# Anand Chhatpar

Anand Chhatpar writes about Amazon advertising and retail media, including how brands can assess marketplace profitability, Amazon DSP, and AI-driven shopping.

- Profile: https://b2binfluencer.marketing/creators/anand-chhatpar/
- LinkedIn: https://www.linkedin.com/in/anandvc
- LinkedIn followers: 13,212
- Topics: artificial-intelligence, agentic-commerce, retail-media
- Based on 14 dated posts, latest 2026-09-28

## Summary

Anand Chhatpar is most useful for Amazon advertising and retail media analysis on profitability and AI shopping.

- Best for: Retail media agencies or Amazon-focused brands wanting commentary or advisory on Amazon DSP, AI shopping, and profitability.
- Not for: Consumer lifestyle brands needing a paid product launch, sponsor formats, audience demographics, and engagement performance.
- Check first: Confirm availability, sponsorship terms, rates, audience demographics, and recent post performance.

### Takeaways

- AI shopping agents judge trust signals like listings, reviews, returns, complaints, Q&A, repeat purchase.
- A $30 product can land at $32 to $34 per sale, exceeding the price.
- Judge PPC by profit dollars, not the ACoS percentage.

## Main ideas

- **AI shopping agents judge trust signals, not ad tactics**: Chhatpar treats agentic shopping as a live change, not a future one: Rufus handles product discovery, “Buy for Me” handles reorders, and AI completing a full purchase with no human in the loop is in testing. They argue that when software shops on a person’s behalf, it filters for confidence rather than responding to a keyword, image, price, or review. Those confidence signals include return rate, review sentiment, complaint patterns, listing clarity, Q&A, use-case specificity, repeat purchase rate, and brand reputation. They put the window to build those signals at roughly 18 to 24 months, warning that brands treating it as a 2028 problem will spend 2027 trying to work out why conversion is falling.
- **Fix the unit economics before spending on ads**: Chhatpar argues that advertising is a scaling lever for a business with healthy economics, not a fix for one that loses money per order: more spend simply loses money faster. They describe turning down a seven-figure client on that basis and say that even hitting a 10% TACoS on a negative-margin product would only optimize the rate of loss.
- **Judge PPC by profit dollars, not the ACoS percentage**: Chhatpar calls obsessing over low ACoS the number one Amazon PPC mistake. A higher ACoS driving more sales can leave more actual profit than a lower ACoS driving less, they argue. The goal is profitable scale, not a smaller percentage.
- **Amazon's closed measurement loop gets more valuable as attribution elsewhere breaks**: Reporting from the IAB Connected Commerce Summit, Chhatpar quotes Collin Colburn, IAB VP of Commerce & Retail Media, saying the industry needs to “blow attribution up.” Colburn argues that one-to-one attribution has gone too far now that AI mediates product discovery, and that the next model is probabilistic contribution and commercial influence. Chhatpar counters that Amazon is the only major platform that closes the loop in one place, from ad impression to product search to purchase, with a real sale verifiable in the same dashboard. They argue that when Google or Meta attribution becomes harder to trust, budgets should move toward the platform with closed-loop measurement, not away from accountable platforms.
- **Amazon's ad machine depends on sellers, which gives sellers leverage**: Chhatpar analyzes Amazon's reversal of a cash flow policy within nine days, calling it a tell rather than customer service. Amazon announced on April 15 that it would switch ad payments from credit card billing to proceeds-deduction. Sellers organized, seven-figure accounts publicly threatened to pause spend, and after a Modern Retail story landed before Amazon's May 11 Upfront, Amazon backed down and delayed the change to August 1. Chhatpar argues that the $69 billion ad business, growing 23% year over year, is more fragile than it looks: internal models showed real downside from even a 1 to 2% spend cut by top accounts. They also note that Amazon has compressed seller margins for years through fee increases, rising fulfillment costs, return policy shifts, and billing changes. On policies that directly threaten the ad revenue line, they argue, Amazon will blink.
- **Programmatic waste is a fixable infrastructure problem, and Amazon is helping fix it**: Chhatpar explains Amazon's decision to open-source its Dynamic Traffic Engine and donate it to IAB Tech Lab. Demand-side platforms receive millions of bid requests per second and must process them all, even though most will never win, inflating infrastructure costs and compressing margins. Dynamic Traffic Engine is a file-based framework that lets DSPs communicate bidding priorities to SSPs so irrelevant requests are filtered before reaching the DSP; TripleLift integrated first. Chhatpar argues that Amazon is betting industry-wide modernization will benefit its own DSP, which holds first-party retail signals — helping build the road because they have the best car. Agency operators running Amazon DSP should expect lower CPMs and more efficient delivery as adoption spreads, without bidding differently.

