The Grocery Store That Beat the Soviet Union and What Amazon Sellers Can Learn From It

Most sellers think competition is the problem. But what if too many options, too many SKUs, and too many competitors are actually the system working?

In this episode of Selling on Giants, Mr. Will breaks down why crowded marketplaces are not always a warning sign. In many cases, competition is proof that demand already exists, and the brands that know how to read that demand can turn a noisy category into a source of intelligence.

The episode starts with the famous story of Boris Yeltsin walking into a regular grocery store in Houston in 1989 and being shaken by what he saw. Fully stocked shelves. Endless product choices. Multiple brands, flavors, pack sizes, and price points. It was not luxury that made the store powerful. It was normal abundance.

That grocery store represented something bigger than food. It showed the strength of a system where millions of small decisions from businesses and consumers created more variety, more feedback, and better outcomes than one central plan ever could.

That same idea applies directly to Amazon, Walmart, Target, and modern marketplace strategy.

Amazon is not just a marketplace. It is a real-time feedback loop. Sellers launch products, customers click or do not click, ads test demand, listings convert or fail, reviews build or stall, competitors respond, prices shift, and the algorithm reallocates visibility based on what the market is telling it.

In this episode, we cover:

• Why competition is not just a threat, but useful market intelligence
• How crowded categories reveal demand, price points, review gaps, and customer objections
• Why Amazon rewards brands that test, learn, adapt, and double down
• How too much internal planning can delay the feedback sellers need most
• Why every SKU, click, conversion, and failed campaign can become useful data
• The difference between random chaos and structured experimentation
• How brands can use marketplace signals to improve listings, pricing, creative, and ad strategy
• Why trying to outsmart the market is usually weaker than building a system that learns
• How BellaVix helps brands create feedback loops across listings, ads, pricing, promotions, and merchandising
• Why choice wins because choice creates learning

This episode is for Amazon sellers, ecommerce founders, brand operators, and marketplace teams that feel stuck in crowded categories and are trying to decide whether the opportunity is still worth pursuing.

The answer is not always to pull back. Sometimes the better answer is to study the category more closely.

Competitors show you what customers already buy. Reviews show you what customers care about. Pricing shows you what the market accepts. Creative shows you what messages are being tested. Search results show you where demand already exists.

The brands that scale are not always the ones with the cleanest plan before launch. They are often the ones that create better feedback loops, test with discipline, and respond faster than everyone else.

At BellaVix, we help brands turn marketplace complexity into clear operating plans. That means structured testing across listings, pricing, ads, creative, promotions, and merchandising, with real performance data guiding what gets scaled and what gets cut.

BellaVix has helped brands sell over five hundred million dollars on Amazon and is a Verified Ad Partner, but the real work is helping brands stop guessing from a boardroom and start learning from the market.

The key question:
Are you using a crowded category as an excuse, or are you using it as a source of intelligence?

