I started in this industry twenty or twenty-five years ago, back in college, selling ecommerce websites to companies before they even had email addresses—going out and explaining the value of selling products online. That was really fun. That was a highlight of my career.

This is the next big lightning-bolt opportunity that has me super excited because it is something net new.

[00:09:23] Louis Camassa: It's a new behavior now—a different way of shopping that we've never had before. And how we're helping clients is by reframing this. We don't want to take from the past and just push it into the future.

For instance, if you look at your desktop or your mobile phone, the save icon still uses a floppy disk. Most people have never even held a floppy disk, but that icon is still a relic from how we understand saving. Digital cameras mimicked the analog click when you take a picture. We've taken old concepts and brought them forward, sometimes just for nostalgia.

But we don't want to do that with AI. When we go into a chat experience, we don't want to drop someone onto a homepage with a banner and a bunch of categories they have to click through, then use search and filters to find products. Let's think about this differently. I'm coming in with specific needs—specific requirements for a product I'm looking for. And the best analog experience in real life is Men's Wearhouse.

[00:10:31] Louis Camassa: When I was younger, I was going for a job interview, and I went there to get a suit. I remember when I walked in, this well-dressed sales associate came up to me and said, "Hey, what are you doing here? What are you looking for?"

I said, "I need a suit." He said, "What do you need it for?" I said, "An interview." He said, "Okay, let's do some measurements. How long are your arms and legs?"

Then he said, "By the way, do you have a dress shirt?" I said, "No." He said, "Do you have a belt?" I said, "Yeah." He said, "What color belt?" I said, "I have a black belt." He said, "What color shoes?" I said, "Brown." He said, "You want a belt that matches your shoes. Let's get you a new belt."

So they sold me the suit, the shirt, and the belt. I walked out spending a lot more than I wanted, but I was informed. I had that concierge service.

That's how I like AI shopping to work—as a concierge service. You put in the needs you have. Recently, I was looking to buy a new backpack. I knew I wanted something that could store two to three days' worth of clothes, fit under the seat in front of me on an airplane, had a water bottle holder, and was waterproof.

[00:11:24] Louis Camassa: I put that criteria in, and the AI agent comes back with suggestions that meet those requirements. And to your point, Brian—what about speed? You're right; there are two components here.

One is brand esteem and brand cachet. I might buy a Jansport, a North Face, or another well-known brand because, in my mind, that means quality and authenticity. I know it's going to be a good purchase, and if it's not, I know I have a good return policy and support.

The second part is speed. How fast can I get it? Is it possible that I buy a brand I don't know that can ship faster or at a lower cost? That's where we're at right now—how brands with strong esteem and cachet compete with new upstarts that develop products quickly, ship faster, and use influencers. That's where AI agents and commerce are meeting in the middle.

[00:12:22] Phillip: Yeah. What's really interesting is that incumbent marketplaces, in their rush to develop their own agentic solutions and on-site agentic experiences, are also becoming walled gardens—closing off outside agentic discovery channels. The idea that we'd have a Google-like front door for agentic shopping through something like ChatGPT is becoming less of a panacea.

If you're using Perplexity, for example, it may no longer be able to access something like Amazon. We're in a strange time where these deals are being negotiated, and you can't access everything. It's a great time to be on a discoverable website where your site is crawlable.

So when I think about AI agents, I'm wondering whether decision-making is shifting. Are AI agents taking over back-office functions—assortment, pricing, media spend? How are your customers talking about that? And how does that relate to higher-order functions like strategic planning?

[00:14:08] Louis Camassa: Definitely. AI has given us some great potential future features. What it does is help reduce cognitive load in decision-making. Right now, if you go into most platforms, you have all these buttons, configurations, settings, filters—knobs you have to manipulate to get the results you want.

With AI, what we're doing at Rithum is focusing on outcomes. Just like the Men's Wearhouse example, instead of going through shelves and figuring things out, you have a concierge asking what your needs are. That's how we're looking at our platform build-out and how we serve clients.

What are your profit margins? Where are you willing to sell geographically? What kind of media budget do you have? Give us those outcomes and criteria, and we'll develop a roadmap and take the actions to make it happen. That way, you don't have to be as deep in the platform doing heavy configuration and review.

And maybe the best way to think about this is with Waymo. Have you been in one of the autonomous Waymo cars yet?

[00:15:21] Brian: Oh, yeah.

[00:15:21] Phillip: Oh, yeah. For sure.

[00:15:23] Louis Camassa: So you've been driving around in those. For anyone who doesn't know, Waymo is the leading autonomous car company. They're in San Francisco and LA, and they're putting cars in New York and London soon.

One of my buddies is an engineer who worked for Waymo via Google. He explained the technology—LiDAR, cameras—and how they navigate so efficiently. One unfair advantage Waymo had was Google Maps data. Google Maps spent two decades plotting potholes, street signs, streetlights—every road. They leveraged that to get cars where they need to go faster.

Likewise, at Rithum, since we've been doing this for over two decades, we have vast data on what's being sold, on which channel, in which geography, at what price, with what media spend. We have granular details—average order value, shipping, tax, return rates. With that data, we can help clients get to their desired outcomes.

