eBay Price Guide

A trading card price tracking tool, leveraging data to build customer confidence.

Project Overview

Have you ever wondered how much your old Pokemon cards are worth?

I designed a scalable 0>1 experience that allows customers to view real-time market values of their trading cards on eBay for the first time.

ROLE

Product design lead working directly with UX Researcher, Product Manager, and Engineering team.

TIMELINE

2022 - 2023 including initial launch and iterations.

OUTCOMES

- 4x yearly revenue goal
- 40% Retention
- 500k> unique users

Problem Space

eBay is the world's biggest trading card marketplace with over $4 billion in annual trading card sales. However, people couldn't find the value of trading cards on eBay. This led to two problems:

1. Customer Problem

Customers didn't know how much their trading cards were worth on eBay. This led users to search for an "estimate" by digging through past eBay transactions, or by migrating to the competition.

2. Business problem

Competitors were integrating eBay sales data into their own marketplaces, and presenting in a much more digestible way to attract customers away from eBay.

Existing user workaround

Project Goal

We needed to provide customers reliable and accurate values for their trading cards on eBay. By presenting this data in a transparent and actionable way we're building trust by pulling back the curtain and allowing customers to buy and sell with confidence.

This will, in turn, lead to an increase in revenue and retention.

Initial user research

Since this was uncharted territory for the company, we began with user research to understand our customers and how to best approach designing this new tool.

I created three basic concepts to test with customers and get a better understanding of task flows, user goals, existing workarounds, all to form a strong base of knowledge of our customers.

Example Initial concepts tested

Key insights from research

We kicked off the project with a user research study testing high-level concepts. Here's what we learned:

🎯

Specific workflows

Customers relied on a search-based workflow, suggesting that our feature had to fit into their mental model.

⏱️

Customers search iteratively

Pricing data is only helpful when searches become specific, so the tool needs to be configurable.

🎢

Volatile market

Understanding trending prices is important as card prices fluctuate rapidly.

💾

Untrustworthy data

eBay data perceived as untrustworthy because of "fake listings" and miscategorized items.

Personsas

Flipper

Higher number of low value cards. Looks to make profit and likes to trade quickly and often.

Enthusiast

May have high or low value cards. Driven by a desire to purchase cards that fuel a feeling or completion or nostalgia.

Investor

Deals with mostly high value cards. Willing to hold onto cards for a long time to make the most profit.

Personsas

Flipper

Higher number of low value cards. Looks to make profit and likes to trade quickly and often.

Enthusiast

May have high or low value cards. Driven by a desire to purchase cards that fuel a feeling or completion or nostalgia.

Investor

Deals with mostly high value cards. Willing to hold onto cards for a long time to make the most profit.

A closer look at end point of broken UX

A piece of the journey

At the time, our team was building out an entire Collectibles-based ecosystem of products. Therefore, it was important to stay grounded in the entire customer journey, taking into account real world actions and motivations, and other eBay touchpoints while building out the Price Guide.

I did this by staying in constant communication with my design colleagues, and frequently sharing out work to stay in sync. Also, I created artifacts like the Golden Path user journey below were useful in staying aligned in design and review.

Final design

Search-based workflows

Customers told us that they were used to a Search-based workflow. So, working with partners on the Search team, I implemented an entry-point to a distinct Price Guide page directly from trading card search results.

Configurability

Customers can search for cards iteratively by either using the search bar at the top of the page, or by using the filters to account for professional grade, variation, and buying format. This allows them to configure their dataset how they want.

Show me the money

The Price Guide provides customers with an anchoring price metric based on eBay transaction data. Customers can view how this metric has trended over time to better understand market volatility.

Now, for the first time, customers can know how much their card is worth on eBay.

Building Trust

Customers were skeptical of eBay data. To build trust, customers can view the recently sold items that make up the data powering the pricing metrics. In addition, I later designed a feature that allows customers to manually remove listings they themselves deem as outliers.

Expanding across the ecosystem

The new price trend graph and value cluster components were designed to flex and scale across eBay. I aligned the component design with other design stakeholders, and then worked with the Design Systems to make them available for anyone to use.

Putting it all together

I made a fully functioning interactive prototype, working with a motion designer to create a demo video that highlights the entire experience so we could gain alignment, communicate functionality, and enhance understanding.

Outcomes

The eBay Price Guide launched in early 2022. For the first time ever, users could get a value of their trading cards on the eBay platform.

Revenue

4X of goal

Generated from viewing Price Guide

Retention

40%

Of users who return to use Price Guide

Usage

>500k

Buyers that have used Price Guide

Debrief

Our team had a debriefing session after launch. Team members expressed frustration over shifting executive priorities and technical issues being discovered late during the design process. This led to frustrating churn between design, engineering, and product teams.

Ultimately, we were able to get support for improving the experience after the Beta was launched. This is a credit in particular to my product partner who really championed our cause with senior product leadership.

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