Hayan Khan is a conversion-rate optimization designer who shares advice on improving Shopify stores. The posts focus on making product pages and store navigation answer shoppers’ questions and build confidence to buy.
Hayan Khan is most useful for diagnosing Shopify conversion problems and suggesting practical product page and navigation fixes.
Best for
A Shopify brand wanting evidence led CRO help for product pages or navigation.
Not for
A fashion or lifestyle sponsored video series needing reach and published rates.
Key takeaways
Trace the promise from ad to landing page to product page.
When a page explains but does not convince, the problem is proof, not information.
One post reports conversion rising from 1.8% to 5.8% and revenue from $18,000 to $58,000.
Check first: Ask for underlying data on reported results and whether Khan accepts paid sponsorships.
Main ideas
A polished page isn’t automatically persuasive · When a page explains but doesn’t convince, the problem is proof, not information · Trace the promise from ad to landing page to product page
Hayan Khan shares Shopify conversion-rate optimization advice, focusing on how product pages and store navigation help shoppers determine whether a product fits their needs and trust its claims.
The posts offer practical ways to spot friction beyond visual design: match a product page to the promise that brought a shopper there, make proof easy to find, and organize navigation around customer concerns.
One post reports a redesign’s conversion rate rising from 1.8% to 5.8% and revenue from $18,000 to $58,000.
Ask for the underlying data before using those reported results as a benchmark.
Hayan Khan diagnoses the shopper’s decision rather than simply recommending a redesign.
Across the posts, the diagnosis shifts with the problem: a polished page may bury evidence behind an ad’s promise; a page may explain a product yet leave shoppers unsure whether its claims apply to them; or a menu may use product categories that make sense to its builders but not to customers.
Khan suggests practical checks, including comparing menu labels with customer reviews and support messages, tracing the path from ad to product page, and backing prominent claims with specific proof.
The Wuffes example illustrates a navigation hypothesis, but the post does not attribute the company’s reported sales to its menu.
Follow this work for concrete CRO questions and examples, and treat individual results and proposed tests as context-specific, not universal proof.
Hayan Khan argues that Shopify conversion work should start with the shopper’s decision, not brand storytelling or a visual redesign.
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The posts return to a connected set of priorities: put the product benefit and likely objections early, provide proof behind claims, carry the ad promise through to the product page, write navigation in the customer’s problem language, and make the product page a standalone verification page when AI sends shoppers straight there. More polish or information won’t resolve uncertainty; even a well-designed store can make customers work too hard.
A polished page isn’t automatically persuasive
Hayan Khan contrasts a polished AI-generated ecommerce design with a redesign built around the questions shoppers need answered before buying.
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The original leaned on brand messaging, visual appeal and general product storytelling. The redesign led with a clear benefit, addressed purchase objections, added reasons to believe and followed a deliberate sequence: problem, solution, benefits, proof, product, purchase.
In the Liquid Plus fiber and gut product example, the revised page opens with “Your fiber and gut support in seconds,” addresses convenience, taste and cost, and adds ingredient information, testing and certification, nutrition information, functional claims and social proof. The post reports conversion rising from 1.8% to 5.8% and revenue from $18,000 to $58,000; ARPU was not reported.
When a page explains but doesn’t convince, the problem is proof, not information
Hayan Khan describes a recurring gap between understanding and belief.
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A page can explain what a product does but still fail to answer why a skeptical customer should believe it will work for them.
They call this uncertainty rather than confusion, and argue that more information does not always increase conversion.
The fix: provide reasons to believe, tied to the claims that matter most.
Hayan Khan quotes an unnamed Shopify store owner: “People understand the product.
They just don’t seem convinced enough to buy.”
The product page had a clear headline, good photography, strong reviews, easy-to-understand benefits and a clear call to action, but the reviews were mostly generic and the main claims lacked supporting proof.
They suggest asking what would make a skeptical customer feel confident enough to buy today.
Trace the promise from ad to landing page to product page
Hayan Khan treats message-match as part of conversion work.
