Regardless of whether you are selling digital or physical goods, product information plays a critical role in your customer’s purchase journey. You may succeed or fail in conveying your offering depending on the accuracy of your product data. Limited, inconsistent or inaccurate data typically leads ecommerce customers to lose trust, abandon their cart, or return items not matching their expectations. Almost 70% of shoppers give up on their purchases due to a lack of information or details on the product page. Enhancing the quality of your data is not only crucial for shopper conversion but it is also likely to improve customer loyalty over time.
As operations and product catalogs expand, managing complexities becomes overwhelming without the right technology. A state-of-the-art PIM solution, in-house or vendor-made, is a powerful tool to manage product data quality. But, if you are not there yet, or need to expand the capabilities of your existing PIM, you can take strategic action and move closer to customer expectations making the best out of product data you already have.
How can you improve the data quality of your ecommerce product portfolio? Here are five quick wins you can start working on today:
1. Use what you have to fill missing content
Product data quality is a challenge for many companies. This is because the data can be scattered across different platforms, languages, and formats. A good starting point for improvements is quickly repurposing available information for other channels and languages. Content from similar products, either on-site or public, can provide instant inspiration to fill out key missing pieces.
76% of online shoppers prefer to buy products in their native language, and 40% will never buy in other languages especially in France, Turkey and Germany.
The importance of having content available in your prospects’ preferred language cannot be emphasized enough. By elevating the shopping experience and overall confidence in the brand, a multilingual site significantly increases the likelihood of completing a purchase.
One way to ensure that you are creating great localized content is to use translation tools and resources. A variety of resources including Google Translate, Bing Translator, and other online translators allow you to instantly fill in missing channel and language content. 66% of international shoppers use online machine translation when making purchases, although they frequently struggle to accurately understand the content. Not being able to understand the available content creates doubts and reluctance to complete a purchase. By providing an accurate validated translation of your website content for a global audience, you promote understanding and credibility, which are two essential elements for the success of an e-commerce operation.
2. Speed up your data quality checks with AI
AI can help you speed up the process of data quality assessments through consistent automated checks. There are many algorithms readily available to evaluate both the content and visual assets. From basic controls on typos and missing fields to more sophisticated analyses such as similarity detection and category matching, the use cases are endless.
The starting point is coming up with a comprehensive set of business rules for data quality checks. It is critical that these rules are tailored to your business focusing on what matters and adds the most value. They can, then, be implemented on your product data through point solutions or by internal data scientists. Transforming this into a standard practice completely eliminates the need for manual work saving time and energy.
3. Identify and fix image quality issues
Visual asset quality is crucial for attracting the target audience’s attention and making lasting positive impressions. It goes without saying that high-quality product images create confidence in potential customers, which helps to increase brand recognition and recall.
Products need to be represented accurately and effectively. The right product images can help you increase sales by up to 30% at the point of sale. In order to display your products in the best way possible, there are some key considerations you need to keep in mind:
Use high-quality images. Images that are fuzzy and have a low resolution are not likely to attract customers’ attention. This is mostly because if you don’t have good product images, it will be difficult for shoppers to understand what a product genuinely looks like. The ability to zoom into specific areas comes in handy bringing the experience closer to in-store. Channel-specific customizations are also important to keep in mind where, especially FMCG products, benefit from mobile-ready images that emphasize key product attributes.
Use multiple images, from multiple angles. If you want your customers to envision how that black dress would look on a night out, or how that cozy sofa would fit in their living room, make sure you include several pictures of the same item in different settings. Customers find it easier to envision the product in real life after viewing the product from multiple angles. Incorporating 3D models and augmented reality capabilities also enhances the experience by increasing shopper interaction with products.
4. Align with high-performing similar products
Marketplaces suffer the most from data quality issues as they source products from numerous vendors. Without post-processing, the same product from different vendors ends up having different names, categories and specs. This makes it extremely difficult for users to find and compare alternatives.
Inconsistencies are not unique to marketplaces. They can occur any time data is sourced through different processes or from different people entering data into your system. 51% of businesses believe that product information inaccuracies/inconsistencies are their main barrier to stocking or obtaining a distributor to carry products.
Worse yet, 58% of businesses report returns or unhappy customers as a result of subpar product information.
Standardizing product data across your platform is likely to improve search performance, leading to more accurate results for consumers. Our Cyber Week research revealed “searching for specific products” to be the most disappointing part of the shopper experience with 45%. Misclassification of products and misalignment of content with search keywords are common culprits leaving customers frustrated and dissatisfied.
The fastest solution to this lies within your product portfolio. You can use your high-performing products as a reference point to improve categories, tags, names, and descriptions on the rest of your products. Moreover, if you are sourcing product data from multiple suppliers, it is vital to specify a standard format that will ensure consistency across data sources.
5. Enrich criteria for future data quality checks
One of the biggest challenges with product data quality is maintaining it over time. Many initiatives provide a quick fix but fail to create long-term impact. Data integrity is an ongoing process that requires constant vigilance and attention to detail.
If you’re using business rules to define your product data quality criteria, then the first thing to do is make sure you’re defining them correctly. From each quality check, new learnings and focus areas will emerge. It is important to incorporate those learnings and expand your business rules for future quality checks. Moreover, to ensure a high standard, it is crucial to set measurable goals (like improving accuracy) as well as aspirational ones (like making sure every piece of data has been verified). Linking product data quality to topline metrics such as revenue and customer satisfaction emphasizes impact throughout the organization and garners additional support. If you take the time to plan ahead and implement systems that will ensure future productivity, then product data quality issues will become less daunting over time.
Since more and more products are being sold online, providing accurate and thorough product information is becoming more and more critical. Many consumers resort to online shopping channels, even for offline purchases. High-quality product data provides your customers with access to all the information required to make an informed purchase decision.
The best way to improve your product data quality is by starting with the basics: consistent localized definitions and engaging imagery. As your company grows, it will become harder to maintain such consistency without a centralized management mechanism. Automation is also a critical asset at scale freeing up valuable bandwidth of product and category managers. Every business is unique, and quality checks should be smart enough to accommodate their unique needs.
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