[00:16:47] Brian: And given that aggregate view of data at Rithum, you have a pretty interesting look into the future. With the market readiness report in hand, what do you think brands will be surprised by in 2026, for better or worse?

[00:17:18] Louis Camassa: I think the big one is agentic commerce and how it upsets shopping behavior. We're already seeing the zero-click phenomenon on Google. People search, get an AI overview, and don't need to click through. We're seeing drops of about 9% across ecommerce referrals from Google.

Media companies like The Washington Post, Huffington Post, and The New York Times are seeing double-digit drops because their data is being propagated into AI overviews. Combine that with ChatGPT having around 60–70% market share—though that's fragmenting now with Perplexity and Gemini launching in Chrome—and the experience is changing.

[00:18:21] Louis Camassa: All of this impacts how we shop. Before, it was TikTok and social media driving impulse purchases. Meta and TikTok do an amazing job of that. Now, with LLMs, it all comes down to product data.

Do I have the right content so the LLM can match a customer's prompt to my product? Is inventory synced frequently enough? Price is always a competitive variable. Data quality is foundational here.

[00:19:32] Phillip: When you look at cherry-picked data points from the report—being stuck at spreadsheet speed, reacting slowly—it's wild to me. These are things we were talking about ten years ago. Data quality issues affecting business decisions are still happening often or all the time.

If you want to be in the answer engine world and avoid being disintermediated, data quality is key. What other data points from the study should listeners pay attention to?

[00:21:03] Louis Camassa: One big one is using store locations as mini fulfillment hubs. If you have 2,000 stores, how do you convert them into delivery hubs for the surrounding community? Speed and velocity matter.

If I'm searching on DoorDash, Instacart, or Uber Eats—even for apparel or home goods—it's about getting something in a couple of hours. If I'm on ChatGPT looking for dog food and see DoorDash can deliver from a local store in an hour, that's powerful.

[00:22:22] Louis Camassa: This reduces shipping timelines and differentiates products. Inventory latency is a big game changer. If inventory only syncs once a day, you oversell, waste ad spend, and disappoint customers. Reducing that to every five or ten minutes changes everything.

[00:23:37] Phillip: I still can't believe this is a problem. Even with AI recommendations, inventory accuracy is off. It's friction for shoppers and retailers. It shows we still have a long way to go.

That brings me to downstream effects—AI data centers, power needs. Lou, you've thought a lot about future scale. What's your view?

[00:25:12] Louis Camassa: If we look at technology adoption timelines—electricity took seventy years, the internet thirty, smartphones seventeen—AI reached around 60% adoption in about three years.

As these technologies integrate into daily life, they change how we interact with the world. AI is everywhere—from autonomous driving to shopping to medical scans like CCTA with CLEARLY technology, which can scan your heart in 3D.

[00:26:21] Louis Camassa: The big challenge is power. This demand isn't ephemeral—it's here to stay. Power generation is the bottleneck. Regulations make it hard to spin up new power sources.

My father-in-law worked at the only nuclear power plant in California, near where I live. I'm in the blast radius, if anything should happen.

[00:27:19] Phillip: God forbid.

[00:27:21] Brian: You're not worried. You're not worried.

[00:27:24] Louis Camassa: I'm not worried because I know how regulated it is. But the perception is that nuclear is dangerous. Because we're not adding enough generation, demand will outpace supply. That's the bottleneck for AI advancement.

We're investing heavily in data centers and chips—GPUs—but power is the constraint. Some data centers are building their own turbines because they can't rely on the grid. This is one of the biggest unlocks ahead.

[00:29:01] Phillip: That aligns with what I'm hearing elsewhere as well.

[00:29:12] Brian: The power required is insane. Just revising models like Grok takes enormous energy. Designing for efficiency is essential. How does this affect global trade and connectivity?

[00:30:28] Louis Camassa: A year ago, LLM prompts took ten times the resources of search. Now they're roughly equal. Chips and models are getting more efficient. Compute costs are compressing.

Geopolitically, direct-to-supplier sales are growing. Amazon led the way. TikTok, Temu, and Shein are part of that. Some purchases don't require brand trust, but for most—phones, cookware, apparel—brand esteem still matters.

[00:32:03] Louis Camassa: This direct model adds pressure but hasn't been as transformative as expected. Most consumers still want reputable brands with quality and return policies.

[00:33:26] Phillip: The biggest transformation comes from culture shift—consumer adoption and internal adaptation. We're back to the build-versus-buy debate. It's exciting because innovation feels alive again.

Lou, where can people find you online?

[00:35:14] Louis Camassa: LinkedIn—Louis Camassa. Run a search and you'll find me. Happy to chat.

[00:35:19] Phillip: Once again, it's the 2026 Commerce Readiness Index, linked in the show notes and at Rithum.com. Thank you to Rithum for partnering with us, and thank you for checking out this episode of Future Commerce. We'll see you at NRF.

[00:36:00] Louis Camassa: Take care. Thanks.

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