People have long been able to search the internet for images. But using images to search the internet? Well that’s a much more recent phenomenon. 

For one thing, creating algorithms and code capable of completing such a complicated task is incredibly difficult. Not to mention the fact that image files are non-standardised; that competing with the search engine giants (indeed Google itself offers a reverse image search option) is extremely daunting; and that the tech start-up market is one of the most competitive in the world.

One app company however, Snap Fashion, has taken up this challenge with gusto. With a unique and unusual set of skills – namely coding and a genuine interest in fashion – the company’s founder and CEO, Jenny Griffiths, found herself in the perfect position to create a reverse image search specifically aimed at the fashion industry.

Cleverly allowing users to search an extensive database of hundreds of thousands of products from over 150 top UK retailers – including John Lewis, French Connection, Topshop and Reiss – Snap Fashion generates a list of images similar to the original used for the search – effectively enabling users to search for clothes and outfits via photos they’ve either taken themselves or found elsewhere.

The growing success of Snap Fashion – which has received countless positive reviews and various awards – can be attributed to Jenny herself (her talents and her vision); the popularity of the app model; and, importantly, the decision to tailor a general product (reverse image searching) to a specific market (the fashion industry).

This raises an interesting question: are there any other potential uses for reverse image searching?

We think so. In fact any consumer market in which the product range is so diverse that individual products are not immediately identifiable may benefit from a similar product.

Can you think of any good applications for reverse image searching? Let us know.