Re-thinking the online auction experience for 7m visitors

Project:  2-sided e-commerce experience
Role:  Lead product designer, Supply division

Catawiki is an online auction house. Think of eBay but if every item listed has been checked by an expert to ensure its quality, authenticity and value.

Naturally, having a human being manually check each item doesn't come easily – extremely complex operations and systems sit behind the scenes to make it happen.

With that complexity comes a lot of friction in different parts of the process, but also lots of potential to make things smoother more efficient.

In my time at Catawiki I worked on multiple different initiatives, and what follows is one of my favourites.

Starting with the humans

Catawiki employs hundreds of Experts who review items submitted to the platform by sellers, and depending on the type of object, they can each get through a hundred of more submissions per day.

It's also the Expert's job to correct inaccuracies in how an item has been described by a seller. These corrections can range from sorting typos to adjusting the estimated age of an item. We called them "Silent edits".

However, fairly often the Seller might disagree with the correction. Then these edits weren't so silent anymore, and could lead to disputes and frustrated Sellers – and not a great use of anyone's time.

Helping Sellers to provide better info

We figured if we could reduce these disputes we'd been doing our Experts a big favour by saving them time and stress, as well as making our Sellers a bit happier and less likely to end up in conflict with their Expert.

We knew that the item listing experience itself wasn't exactly helping set up Sellers for success. There were confusing UI elements, inconsistent and excessive options, poor management of expectations and more.

That seemed like a good place to start looking for improvements.

Simple solutions buried in a complex organisation

We knew our UI was old and increasingly showing the mounting technical and design debt, and our user testing had confirmed this was leading to issues with usability and accuracy.

At the same time, the way that Catawiki's category management worked was making things extra challenging. Each category manager had previously been allowed to set their own options for describing items, leading to inconsistencies like those below where each category asks about an item's condition differently.

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Finding solutions together

The impact of making changes to the submission flow ran far and wide, and so we knew we needed to involve different people from across the business in first understanding the problems and then in developing solutions.

We brought heads together by running different workshops online, first to simply listen, then to gather pain points in a more structured way, and later to capture and develop ideas and solutions.

One of the best ways I've found to help make progress on complex issues involving multiple different people and departments, is to find simple ways to involve everyone from the start – to understand problems together and and build solutions collaboratively.

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Using the Value Proposition Canvas to help capture pain points and relievers.

Crazy 8s to help bring ideas out of the different people involved.

Advanced prototyping

Many of the solutions to our problems lay in humble form fields – but these are only deceptively simple, and the success of them lies in small details and micro-interactions. In order to develop these successfully therefore, we needed to be able to use them in real time, with real data.

To do this we moved pretty quickly from wireframes and static UI designs into Framer, where we could use React to build functional prototypes that we could actually use, and importantly, test with customers.

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Impactful solutions in small details

User tests helped us build confidence in the new interactions, and importantly helped us to convince the numerous stakeholders that it was ok to go ahead and implement the new field types.

User tests helped us build confidence in the new interactions, and importantly helped us to convince the numerous stakeholders that it was ok to go ahead and implement the new field types.

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Some of the new fieldtypes we introduced

The changes included new visuals, copy and error feedback and modernised interactions

Measuring results

On a platform of this scale, any small movement in conversion up or down could mean a big financial impact, and so it was fundamental we monitor changes and work carefully to ensure any difference is indeed a result of the changes we introduced.

Working closely with product managers, front end engineers and data scientists, we were able to ascertain some small changes in metrics resulting from the revised UI.

Success had been defined at the start of the initiative as being measurable in terms of:

  • Ease
  • Accuracy
  • Efficiency

We were successful in two of them. Especially helpful was the reduction in the use of the 'other' field, when a customer can't find the relevant pre-defined value for their item and has to use the wild card. This makes our data messy and adds work for the Expert. A 14% reduction here was very significant.

  • Ease: +1,8% increase in fields filled in, and -14% use of the ‘other’ field
  • Accuracy: -1% reduction in edits required by Experts
  • Efficiency: +1.5% increase in lots rejected

The last one was tricky – we hadn't expected more rejected lots to result from this work, and it was difficult to theorise why this could be happening. Perhaps an increase in accuracy had led to the correct rejection of lots that might have otherwise made it though? The decision was taken to carry on monitoring this one. To be continued!

The ones that got away

In any project like this there are ideas that don't make the final cut, in this case largely because having solved the most problematic cases the team was soon pulled onto other more pressing challenges.

Here are a few of the field types that didn't make it!

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Date ranges in drop -downs were always a challenge, being different for every category of object.

Who can ever remember which is depth and which is width??

Condition ratings are also dependent on object type, so a visual device could help make sense of these for the less experienced.