Shane's Recent LinkedIn Posts

Are you an Amazon seller or a brand that sells on Amazon (yes, there is a difference). That "branding" decides if long-term margin lives or dies. A product seller chases trends, optimizes for short-term hacks, and is locked in a permanent race to the bottom on price. The moment ads stop or competition increases, sales collapse. There's no foundation underneath. A brand owner builds differently. Clear differentiation. Consistent customer experience. Trust signals that compound over time. A catalog strategy that increases lifetime value. Generic sellers compete on price and speed. Brands compete on identity and certainty. When a shopper recognizes your brand, they don't have to re-evaluate every time they see your listing. That recognition reduces friction and drives repeat purchases. The distance between a "one-time purchase" and a "household staple" is wider than most sellers realize. Closing that gap requires a system (not a logo refresh). I broke down the full framework in a new guide covering everything from Brand Registry to keyword infrastructure to review management to scaling. Full article here →

Amazon sellers spend thousands driving traffic to their listings. Then one bad review kills the conversion rate on all of it. Influencer traffic, paid ads, organic... none of it matters if your listing isn't clean when those eyeballs land on it. That's something I don't think enough brands connect the dots on. You can build the best creator strategy in the world, but if your review profile is working against you, you're paying to send people to a page that talks them out of buying. I'm joining Vincenzo Toscano, Danil Saliukov, Jonathan Tilley, Andri Sadlak, and Bryan Rangel this Wednesday to talk about how Amazon sellers can actually turn influencers into a real sales channel. This is something I used to teach about at UCLA. Now with TraceFuse, I've developed a whole new way of looking at influencer marketing, with an added emphasis on review management. March 25th at 9 AM EST. Live webinar. If you're investing in creator partnerships (or thinking about it) come through. Register here: https://buff.ly/rgVemEN

Fighting unauthorized sellers can be a fruitless, annoying game of whack-a-mole. (this is also a game you can't afford to lose). You can send a hundred cease-and-desist letters to unauthorized sellers on Amazon. Most of them aren't worth the email they're written on. The seller disappears for 48 hours, pops back up under a new name, and keeps undercutting your MAP, stealing your Buy Box, and eroding the customer trust you worked to build. It's like swatting at an ever-growing swarm of flies. At scale. And it's a losing strategy for any brand trying to grow. That's why I wanted to put a spotlight on my friend Zac Garthe and his team at Sigil. Zac is an intellectual property attorney who spent over a decade fighting IP infringement in actual courtrooms. He built Sigil because he saw the gap (Amazon moves way too fast for traditional legal strategy). You need the legal teeth AND the speed to actually execute. One of their clients, Tru Earth, was getting hammered by rogue sellers stealing their Buy Box and undercutting their pricing. Within two weeks of onboarding with Sigil, they saw a major lift in sales. Within two months, the unauthorized sellers were delisted and significant revenue was recovered. What separates Sigil from most brand protection plays is the combination: Deep IP expertise designing the strategy, proactive identification of distribution leaks before they become a full-blown crisis, and scalable execution that actually gets sellers removed. Not flagged. Removed. E-commerce should be honest. You shouldn't have to compete with ghost sellers who have zero investment in your brand's long-term health. If unauthorized sellers are draining your revenue and messing with your pricing integrity, talk to Zac's team at Sigil. Check them out here: https://buff.ly/SqWgcY6

Amazon sellers treat their image stack like a photo album. Here's all the angles. Here's the product in a box. Here's a random lifestyle shot. Done. None of it factors in the buying journey. It's all random, stuff you thought "looks nice." Your 7 image slots should work like a sales funnel. Each slide has a job. Each one moves the customer closer to buying. Slide one gets the click. Slide two shows the core benefit (not the spec, the benefit). "3 full days of power" hits different than "10,000mAh battery." Slide three builds trust. Slide four handles the objection. And so on. One message per slide. Not five points crammed into one graphic that nobody can read on their phone. If your images aren't doing a job, they're taking up space.

It's the universal law of eCom: You are bleeding money somewhere. Ad spend, product, logistics... these are the common culprits. Founders are always looking there to optimize and cut needless costs. But the stuff hiding in plain sight on your listing... that's what gets you in the end. The reviews you never flagged, the policy violations you didn't catch, the reputation damage that quietly tanks your conversion rate while you're busy optimizing everything else. I'll be breaking this down on Wednesday alongside some sharp operators in the space (Burak Yolga, David Balan, Fabricio Miranda, Richard Carreon, and Jonathan Tilley). We're going live March 25th at 12 PM EST. Sharing all the hidden ways sellers lose money. If you sell on Amazon and you've ever looked at your numbers and thought "something isn't adding up" — this one's for you. Register here: https://buff.ly/WcRfFoa

One of the top reasons Amazon sellers get negative reviews: Product size... not quality. Customer opens the box, the product is smaller (or bigger) than they expected... And now you've got a one-star review that says "way smaller than I thought" sitting on your listing forever. The fix is dead simple. Stop relying on dimensions alone. Nobody reads "7.5 x 4.2 x 3.1 inches" and actually pictures the product in their hands. Put it next to something people recognize. A phone. A coffee mug. A human hand. Instant scale. Think of the classic "banana for scale" meme. One image slot dedicated to comparative sizing can save you from dozens of "not as described" returns and the reviews that come with them.

