At a glance
Count of catalogue products with missing or empty description field. The single most common SEO and conversion gap on BigCommerce stores. Missing descriptions hurt organic ranking, depress on-site conversion, and break marketplace syndication when feeds expect description text.
Calculation
Calculated automatically from your BigCommerce data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
A US homewares brand on BigCommerce Pro with 4,820 active SKUs, snapshot at 12 Apr 26.
Effectively missing share: 9.7% (320 short + 150 empty), above the 5% alert threshold.
What’s interesting:
- 9.7% effectively-missing is action territory. That’s 470 products either invisible or dramatically underweighted in organic search. Even at modest assumptions (each product = 5 organic visits/month at full strength, 0 at missing), that’s 2,350 missed organic visits/month. At 2-3% conversion and 4-6k/month of missed revenue, $48-72k/year.
- The 23.7% “adequate” bucket is the silent killer. These products have enough description to satisfy basic feed requirements but not enough to rank competitively. Expanding from 30 to 100 words typically lifts organic rank position 3-8 places per product, the second-largest opportunity after fixing the missing ones.
- Marketplace feed rejection is the immediate cost. Amazon’s product feed requires 100+ characters of description; Google Shopping requires 50+. The 150 empty + 320 short products are likely being filtered out of those feeds entirely. Pair with the marketplace seller dashboard’s “feed errors” report.
- The chronic-missing pattern usually concentrates in 2-3 brands or categories. A brand with 80 SKUs onboarded by one merchandiser in a hurry typically has 60-70% of those SKUs lacking descriptions. Drilling by
brandorcategorymakes the fix-list shorter and more actionable. - AI-assisted bulk drafting is now realistic. GPT-4-class models can draft a 100-word description per product in 5-10 seconds at 10-20 of API cost; the human reviewer step adds 4-8 hours of editing time.
- Sort missing/short descriptions by
revenueRankorviewCount. Fix the top 50 products first; they generate 60-80% of the SEO impact. - Use AI for first drafts, human for finalisation. Tools like Jasper, Copy.ai, or direct GPT-4 API calls can produce passable first drafts; human editing for brand voice, accuracy, and SEO keyword targeting is essential.
- Set a description-length minimum at the catalogue layer. BC supports product-validation rules; configure a “description must be 80+ characters” rule to prevent regression. Won’t fix existing gaps but prevents new ones.
- Add a category-level template for brands or categories where structured copy makes sense (specs, dimensions, materials). Reduces blank-page paralysis for the merchandising team.
- Run a quarterly catalogue audit. New SKUs get added in batches; the description gap accumulates if no one is watching. A quarterly review of “products added in the last 90 days with missing descriptions” catches the regression early.
Sibling cards merchants should reference together
Reconciling against the vendor’s own dashboard
Where to look in BigCommerce Control Panel: Catalogue → Products supports a column-level filter for description length (advanced search). Bulk-export to CSV and filter empty / short rows for the manual count. There is no native “products missing description” tile. For SEO-side validation, Storefront → Page builder shows individual product pages; running a Google Search Console crawl error report shows the downstream effect. Why our number may legitimately differ from BC catalogue export:
Cross-connector reconciliation:
Same-metric documentation cross-reference:
shopify.missing_descriptions(planned)adobe_commerce.missing_descriptions(planned)
Known limitations / merchant FAQs
My count says 470 products have missing descriptions, but my BC export says 150, why? We treat “trivially short” descriptions (under 30 characters) as effectively missing. BC’s empty-string filter only catches truly empty. The 320-product gap is products with descriptions like “Available in 5 colours” or “New in” that are technically non-empty but functionally useless for SEO and feed compliance. How long should a product description be? Practical minimum 80-100 words for SEO value; sweet spot 150-300 words for most categories. Beyond 500 words you hit diminishing returns. The right length is whatever conveys the product’s selling points + answers obvious questions + targets the keyword variations the customer searches. Generic templates that just repeat the product title don’t help. Should I write descriptions for every variant? No, write at the product level. BC’s product-vs-variant model is parent-child; the parent description is what serves SEO and feeds. Variants need short, distinguishing descriptions (“Black”, “Large”) only. Is AI-generated copy good enough for SEO? Yes for first drafts, no for final. AI-generated copy passes SEO basics but lacks brand voice and accuracy of specific product details. The right pattern: AI generates a 100-word first draft, human editor (10-30 minutes per product) adds brand voice, accurate dimensions, materials, and use cases. The combined cost is 10-15% of writing from scratch and 90% of the quality. How do missing descriptions affect Google Shopping feeds? Significantly. Google Shopping requiresdescription of at least 50 characters; below that the product is rejected from the feed. A store with 9.7% missing/short descriptions is missing those products from Google Shopping entirely.
Does Amazon penalise missing descriptions?
Indirectly via the Listing Quality Score. Amazon expects 100+ characters of description plus 5 feature bullets; under-populated listings rank lower in Amazon search and may be temporarily delisted from category browse. The cost is meaningful for Amazon Channel Manager users.
Should I worry about descriptions on disabled products?
Lower priority. Disabled products aren’t visible to customers or feeds; they only matter if you re-enable later. Most stores treat disabled-product description gaps as “fix when re-enabling”.
My B2B portal doesn’t need fancy descriptions, why care?
For B2B-only stores, you’re right, sparse descriptions are fine if your buyers are spec-list-driven. For B2B + retail multi-channel stores, the same SKUs appear on consumer-facing channels where descriptions matter. The shared-catalogue problem is what makes this card relevant for hybrid stores.
Can I auto-generate descriptions from my PIM?
Yes if your PIM has the data. Most BC stores integrate with a PIM (Akeneo, Plytix, Salsify) that holds richer product metadata; the PIM-to-BC sync can include description generation from structured fields. Set up the integration once; descriptions populate automatically going forward.
My most recent count shows 470 missing, last week was 320, what changed?
Almost certainly a bulk SKU upload without description data. Common pattern: merchandising team imports a CSV from a supplier; the CSV has SKU, price, image, but no description. The 150 new products land in the catalogue with empty descriptions. Configure a pre-import validation rule to catch this at import time rather than after the fact.