A Ghost Data study reported by NBC News in 2019 found counterfeit-linked Instagram accounts for luxury brands, Gucci, Chanel, Balenciaga, Louis Vuitton and Dior among them, had nearly tripled in three years, from around 20,000 accounts in 2016 to over 56,000. More recently, in May 2026, City of London Police raided a warehouse in Rotherham and seized more than 26,000 counterfeit items, plus roughly £1.16 million ($1.5 million) in suspected stolen clothing, after finding a suspect livestreaming the sale of counterfeit goods on TikTok Shop. Consumer-safety coverage of this pattern has been thorough for years: spot the red flags, don’t pay through CashApp or Venmo, check reviews before you buy, use reverse image search on the product photos. What almost none of that coverage addresses is the other side of the same problem, what a brand is actually supposed to do about it, and why the usual brand-protection playbook doesn’t reach this format at all.

The mechanism, shot by shot

The format repeats often enough to describe almost frame by frame. A phone camera pans slowly across shelves or a table stacked with shoeboxes and pairs on display, sometimes inside a small shop, sometimes what looks like a home storeroom. A price flashes as on-screen text, usually crossed out against a higher “original” price beside it. The brand’s name might be spoken in the voiceover or shown briefly in a logo close-up, rarely spelled out in the caption itself. The caption ends with some version of “DM to order,” “price in inbox,” or a WhatsApp number. The comment section fills with past buyers replying “sent 🙏” or “arrived, thanks bro,” which reads as social proof to the next person scrolling past, and costs the seller nothing to generate.

None of this is unique to shoes or to any one platform. The same shape shows up across counterfeit apparel, accessories, electronics, wherever a physical product photographs well and a discount is the obvious hook. What makes it worth naming as its own pattern isn’t the product category, it’s the structural choice sitting underneath all of it: the actual transaction never happens anywhere public.

Why the sale never becomes a reportable listing

A public listing with a price and a “buy now” button is exactly what marketplace and social-commerce monitoring is built to catch, a specific product, a specific price, a specific seller account, all sitting somewhere a brand can screenshot and report. Moving the transaction into direct messages removes all three from anything publicly visible. There’s no fake product listing to flag, no storefront page to send to a platform’s brand-abuse team, and no public price to prove the product was ever claimed as genuine, only a video that, read literally, shows a shop and some shoes without a single written claim of authenticity.

This is the same underlying deception as any other counterfeit sale. What’s changed is that it’s been restructured so it never generates the one artifact, the listing, that makes a fake listing reportable in the first place. A seller doesn’t need to be more careful about hiding evidence when the evidence was never created publicly to begin with.

Why the algorithm helps, not just the seller

A Which? investigation found 23 of 34 cosmetic products it bought across Amazon, eBay, TikTok Shop and Vinted were likely counterfeit, including five of six bought directly through TikTok Shop, evidence the pattern already extends well beyond shoes into any category that photographs well on a phone camera. Short-form recommendation systems reward watch time and engagement, not verified authenticity of what’s on screen. A video of a shop full of steeply discounted branded-looking shoes performs exactly like any other bargain-hunting or local-business content, gets the same recommendation boost, and reaches viewers who never searched for it in the first place. The comment section’s “sent, thanks” replies read as genuine customer testimonials to anyone scrolling past, which pulls more DMs in without the seller doing anything beyond posting the next video. The platform’s own incentive to keep people watching works in the seller’s favour here, not against them.

The blind spot in brand-side monitoring specifically

Most brand-protection monitoring is built around marketplace monitoring, scanning listings, prices and seller accounts on e-commerce platforms. A DM-to-order video on a short-form platform never touches a marketplace, so a brand relying solely on marketplace scanning isn’t missing this because it’s hard to find. It’s missing it because nothing in that monitoring was ever pointed there. The content lives entirely inside the social platform’s own video and comment ecosystem, a different surface that marketplace tooling was never built to reach.

This distinction matters because it changes what “we have brand protection in place” actually covers. A programme built around counterfeit listings and unauthorised resellers on Amazon or Flipkart can be running perfectly and still never encounter a single instance of this pattern, simply because it’s looking in a different place. The gap isn’t a quality problem with existing monitoring. It’s a coverage-surface problem, and it only shows up once someone goes looking specifically for it.

What actually has to change: content and account signals, not listings

Since there’s no listing to match against a catalogue, detection has to work on the video and the account instead, flagging content that pairs a brand’s name or visual identity with discount language and “DM to order” phrasing, then reviewing the account’s pattern of posting rather than waiting for a single reportable product page. This sits closer to brand impersonation monitoring than traditional listing detection, because the target is the account and the recurring pattern, not one page. Truviss’s Social Media Monitor is built around exactly this kind of account and content-level signal, watching for accounts and posts trading on a brand’s identity across Instagram, YouTube, TikTok and similar platforms, rather than assuming every threat will eventually surface as a listing somewhere.

A few practical questions separate a brand that’s actually covered here from one that only assumes it is. Does existing monitoring look at video content and comment sections at all, or only at listings and storefront pages? Is there a defined process for flagging an account, not just a single post, once a pattern of DM-to-order content is spotted? And when a video does get reported, is there a documented trail, screenshots, timestamps, the account handle, in case the same seller reappears under a new account after the first one is taken down, which happens often enough to plan for rather than treat as a surprise.

Getting started

If a brand sells footwear, apparel, or anything else that shows up often in “discounted branded goods, DM to order” content, the fastest useful check is whether current monitoring even reaches Reels, Shorts and comment sections at all, not just marketplace listings and impersonator profile accounts. Most brand-protection programmes built before this format became common were never pointed there in the first place, and the gap only closes once someone deliberately extends coverage to the accounts and content driving it, rather than waiting for it to eventually show up as a listing that never comes.