Invest in high quality product data feed

Data qualityFeed managementEcommerce
By Yuval Ginor, Feb 03,2022

In order to stand out in the highly competitive world of ecommerce, sellers must invest in high quality product data feed. Poor quality product data most often leads to poor performance.

One of the main keys to retailers’ success in ecommerce is the quality of their product data feed. The competition in the online shopping world is fierce, and the Coronavirus pandemic only brought a sharp increase in online sales. This has spurred sellers to put more resources in their online store in order to stand out, make a name for themselves, and attract more shoppers.

Despite all their efforts, somehow most sellers ignore their product data feed, and fail to optimize it, even though it has a tremendous effect on the performance of the store and its overall shopping experience. This mainly stems from the fact that most sellers are unaware of how the quality of the product data feed impacts the performance of their listings. 

The thing a lot of sellers don’t realize is that the quality of the product data feed determines how the product will fare in searches. If the product data does not exactly match shoppers’ search queries, it will appear at the bottom of the search result page, if it appears at all. In other words, poor quality product data hurts the product's exposure to shoppers.  

The Significance of High Quality Product Data

Product data is the basis of every ad campaign. When the data is accurate, complete and uniform, it increases the chances that the products will appear in relevant searches, thus attracting more potential customers to the listing. This makes for a good and efficient shopping experience, which of course contributes to increase in conversion rates and overall sales. 

No matter what retail channel sellers operate through, whether ecommerce marketplace, social media or other channels, the main emphasis is on the shopping experience. Each channel has its own rules governing what product data every listing should include (product details such as category, brand and type), and failure to obey these rules may cause the listing to be rejected from the channel. 

Product Data Feed and Online Stores

The shopping flow in an online store is different from the ad campaign flow, which heavily relies on product data feeds.

  • Online Store Flow - a shopper entered an online store, knowing exactly what she is looking for. Using site navigation, she narrows the results and locates the product by selecting its relevant attributes. Finally, she picks the product she likes from a small group of relevant products. 
  • Ad Campaign Flow -  Another shopper, who has no idea where to find the product he is looking for, begins his journey with Google Shopping. He searches for certain keywords that describe what he is looking for, and the search engine brings back results whose product data most closely matches the search query. Browsing the results, he clicks the ad most relevant to him, which brings him to the listing. This type of flow accounts for 50% of all online purchases

In order to make the ad campaign flow efficient, the product data feed should be accurate, relevant and complete, so it matches most possible keywords and keyphrases searched by shoppers. On the other hand, if the product data is not accurate or complete, the product may not appear in relevant searches, or worse, it could completely disappear.  

High Quality Product Data Feed

As mentioned above, it is important that the product data feed be accurate and relevant, containing engaging product descriptions. The more accurate information the product data contains, the easier it is for shoppers to make an informed purchasing decision.  

As every channel has its own set of product data feed requirements, sellers must adjust their feeds to meet these requirements, or risk rejection. Product data such as titles, categories, images and other values, which in the past were optional, have become the mandatory basis of product data feed requirements.

Titles - titles are the first thing shoppers see, and this is what leads to clicks and conversions. Therefore, the product titles should provide accurate and relevant information that will encourage the shopper to click through. 

Comparing the titles of an online store listing and that of a product data feed, the difference is clear. While the title “PUMA Serve Pro Sneakers” will be sufficient for an online store title, the product data feed title should contain more information (such as gender, color and size, for instance “PUMA Men's Serve Pro Sneakers White All Sizes”.

Sellers who sell to different markets online should adjust some keywords to address phrasing variations. For example, sellers who sell flip-flops in Australia should add the keyword “thongs” to the title.
Colors - Color is usually one of the most important attributes of the products, no matter what it is. That is why it is crucial to include color information both as a value and in the title. While using unique or highly specific colors (such as tangerine orange) may seem like a good idea and a novelty, it only serves to make shoppers miss out on the listings, so keep it simple.
Images - Images are as important as titles, as they are one of the first things shoppers look for in a listing. Grainy or obviously photoshopped images will deter shoppers from clicking through, while high quality and accurate images will help build confidence, and entice shoppers to click through. 

Product Description - Product description is another important part of the listing, providing the majority of information. An informative and engaging description helps boost conversions and overall performance of products. 
Product Type - Product type helps shoppers understand what exactly the product is. Using attribute keywords in the title and description lets them know what they are buying. Using the example above, “Sneakers” lets the shoppers know exactly what the product is.

Categories - Creating a structured category taxonomy and placing each product in the relevant category makes navigation much more efficient and helps sellers locate the products much quicker.

Inventory - Sellers who offer real store pick-up must keep track of their inventory in every location, so they know where to direct the customers.
Global Trade Item Number (GTIN) - every mass produced product carries a GTIN. The GTIN appears in the barcode and helps pinpoint the exact product. 

The quality of the product data is dependent on the scope and quality of information provided at the source. The more accurate and complete the data, the better the products perform. The increased demand for product data helps make listings more relevant and improves the shopping experience. 

Omni-Channel Retail

After making sure their product data feed is optimized, sellers can start making the best of it. Omni-Channel retail is a good way to boost visibility while reaching new audiences.

Optimizing data for multichannel distribution is key. However, since each channel has its own rules and requirements regarding product data, sellers have to adjust their data feeds to each channel separately. This is a task that takes up a lot of time and effort. 

This is where Lisuto could help. Lisuto combines technology with deep ecommerce consumer product knowledge helping sellers optimize their product data and extract much more out of the online store. Using proprietary AI technology, Lisuto goes through the existing product information, tagging the data with marketplace specific navigational tags, making necessary corrections and completions, bringing the quality of the sellers' product data feed up to highest standard in terms of uniformity and completeness, making it perfectly optimized for each channel and for the user's eyes. 


In order to stand out in the highly competitive world of ecommerce, sellers must invest in high quality product data feed. Poor quality product data most often leads to poor performance. It is also important to continually optimize the product data and follow the requirements of the different channels to ensure product discovery across platforms.

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