If you manage an eCommerce catalog, you already know the feeling: thousands of SKUs, the same manufacturer blurbs everyone else has, and pages that don’t attract or convert the way they should. This guide explains why that happens, what “good” looks like now, why scaling high‑quality content is hard, and practical steps to fix it—without blowing up your budget.
The history of product content
In the early days of eCommerce, many product pages had only a title and maybe a one photo. In the early days, to fill the gaps at scale, syndication services—such as CNET Content Solutions—licensed standardized copy and specs to retailers. Over time, manufacturers realized it was in their interest to supply copy and images directly, and global data networks such as GS1’s Global Data Synchronisation Network (GDSN) emerged to distribute product data automatically. Today, manufacturer‑supplied content remains the default for many eCommerce sites because it’s easy and inexpensive to publish.
What’s wrong with manufacturer‑supplied content?
Two big issues hold it back:
Duplicate content limits discoverability. Search engines consolidate near‑identical pages by selecting a representative (canonical) URL. In practice, this can mean the manufacturer’s page or a dominant retailer is chosen, while other duplicates are filtered, never making page one. It’s not a “penalty,” but it does limit your visibility unless you add original value and differentiation.
Typically, manufacturer content doesn’t address the buyer’s real questions. Shoppers want to understand risks as well as benefits, real‑world usage details, compatibility, and social proof. Brand‑authored copy tends to be one‑sided and less trusted than reviews, on‑page Q&A, and balanced explanations—exactly what customers (and AI‑powered search features) look for.
Ideal product content
High‑performing product pages do a few things consistently well:
- Original, buyer‑focused copy that explains features and turns them into benefits and outcomes.
- Structured data (e.g., Schema.org) so Search can understand the page and show rich results.
- Clear specs and comparison‑ready attributes, not just marketing prose.
- Multiple high‑quality images (and video when available) that answer common visual questions (scale, ports, textures, what’s in the box).
- User‑generated content: reviews and on‑page Q&A to surface the voice of the customer.
- Coverage of common decision friction: compatibility, sizing, installation, safety, maintenance, and return policies.
- Search‑informed phrasing: incorporate terms buyers actually use without keyword stuffing.
This mix helps with traditional SEO and with emerging AI‑led experiences that summarize answers while citing helpful, trustworthy sources.
Cost & scaling challenges
If “ideal” sounds expensive, that’s because high‑quality content has historically required research, writing, editing, and QA across thousands of SKUs. Freelance and agency rate cards commonly price writing by the word or project; typical published ranges for professional writers span from low double‑digit cents per word to well over a dollar per word, depending on the complexity. Multiply that by a catalog of tens of thousands of products, and the budget adds up quickly.
It was not unusual to spend $70 per page before 2022. The introduction of AI more than halved these costs. AI wrote the first draft, and humans ensured consistency and accuracy. The return on content spend (ROCS) was still strong even at these rates, and yet many felt that at this price, original content was a risky investment.
How to solve your product content problem
Today, AI can do much more for a lot less. Think of AI as the engine inside a governed workflow, not a one‑click writer. Here’s a pragmatic blueprint you can run now:
- Centralize truth and context: Ingest manufacturer feeds when available. This should include manuals and existing PDPs into a single source of truth. Map attributes to your taxonomy so AI has reliable facts to pull from.
- Deep Research: For some products, the challenge of matching specifications to specific products requires a robust range of matching techniques. This might include searching for images, attempting to identify original equipment manufacturers, reading engineering change orders, and other product clues.
- Competitive: Search-optimized product descriptions have to be better than alternatives in order to maximize visibility. Creating a superset of content is just as important as getting all the details correct.
- Keep it fresh: Schedule periodic re‑crawls of competitor pages and vendor feeds. When specs, policies, or buyer questions change, update the page—and its schema—automatically.
Platforms like DynEcom operationalize this approach for large catalogs by comparing your PDPs to competing listings, identifying content gaps, drafting original copy in your voice, and monitoring changes over time so pages improve continuously. DynEcom is also able to solve the UGC challenge of falling review rates by leveraging reviews across the internet.
Manufacturer copy is a reasonable starting point, but not a growth strategy. Original, structured, review‑rich PDPs win more impressions and convert more buyers, and AI makes that level of quality achievable at scale when paired with the right workflow.
Sources & further reading
Google Search Central — Canonicalization & consolidating duplicates (how Google chooses a representative URL). https://developers.google.com/search/docs/crawling-indexing/consolidate-duplicate-urls
Google Search Central — Product structured data (requirements and guidelines). https://developers.google.com/search/docs/appearance/structured-data/product
Google Search Central — FAQ structured data & August 2023 changes (FAQ rich results limitations). https://developers.google.com/search/blog/2023/08/howto-faq-changes
Google Search Central — AI features and your website (AI Overviews / AI Mode). https://developers.google.com/search/docs/appearance/ai-features
Google Search Central — Guidance on AI‑generated content. https://developers.google.com/search/blog/2023/02/google-search-and-ai-content
GS1 — Global Data Synchronisation Network (GDSN) overview. https://www.gs1.org/services/gdsn
1WorldSync — Press release on acquisition of CNET Content Solutions (Dec 2020). https://1worldsync.com/about-us/news-press/1worldsync-completes-acquisition-of-cnet-content-solutions/
Nielsen — Trust in Advertising research: trust in reviews and recommendations. https://www.nielsen.com/insights/2021/beyond-martech-building-trust-with-consumers-and-engaging-where-sentiment-is-high/
BrightLocal — Local Consumer Review Survey 2024 (review behavior and trust trends). https://www.brightlocal.com/research/local-consumer-review-survey-2024/