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Transcript

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Most sellers think competition is the problem, but what if too many options, too many SKUs, and too many competitors are actually the system working? Welcome back to the Selling on Giants podcast. I'm your host, Mr. Will, and today we're talking about competition in a way I think most sellers need to hear, because the default reaction on Amazon, Walmart, Target, or really any marketplace is to look at a crowded category and assume the crowd is the problem. Too many sellers, too many SKUs, too many ad placements, too many price points, too many options for the customer to compare. And the natural instinct is to say the opportunity is gone because the category is too noisy. I do not think that is the right read. Competition is not just a threat. Competition is information. And when you learn how to read that information, a crowded marketplace starts looking less like a wall and more like a live operating system that is constantly showing you what customers care about, where demand already exists, which offers are working, which reviews matter, which price points are believable, and where the gaps are hiding. That is the part most brands miss because they want the market to be clean before they enter it, and they want the path to growth to feel obvious before they commit resources. They want fewer competitors, easier CPCs, cleaner search results, and more predictable conversion. But the reality is that markets do not create opportunity by being quiet. They create opportunity by producing signals. And the brands that scale are usually the ones that stop complaining about the signals and start using them. There is a story I like because it has nothing to do with Amazon at first, but once you understand it, it explains a lot about why marketplaces work the way they do. In 1989, Boris Yeltsin walked into a grocery store in Houston after visiting NASA's Johnson Space Center, and what he saw was not luxury retail, not a staged political event, and not some special American showcase built to impress him. It was a normal grocery store filled with normal products for normal families, and that is exactly what made it powerful. The shelves were full, the options were everywhere, the category depth was real, and there were endless variations of everyday items that solved slightly different problems for slightly different people. The story is famous because Yeltsin was reportedly shaken by the abundance, not because the store had one perfect product in every category, but because it had so much choice that no central planner could have designed it from the top down. One system produced scarcity and limited options, while the other produced variety, feedback, and constant adjustment. And that is the deeper point that matters for business owners and sellers. The Cold War often gets talked about as capitalism versus communism, but from an operator's perspective, the more useful lesson is centralized planning versus decentralized decision making. In one model, a small group decides what gets made, how much gets made, where it goes, and what people should want. While in the other model, businesses test, customers respond, prices move, supply adjusts, and the system keeps learning because millions of small decisions are happening closer to the customer. That is why choice matters, because choice is not just clutter and it is not just a bunch of redundant products sitting on a shelf. Choice is how the system collects information, and every time a customer picks one item over another, ignores one offer, clicks one image, chooses one price point, or leaves one review, the market gets a little smarter. Now bring that back to Amazon because Amazon is basically that grocery store turned into a real-time feedback machine. Sellers launch products, customers click or do not click, ads test demand, listings convert or fail, reviews build or stall, competitors respond, pricing shifts, and the algorithm reallocates visibility based on what the market is telling it. There is no executive sitting in Seattle deciding that your product deserves to win because your team worked hard on the listing. And there is no category referee handing out visibility because your brand has a better internal story. The marketplace does not care what you intended. It cares what customers do, and that can feel harsh, but it is also what makes the system so powerful. This is where a lot of brands get Amazon completely wrong because they try to perfect the idea before the market ever gets a vote. They want the perfect listing, the perfect ad strategy, the perfect creative, the perfect price, the perfect forecast, and the perfect launch plan before they expose the product to real customers. And while that feels disciplined on the surface, a lot of the time it is just central planning with better branding. I am not saying planning does not matter, because it absolutely does. You need clean data, good margin structure, inventory discipline, strong creative, compliance, pricing logic, and a clear view of what you are trying to learn, but there is a point where planning stops reducing risk and starts delaying feedback. That delay is expensive because the market keeps moving whether your team feels ready or not. Competitors keep testing, customers keep choosing, search results keep shifting, and if you are still trying to protect the perfect version of the strategy before launch, someone else is already collecting the feedback you are waiting on. We have seen this play out with brands that come in with a tight catalog, a clean point of view, and a very controlled idea of what the customer should want. Everything looks polished internally, but once the account hits the marketplace, conversion stalls, ads, plateau, ACOS climbs, tacos gets uncomfortable, ROAS does not justify more spend, and suddenly the conversation turns into what is wrong with Amazon? A lot of the time, nothing is wrong with Amazon. The product may not be bad, the category may not be impossible, and the brand may not be doomed, but the system does not have enough inputs to learn from because the team gave the market one version of the idea and expected the customer to validate it exactly as imagined. So the work becomes creating better inputs. We test variations, price points, creative angles, keyword clusters, offers, bundles, pack sizes, coupons, main images, lifestyle positioning, comparison charts, and different ways of explaining why the product deserves to be chosen over the other options already in the search results. That is messier than a perfectly controlled plan, but it is also more useful because every SKU is a hypothesis, every click is feedback, every conversion is validation, and every failed campaign is still information if your team is mature enough to read it without getting defensive. The goal is not to be right on the first try, because very few brands are truly right on the first try. The goal is to build a system that gets smarter faster than everyone else. This is where competition becomes useful. A crowded category gives you pricing, benchmarks, review language, creative angles, search behavior, offer positioning, common objections, feature gaps, and proof of demand before you even spend a dollar. And if you look at that category emotionally, it feels intimidating. But if you look at it like an operator, it becomes research. The weak operator says, too many people are already here. The strong operator says, good, now we can study what is working, what is missing, where customers are frustrated, and where the category has become lazy. That is the mindset shift. Competition is not just something you fight, it is something you