Walmart Marketplace Listing Quality: Fix Weak Items With AI

Open the Listing Quality dashboard in Seller Center, sort items by score and work the lowest scores that also get page views. Fix the component scoring under 60% first: content, price, shipping, stock or reviews. AI helps only with content: drafting titles, descriptions and key features that you then check against the product.

Walmart builds the score from five parts, and four of them cannot be fixed with better wording. That is the most common wasted afternoon: rewriting a description for an item whose real problem is a shipping promise of seven days or a price well above rivals. The list below goes component by component, starting where the effort pays most, and marks the single step in each where AI is worth using.

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What the score is made of

As of Walmart's guide updated in April 2026, Listing Quality measures item quality through five components, and you have both a catalogue-level score and an item-level score for each listing. The catalogue score is an average of the item scores, so a few very weak items pull it down visibly. Menu names and component names change from time to time, so treat the following as a map and check Seller Center for the current wording.

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Two exclusions are worth knowing before you panic about a low shipping score: items that weigh more than 50 pounds, or that are listed at $10 or less, are left out of the Shipping calculation. If a cheap accessory shows no shipping score, that is probably why.

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Step 1: Find the items worth fixing first

In Seller Center, open Listing Quality (it sits under the Growth area at the time of writing). The dashboard lists your items with their scores, and the "Improve individual items" section carries a "Fix issues" link per item. Walmart's guidance is to prioritise component scores between 0% and 59%, and to treat items marked Mid or High under the Impact column as the best opportunities.

Export or copy your list into a sheet and add three columns of your own: units sold last month, page views if shown, and gross margin per unit. A weak score matters when sales or views are there to be won. An illustrative catalogue of 120 items:

Spending the first week on the 14 tier-A items is worth more than spreading it across all 120. Write the date next to each item before you change it, so that the next export shows whether the work moved the score.

Step 2: Read each weak item's component breakdown

Select "Fix issues" on an item. The page shows the overall score and a breakdown by component. Note which of the five is lowest, because that decides the next step. Here is an illustrative reading of three tier-A items:

The bottle is the AI job. The mat needs a pricing decision, not better copy. The lamp has a promise problem and a stock problem, and copy will not touch either. This table is the point of the whole exercise: send each item to the right fix before anyone writes a word.

Step 3: Fix content quality, with AI doing the first draft

Content quality looks at the item name, description, key features and images. Walmart's product detail policy sets the rules the draft must meet. Paraphrasing its published requirements:

• Title: up to 150 characters, in proper capitalisation, with relevant values such as size or count. No all-capitals, no special characters, no promotional claims such as "best-selling", "top rated" or "free shipping", no retailer names, no URLs, no years unless the product type's content standards recommend them, and no repeated keywords.
• Description: one paragraph with a minimum of 150 words (the required length varies by product category). No bullet points or numbered lists, no emojis, no promotional claims, no authenticity claims unless approved, and no external links.
• Key features: three to ten, each up to 80 characters including spaces, as short phrases without HTML, special-character bullets or emojis.

Walmart also states that AI-generated content must be truthful and accurate and that you are responsible for reviewing and substantiating it before publication. That puts the checking step firmly with you, not the tool.

A prompt that bakes the rules in

Rewrite the Walmart Marketplace content for this item using ONLY the facts below.
Title: max 150 characters, proper capitalisation, include brand, product type, size or capacity and one key attribute. No promotional words, no special characters, no years.
Description: one paragraph, at least 150 words, no lists, no emojis, no claims that are not in the facts.
Key features: 6 items, each under 80 characters including spaces.
Then list every fact you used and mark anything in the current listing you could not support from the facts.

FACTS: brand "[brand]", 24 oz double-wall stainless steel bottle, dishwasher-safe lid only (body hand wash), BPA-free lid, fits most cup holders (tested in 4 cars), colours black, sage and white, weight 14 oz.
CURRENT TITLE: BEST Water Bottle 24oz!!! Free Shipping Hot Sale Stainless Steel Insulated

An illustrative reply gives the title "[Brand] Stainless Steel Water Bottle, 24 oz, Double-Wall, Black", six key features such as "Double-wall stainless steel body" and "Fits most car cup holders", and a description of about 160 words. Notice what it did to the old title: it dropped "BEST", the exclamation marks, "Free Shipping" and "Hot Sale", all of which the policy lists as prohibited, and it moved "24 oz" next to the product type. The "mark anything you could not support" line also caught "Insulated" in the old title, because the facts you gave it never said how long the bottle holds temperature. You either add a measured fact or leave the claim out.

Check the draft against the physical bottle: the capacity, the colours offered, the lid detail. Do not let the draft carry a claim you did not supply, such as "keeps drinks cold for 24 hours". If you want to go deeper on how titles and attributes are drafted and loaded, the companion tutorial on drafting Walmart titles and attributes with AI covers that stage.

