New research from Storyblok, in collaboration with FT Longitude (part of The Financial Times), uncovers the true cost of content debt: content that is outdated, poorly structured, not optimized for search or AI discovery, and difficult to update and publish efficiently.
According to a survey of organizations with at least $1 billion in annual global revenue, content debt is costing retail enterprises $381.3 million on average, based on spend devoted to fixing it and revenue at risk from it.
AI search made a bad problem even worse
Content debt has always been buried in Google searches, but companies ignored it because they didn’t feel the impact. Now that AI is using that outdated content in its answers, many brands are either being misrepresented or left out entirely, explained Storyblok.
The business impact of content debt is significant for retail companies:
- 5.5% – Average annual revenue at risk from content debt
- $4.5 million – Average amount spent fixing content debt (33.4% of total content spend)
- 93.6 – Average hours spent each week maintaining existing content
Retail executives realize they have a content problem
After decades of letting brand inconsistencies spread online, executives understand that their bad content habits have to change now:
- 85% say improving the quality, structure, and governance of their content would deliver measurable business value for their organization
- 78% say their organization carries more digital content than it can realistically keep accurate, relevant, and up to date
- 69% say outdated or inconsistent content is making it harder for customers to find, trust, or act on their information
- 68% say the lack of visibility they have of their content is a compliance risk for their organization
- 60% say poor content quality or structure is weakening their visibility in search and AI-driven discovery
Content debt is a technical problem that can be solved
The report said 68% of retail executives agree that improving their content strategy is more of a technical challenge than a creative one, which suggests that teams are being held back by their CMS and tech stack, not their abilities.
Dominik Angerer, CEO and Co-Founder of Storyblok, said: “For decades, publishing as much content as possible, hoping it ranks in search, and letting the content and platforms decay has been a business strategy. It felt good at the time, just like loading up a credit card with a bunch of impulsive purchases and not thinking about the true cost of the debt. But now AI has exposed the scope of the problem and it can’t be ignored anymore. The bill is past due.
“In the same way that consumers need to develop a plan to pay off debt, retail brands need a content debt recovery plan that helps them eliminate the content and tech debt that is a burden to their business. The fact that they’re already spending so much time and money maintaining content and it isn’t decreasing the overall effects of content debt in a meaningful way proves that what they’re doing isn’t working.
“The retail companies that audit all of their content, implement new ways of managing it, and measure the results will have confidence that their content is accurate, optimized, visible, and driving revenue in AI and every channel that’s important to them.”
In an interview with Retail Insider, Angerer talked about the issue.
Question: What does “content debt” look like for retailers in practical terms, and why has it become a more significant problem as AI increasingly influences product discovery and purchasing?
Answer: For retailers, content debt often looks harmless. It’s an old product page that’s still live, a pricing page from a promotion that ended months ago, a return policy that was updated on the main site but never changed on an old campaign page, a link where the product is sold out. It’s duplicate product descriptions, or different versions of the same information sitting in different parts of the business.
Most of this happens simply because retail moves fast. Products get discontinued, promotions end, new campaigns launch, people move teams and the old content doesn’t always get cleaned up behind them. Our research found 78% of retail executives say they’re carrying more digital content than they can realistically keep accurate and up to date, and 85% say improving the quality, structure, and governance of that content would deliver measurable business value. That’s a big gap between knowing there’s a problem and having fixed it.
AI is what turns this from a background issue into an active one. Customers can now run into old information without ever visiting the page where it lives. If someone asks an AI tool about a return policy, they might get an answer pulled from information the retailer changed years ago. Content that used to be easy for a customer to miss can now show up right when they’re deciding what to buy. For retailers, that turns an old content problem into a customer and revenue problem.
Q: Your research found that 5.5% of revenue is at risk for global retail organizations with more than $1 billion in revenue. What are the biggest sources of that potential revenue loss, and how should retailers assess their own exposure?
A: The biggest risk sits around anything that directly affects a customer’s decision. When that information is outdated or inconsistent, it costs a sale, causes a return, or damages trust. Retailers are already spending $4.5 million a year on average trying to fix this, and putting in nearly 94 hours a week maintaining existing content, and the revenue impact is still there. That tells you the issue isn’t effort, it’s where the effort is going.
AI makes this harder to control because customers no longer have to visit a retailer’s website to get that information. They can ask an AI tool and get an answer based on content the retailer didn’t realize was still out there.
The first step is figuring out what you actually have. Audit product and policy content, including older pages and anything sitting outside the main site, then check that against what AI tools are actually surfacing to customers. That comparison is what tells retailers where the real gaps are and what to prioritize first.
Q: With 78% of organizations saying they have more digital content than they can realistically keep accurate and up to date, what should retailers prioritize when deciding which content to fix, update or eliminate?
A: Start with what matters most to the customer and the business so pricing, availability, product details, sizing, shipping, returns, and warranties. Getting those wrong directly affects a purchase. Then look at anything that creates compliance, safety, or brand risk. After that, retailers can work through older campaigns, discontinued products, and duplicate content.
The goal isn’t to keep every page alive. It’s to have confidence in the content that matters, knowing what exists, knowing what’s accurate, and knowing who’s responsible for it. That’s where the audit becomes the foundation. Once you’ve identified the problem, you need ownership and a review process, or the same debt just builds back up.
Q: How is the rise of AI-driven shopping and agentic commerce changing the way retailers need to structure and manage product information compared with traditional search and e-commerce?
A: Traditional ecommerce was built around a shopper landing on a product page and making the decision themselves. With AI-driven shopping, more of that process happens through a system comparing products, prices, availability, and policies on the shopper’s behalf.
That puts a much bigger premium on product information being accurate, structured, and consistent. If pricing says one thing in one place and something different somewhere else, the AI system has to decide which version is right, and the retailer may not control which one wins.
Interestingly, 68% of retail executives already say this is more of a technical challenge than a creative one, and it’s worth noting that the retailers who feel most confident in their content are the ones most likely to agree with that. This isn’t because tooling was the cause of their success, but because they’ve already done the harder governance work, and now technology is just helping them continue to get it right.
So retailers need to think beyond individual product pages and build a reliable source of truth behind them, one that both a human and an AI system can trust equally.
Q: What specific investments or changes to their content infrastructure should retailers be making now to ensure their products remain accurate, discoverable and competitive as AI agents become a larger part of the shopping journey?
A: Start with an audit. Retailers need a clear picture of what content they have, where it lives, what’s accurate, what’s outdated, and who owns it. You can’t have confidence in your content if you don’t know what’s actually out there.
Then put a process around it. Products, promotions, and policies change constantly, so there needs to be a clear owner and a clear trigger for reviewing, updating, or removing content when something changes.
Retail scored well overall in our research, ranking the highest of any industry we surveyed in our Content Confidence Index at 76.8, and it’s still carrying $381.3 million in average content debt. That tells you even strong performers can’t out-create their way past this and it is a challenge that has to be managed on an ongoing basis.
This is where the CMS and underlying content infrastructure matter. Giving retailers a way to manage structured product information consistently across their website, marketplaces, and new AI-driven channels, instead of maintaining different versions for each one.
But it is important to call out that while technology supports this, it doesn’t replace the ownership and process work. A retailer that buys new infrastructure before deciding who’s responsible for keeping product information accurate will just build the same mess, faster.
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