My Role
Product Designer
Team
Product Manager
2 Software Developers
Data Scientist
Timeline & Status
4 weeks
Launched in September 2022
Overview
Mobile Premier League (MPL) is a fantasy gaming startup based out of India. I interned with the Marketplace team of Striker, an advanced fantasy game for power users.
Problem Statement
Striker Marketplace was experiencing poor transaction success rate and lacked buyer engagement due to the difficulty in making offers on multiple cards despite active sellers.
Outcome
As the lead designer, I worked with cross-functional partners to identify the core problem, brainstormed solutions and owned end-to-end design of the mobile experience. The launch of this feature met with an outstanding public sentiment from the community and led to increase in successful transaction rate by 49%.
HIGHLIGHTS
An intuitive way for users to place a single offer on multiple cards in order to increase the transaction success rate.
First Time User Experience Journey
Video
Placing a “Collection Offer”
Video
CONTEXT
Mobile Premier League launches Striker
Players win real cash prizes by playing on Striker
The Indian fantasy gaming industry is worth $24 billion and growing at 14% CAGR. Mobile Premier League (MPL) is second largest player in the market.
In order to expand its market share, MPL launched Striker as an advanced fantasy game for power users. Initially, I mapped down the gameplay for a user in Striker.
Striker Gameplay
Diagram
DISCOVERY
The project started with an observation
Marketplace is highly active because…
Buyers are trying to grab cards of their favorite players
Sellers are trying to sell their cards to make money
OBSERVATION
The product team noticed a poor transaction success rate despite users repetitive attempts to buy/sell cards.
TEAM DISCUSSION
Initial troubleshooting with product and engineering
Struggles with connecting the buyer & seller
We had an initial discussion with the team to understand the market dynamics and find reasons behind the poor transaction success rate.
The team understood that the marketplace is not able to connect the right buyer with the right seller leading to poor transaction success rate. Engineering team believed building better AI / ML models could increase the marketplace efficiency.
A marketplace transaction
Diagram
STAKEHOLDER INTERVIEWS
Looking beneath the surface
Understanding marketplace for buyers & sellers
As a first step, I understood the working of the marketplace for a buyer and seller with some help from the Product Manager.
I explored the buying and selling experience for a user on Striker marketplace.
Existing Buyer and Seller experience
Diagram
Evaluating adoption rate
In collaboration with our data scientist, we evaluated adoption of each one of the trading mechanism that led to us a key insight.
DATA ANALYSIS
Buyers were not purchasing cards using “Buy Now” or "Make an offer” even when sellers were actively selling cards.
USER INTERVIEWS
UXR led to a new project direction
Broken “Make an offer” experience
Conducted user interviews and synthesized user insights to identify pain points in the buying process. The experience of making offers on multiple cards is the biggest pain point for users.
The team agreed that we should dedicate our resources in improving the core buying experience.
User pain points in the “Buying experience”
Diagram
VISION & GOAL
An opportunity to craft a better experience
VISION
We aim to boost buyer engagement on the marketplace by improving the experience of making offers on multiple cards from different sellers
So how do we improve our key metrics?
Increase the transaction success rate
Increase total number of transactions
HOW MIGHT WE?
What if we can place one offer on multiple cards?
Building out the User Journey
I sketched out the user journey of placing a singular offer on multiple cards and figured out other important flows like editing & deleting an offer or knowing more about the collection offer.
User Journey for Collection Offer
Diagram
DESIGN
Imagining Collection Offer V1
Enhanced version of “Make an Offer”
In order to improve the user experience of "making an offer", we envisioned the idea of a collection offer. We thought, "What if the user can place a single offer on multiple cards of their desired player?"
V1 Collection Offer User Flow
Image
How did we solve the user problems?
Avoids wastage of time & effort
Single offer on all the filtered cards avoids duplicate effort and wastage of time to place offers on multiple cards.
Minimal balance on hold
When a single offer is placed, the balance of that specific offer is locked, allowing for the more funds to be used on trading other cards.
No confusion in choosing the cards
Users can filter cards based on minimum XP & HP and apply an offer on the filtered search which streamlined the process of choosing cards.
Prevents duplicate trades
Once the trade is executed, the collection offer is shifted to completed orders avoiding any duplicate trades.
USER TESTING
Collecting some user feedback
4+ user testing sessions later...
When I shared the initial design ideas with the stakeholders, they expressed the need for prompt user testing in order to gather feedback from the users. This shift in their perspective was a positive development.
We distributed the prototype to several users within the office and collected valuable feedback. The feedback we received is summarized below;
Before
Users were confused between “Buy” and “Buy Any” Tab and could not tell the difference between them.
After
We removed the tab structure and added a clear CTA saying “Make offer on all cards” which helped declutter the surface.
Before
Users felt anxious going through a long flow in popup mode, as they could accidentally click outside the popup and loose their progress.
After
By introducing a new surface for the flow, we created a more focused experience for the user, consolidating all the essential information into one clear interface.
Before
Users struggled to find the right price for a collection offer. They needed assistance and were confused on how to make the decision.
After
We added recent sales column to help users decide their offer price based on recent trades of different XP & HP cards on the marketplace.
Before
Some users expressed concerns about receiving a card after the deadline of entering a fantasy contest.
After
We added an expiry input box for users to place time bound collection offers.
FINAL SOLUTION
Designing for different lifecycles
First time user experience (FTUE)
In our user testing sessions, the users took time to understand the difference between “Make an Offer” & “Collection Offer”.
A FTUE flow explained the value proposition to first time users in three simple steps and was monitored for efficacy post launch for any drop in the funnel.
First Time User Experience
Image
The steady state surface
The collection offer surface helps the users to place one offer on multiple cards along with other requirements like offer price discovery, editing / deleting offers, and knowing more about the collection offer.
Collection offer features and user flows
Image
Other screens in the user flow
It was important to design entire user flows with error states, edge cases, and impact of the feature on other surfaces for a smooth developer handoff.
Other user flow screens and surfaces
Image
IMPACT & LEARNINGS
Some key takeaways
Business impact
The introduction of the "Collection Offer" feature received an exceptional response from the Striker community.
It not only facilitated progress in key business metrics but also made a substantial contribution towards achieving the year-end target trade volume of $100K within a mere three months.
23% to 72%
Jump in successful transaction rate
53%
Increase in total no. of transactions
It was a life changing experience
Working in a fast-paced and high-growth environment provided me with valuable exposure to rapid product development and innovation in building 0 to 1 products.
Importance of user research
Small user research initiatives have a significant impact on project direction, helping us understand if we are solving for the right problems.
Convincing stakeholders
Building trust with stakeholders necessitates dedicated effort. Rather than simply telling them, showcasing relevant examples and data can significantly aid in achieving alignment and fostering trust.
Power of 80:20 rule
I've come to appreciate how putting just 20 percent of the effort into fixing core user problems can result in an enormous 80 percent improvement in user experience and business metrics.
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