No bet left behind.

Bet matching on Wagr.

Bet matching on Wagr.

Bet matching on Wagr.

Context

Context

Wagr is a startup that sought to combine sports betting with consumer social. It was a platform where friends could bet against one another on their favorite games in a way that was friendly, safe, and fun.

Bet matching was a feature that sought to combat high churn rates by expanding the network of who could receive bets on the platform.


As the designer for this project, I spearheaded the user research, detailed user flows, and crafted hi-fi prototypes.

Wagr is a startup that sought to combine sports betting with consumer social. It was a platform where friends could bet against one another on their favorite games in a way that was friendly, safe, and fun.

Bet matching was a feature that sought to combat high churn rates by expanding the network of who could receive bets on the platform.


As the designer for this project, I spearheaded the user research, detailed user flows, and crafted hi-fi prototypes.

Role

Role

Product Design, Prototyping

Product Design, Prototyping

Tools

Tools

Figma, Origami Studio

Figma, Origami Studio

Timeline

Timeline

April 2022 - August 2022

April 2022 - August 2022

How to not leave behind bets.

How to not leave behind bets.

How to not leave behind bets.

A how-to guide you can trust.

A how-to guide you can trust.

A how-to guide you can trust.

Step 0: Context

Step 0: Context

What differs Wagr from other sports betting platforms

What differs Wagr from other sports betting platforms

What differs Wagr from other sports betting platforms

Wagr allows users to know who is on the other side of their bets by shifting the focus from betting against the "house" to betting against people in a user's social network

Wagr allows users to know who is on the other side of their bets by shifting the focus from betting against the "house" to betting against people in a user's social network

Wagr allows users to know who is on the other side of their bets by shifting the focus from betting against the "house" to betting against people in a user's social network

Step 1: Identify the problem

Step 1: Identify the problem

Step 1: Identify the problem

The first step to changing is to be honest with yourself and the situation that you are in. Here is when I did that.

The first step to changing is to be honest with yourself and the situation that you are in. Here is when I did that.

The first step to changing is to be honest with yourself and the situation that you are in. Here is when I did that.

Wagr was witnessing high churn rates right after users invited their friends to take on the other side

Wagr was witnessing high churn rates right after users invited their friends to take on the other side

Wagr was witnessing high churn rates right after users invited their friends to take on the other side

Users would determine who took their bets through direct invites. However, most bets were ignored or unaccepted. When users experienced their bets not going through their full lifecycle, they were more likely to leave the platform.

Users would determine who took their bets through direct invites. However, most bets were ignored or unaccepted. When users experienced their bets not going through their full lifecycle, they were more likely to leave the platform.

Users would determine who took their bets through direct invites. However, most bets were ignored or unaccepted. When users experienced their bets not going through their full lifecycle, they were more likely to leave the platform.

Step 2: Research, reflect, rework

Step 2: Research, reflect, rework

Step 2: Research, reflect, rework

I conducted user research and tested a couple hypothesis as to why bets were not being taken.

I conducted user research and tested a couple hypothesis as to why bets were not being taken.

I conducted user research and tested a couple hypothesis as to why bets were not being taken.

Why were users turning down bets?

Why were users turning down bets?

Why were users turning down bets?

I had initially designed Wagr so that users would invite their friends to take on the opposing side of the bet. However, I realized that most users in the same friend groups enjoy the same sports teams and are unlikely to bet on their rivals.

I had initially designed Wagr so that users would invite their friends to take on the opposing side of the bet. However, I realized that most users in the same friend groups enjoy the same sports teams and are unlikely to bet on their rivals.

I had initially designed Wagr so that users would invite their friends to take on the opposing side of the bet. However, I realized that most users in the same friend groups enjoy the same sports teams and are unlikely to bet on their rivals.

Was the price not right?

Was the price not right?

Was the price not right?

Were users rejecting bets because they were too expensive?

Were users rejecting bets because they were too expensive?

Were users rejecting bets because they were too expensive?

Verdict: No

Verdict: No

Verdict: No

Users were accepting bets of all price ranges

Users were accepting bets of all price ranges

Users were accepting bets of all price ranges

Stranger danger?

Stranger danger?

Stranger danger?

Were users rejecting bets from people they didn't know?

Were users rejecting bets from people they didn't know?

Were users rejecting bets from people they didn't know?

