Improving the online shopping experience with better data quality

Renovating my bathroom has shown that there is much room for improvement in e-commerce.  In my Master’s program we learn how to study and improve the customer’s experience.  It turns out that many frustrations of the online shopping experience are actually data quality issues that retailers could resolve:

Insufficient data:  There is one low-resolution photo of the white product on a white background.

Missing data:  There are 836 products and I want to filter for chrome finishes, but only 582 of them have data in the Metal field.

Non-standard data:  There are three different names for bronze in the Metal field, and six varieties of beige in the Colour field.

Ambiguous categories:  I want a cabinet that’s about 24 inches wide.  Do I filter for the 18″-24″ category, or 24″-30″?

No categories:  There’s no size filter, so I’m searching the product titles for “24 inches”.

Ambiguous definitions:  I want a 60-inch curtain rod.  The length measurement is sometimes in the Width field, and sometimes Depth.

Duplicative data:  My search results are cluttered with 12 colour variations on a product that I don’t want.

Of course, cleaning up the data and improving the product browser does not solve all the customer experience problems.  I was pretty surprised when the delivery person brought me an 84-pound fixture, then declared that he couldn’t take it upstairs to my second-floor apartment!

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