Better inputs.
Useful output.

Review the attached brand brief, product specifications, customer reviews and competitor pages. Identify claims this Shopify store can substantiate that competitors cannot easily copy. Separate: verified product facts, customer-observed benefits, unsupported marketing claims and open questions. Produce a positioning matrix and ten search or AI-answer topics built only from verified evidence.

Segment this Shopify catalogue into: discovery products, comparison products, replacement products, replenishment products, gift products and low-search products. Explain the evidence for each classification, flag ambiguous items and recommend the SEO/GEO page, internal-link and content treatment for each cohort. Return a table that preserves handle or SKU so the plan can be implemented.

Turn the attached audit findings into a 90-day Shopify SEO and GEO roadmap. Score each task for commercial impact, reach, confidence, effort, dependency and reversibility. Group work into days 1–30, 31–60 and 61–90. Name the owner type, acceptance test and success signal for every task. Reject vague tasks such as ‘improve SEO’ and do not promise rankings.

Using customer-support transcripts, reviews, on-site search and Search Console queries, cluster the language customers use before purchase. For each cluster, identify intent, funnel stage, current best page, content gap and recommended canonical owner. Flag clusters where two pages compete for the same job. Quote source phrases exactly and redact personal information.

Analyze the attached crawl and Search Console indexing export by Shopify template: product, collection, article, page, search, tag, parameter and market URL. Calculate useful-index ratios where the data allows. Identify duplicate, excluded, orphaned, soft-404 and low-value cohorts. Recommend rules and tests by template, not a list of isolated URLs. Do not treat every excluded URL as an error.

Review the attached URL sample with rendered canonical tags, status codes, internal links and sitemap presence. Identify canonical contradictions, chains, cross-market mistakes and pages that canonicalize away unique value. Return a decision for each pattern: keep, canonicalize, redirect, noindex, 404/410 or investigate. Explain the customer and crawl consequence.

Given the attached collection filters, URL patterns, query data and inventory counts, design a faceted-navigation index policy for this Shopify store. Select only stable combinations with distinct demand, sufficient products and useful content. Define crawl rules, canonical behavior, internal-link rules, empty-state behavior and monitoring. List combinations that must stay unindexed and why.

Compare the attached before-and-after crawls for a Shopify theme release. Report changes in status codes, titles, canonicals, robots directives, structured data, headings, internal links, rendered product content, image loading and Core Web Vitals proxies. Classify each change as intended, risk, regression or needs human review. Produce a release gate with pass/fail evidence.

Using the old-site URL inventory and the new Shopify URL list, propose one-to-one redirect targets based on intent and content equivalence. Never default unmatched URLs to the homepage. Flag high-value URLs without a true replacement, redirect chains, parameter traps and content that should be recreated. Return source, destination, rationale and confidence.

Create an implementation brief for the Shopify collection [COLLECTION]. Use the attached products and query evidence. Include primary buying job, eligible products, inclusion rules, title and heading direction, 120–180 words of useful introductory guidance, filter priorities, comparison facts, internal links, FAQs with evidence requirements and claims to avoid. Do not keyword-stuff or invent product attributes.

Review the attached collection list, copy, product overlap, traffic and query data. Identify duplicate or cannibalizing collections. Recommend keep, merge, reposition, redirect or retire for each. For retained collections, define a distinct audience, buying job, assortment rule and internal-link source. Preserve valuable URLs and call out decisions needing merchandising input.

Using product attributes, support questions and on-site search terms, propose the filter system for [COLLECTION]. Rank filters by decision value, not database availability. Define normalized labels, value order, missing-data issues, mobile behavior and which combinations—if any—deserve indexable landing pages. Include a data-cleanup list.

Map how users and crawlers should reach [COLLECTION] and its products. Use the attached navigation, breadcrumbs, related collections, articles and priority products. Recommend anchor text and placement for meaningful links, identify orphaned or overlinked pages, and produce a before/after link map. Use normal anchor links; do not depend on site search.

Design rules for collection pages when product count falls, all items sell out or a seasonal range closes. Cover indexation, visible messaging, alternatives, internal links, redirects and reactivation. Use the attached replenishment calendar and historic query value. Return deterministic rules the merchandising team can follow.

Using the attached product specification, support questions, review themes and approved claims, create a Shopify product-content brief. Include a one-sentence definition, who it is for, who it is not for, specifications, variants, compatibility, use steps, care, delivery, returns, five comparisons, FAQs and structured-data inputs. Mark every missing fact as UNKNOWN. Never infer a claim.

Compare [PRODUCT A] and [PRODUCT B] using only the attached verified facts. Build a table covering audience, specifications, strengths, limitations, compatibility, price basis, availability and best-fit scenarios. State when there is no meaningful difference. List missing information and produce a neutral recommendation tree. Do not use review sentiment as a product fact.

Compare the attached rendered product page, Product structured data and Merchant Center feed row. Identify mismatches in URL, identifier, title, variant, image, price, currency, availability, shipping, return policy and review data. Prioritize errors that can mislead customers or disqualify merchant listings. Return exact source-of-truth and owner for each field.

Analyze the attached product reviews. Group recurring praise, objections, fit issues, usage problems and expectation gaps. Quantify themes only when the sample supports it. Recommend product-page clarifications, FAQs, images or instructions that address the themes. Separate reviewer opinion from verified product facts and exclude personal data.

Create a product photography and media shot list for [PRODUCT] based on the attached specifications and customer questions. Include hero, scale, detail, material, dimensions, variants, use, packaging and limitation shots. For each frame, state the question it answers, required props, crop variants and factual alt-text direction. Do not put promotional claims in alt text.