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A store can have strong photography, reviews, benefits and calls to action and still lose sales if customers have to mentally connect the ad promise to the product page. To diagnose the gap, read the ad, landing page and product page in sequence and find where the connection breaks.
Hayan Khan quotes an unnamed Shopify store owner: “We’re getting sales, but I feel like we’re leaving money on the table.”
The customer journey showed a shopper arriving from a Meta ad promising a specific benefit, then scrolling through several sections of the product page before finding information that supported that promise.
Nothing was technically broken; the page made the customer think too hard.
Navigation should use the customer’s language for their problem
Hayan Khan argues that menus built around a store’s product categories can leave shoppers translating.
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Organising products around customer concerns helps shoppers connect a problem to a product before they reach the product page. Start by reading reviews and support messages, then compare how customers describe what they want to solve with the language in the menu.
Hayan Khan looks at Wuffes, reportedly a dog-supplement brand that crossed $100 million in annual sales, and highlights navigation categories such as Allergy & Itchiness, Joint Health, Stress & Anxiety and Gut Health, plus a quiz under joint care. They offer this as a hypothesis to test: would shoppers find the right product more easily if the store were organised around their needs?
AI-referred shoppers make the product page the first impression
Hayan Khan argues that AI assistants now compare products, filter options and recommend a shortlist, so shoppers may click directly to a product page rather than a homepage or collection page.
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That shifts the page’s job from persuading to verifying the recommendation. It must show why shoppers should believe the recommendation is right for them.
Hayan Khan describes a shopper asking an AI tool for the best moisturizer for sensitive skin under $40, then clicking through to a product page after the AI compares and recommends options.
The post says the page needs clear product-specific benefits, proof behind claims, verifiable ingredients or specifications, reviews that explain real use cases, comparison information, and clear pricing, shipping and returns.
It cites Shopify 2026 data showing that more than half of AI-referred sessions start on product pages.
Diagnose where customers are working too hard before redesigning
Across the posts, Hayan Khan’s priority is to locate the problem before changing the page.
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“Let’s redesign the page” is often the wrong starting question. Better questions include where money is being left on the table, what customers expected to find, how quickly the store delivered it, and what would make a skeptical customer confident enough to buy.
In one example, Hayan Khan asks a store owner where they believe money is being lost, then traces the customer journey.
In another, they ask what would make a skeptical customer feel confident enough to buy today.
For navigation, the method starts with customer reviews and support messages, not the menu as built.
The clearest before-and-after example of Hayan Khan's conversion-focused design, with specific page changes and reported business results.
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Hayan Khan contrasts a polished AI-generated ecommerce page with a redesign built around the questions shoppers need answered before buying.
The original concept emphasized brand messaging and visual appeal.
The redesign opens with the product benefit 'Your fiber and gut support in seconds,' brings convenience, taste, and cost objections forward, adds ingredient, testing, nutrition, functional-claim, and social-proof material, and follows a problem-to-purchase narrative.
The post reports conversion moving from 1.8% to 5.8% and revenue from $18,000 to $58,000, while noting ARPU is not reported.
For brands planning a campaign
For a Shopify brand, use this as a case for sequencing: answer purchase barriers and show proof before adding visual polish or brand storytelling. It supports a PDP test that organizes sections around shopper questions rather than the catalog.
Shows why product pages need to stand alone when shoppers arrive from AI recommendations rather than browse the store.
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Hayan Khan explains how AI-assisted shopping changes the entry point.
A shopper can ask an AI tool for the best moisturizer under $40, let it compare and filter options, then click directly to a product page rather than a homepage or collection page.
That makes the PDP responsible for answering, 'Why should I believe this recommendation is right for me?' The post recommends clear product-specific benefits, proof behind claims, verifiable ingredients or specifications, use-case reviews, comparison information, and clear pricing, shipping, and returns.
It cites Shopify 2026 data showing AI-referred shoppers often start on product pages.
For brands planning a campaign
For brands affected by AI-assisted discovery, treat the PDP as a standalone page that can verify a recommendation without help from the homepage. Add proof, specifications, comparisons, and clear shipping and returns details.
