# Muhammad Umar Saeed Chishty

Muhammad Umar Saeed Chishty shares advice for ecommerce brands on AI and search visibility, customer retention, discounts, and measuring paid advertising against business results.

- Profile: https://b2binfluencer.marketing/creators/muhammad-umar-saeed-chishty/
- LinkedIn: https://www.linkedin.com/in/muhammad-umar-saeed-chishty
- LinkedIn followers: 2,583
- Topics: artificial-intelligence, ecommerce, paid-ads, seo, ai-search-visibility, ecommerce-retention
- Based on 13 dated posts, latest 2026-10-09

## Summary

They are most useful for short LinkedIn advice on ecommerce AI search visibility, retention, discounts, and ad measurement.

- Best for: DTC ecommerce brands with Meta and Google spend facing AI invisibility and shrinking margins.
- Not for: B2B software thought leadership needing long-form research, verified case studies, and documented methodology.
- Check first: Confirm audience demographics, paid partnership terms, and any performance data before contacting them.

### Takeaways

- Ask ChatGPT for the best brand in your category to check AI visibility.
- Frequent discounts can train customers to wait for a sale.
- Check platform-reported ROAS against business results, not the platform dashboard.

## Main ideas

- **Being named in an AI answer matters more than ranking in a list**: Chishty’s central argument is that the buying path has changed: customers no longer search, click and compare a list of results. They ask an assistant, get a single written recommendation and buy. If a brand is absent from that recommendation, the problem is invisibility, not an SEO gap; the buyer may never reach the site. In this account, models name brands not because of keywords but because of mentions across podcast episodes, Reddit threads, review sites and directory listings, accumulated consistently enough for the brand to surface in answers to real questions. The priority shifts from winning the click to being mentioned in the answer. Chishty offers two free brand audits a week to readers who want to know what AI tools currently say about them.
- **Search didn’t shrink; it moved to social platforms and AI tools**: A second, repeated position holds that consumers, especially younger ones, no longer start on Google but search within YouTube, TikTok, Instagram and AI tools—and that these platforms now drive product discovery and purchase decisions. Chishty concludes that ranking on one platform is no longer enough; brands need to be findable wherever attention, intent and decisions occur. They call this practice Search Everywhere Optimisation. The argument is directional, not measured: it identifies where discovery is happening but offers no channel-level data. It supports widening a brief beyond Google, not deciding how much budget each surface deserves.
- **Discounts rent customers; programs buy them**: Chishty argues that permanent sales are the most expensive marketing an ecommerce brand runs because every discount teaches buyers to wait for the next one. Repeat customers, in this account, are often coupon hunters who know the logo but not the product; they leave as soon as a competitor offers a slightly deeper cut. The sale did not win a customer; it rented one. The alternative is a retention program worth staying in: first access, real perks and a product people genuinely reorder. The argument distinguishes transactions from loyalty: margins suffer from a sale the brand never planned to stop running, not from advertising costs.
- **A five-point diagnostic of what is eroding ecommerce margins**: In one post, Chishty lists five problems said to be quietly eating margins: creative fatigue from running the same few user-generated formats as everyone else; retention treated as the tab nobody opens; discount addiction that trains buyers to wait; reliance on a single advertising channel, where a bad few days on Meta flatten revenue; and blaming the algorithm instead of fixing the offer, landing page and follow-up emails. These are self-inflicted and addressable, the post argues, and it ends by asking which one hurts readers most. It works as a self-diagnosis checklist, not a ranking of causes.
- **Reconcile advertising against the bank account, not the platform dashboard**: Chishty is skeptical of platform-reported performance: Meta takes credit for sales it barely touched, Google counts clicks that were never going to buy, and the dashboard can look strong while the profit-and-loss statement tells a different story. The recommended discipline is to reconcile money in against money out as the business measures it, rather than optimise for figures supplied by the platforms themselves. The test is whether revenue would actually fall if all advertising were paused for 30 days—a question Chishty says most operators cannot answer confidently.
- **Fix the funnel before buying more visibility**: Read together, Chishty’s visibility and margin arguments point in the same direction: the answer is not more ad spend, but more of the right kind of presence. The posts urge brands to earn mentions across podcasts, communities and review sites, stop feeding a broken funnel with more budget, and replace discounting with a retention program. A brand working on AI-search visibility should expect Chishty to pair it with offer, landing-page and follow-up fixes, and to judge results by full-price sell-through and repeat behaviour, not spend.