Using the attached answer-engine exports for the fixed prompt set, analyze brand mentions, position, sentiment, cited sources, product accuracy and competitor overlap. Separate observation from inference. Identify incorrect facts, missing source pages and citation opportunities. Produce a prioritized action list tied to pages or external sources; do not claim causation from one run.

Design a stable GEO measurement set for this Shopify store. Use the attached customer questions, catalogue and markets. Create prompts across category discovery, product comparison, compatibility, trust, local availability and post-purchase use. For each prompt, define market, audience, expected evidence, relevant products, success classification and why the question matters commercially. Avoid prompts that merely ask for the brand by name.

Audit the attached page for answer-engine usefulness. Identify the central question, directly supported answer, named entities, definitions, comparisons, source quality, update signals and missing caveats. Rewrite only the sections that are vague or unsupported. Keep the brand voice and do not add invented statistics, fake quotations or FAQ markup for invisible content.

For each attached AI answer and cited competitor source, identify what evidence the source provides: definition, data, comparison, authority, freshness, first-party detail or accessibility. Compare that with our best page. Recommend content, entity or external-authority work that closes the factual gap. Do not recommend copying the source or chasing a citation without customer value.

Create a fact-consistency matrix for [PRODUCT] across the Shopify page, structured data, feed, help center, marketplace listings and approved press material. Flag conflicts and stale facts, select a source of truth and propose an update sequence. Include price and availability only as timestamped observations.

Cluster the attached support questions by buying stage, product, urgency and reusable answer. For each cluster, recommend the best destination: product page, collection, comparison, guide, policy, help article or no public page. Score by frequency, revenue relevance, risk and evidence readiness. Draft titles only after assigning a canonical owner.

Evaluate the attached article using its Search Console queries, engagement, internal links and current product facts. Identify intent mismatch, stale sections, weak evidence, competing URLs and missing next steps. Produce a section-level keep/update/merge/remove plan, a new outline and internal-link changes. Preserve useful passages and URL equity.

Using the attached first-party dataset, propose an editorial study that is useful to Shopify merchants. Define a narrow research question, inclusion criteria, cleaning steps, limitations, calculations, charts, expert review and reproducibility notes. Identify what may be published safely and what must remain private. Do not produce conclusions until the data passes validation.

Based on the attached original resource and audience, define the types of publishers, experts, communities and partner pages that would genuinely benefit from it. Produce qualification criteria, personalized angles and reasons to exclude a prospect. Do not invent contact details, publication history or relationships. Prioritize relevance over list size.

Create an editorial standard for Shopify comparison pages. Define evidence sources, fact timestamps, comparison dimensions, conflict disclosures, update cadence, language to avoid and how to handle unavailable pricing. Include a reusable table structure and reviewer checklist. The standard must prevent fabricated tests and unfair claims.

Review the attached crawl of all market URLs. Validate self-referencing canonicals, reciprocal hreflang, language-region codes, x-default, sitemap inclusion, status codes and internal links. Identify auto-redirect or rendering behavior that could block crawlers. Return issue patterns by market and a representative test URL for each.

Localize the attached collection page for [MARKET] and [LANGUAGE]. Preserve verified global product facts, then adapt terminology, units, season, delivery, returns, availability and examples using the attached market brief. Flag legal or cultural questions for a local reviewer. Do not translate unsupported claims or assume local demand.

Evaluate subfolders, subdomains and country domains for this Shopify Markets expansion. Use the attached operational, brand, legal, language and authority constraints. Compare implementation effort, governance, shared authority, localization needs and migration risk. Recommend one approach with prerequisites and reasons the other options were rejected.

Using the attached market landing-page and query exports, find cases where users land on the wrong country or language version. Check hreflang, canonicals, internal links, translated titles, availability and redirect behavior. Classify technical versus content causes and provide a market-by-market correction plan.

Create a localization QA checklist for Shopify product, collection and policy pages in [MARKET]. Cover language quality, local terminology, currency, units, tax, delivery, returns, assortment, claims, metadata, structured data, links and hreflang. Separate automated checks from native-speaker review and legal review.

Analyze the attached Search Console export by query and landing page. Group rows into brand, category, product, comparison, informational and irrelevant demand. Identify high-impression weak-CTR pages, positions with realistic upside, cannibalization and queries with no suitable page. Weight recommendations by commercial fit and inventory, not impressions alone.

Design two connected scorecards for this Shopify store. SEO should cover crawl/index quality, search visibility, qualified sessions and commercial cohorts. GEO should cover a fixed prompt set, mentions, citations, answer accuracy and qualified referrals. Define metric formula, source, cadence, owner, limitations and decisions each metric supports. Do not create a blended vanity score.

Investigate the attached organic traffic decline. Compare dates, page cohorts, queries, countries, devices, indexation, releases, inventory and tracking changes. Separate demand change, ranking change, CTR change, deindexation, migration, outage and measurement failure. Produce evidence for and against each hypothesis and the next test needed.

Using the attached analytics paths and ecommerce events, evaluate how guides and comparisons contribute before purchase. Define eligible entrances and assists, remove internal and consent-related distortions where possible, compare cohorts and note attribution limits. Recommend a reporting view that does not claim causal lift from observational paths.

Create a 30-minute weekly operating review for Shopify SEO and GEO. Use the attached dashboards and work queue. Specify pre-read, five decision questions, thresholds for investigation, owners, actions and what should not be discussed weekly. Keep long-term performance, incidents and experiments distinct.