Shows how store-menu language can reduce or add translation work for a first-time shopper.
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Hayan Khan examines the navigation of Wuffes, reportedly a dog-supplement brand that crossed $100 million in annual sales.
The menu organizes products by customer concern: allergy and itchiness, joint health, stress and anxiety, and gut health.
A quiz also appears under joint care.
Khan argues that navigation is part of the sales conversation: it helps shoppers connect a problem to a product before reaching a product page.
The post does not claim the menu caused the growth; it proposes testing the hypothesis by comparing customer review and support language with the menu.
For brands planning a campaign
For navigation work, start with customer reviews and support messages, then test categories named for shopper problems rather than internal product lines. Add a quiz for shoppers who still need guidance.
Explains how a store can look well designed and still lose sales through message-match gaps in the customer journey.
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Hayan Khan describes a Shopify store owner whose homepage and product page both looked strong, with good photography, reviews, calls to action, and clean design.
The problem emerged in the customer journey: a shopper came from a Meta ad promising a specific product benefit, but the product page did not provide supporting information until several scrolls down.
Nothing was technically broken, but the page made the customer mentally connect 'This is what I need' with 'This product can solve it.' Khan recommends tracing the journey from ad to landing page to PDP before deciding to redesign.
For brands planning a campaign
Before a redesign, trace the ad promise to the landing page and the PDP. Test whether the PDP delivers the clicked benefit in the first screen or an early section, not several scrolls down.
Helps newcomers distinguish confusion from uncertainty, a distinction that changes what a brand should fix on a product page.
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Hayan Khan describes a product page that explained what the product does but did not answer why a skeptical customer should believe it would work for them.
The reviews were present but generic; the claims were clear but lacked proof behind the most important ones; and the benefits did not connect to the customer's own situation.
Khan calls this uncertainty rather than confusion and argues that adding more information does not always increase conversion.
The key question: what would make a skeptical customer feel confident enough to buy today?
For brands planning a campaign
For product pages, give shoppers specific reasons to believe: named-ingredient or testing evidence, reviews describing real use cases, proof behind the main claims, and comparison information. More copy won't necessarily solve an uncertainty problem.
Design the page around the buying decision, not the brand story1
The journey from ad promise to product page1
Navigation written in the customer's problem language1
AI-referred shoppers arrive on the product page1
Design the page around the buying decision, not the brand story
Khan's central argument is that a polished page is not necessarily persuasive.
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In one account, an AI-generated concept built on brand messaging and general product storytelling gave way to a page structured around what shoppers need to know before buying.
The revised page led with the product benefit, addressed three objections — convenience, taste and cost — and added reasons to believe, including ingredient information, testing and certification, nutrition information and social proof.
Khan describes the sequence as Problem, Solution, Benefits, Proof, Product, Purchase, and reports that the page's conversion rate rose from 1.8% to 5.8% after the redesign.
Structure the page in sequence: benefit first, then the shopper’s purchase barriers, evidence for each claim, and finally the product and purchase path.
For brands planning a campaign
For a product-page brief, lead with the core benefit, list the objections the page must answer before purchase, then check that each section advances the decision rather than repeating the brand.
Pages can explain a product clearly and still fail to convert.
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Khan describes a store owner whose customers understood the product but weren't convinced to buy.
The problem, they argue, was uncertainty rather than confusion: generic reviews, unsupported claims and benefits customers had to connect to their own situations.
Adding information won't fix this; the page needs more reasons to believe, tied to the claims that matter most.
List each claim on the page and the support shown for it. Treat a review as proof only when it describes a real use case.
In the Liquid Plus redesign account, the reported conversion change is the strongest performance figure; some commercial figures were not measured or were not yet available.
For brands planning a campaign
Audit every product-page claim against its supporting proof before commissioning more copy or page sections.
Khan traces a shopper's path from a Meta ad promising a specific benefit, through a landing page, to the product page.
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A store can have good photography, strong reviews, an easy-to-read set of benefits and a clear call to action, yet still make customers mentally connect the ad promise to the product.