Images: the part AI should not decide

Walmart's image guide asks for JPEG, JPG, PNG or BMP files (no GIFs) in RGB, 5 MB or less, 2200 by 2200 pixels with a minimum of 1500 by 1500 for zoom, square, with a plain white background (255/255/255 RGB) on the main image, and it recommends at least four images per listing. Images must match the product name and key attributes, show the product or its features, and must not repeat. It also says AI-generated content has to be accurate and truthful, so use editing tools for cleanup and white backgrounds, never to invent a feature or a colour. A quick check list per image: right colour, right quantity (a 2-pack shown as a 2-pack), no text claiming "best" or "sale", no duplicates.

Step 4: Fix many items at once with the Bulk Attribute Editor

For a batch of items, Walmart's Bulk Attribute Editor works from the Listing Quality dashboard. In outline: choose Create spreadsheet, filter by Customer Favorites, Walmart Fulfillment Services items, Attributes with issues or Refine by item, pick the product type so its attributes appear, and create the file. Then open the Activity Feed, find the file under the Downloads tab, download it, edit the values, return to the dashboard and choose Upload spreadsheet from the Bulk edit via spreadsheet dropdown.

This is the right place for AI when 30 items need the same kind of fix. Paste the spreadsheet rows, not the whole file, into your assistant in groups of ten, and ask it to fill only blank or flagged cells using facts you supply from your own product data. An illustrative rule set:

Here are 10 rows from the bulk edit file with columns: item name, key feature 1-6, description, and the facts column from our product sheet. Fill or rewrite only cells flagged "needs fix". Obey: title max 150 characters, key features max 80 characters, description one paragraph of 150+ words, no promotional words. If the facts column lacks a fact, leave the cell blank and write "NEED FACT: [what is missing]" in the notes column. Return a table with the same columns.

The "NEED FACT" instruction turns gaps into a visible to-do list instead of invented text. Keep the original file untouched and work on a copy, and upload a small batch of five first to see whether the system accepts the changes before sending all thirty. As Walmart's guide notes, a score may not update straight away, and newly published offers can take up to a week to show in the dashboard.

One limit to know about: some attributes can only be changed by the brand owner or authorised resellers. If an edit will not save, it may belong to the brand rather than to you. If you resell other makers' products, expect some content to be outside your control.

Step 5: Shipping and stock, where copy does nothing

Walmart's fix list for Shipping says a 100% score comes from offering fast and free shipping, three days or less, through its Simplified Shipping Settings or through Walmart Fulfillment Services, and staying stocked. In practice this is an operations choice with a cost: shorter promises need stock close to buyers and carriers that meet the time. Work it out before changing it. Illustrative figures for the desk lamp: it sells at $34.99, costs $14 to buy, and ships by the cheapest ground service at about $7.50 on average. Offering free, faster shipping might raise the shipping cost by $3 an order. If the shipping score gains 70 points and conversion rises, the $3 may pay for itself; if the margin per order is only $6, it may not. The lamp's 62% stock score is a different fix: 62% means the item was unavailable for a share of the last seven days, so the answer is a reorder point, not a rewrite. A tutorial on forecasting stock and reordering with AI helps there.

Step 6: Price competitiveness is a decision, not a draft

Walmart compares your price with similar products on external marketplaces, and its fix list points to the Repricer or the Price Incentives programme. Before using either, do the sum on the yoga mat: it sells at $29.99 with a landed cost of $12.40, fees you can read in your own settlement report and shipping of $5.20. A rival price of $24.99 means matching would leave you around $7 a unit before fees. Decide a floor price you will not go below, set it in the Repricer if you use it, and accept a lower score on items where matching would lose money. A score is a means to visibility, not a reason to sell at a loss. AI can help build the margin table, but the choice to match belongs to you.

Step 7: Reviews, slowly and honestly

Ratings and reviews depend on the number of reviews and the average rating. Walmart's fix list names the Review Accelerator and Review Syndication programmes for eligible items. Check eligibility in Seller Center before planning around them. Never write, buy or offer reviews for money; Walmart's product detail policy explicitly prohibits AI content that fabricates reviews or endorsements. What AI can legitimately do is read your existing one- and two-star reviews and group the causes, so a product fix replaces another round of copy. A mat with 60 reviews where 14 mention "slips on hardwood" needs a design or description change that states the surface it suits, not a better headline.

A fix log that proves the work, filled in

Keep one log line per change. Without it, a month later nobody can say which edit raised which score, and the same dead ends get repeated. An illustrative log for the three items above:

Ask the AI to turn the finished log into a three-line summary for the month: which fix type moved scores most, which did nothing, which items still need a human decision. It will do this well because you gave it figures. It will do it badly if you gave it only a feeling that things improved.

A description before and after, with the problems marked

Descriptions are the part sellers most often get wrong when they let a tool run. Here is an illustrative before, shortened:

Before: "Top rated 24oz bottle, perfect gift! Great for gym, hiking, office. Features: leak proof, keeps cold 24 hours, BPA free. Buy now while stocks last. Amazon customers love it."