## Work to read

- [AI search turns brand mentions into the new ranking](https://www.linkedin.com/posts/muhammad-umar-saeed-chishty_aisearch-seo-ecommerce-activity-7514255071216570368-ApEz)
- [Search did not disappear; it moved to social and AI](https://www.linkedin.com/posts/muhammad-umar-saeed-chishty_search-didnt-disappear-it-moved-activity-7427335975149694976-AefW)
- [Five things quietly eating ecommerce margins in 2026](https://www.linkedin.com/posts/muhammad-umar-saeed-chishty_ecommerce-dtc-growthmarketing-activity-7513237064885186560-TnPf)
- [Your 30% off sale is the most expensive marketing you do](https://www.linkedin.com/posts/muhammad-umar-saeed-chishty_ecommerce-dtc-growthmarketing-activity-7513817238177705986-1uUn)
- [Your ROAS is 4.2x. Your bank account disagrees](https://www.linkedin.com/posts/muhammad-umar-saeed-chishty_marketinganalytics-attribution-paidmedia-activity-7513599048306692096-UX0Y)
- [A poll on where ecommerce margins hurt most](https://www.linkedin.com/posts/muhammad-umar-saeed-chishty_ecommerce-dtc-growthmarketing-activity-7513961525880160256-X2hl)

## Partnerships

The LinkedIn posts publish no sponsorship packages, rate cards, partner policies, or disclosure terms. The recurring commercial invitation is an offer of free audits: "I do 2 free audits a week — DM me 'audit'" appears in posts about AI-search visibility and margin leaks. This opens a conversation, not a defined partnership format. A brand planning a paid placement should expect to negotiate scope, deliverables, pricing, and usage rights from scratch. Intake runs through a LinkedIn message, not a booking page or brief form, and audit capacity is capped at two per week, suggesting limited personal capacity rather than an agency or team roster. Before committing budget, ask whether paid sponsorships are accepted and confirm deliverables, pricing, disclosure practice, and approval turnaround.

## Alternatives

- Azhan Shafique: Choose this alternative when AI systems and Google describe the company wrongly, or when a keyword list generated by an AI tool contains high-volume terms the company cannot realistically rank for. The two posts cover both cases. One describes a surgical-instrument manufacturer that already held government and ISO certifications, industry memberships and a long trading history, yet was being misread by ChatGPT and Google AI. The work strengthened the information layer — who the company is, what it manufactures, where it is, its product categories and certifications — and got the key pages reindexed. The AI systems then identified the company correctly. The other post describes a prospect who believed an AI tool had replaced the need for an agency. Their keyword list lacked difficulty ratings and search intent, and had not been checked against existing rankings. The method offered: start with lower-competition terms, verify intent one by one, choose backlinks for relevance rather than domain score, and assign one keyword cluster per page so pages do not compete with themselves.
- Aminat Hammed: Choose this alternative when the brand's priority is the earlier part of the shift: how shoppers discover and compare products through AI before reaching a brand's site, and the quality of the product information an assistant has to read. The first post argues that vague descriptions are not enough when AI helps someone choose between five products. A product page should state what the product does, who it is for, what makes it different, how it compares and why someone would choose it. The post cites industry figures showing GenAI referrals to retail ecommerce grew 203% year over year and 51% of U.S. consumers used an AI shopping tool in the past month. The second post focuses on retention. It uses Omnisend's 2026 report, based on activity from 150,000 brands, showing automations made up just 2% of email sends but produced 30% of email-driven revenue. It argues that campaigns and triggered flows should have separate jobs, and suggests starting with the question: which customer behaviour is the brand not yet responding to?
- Andriy Boychuk: Choose this alternative when the brand wants a retention operator for a live commercial moment and short, frequent, action-led breakdowns. Both posts are tied to dated events. The first, written around Amazon's Prime Big Deal Days, argues that DTC brands should not try to out-discount Amazon but instead run counter-programming on channels they own: a list-only sale for email and SMS subscribers, a free gift with purchase instead of a percentage off, or early access for subscribers. It also says to treat every visitor during the research week as a capture opportunity: Amazon gets the order and the customer, while the list lets the brand keep the relationship. The second covers Google opening AI Mode monitoring alerts to everyone on 28 September. It argues that brands with a back-in-stock flow capture the customer at the out-of-stock moment, while those without one hand their highest-intent moment to an algorithm that does not owe them the click.

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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/