In the example, shoppers had to scroll through several sections to find information supporting the promise they clicked on.
Khan advises reading the promise, landing page and product page in sequence to find where the link breaks.
A conversion problem may not look like bad design; it can be a well-designed page that makes customers think too much.
Read the ad promise, landing page and product page in sequence. Mark where the promised benefit first goes unstated or unevidenced.
For brands planning a campaign
Map the ad-to-product-page path for the client's highest-spend campaigns and restate the promised benefit near the top of the landing page.
Navigation written in the customer's problem language
Khan uses Wuffes, reportedly past $100 million in annual sales from dog supplements, as a navigation example.
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Instead of product-category names, the menu starts with concerns shoppers already have — Allergy & Itchiness, Joint Health, Stress & Anxiety, Gut Health — and offers a quiz for those who still need guidance after clicking.
Every unfamiliar product name adds another question; organising around customer concerns helps shoppers connect a problem to a product before reaching the product page.
Khan's starting point is to read reviews and support messages, then compare how customers describe what they want to solve with the menu labels.
Mine reviews and support messages for how customers describe their problems, then test whether the menu lets shoppers find products using that language.
The menu example doesn't establish that navigation drove Wuffes' growth; Khan presents it as a hypothesis to test on another store.
For brands planning a campaign
For a navigation brief, base category labels on the language customers use about their problems in reviews and support tickets, then test whether shoppers can find the right product without translating.
Khan argues that AI assistants now compare products and recommend a shortlist.
Read more
Shoppers may click straight through to a product page already knowing what they want, what alternatives exist, roughly what they will spend and why the product was recommended.
The page's job shifts from persuasion to verification: it must show why the recommendation is right for that shopper, with product-specific benefits, verifiable ingredients and specifications, reviews that explain real use cases, comparison information, and clear pricing, shipping and returns.
The post cites Shopify 2026 data that more than half of AI-referred sessions begin on product pages.
For brands planning a campaign
Test whether the product page works as a standalone asset, without a homepage to explain anything. Include comparison and verification content for shoppers arriving via AI recommendations.
Across the posts, Khan's approach is to locate the problem before changing the page.
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In one example, they ask a store owner where they believe money is being left on the table; in another, they ask what would make a skeptical customer confident enough to buy today. Rather than start with “let's redesign the page,” they focus on the gap between what customers expect to find and how quickly the store delivers it.
Start with the commercial symptom, trace the customer's path from ad through landing page to product page, and use reviews and support messages to identify customer language.
For brands planning a campaign
Structure an engagement around a journey audit and proof audit before committing budget to visual redesign work.
A supplement called Liquid Plus appears in a redesign case study they describe carrying out, while Wuffes, a dog-supplement brand, appears as a third-party navigation example they analyze.
Neither post states a sponsorship, affiliate arrangement, employment, or ownership; ask about any commercial relationship with Liquid Plus before booking.
Wuffes is a mention only.
Three other posts discuss unnamed Shopify store owners and reference platforms such as Shopify and Meta incidentally, which is not enough to establish a brand relationship.
Liquid Plus
Disclosed partnership
Khan walks through a conversion redesign for a fiber and gut-support supplement page, describing the shift from brand storytelling to shopper questions, the objections brought forward (convenience, taste, cost), the trust signals added, and the reported results: conversion rate 1.8% to 5.8%, average order value $54.99 to $57.59, revenue $18,000 to $58,000.
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The post does not state whether this was client work, employment, or another arrangement; ask about the relationship before booking.
Wuffes, a dog-supplement brand, serves as a worked example of organizing store navigation around customer concerns such as allergy and itchiness, joint health, and gut health, plus a joint-care quiz.
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Khan frames it as a hypothesis to test among Shopify founders and notes that the example does not prove the menu drove the brand's growth. No working or commercial relationship is claimed.
Hayan Khan’s posts offer a practical starting point for understanding why a polished Shopify product page can still underperform.