## Work to read

- [Amazon is quietly building a world where AI agents buy things](https://www.linkedin.com/posts/anandvc_amazon-is-quietly-building-a-world-where-activity-7451651550290132992-xRg6)
- [We turned down a 7-figure client last quarter](https://www.linkedin.com/posts/anandvc_we-turned-down-a-7-figure-client-last-quarter-activity-7452023743062687744-jhrM)
- [Amazon quietly did something significant for programmatic advertising today](https://www.linkedin.com/posts/anandvc_amazon-quietly-did-something-significant-activity-7450349585895538688-EKXV)
- [The IAB just held its annual Connected Commerce Summit in New York](https://www.linkedin.com/posts/anandvc_amazoncom-spend-less-smile-more-activity-7450686139390197760-fiCQ)
- [Amazon reversed a cash flow policy in 9 days. That’s not customer service. That’s a tell.](https://www.linkedin.com/posts/anandvc_amazon-reversed-a-cash-flow-policy-in-9-days-activity-7450235478353809411-Fcgb)
- [The #1 mistake Amazon sellers make with PPC? Obsessing over low ACoS.](https://www.linkedin.com/posts/anandvc_amazonfba-amazonppc-ecommerce-activity-7434729021541748736-EL9J)

## Brand relationships

- **Amazon** (mention)
- **IAB Tech Lab** (mention)

## Partnerships

Anand Chhatpar's posts do not describe a sponsorship format, rate card, or partnership terms, or say whether they accept sponsorships. The one commercial relationship described directly is client work: a post explains turning down a seven-figure brand after modeling its Amazon P&L showed the product losing money on every sale — roughly $32–$34 in landed cost against a $30 selling price, with advertising at 18–22% TACoS. It sets out four conditions for Amazon advertising to make sense: 50%+ gross margin before ad spend, 8%+ listing conversion without paid traffic, a supply chain that can scale 3–5x, and lifetime value that justifies acquisition cost. Brands approaching them for client work should expect their unit economics to be examined before any agreement, not just their budget. The remaining posts are market analysis for Amazon sellers and agency operators: agentic shopping and trust signals, Amazon's open-sourced Dynamic Traffic Engine, attribution in an AI-mediated discovery path, and why a 15% ACoS on $50K can beat 10% on $20K. They include no offer, availability, or booking process. Their posts provide no official partnership, sponsorship, or advisory inquiry route, so the inquiry link is left empty rather than pointed at a general profile. Ask for a media kit, services page, or post stating terms; until then, treat a paid commentary or advisory engagement as unconfirmed and open the conversation directly.

## Alternatives

- Bernard Nader: Choose Nader when the campaign need is a working session on a specific account problem rather than a market-shift narrative. The posts show account-level profit diagnosis in detail: one child SKU produced $29,519 in sales at 24.79% TACoS and still lost $4,078, while a sibling SKU on the same parent listing made $3,087 on $19,587 in sales. Nader separates parent-level fees into FBA fulfillment ($24,461.88), referral fees ($9,275.65), storage ($3,463.84) and FBA inbound defect fees ($5,287.68), then asks which lever would actually remove the loss. Lowering bids, Nader notes, does nothing to fix $5,287.68 in inbound defect fees. A second post describes ending an engagement by telling a client that PPC could not fix the business, even though CPC, ACoS, CTR and TACoS were improving. For a brand that suspects its ads are being blamed for an unprofitable SKU, that operational framing is more useful than a forward-looking AI story.
- Abhiraj Aggarwal: Choose Aggarwal when the need centers on seller tooling adoption and Amazon's own margin enforcement. One post walks through Amazon Accelerate 2026's Seller Assistant: persistent memory of a seller's pricing patterns, inventory cycles and growth goals across sessions; a canvas for modeling pricing scenarios against live data; and automated workflows that keep every action behind approval with an audit trail. The other covers Amazon's margin strategy, arguing that profitability now outranks selection: SKUs missing contribution-margin targets are pushed into Direct Fulfillment, items below profitability thresholds face search suppression, and Gross Margin Guarantee pressure can leave vendors writing a check back. For an agency briefing clients on what changed in Seller Central and how Amazon's margin calculus affects listings, that pairing is practical.
- Brandon Fishman: Choose Fishman when the audience wants a fast, actionable digest of what Amazon just shipped. The two posts summarize Accelerate announcements for sellers: day one covers Prime Air 30-minute drone delivery, Amazon Quick's direct connection into Seller Central, and Seller Flex, cited as a 17% conversion lift from keeping bulky inventory in the seller's own warehouse. Day three covers Profit Analytics pulling revenue and costs across advertising, fulfillment, refunds and returns into one view; scenario modeling before a price or inventory decision; better inventory visibility; and AI supply-chain planning. Each item is tied to an operator action, and Fishman states a method: start audits at the SKU-level P&L, find which SKUs actually make money, then put more budget behind those. That makes the posts useful for a newsletter, internal briefing, or client-facing summary of the news itself.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/