Imagine browsing an online shop for a new mobile phone. The technical specifications look promising, but the battery life is not mentioned. The pictures show two different colours. And the release date? Confusingly, it is listed as both 2024 and 1970. Would you still buy it? Probably not.
Messy, incomplete product data doesn’t just slow down your internal processes - it also puts customers off, increases return rate and damages trust in your brand. Fixing these issues manually is an endless headache, but there is a faster and smarter way.
No more second-guessing if a listing is complete or accurate - AI does the heavy lifting so your customers always get the right information and you can focus on selling instead of fixing errors like missing details or even spelling mistakes.
How Incomplete or Incorrect Product Data Affects Customers
Rich product content – detailed, accurate, and engaging product data that helps customers choose the right products – is essential for a smooth shopping experience.
But if the product data is incomplete, inconsistent or incorrect, it can cause problems for your business in the following ways.
1. Loss of Trust and Confidence
Customers rely on detailed product descriptions, specifications and images to make an informed purchasing decision. If a product listing lacks important details such as dimensions, materials or compatibility, customers may doubt the credibility of the seller and look for another supplier.
Once trust has been lost, it is difficult to rebuild it.
2. Higher Return Rates and Customer Frustration
Incorrect product information leads to unfulfilled expectations. An incorrect colour, an inaccurate size or a misleading list of features can result in customers receiving something other than what they expected.
This not only increases return rates but also frustrates buyers, making them less likely to purchase again. For instance, in 2022, 56% of U.S. online shoppers reported returning items because the product didn’t match its description, and in Germany, 47% of consumers said better product details would reduce their returns.
3. Negative Reviews and Brand Reputation Damage
Dissatisfied customers are quick to share their experiences via negative reviews and social media. A product with misleading descriptions or missing details can trigger complaints, reduce credibility and affect future sales.
Online reputation is crucial - a single bad review can put off potential buyers. According to a 2022 report by ReviewTrackers, 94% of consumers say a bad review has convinced them to avoid a business.
4. Reduced Searchability and Missed Sales Opportunities
Incomplete product data has an impact on SEO and internal search results. Without the right keywords, attributes, or tags, products may not appear in search results, reducing visibility and leading to missed sales. Customers who can’t quickly find what they need will leave the website in favour of the competition.
5. Inconsistent Omnichannel Experience
Customers expect a consistent experience, whether they shop online, in-store or on marketplaces. If the product information is different on the various platforms, e.g. different prices, descriptions or availability, this leads to confusion and reduces the likelihood of a purchase. Consistency is the key to conversion.
AI-Driven Workflow for Product Data Optimisation
PIM systems are designed to tackle product data issues, and with AI-powered features, they can do an even better job.
Bluestone PIM, together with its AI Analyst, allows you to identify and resolve product data inconsistencies efficiently. Instead of spending countless hours manually reviewing product descriptions and attributes, AI can analyse your data in bulk, flag missing or incorrect information and even suggest or apply corrections.
The dashboard provides a clear overview of the products that need improvements. A single click on a highlighted product reveals specific issues, such as missing e-commerce descriptions, inaccurate colour information or outdated publication years.
Here's what the AI Analyst looks like:
How Does AI Analyst Work?
AI Analyst takes the guesswork out by scanning your catalogue for inconsistencies, suggesting fixes, and even applying corrections with your approval.
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Establish quality standards: Establish product data quality standards by selecting ideal products to serve as the basis for your analysis.
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Select products: Select one or more products for a detailed analysis.
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Select attributes: Determine specific attributes such as the product name, description or size for the analysis and let the AI analyst do the rest.
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Review and apply: Review the analysis report, evaluate the suggestions with reliability scores, and apply the corrections to multiple products effortlessly.
See this process in action in our video:
AI-Powered Product Enrichment
Beyond basic corrections, AI in PIM can not only help you write product descriptions but also improve upon them.
AI Enrich (product enrichment feature in PIM) analyses product attributes and existing labels to create optimised, search-friendly content that increases visibility and conversion rates.
AI automatically creates and refines descriptions to ensure accuracy, relevance, and consistency – all while reducing manual labour.
For example:
- Original description: "Smartphone with 128 GB memory"
- AI-enhanced description: "Powerful smartphone with 128 GB storage, high-resolution display and long-lasting battery - perfect for streaming and gaming."
By integrating AI-driven PIM solutions, companies can ensure that their product data is accurate, complete and optimised across all platforms. The result? Greater efficiency, fewer errors and a seamless omnichannel shopping experience.
Discover the cost difference between manual product data enrichment and AI-driven enrichment.
Number of products requiring description
Average Word Count per Product Description
Manual/Human Copywriting Cost per Word
Your Current Cost Estimation:
$ for human copywriting of words to create product descriptions.
You are just one step away from discovering how much you can save with AI in PIM!
The AI calculates costs based on the number of input and output tokens, with each token representing approximately four characters. The cost per token varies depending on the model used.
Basic GPT Model: Less powerful, lower cost, produces simpler or less detailed responses, and might be faster due to smaller size or fewer computations.
Advanced AI Model: More powerful, higher cost, produces higher-quality and more detailed responses, but could be slower because of increased computational complexity.
Pricing for AI models often decreases with each new release, making advanced processing more cost-effective over time.
Bluestone PIM AI Enrich estimation
Fix Product Data Gaps with AI-Powered PIM
Disorganised product data frustrates customers, increases the number of returns and damages trust in your brand. Missing specifications, inaccurate colours and outdated details can put off potential buyers. Fixing these issues manually is time-consuming, but with AI-powered PIM, you can automate product data management, recognise errors immediately and make corrections effortlessly.
If you want to increase your efficiency and reduce errors in product data management, now is the time to do it. Fill out the form below, and our team will reach out to give you a walkthrough of our AI-powered PIM solution.
