# Amit Bachbut

Amit Bachbut writes about ecommerce marketing, with a focus on how AI is changing product discovery, visibility, and checkout. Bachbut's posts explain practical implications for online stores, including Shopify settings and measurement trade-offs.

- Profile: https://b2binfluencer.marketing/creators/amit-bachbut/
- LinkedIn: https://www.linkedin.com/in/amitbachbut
- LinkedIn followers: 11,441
- Topics: artificial-intelligence, ecommerce, seo, agentic-commerce, ai-search-visibility, ecommerce-marketing, shopify, peak-season-planning
- Based on 9 dated posts, latest 2026-10-02

## Summary

Amit Bachbut is most useful for explaining AI-driven ecommerce discovery and Shopify checkout changes to store and agency teams.

- Best for: A Shopify agency or ecommerce platform team preparing clients for AI discovery and checkout.
- Not for: A consumer brand campaign needing shopper-facing content to drive direct seasonal sales.
- Check first: Ask for webinar details and verify the 752% AI referral figure before client-facing use.

### Takeaways

- AI is taking the decision, not the checkout.
- The default setting may already have enrolled the store.
- Measurement is what breaks in AI-native checkout.

## Main ideas

- **AI is taking the decision, not the checkout**: Amit Bachbut argues that the contest over AI commerce is not about who processes the payment. In-chat buying came and went, but shopping before a purchase — discovery, inspiration, the fitting room, the wishlist — kept moving into AI assistants. The click still leads to the brand's own site, but by then the choice is largely made somewhere the brand cannot watch, A/B test or retarget. That shifts the practical question from "should we sell inside ChatGPT?" to "are we winning the conversation that happens before the click?" Bachbut's answer points to product data, imagery, reviews and AI visibility, each with an owner and a budget.
- **The default setting may already have enrolled the store**: On Google's native checkout inside AI Mode and Gemini, Amit Bachbut's point is that inclusion is opt-out rather than opt-in. Google emailed some Merchant Center users to say eligible products are automatically included with nothing to set up, and direct checkout is on by default for eligible Shopify stores. Bachbut also flags that leaving Shopify's management setting on enrols the store automatically in future agentic storefront channels. Check the settings now rather than plan around them later, and treat automatic enrolment as something the store should knowingly consent to.
- **Measurement is what breaks in AI-native checkout**: Their recurring test for any new commerce surface is whether the store can still see what happened. Inside the AI Mode checkout, Shopify says Google Analytics and custom pixels do not fire; only server-to-server checkout-start and checkout-completion events do. The order still arrives in Shopify with channel or referrer attribution, so the sale is visible while the journey is not. Reporting or retargeting built on browser pixels quietly loses data. Bachbut also lists other losses — upsells and custom fields may be missing, and subscriptions and bundles are not supported — and weighs fewer steps to purchase against the measurement trade-off instead of declaring the feature good or bad.
- **Visibility work has a deadline before peak season**: Amit Bachbut argues that during a peak trading season, a brand's biggest competitor can be whichever brand AI recommends instead. They say AI answers are shaped by brands' visibility months earlier, not during the sale period, making AI search visibility pre-season work with a calendar rather than a November reaction. They frame it as a trust question — what AI engines actually trust and where brands lose visibility — and point readers to a longer discussion for the detail.
- **Two platforms, opposite directions on the same idea**: Read together, the posts show a tension Bachbut does not smooth over. OpenAI retired its in-chat checkout after weak conversion, while Google's native checkout inside AI Mode and Gemini expanded with eligible products included automatically. They assess each platform separately and on its own terms, making the case for treating agentic commerce as a set of platform-specific pilots with defined measurement rather than one trend to adopt wholesale.

## Work to read

- [OpenAI’s shopping strategy, in 4 dates](https://www.linkedin.com/posts/amitbachbut_aeo-seo-ecommerce-activity-7511744587594649600-XI8y)
- [Checking agentic checkout settings in Shopify](https://www.linkedin.com/posts/amitbachbut_ai-aimode-checkout-activity-7508634798710673409-KLzL)
- [BFCM timing: the brands AI recommends are decided before November](https://www.linkedin.com/posts/amitbachbut_bfcm-aisearch-ecommercemarketing-activity-7505636335387508737-6TYB)

## Brand relationships

- **Shopify** (mention)
- **Google** (mention)
- **OpenAI** (mention)
- **Walmart** (mention)
- **Yotpo** (mention)

## Partnerships

Amit Bachbut's posts do not describe a sponsorship offer. They publish no rate card, media kit, sponsorship policy, or partnership inquiry page or address. The three posts read as analysis for ecommerce operators rather than pitches to brands, and none discloses a paid brand arrangement or its terms. One points to a recorded webinar hosted with two named guest speakers, showing that longer-form, collaborative formats feature in their work, but not how a brand could commission, sponsor, or co-host one. A brand considering a paid engagement should ask which formats they accept, whether sponsored posts and webinars are labelled as paid, what the lead times and turnaround are, what usage, exclusivity and republishing rights apply, and how Shopify- or measurement-specific questions are scoped.

## Alternatives

- Ben Salomon: Choose this for a campaign about putting a loyalty or retention programme in front of customers at the point of decision, or when the agency needs a dated programme rather than a settings walkthrough. The posts cover a Shopify-native loyalty placement on the product page and in the cart, with named results (30% uplift in logins, 70% of engaged shoppers completing the login flow, 20–40% more redemptions, and a quarter of purchases landing within minutes of a redemption). They also lay out a 16-week AI visibility plan with three deliverables: a prompt-set audit scoring the brand against competitors, a dated task plan, and a review-capture email aimed at the 72 hours after peak. The plan is a client-ready artefact; Amit Bachbut's posts provide the argument and admin path, not the schedule.
- Jade Beard-Stevens: Use this when a client needs a plain-language account of ChatGPT becoming a shopping destination: real-time product picks, reviews and prices inside the chat; buy-now links to merchant sites; and recommendations personalised from earlier conversations. It also suits clients facing a retail-operations problem: a store running Square at the till and Shopify online, with stock drifting between the two and card fees jumping from 0.8% to 2.4% under the alternative. The pet-store post candidly describes a live sync failure at up to 80 customers a day—a worked example that can prompt a client to describe their own setup honestly.
- Tom Shivers: Choose this when the briefing needs the standards behind agentic checkout: how OpenAI and Stripe's Agentic Commerce Protocol and Google's Universal Commerce Protocol let an agent compare products, check inventory, build a cart and complete checkout while the retailer stays merchant of record. The posts explain what that requires: a structured product feed, checkout endpoints, delegated payments, consistent pricing and inventory and fulfilment data, and clean feed and schema data for eligibility. The 'structured feed is the new homepage' framing and the Merchant Center action list translate directly into a data-readiness workstream.

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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/