Richard Turner
Mar 30, 2022
Cleansing Data, Classification, Duplicate Parts

3 Common Data Structure Mistakes That Hurt Ecommerce Sales

The primary benefit of shopping online is convenience, right? Shoppers visit your B2B or B2C online store rather than a bricks-and-mortar shop because they enjoy the convenience of shopping on their own time, without having to talk with a salesperson.

 

If you want to attract and retain online shoppers, you must focus on the customer experience—and that means focusing on your data. 

 

Your ecommerce website is only as good as your product data. Ecommerce retailers who fail to structure their data correctly create online stores that are poorly optimized for on-site search. They create inconsistent product descriptions that puzzle and frustrate store visitors. And they drive visitors into the arms of their online competitors.

 

If you want to deliver an outstanding customer experience with your online store, start with your data—and avoid these common missteps.

 

Mistake 1: Using an Inconsistent Data Model

Your priority with your ecommerce store is nailing down your data model. This model consists of a schema for products, attribute category profiles, search-engine optimized product descriptions, and enhanced images.

 

You can easily spot an ecommerce retailer with an inconsistent data model:

  • Products are not grouped into logical categories or classes.
  • Product categories are inconsistent across the entire product catalog.
  • The product taxonomy is inconsistent. Multiple products are missing key product attributes (size, weight, color, product type, price, materials, design features).
  • Product descriptions are generic, lacking necessary keywords and specific attributes.

Online stores that lack a consistent data model infuriate shoppers. They make their sites harder to navigate and their products more difficult to find. This hurts the customer experience, hinders sales, and damages your customer satisfaction scores.

 

The Solution

The remedy for an inconsistent data model is to use a tool that cleanses, enriches and validates your product data before you import it into your product information management (PIM) system. With this tool, you create a classification structure that aligns with your products. Then, you classify and enrich your products with key attribute data, optimizing them for your ecommerce platform.


Ideally, you’ll complete this step before you upload any data to your PIM system. Changing your data model after you’ve already invested time, resources and effort classifying and enriching your product data can be a complex undertaking, though it’s possible with the help of a data expert trained in multiple PIM systems.

 

Mistake 2: Inconsistent Images

You already know that good product images can make or break a sale. But what about the quality and consistency of your images? 

 

If your product images are inconsistent in their quality, size, resolution and aspect ratio, your sales will suffer. You will also attract fewer store visitors, and hinder your customer experience.

 

The Solution

Before you place any images next to any product descriptions, define your image parameters. Document the criteria that each image must meet before it appears in your store. 

 

These criteria include:

  • Image size
  • Image aspect ratio
  • Image resolution
  • Image background
  • Image thumbnail
  • Number of images
  • Watermarks (present or not, at your discretion)

Mistake 3: Poor Data Governance

Data quality tends to degrade over time as merchants add products, remove products, and tweak product SKUs, descriptions, attributes and images. These changes typically translate over time into product duplicates, back-office inefficiencies, and wasted time and resources.

 

If you sell a t-shirt, for example, does the product come from your supplier or the manufacturer? Is there a “middleman” from whom you purchase? You need to gather these details from the appropriate party. Without this level of detail, you're not putting complete descriptions online.

 

The Solution

With the right ecommerce product management tool, you identify which of your duplicate products is most profitable, and work slowly with your vendors to gradually eliminate duplicate orders.

 

Another benefit of a good ecommerce product management tool is that it helps you boost your profitability. If you have five suppliers for the one t-shirt, for example, an ecommerce product management tool identifies which supplier offers the lowest price, or the best terms.

 

But that’s only the start. Effective data governance reduces the impact of duplicate items that have the same or similar attributions. Your data governance program should include a process where people trained in the taxonomy review each new product classification. Having a proper workflow to make sure new products are reviewed and approved by the right people will drive long-term data consistency. 

 

There should also be a validation step to make sure the critical fields for a new product are completed correctly.

 

This type of data governance prevents your team from creating new products without meeting the specified parameters for all attributions—this means no more products being added to your PIM without each detail needed for your ecommerce website.

 

How to Improve Your Ecommerce Presence With the Data Experts

Your success as an ecommerce merchant depends on your data. You must make your products stand out from your competitors with optimized product data, an organized schema, and consistent images. 


If you need help in this area, trust the ecommerce data experts at Convergence Data with your data upgrade and ecommerce website success. We transform ecommerce product data from inconsistent and incomplete to organized and efficient. Let’s talk.