study. And once you start studying it properly, you stop treating every competitor like a threat and start treating the category like a public database of customer behavior. This is also why too much choice gets misunderstood. Choice can feel inefficient, and if you manage it poorly, it absolutely can become noise, wasted budget, and operational clutter. But structured choice gives the marketplace more ways to show you where the opportunity is. More options create more data, more data creates clearer patterns, clearer patterns create better decisions, and better decisions create stronger winners that you can scale with more confidence. That is not chaos if it is managed correctly, that is experimentation. There is a big difference between chaos and experimentation. Chaos is launching random SKUs, random campaigns, random discounts, and random creative because someone had an idea in a meeting, while experimentation is creating controlled inputs so the market can teach you something that improves the next decision. The brands that win understand that difference. They enter the market with a point of view, but they do not marry the first version of the idea, and they let performance reshape the product page, the pricing, the advertising, the offer, and sometimes even the product roadmap itself. That is exactly where Bellavix creates value for brands, because we are not trying to guess what will work from a boardroom or build some perfect theoretical plan that only looks good until the market touches it. We help brands build systems that learn in-market through structured testing across listings, pricing, ads, creative promotions, and merchandising with feedback loops tied to real performance data so we can scale what wins and cut what does not before emotion takes over. Bellivix has helped brands sell over $500 million on Amazon, and we are a verified ad partner. But the real value is not just managing campaigns or cleaning up listings, it is helping brands turn marketplace complexity into a clear operating plan that the team can actually execute. Because Amazon is not waiting for your perfect strategy, the system is already moving, and the question is whether your brand is moving with it or standing still trying to outthink it. If your brand needs that kind of hands-on marketplace support, visit Bellovics.com. Now, this is where the grocery store story comes back around because Yeltsin was not shaken because Americans had more cereal flavors or better frozen desserts. He was shaken because the store revealed what a planned system could not produce at scale, which was abundance created by choice and constant feedback. That is the same lesson sellers need to understand about marketplaces. You do not need to know every answer before you launch, but you do need a system that helps you discover the answers faster than your competitors. And you need to be willing to be wrong in small controlled ways so you can become right in bigger, more profitable ways later. The customer has information you do not have. The search results have information you do not have. The ad data has information you do not have. The review section has information you do not have. Your competitors have information you do not have. The only way to get closer to the truth is to participate. That means launching before it feels perfect, testing more than feels comfortable, letting performance guide decisions, and accepting that most things will not work. Not because the brand is bad, but because that is how the system finds what does. The same principle applies to advertising because a lot of sellers want clean A costs before they understand which terms convert. They want strong row as before they have tested enough creative. And they want tacos to stay controlled while also asking the business to grow aggressively. That math does not always work in the learning phase. There is a difference between waste and investment. Waste is spending without learning, while investment is spending to gather information that makes the next decision better. And if your ad spend helps identify winning terms, winning products, winning audiences, winning price points, or winning creative, then it has value even before the account is fully optimized. The discipline is knowing the difference because serious operators do not hide behind the word testing as an excuse to burn money, and they do not pretend every bad result is valuable just because it created a spreadsheet. They define the test, set the boundaries, know what success looks like, know what failure tells them, and when the data comes back, they act. That last part matters because data does not help you if your team is too slow, too emotional, or too attached to the original plan to use it. The marketplace gives signals every day, but the question is whether your organization is built to respond. For sellers, the market is not an abstract theory or something that lives in an economics book. The market is search terms, conversion rate, ad performance, review velocity, pricing pressure, inventory movement, customer questions, and competitive positioning. That is the marketplace talking, and your job is not to argue with it or explain why the customer should have behaved differently. Your job is to listen, interpret, and move. If customers are clicking but not converting, the market is saying the promise got attention, but the offer did not close. If ads are driving traffic but a cost is too high, the market may be saying demand exists, but your economics, listing, or positioning need work. If one variation outsells the rest, the market is showing you a preference. And if one creative angle performs better than the others, the customer is telling you what matters. That is not noise. That is the system giving you instructions. So when sellers say there are too many competitors, I hear something different. I hear that there are more signals available, more proof of demand, more positioning gaps, more pricing benchmarks, more creative angles to study, more reviews to mine, more customer objections sitting in public, and more data you can use if you are disciplined enough to look at the category without emotion. Competition is not just a threat, competition is information. The weak operator complains that someone else is winning, while the strong operator studies why they are winning, finds the gap, and builds a sharper response. That is why choice wins, because choice gives the system options, gives customers a voice, gives sellers feedback, creates pressure, and forces better execution. Yeltsin questioned his system because of a grocery store. One system produced scarcity, the other produced choice, and choice won because choice creates feedback, feedback creates learning, and learning creates better outcomes over time. The same lesson applies to marketplaces. The brand trying to control every outcome from the top down usually moves too slowly, while the brand that tests, listens, adapts, and doubles down gives itself more ways to win. So the real question is not whether your category is too crowded, the real question is whether you are using that crowded category as an excuse or using it as a source of intelligence. That's it for this episode of the Selling on Giants podcast. If this one helped you think differently about competition, choice, and how marketplaces really work, share it with another founder or operator who is trying to scale without over controlling the process. And if you are getting value from the show, I would be grateful for a quick review because it helps us reach more sellers who are trying to build stronger, smarter marketplace businesses. I'm Mr. Will, host of the Selling on Giants podcast. Thanks for listening and keep building systems that learn.