The problems, by the policy list: "Top rated" and "Buy now while stocks last" are promotional; "Amazon customers" names another retailer; the feature list uses bullet-style fragments in a description that must be one paragraph; "keeps cold 24 hours" and "leak proof" are performance claims with no source; and it is far under 150 words. The repaired version, written from facts you can prove, says what the bottle is made of, its size, which parts go in the dishwasher, what fits in a car cup holder, the colours and the weight, in plain sentences of one paragraph, adding the care routine and what the box contains until it reaches the length required. Where the original claimed 24 hours of cold, either test it and state the measured figure with the test conditions, or take the claim out. Never let a prompt invent the number.

Ask the AI to count the words and list every claim, then check the count yourself. Models often overstate how long their own text is. If the category in Seller Center shows a different minimum, follow that one.

A weekly routine that keeps scores from sliding

1. Monday, 20 minutes: open Listing Quality, note any item that fell under 60% in any component, and add it to the fix sheet with the date.
2. Tuesday, 45 minutes: run AI drafts for the content fixes only, with the facts column from your product sheet. Review every draft against the item.
3. Wednesday, 15 minutes: submit changes, individually for tier A and by spreadsheet for batches.
4. Friday, 20 minutes: check stock and shipping flags, and review pricing on any items marked low on price competitiveness.
5. Monthly, 30 minutes: compare the catalogue score with the fix log. Did the items you changed improve? Which kind of fix moved the score most?

That is about two hours a week, and it shrinks as the backlog clears. A related risk is drift across channels: if you also sell elsewhere, three different marketplaces' rules mean the same copy cannot always be pasted into each, and what passes on one may be rejected on another. Our wider guidance on AI listing mistakes that mislead buyers describes the mistakes that cost returns, which hurt reviews and therefore the score.

A listing fix that backfired

An illustrative case: a seller bulk-rewrote 40 titles to add search words and uploaded them. Twelve were rejected for repeated keywords and "premium quality", two of the accepted ones named a colour the item did not come in, and returns rose. The fix list became: no keyword that is not an attribute of the item, one primary term once per title, a person reads a sample of every batch against the physical item, and a batch of five goes first. A fast tool plus no checking step is how a catalogue gets worse.

How to tell whether the work paid off

Three signals, in order of reliability. First, sales and conversion of the tier-A items over the four weeks after the change against the four weeks before; keep the figures in your sheet. Second, the component score that was low, now higher. Third, the catalogue-level score, which moves slowly and tells you least about any one change. If a content fix lifted the score and sales did not move, the problem sits elsewhere, perhaps price or the first image. Remember that scores lag, sales seasons shift and one big order can mislead, so look at a month, not a day. If you would like help setting up this routine for a larger catalogue, an AI implementation consultation is what that covers.

Listing Quality questions from sellers

Why does a component show N/A for some of my items?

Walmart's Listing Quality guide lists this question, so check there for the current answer. One documented cause is an exclusion: items over 50 pounds or listed at $10 or less are left out of the Shipping calculation. Newly published offers can also take up to a week to appear. Do not chase an N/A: focus on the components that show a score.

How long until my score changes after I fix an item?

Walmart's guides say the score may not update immediately and that newly published offers can take up to a week to appear in the dashboard. After a content change, wait several days before judging it, and log the date you made each change so you can match it to the score later.

Can AI raise my score by itself?

AI can draft titles, descriptions and key features faster, which helps only the Content quality component. Price, shipping speed, stock and reviews need business decisions, not copy. Walmart also says you remain responsible for AI-generated content being accurate, so read every draft against the real product before you submit it.

Should I fix every weak item?

No. Start with items that sell or get page views and have a low score, because an improvement shows up in revenue. Items with no views and no sales may deserve a rethink, a price change or removal from your catalogue instead of an hour of copy work.

Further reads

• Walmart OTIF Fines: Build a Dispute Pack From Delivery Records — Fines for late or incomplete deliveries and how to dispute them.
• Walmart Marketplace vs Amazon: Which Should a Small Seller Add Next? — Whether Walmart is the right marketplace to add next.
• How Small Amazon Sellers Use AI for Listings and Reviews — How Amazon sellers use AI on listings and reviews.
• Bulk Product Description Generator: From CSV Rows to Unique Copy — Bulk descriptions from CSV rows, with checks.
• Online Shop AI Mistakes That Hurt Trust and Conversions — Where AI use in a shop hurts trust and conversion.
• AI Tools and AI Development: The Complete 2026 Guide — the AI hub, including every tutorial in the AI-for-business series.

Sources: Walmart Marketplace Learn guides on the Listing Quality dashboard, fixing Listing Quality issues, the Bulk Attribute Editor, the product detail page policy and image requirements. Report names and menu paths can change, so check Seller Center.