I used to spend 20 hours solving a problem just to avoid paying someone $1,000. I'd sit there afterward feeling great about it. "Look at all that money I saved." Except I didn't save anything. If my time is worth $500 an hour and I burned 20 hours fumbling through something an expert could've handled in two... I lost $9,000 and got a worse outcome. That was Shane 1.0. The "I'll figure it out myself" version. The version that confused stubbornness with resourcefulness. I'm on Shane 4.0 now. And the biggest upgrade between versions was learning to delegate at the speed I used to hoard. I see this constantly with Amazon sellers trying to handle review removal on their own. They'll spend weeks filing cases, testing templates from forums, feeding prompts into ChatGPT. And at the end of it, their removal rate is somewhere between zero and "I think maybe one got taken down?" Meanwhile, the reviews are still tanking their conversion rate every single day they sit there. Every day you spend trying to figure it out yourself is another day those one-star reviews are pushing real customers to your competitor's listing. Old me would've told you to grind through it. Current me can't delegate fast enough. What's something you held onto way too long before finally handing it off?

Fastest way to lose a good hire? Let them walk in with the wrong expectations. At TraceFuse, we tell new team members straight up: you're probably going to file at least four cases before you get a single response. Could take a month to see your first win. That's not a warning. That's preparation. When people know what's coming, they can handle it. When they don't, they start thinking they're failing at something they were never set up to succeed at yet. And if you're someone who's been on the other side of that: took a job, got completely blindsided by how different reality was from the interview, started wondering if you were the problem? You probably weren't. That was a leadership failure, not yours. Sell the truth during hiring. Lose some candidates who can't handle it. Keep the ones who hear the hard stuff and show up anyway. Those are the ones who stay for years.

Too many Amazon sellers make themselves a "soft target." If someone broke into your safe and stole $1,000 (and you didn't change the lock) how fast do you think they'd be back? I couldn't get back to your house fast enough. Word would get out, making you every cat burglar's dream. That's exactly what's happening with review attacks on Amazon. A competitor hits your listing with fake negatives. Your star rating drops. Your conversion tanks. They gain market share. And you go, "Eh, it's probably a one-time thing." You moved on. But if it worked, they're coming back. This is soft target vs. hard target, and most sellers are walking around with the vault wide open. The people running these attacks don't just randomly pick a listing. They've studied the ecosystem. They've tested what gets through Amazon's filters. They've done trial and error until they found what sticks. This is methodical. And when they see a brand that doesn't fight back? That brand goes on the rotation. It's the same logic as a bully. Ignoring the problem doesn't make it go away. You can bury your head in the sand (and that's fine for a minute) but when you pull it back out, the same problem is standing right there waiting for you. Plus a few new ones. When you draw the line, remove the reviews that are already there, you signal that your brand isn't an easy mark. Get the fraudulent reviews removed. Monitor for new ones. Have a system in place so that when the next attack comes—and it will—you're not scrambling. Be the hard target. TraceFuse can help with that.

"Just use AI for that." I hear this constantly. And it's almost always wrong. Specifically when it comes to Amazon review removal. I've talked to hundreds of sellers who tried the AI route. Fed prompts into ChatGPT. Generated case filings. Hit submit and waited... Legend has it, they're still waiting til this day, lol. And I'm not anti-AI. We've been building our own AI tools at TraceFuse for three years (before most people even knew what a prompt was). We use AI every day. But AI is only as good as the information you put into it. If you don't understand how Amazon's case system works, what format their team responds to, and what's changed in the last 90 days... your prompt is garbage. And AI will polish that garbage into a very professional-sounding document that still gets ignored. The target moves constantly. Amazon changes how they evaluate cases. New policies roll out. Internal teams shift priorities. What worked three months ago might get flagged today. AI isn't in the trenches seeing those changes happen in real time. People are. People who are filing cases every single day, reading every response, tracking which arguments land and which ones don't. That institutional knowledge doesn't live in a language model. It lives in experience. And there's the accountability piece nobody talks about. If AI gets it wrong and your listing tanks, who's responsible? AI doesn't give refunds. AI doesn't have a reputation on the line. AI doesn't pick up the phone. AI is a tool. A powerful one. But a tool without expertise behind it is just an expensive way to get the same bad result faster. Where have you seen AI overpromise and underdeliver in your business?