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They form a connected argument: design around the buying decision rather than the brand story, lead with benefits and address purchase objections; close the proof gap that makes shoppers hesitate; align the ad promise with the landing and product pages; write navigation in the customer’s problem language; and account for AI-referred shoppers landing directly on product pages.
The through-line is to identify where customers are doing too much work before changing the page.
Newcomers can start with the redesign sequence, then move to the diagnostic questions, navigation and AI-referral angles.
Both work with Shopify ecommerce brands on store performance and publish tactical LinkedIn posts in the field.
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Nazmul Hassan joy covers paid acquisition and store design for boutique fashion stores, overlapping with Hayan Khan’s focus on storefronts and campaigns.
Nazmul Hassan joy’s posts focus on Meta Ads account structure, scaling, ROAS and theme customization for women’s fashion stores.
Hayan Khan’s posts examine customer decisions inside the store: product-page proof, navigation language and the match between ads and product pages.
Choose Nazmul Hassan joy for paid-media account structure and Shopify theme execution; choose Hayan Khan for CRO diagnosis of product pages and navigation.
Both explain conversion rate optimization for ecommerce and business websites, focusing on why visitors do or do not take action.
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Jitendra kumar’s CRO explainer and website lead-generation checklist address the broad problem Hayan Khan tackles in posts about product pages and navigation.
Jitendra kumar’s posts offer introductory CRO and lead-generation checklists covering what CRO is, where to start, trust signals, mobile checks and message clarity.
Hayan Khan examines specific Shopify product-page information, AI-referred traffic and navigation framed around customer problems.
Choose Jitendra kumar for a plain-language CRO primer or lead-generation audit; choose Hayan Khan for product-page and store-navigation diagnosis.
Both publish LinkedIn posts about hands-on Shopify design and development work for ecommerce stores.
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Sarmin Sultana tests tools and describes client work in a Shopify context, overlapping with Hayan Khan’s focus on Shopify storefronts.
Sarmin Sultana’s posts cover a Canva-to-Shopify asset workflow experiment and a freelance pricing story, emphasizing design tools, development experiments and freelancing.
Hayan Khan focuses on conversion strategy: proof, message match, navigation and AI referral.
Choose Sarmin Sultana for Shopify design tooling and a freelance-practice perspective; choose Hayan Khan for CRO and product-page decision design.
The only measured audience figure in the posts is a LinkedIn following of 145, observed on 8 October 2026.
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That is small for a reach-led campaign.
The key question is whether Hayan Khan's audience is a narrow group of Shopify store owners and ecommerce operators who would act on conversion advice.
The posts show who the writing targets, not who follows.
Four of the five open with a Shopify store owner describing a problem — leaving money on the table, sales without conviction, or a menu that only makes sense to the people who built it — and offer advice to that reader.
A fifth addresses Shopify founders directly about organising navigation around customer concerns.
This content is closely matched to an ecommerce brand working on navigation and product pages.
The posts give no audience breakdown by geography, age, gender, employer, job title, or seniority, and include no engagement figures for likes, comments, shares, or clicks.
Ask for recent results on comparable topics and formats, plus an audience survey covering job role, company type, and seniority.
Accumulated views on one post do not show that a topic or format caused the response.
Treat Hayan Khan as a specialist contributor or consultant for a narrowly targeted Shopify conversion project — a pilot, a teardown, or a small advisory test — rather than as a distribution channel for a broad awareness campaign.
The style suits an audience already running a store and looking for a specific fix; it is unlikely to perform as a top-of-funnel reach play.
Hayan Khan’s five posts are all CRO commentary: worked examples of Shopify product pages and store navigation, plus one redesigned supplement page with before-and-after conversion figures.
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None is sponsored or carries a partner disclosure or affiliate note; none states rates, deliverable types, exclusivity terms, or turnaround expectations.
They write as a CRO designer advising store owners, with client anecdotes including a Shopify owner who felt they were “leaving money on the table” and a product page that explained the product but gave shoppers too few reasons to believe it.
The posts suggest consulting or design work rather than paid content placements, but don’t confirm how a brand can commission them, what a collaboration would include, or what it would cost.
