According to Ventana Research, more than 80% of companies are not confident in their product data. Let that sink in—over 80%! Then, take a sigh of relief knowing that if you are struggling to efficiently manage your product data, you are not alone.
In 2019, we presented five foundations of reliable product data. Here’s a quick summary.
1. Product segmentation
Firms around the world with large and ever-expanding product portfolios have established internal processes and taxonomies to organize their data. Most of the data we see from clients is organized in Excel files with hundreds of columns of categories and millions of rows of unique product SKUs. Product segmentation is the first foundation to a well-managed product portfolio.
By segmenting and categorizing your products meticulously, you can save time, avoid duplication, enrich and manage edits to your data more easily, and feel more confident that you are in control of your product data—even when you are dealing with thousands and thousands of unique items.
If your company doesn’t have a product segmentation strategy, it’s time to establish one ASAP. It’s a necessity for a PIM platform implementation.
According to the author of Data Driven, Thomas C. Redmon, product data teams waste up to 50% of their time dealing with duplication errors. It can be easy to do, especially if multiple people are managing, editing, and moving product data in multiple static files within and across departments.
Why must you ensure you’re avoiding duplication?
- Avoids inaccuracy & confusion
- Avoids data loss
- Saves time
The cost of bad data is absolutely astounding. For most companies, it costs anywhere between 15-20% of their revenue. When downstream customers and end consumers are researching a product online, they need to see clear, consistent data. Consistency in data, such as making sure product categories are consistently named across digital platforms is critical to protecting user experience.
As a product data manger, you have to establish and protect consistency.
- Reduces redundancy
- Maintains clear data appropriately
- Establishes standards for future data loads
- And standards = accountability
When consumers can’t find enough information about a product, they will end their pursuit and look elsewhere. Shotfarm reports that 30% of shoppers have abandoned an online shopping cart due to poor product descriptions.
The scenario is easy to imagine—you’re searching for a new pair of pants but in a cruel twist of fate, you’ve discovered that you’re allergic to cotton. If the retail site you’re exploring doesn’t display the fiber content, and can’t tell you where the fabric is sourced, you’re going to jump ship and find a more reliable and trustworthy brand. For you, accepting incomplete or missing data isn’t an option.
Product data completeness improves data reliability, reduces returns, and reduces customer service complaints. It increases customer trust and satisfaction so don’t stop short when it comes to completing data for every single one of your product.
5. Marketing content
Accuracy, avoiding duplication, consistency, and completeness directly impacts the success of your sales and marketing. If you launch a new website but your product search experience and product detail pages are riddled with inconsistent terms, spelling errors, and missing data, you’re launching in vain. Your integrity of marketing content is arguably the most important factor to consider when you’re working to streamline your data. You must ensure that your organization can produce, manage, and syndicate data accurately.
Consider how your marketing is impacted.
- Product data drives SEO
- Marketing content sells product
- Accurate data empowers customers
- Cross-selling and related product suggestions rely on accurate, well segmented product data
- And, producing content across multiple channels can’t be delayed by product data errors and rework
Don’t wait to clean up your dirty data
The accurate, consistent, complete, and real-time management of your product data can make or break your next sale. Gather the right team members and formulate a sustainable and scalable strategy for your product data portfolio.