Product data is the information that describes the features, benefits, and specifications of a product or service. It is essential for creating effective marketing campaigns, providing accurate customer service, and ensuring compliance with regulations. However, many businesses struggle with managing and maintaining their product data, which can lead to costly consequences. In this blog post, we will explore some of the common problems caused by bad product data and how to avoid them.

Lost Sales and Revenue

One of the most obvious impacts of bad product data is the loss of sales and revenue. Customers rely on product data to make informed purchase decisions, and if they encounter inaccurate, incomplete, or inconsistent information, they may lose trust in your brand and switch to a competitor. According to a study by Oracle, 86% of consumers said that they would be unlikely or very unlikely to make a repeat purchase from a vendor that provided inaccurate product information. Moreover, 65% of consumers said that they had returned products because of inaccurate product information, resulting in additional costs for the business.

Damaged Reputation and Customer Satisfaction

Another consequence of bad product data is the damage to your reputation and customer satisfaction. Customers expect to receive the products or services that match the description they saw online or in-store, and if they don't, they may feel deceived or disappointed. This can lead to negative reviews, complaints, and word-of-mouth, which can harm your brand image and loyalty. According to a survey by Shotfarm, 78% of consumers said that they trust online reviews as much as personal recommendations, and 88% said that they would be less likely to buy from a company that has negative reviews.

Increased Operational Costs and Risks

Bad product data can also increase your operational costs and risks. For example, if you have duplicate, outdated, or conflicting product data across different systems or channels, you may waste time and resources on correcting errors, reconciling discrepancies, and updating information manually. This can also increase the risk of human error, data breaches, and non-compliance with regulations. According to a report by Gartner, poor data quality costs organizations an average of $15 million per year.

How to Improve Your Product Data Quality

The good news is that you can improve your product data quality by following some best practices. Here are some tips to help you get started:

• Define clear and consistent standards for your product data, such as naming conventions, formats, categories, attributes, values, and units.
• Implement a centralized system for managing your product data across different sources, channels, and platforms. This will help you ensure data accuracy, completeness, consistency, and security.
• Use automation tools to validate, enrich, transform, and synchronize your product data. This will help you reduce manual errors, save time and resources, and enhance data quality.
• Monitor and measure your product data quality regularly using key performance indicators (KPIs), such as completeness rate, accuracy rate, consistency rate, and timeliness rate.
• Solicit feedback from your customers, partners, and stakeholders on your product data quality and use it to identify areas for improvement.

By improving your product data quality, you can boost your sales and revenue, improve your reputation and customer satisfaction, and reduce your operational costs and risks. If you need help with managing your product data quality, contact us today. We are experts in product data management (PDM) solutions that can help you achieve your business goals.