Ask directly through the LinkedIn profile whether they accept sponsorships and, if so, what a collaboration entails and costs; the engagement may be consulting or design work rather than a sponsored post.
Strong fit for a scoped CRO, teardown, or design-advisory engagement. The brand should ask directly whether Khan accepts paid sponsorships before budgeting for a placement.
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Brief
A Shopify supplement brand is running Meta ads for a fiber and gut-support product.
The product page converts around 1.8%, and the store owner believes shoppers understand the product but are not convinced enough to buy.
The brand wants evidence-led CRO changes to navigation and the product page.
Reasons
Hayan Khan's posts show a repeatable diagnostic method: trace the promise from the ad to the landing page to the product page, then find where the clicked benefit is not restated or supported early enough. That is exactly the problem in this brief.
The closest published example is a supplement redesign. Khan describes replacing a polished brand-story page with a benefit-first page that addresses convenience, taste, and cost objections; adds ingredient, testing, nutrition, functional-claim, and social-proof material; and follows a problem-to-purchase sequence. The post reports conversion moving from 1.8% to 5.8% and revenue from $18,000 to $58,000, while noting ARPU was not reported.
A separate post diagnoses uncertainty rather than confusion: customers may understand the product but still lack reasons to believe it will work for them. The fix is proof tied to the claims that matter most, including reviews that describe real use cases—not simply more information.
For navigation, Khan's method is to mine reviews and support messages for customers' language about their problem, then test concern-based categories and a quiz. The Wuffes example uses Allergy & Itchiness, Joint Health, Stress & Anxiety, and Gut Health, while treating the menu as a hypothesis to test, not a proven cause of growth.
The AI-referral post adds a useful requirement: a product page should verify a recommendation on its own, with product-specific benefits, verifiable specifications, comparison information, and clear pricing, shipping, and returns.
The audience section shows a small measured following of 145 LinkedIn followers as of 8 October 2026. That supports a specialist contributor or consultant role for a targeted project, not a reach-led distribution campaign.
A fashion or lifestyle brand wants a sponsored short-form video series or Reels package distributed to a broad consumer audience. The main selection criteria are follower count and reach, and the brand expects paid creator distribution with published rates and deliverable formats.
Reasons
The five posts provide no sponsored content, partner disclosure, media kit, rates, deliverable types, exclusivity terms, or inquiry route. Ask for a media kit, rates, and available formats before planning or budgeting a paid placement.
The only audience figure is 145 LinkedIn followers. The posts provide no geography, age, gender, job title, seniority, or engagement data. Ask for an audience breakdown and engagement metrics before assessing a reach-led campaign.
The posts are short-form LinkedIn CRO commentary aimed at Shopify store owners and ecommerce operators. They contain no video, Reels, lifestyle, fashion, entertainment, or broad consumer-audience content.
Khan's content is diagnostic and advisory. It fits an expert teardown, PDP audit, or navigation test better than an awareness campaign measured by impressions or entertainment value.
If a lifestyle brand wants an expert-led CRO angle rather than reach, the fit could change—but that would be a different brief with different success measures.
Ad-to-PDP proof reset for a Shopify supplement or skincare brand. The campaign is a structured CRO engagement: find where the ad promise breaks on the product page, rebuild the page around the buyer's decision, and test navigation using customers' language about their problems.
Pick the highest-spend Meta ad and write down the exact benefit it promises.
Audit the path from ad to landing page to product page. Mark the first point where the promised benefit is not restated and evidenced, following the journey diagnostic in the ad-promise post.
Rewrite the product page opening so the core benefit appears first, in language shoppers already use. Then address the main purchase barriers, such as convenience, taste, and cost in the supplement example.
Build a proof stack for the claims that matter most: ingredient or specification detail, testing and certification, nutrition or functional claims, reviews describing real use cases, comparison information, and clear pricing, shipping, and returns.
Run a navigation test based on reviews and support messages. Compare customers' language about their problems with the menu labels, then test concern-based categories and a quiz for shoppers who need guidance.
Measure conversion rate, average order value, and revenue. Do not force an ARPU figure if it is not reported.
Deliver an annotated journey map, rewritten PDP copy blocks or wireframe notes, a navigation test plan, and a simple measurement sheet. Treat this as a worked proposal, not a guarantee of results: the reported figures come from one published example. Request client-side analytics before forecasting outcomes.
Choose Nazmul Hassan joy when the campaign problem sits upstream of the product page: Meta ad account structure, profitable scaling, or a full Shopify theme and store-design setup.
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Their posts show a concrete paid-acquisition method: separate proven winners from tests, use broad targeting with creative diversity, give retargeting its own role, and scale only after proving the economics.
One post reports $19,391.77 in spend producing $225,526.60 in purchase value and 1,071 purchases at 13.21x average ROAS.
Another covers women's boutique Shopify design, theme customization, product discovery, and mobile checks.
For the same buyer task, this is the stronger pick if the brand needs a broader paid-media and store-design system rather than a focused PDP conversion diagnosis.
For the specific need of improving product-page conversion through proof-led design, Nazmul Hassan joy's posts offer less detail on the ad-to-PDP message gap or how to support product claims with proof.
The Meta numbers are account-level and self-reported, not results from a product-page experiment, and the Shopify post offers design guidance rather than a measured CRO test.
Choose Nazmul Hassan joy when traffic economics or a full store build is the bottleneck; choose Hayan Khan when shoppers reach the PDP but are not convinced to buy.
Choose Jitendra kumar when the buyer task is a general CRO assessment or a lead-generation website rather than a Shopify product page.
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Their posts offer a readable diagnostic checklist for sites that get traffic but few leads: message clarity, easy calls to action, trust signals, friction, mobile usability, and intent match between ad and landing page.
Another post explains CRO basics, A/B testing, key pages, and tools such as analytics and session-recording software.
For a service business, a B2B lead site, or a team that needs an introductory CRO framework, this breadth is useful.
For a Shopify supplement brand with an existing product page and Meta ads, Jitendra kumar's posts are more general.
They do not show a Shopify PDP teardown, an ad-promise-to-product-page trace, or a reported conversion result.
The advice is checklist-style and educational rather than a close reading of a specific store's objections and proof gaps.
Choose Jitendra kumar when the problem is a broad lead funnel or the team needs a CRO primer; choose Hayan Khan when the task is a focused, product-page-level conversion diagnosis.
Choose Sarmin Sultana when the campaign needs hands-on Shopify design or theme implementation, or a Canva-to-Shopify asset workflow.
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Their posts show direct testing of Canva integration with a Shopify test store—editing product images in Canva and sending them back—and a client story about a Shopify redesign and value-based pricing. For a brand whose bottleneck is visual production, theme customization, or asset workflow, this is closer to the work than a diagnostic CRO engagement.
The posts do not show a measured PDP conversion test, an ad-to-PDP continuity check, or a proof-and-objection framework.
The client story is about freelance pricing and client relationships, not CRO results; the Canva post reports what worked and what could not be found rather than a conversion outcome.
Choose Sarmin Sultana when implementation capacity or visual asset production is the constraint; choose Hayan Khan when the need is CRO strategy for product pages and navigation based on proof.
Hayan Khan's five LinkedIn posts discuss Shopify conversion-rate optimization, product pages, store navigation and AI-referred shopping traffic.
The posts are short-form commentary aimed at Shopify store owners and ecommerce operators.
The posts here carry no publication dates, so this page does not present a chronological account of Hayan Khan's work.
The business figures cited, including a supplement redesign reporting conversion moving from 1.8% to 5.8%, come from the posts themselves and are treated as reported results from a single described example, not as guaranteed outcomes.
Brand relationships are stated only where a brand is named, and no sponsorship, rate, employment or ownership arrangement is claimed.
Comparisons with other creators draw on LinkedIn posts from those creators published between April 2025 and October 2026.
No long-form articles, video, transcripts, audience demographics or client-side analytics are presented here, so this page describes Hayan Khan's stated approach and examples rather than verified client outcomes.