Verdict: No

Verdict: No

Verdict: No

Bets were taken regardless of relationship

Bets were taken regardless of relationship

Bets were taken regardless of relationship

Wrong side?

Wrong side?

Wrong side?

Were users expected to support teams they didn't love in real life?

Were users expected to support teams they didn't love in real life?

Were users expected to support teams they didn't love in real life?

Verdict: Yes

Verdict: Yes

Verdict: Yes

Users were turning down bets for teams they didn't already support

Users were turning down bets for teams they didn't already support

Users were turning down bets for teams they didn't already support

Mapping out the key issue

Mapping out the key issue

Mapping out the key issue

When users were only limited to sending bets to people they knew in their immediate networks, there was a higher likelihood that bets were rejected especially if users liked the same teams

When users were only limited to sending bets to people they knew in their immediate networks, there was a higher likelihood that bets were rejected especially if users liked the same teams

When users were only limited to sending bets to people they knew in their immediate networks, there was a higher likelihood that bets were rejected especially if users liked the same teams

Identifying an opportunity from data

Identifying an opportunity from data

Identifying an opportunity from data

How might I create a new flow that allows users' bets to be matched with anyone on Wagr as opposed to just their immediate network?

How might I create a new flow that allows users' bets to be matched with anyone on Wagr as opposed to just their immediate network?

How might I create a new flow that allows users' bets to be matched with anyone on Wagr as opposed to just their immediate network?

At the core, users wanted to have their bets taken by someone on the other side. Based on the data, it did not matter significantly if the bet was taken on by someone who was not in a user's immediate network.

At the core, users wanted to have their bets taken by someone on the other side. Based on the data, it did not matter significantly if the bet was taken on by someone who was not in a user's immediate network.

At the core, users wanted to have their bets taken by someone on the other side. Based on the data, it did not matter significantly if the bet was taken on by someone who was not in a user's immediate network.

Step 3: Create a game plan

Step 3: Create a game plan

Step 3: Create a game plan

Identifying the areas in Wagr where bet matching should be introduced and how to best ease the feature into conversations

Identifying the areas in Wagr where bet matching should be introduced and how to best ease the feature into conversations

Identifying the areas in Wagr where bet matching should be introduced and how to best ease the feature into conversations

Where on Wagr would introducing bet matching be most effective?

Where on Wagr would introducing bet matching be most effective?

Where on Wagr would introducing bet matching be most effective?

The home page was where I initially announced the feature, making it clear to the user as to what was to entail. Invite friends was another opportunity to ensure the user knew there was a chance their bets were matched with someone outside their contacts. I also crafted feedback loops throughout the app to reiterate this feature upon launch.

The home page was where I initially announced the feature, making it clear to the user as to what was to entail. Invite friends was another opportunity to ensure the user knew there was a chance their bets were matched with someone outside their contacts. I also crafted feedback loops throughout the app to reiterate this feature upon launch.

The home page was where I initially announced the feature, making it clear to the user as to what was to entail. Invite friends was another opportunity to ensure the user knew there was a chance their bets were matched with someone outside their contacts. I also crafted feedback loops throughout the app to reiterate this feature upon launch.

Home screen

Home screen

Home screen

Bet confirmation

Bet confirmation

Bet confirmation

Invite friends

Invite friends

Invite friends

Step 4: Execute the game plan

Step 4: Execute the game plan

Step 4: Execute the game plan

I worked closely with engineers and product to ensure the greatest probability of success

I worked closely with engineers and product to ensure the greatest probability of success

I worked closely with engineers and product to ensure the greatest probability of success

Prototypes I demonstrated to design, product, and engineering alike to illustrate how I envisioned each different user lifecycles playing out on Wagr

Prototypes I demonstrated to design, product, and engineering alike to illustrate how I envisioned each different user lifecycles playing out on Wagr

Prototypes I demonstrated to design, product, and engineering alike to illustrate how I envisioned each different user lifecycles playing out on Wagr

Step 5: Adapt the approach

Step 5: Adapt the approach

Step 5: Adapt the approach

Phasing in and out a new feature

Phasing in and out a new feature

Phasing in and out a new feature

I wanted the initial launch of bet matching to be loud and clear for mass adaptation. I wanted later iterations to be seamless and intuitive

I wanted the initial launch of bet matching to be loud and clear for mass adaptation. I wanted later iterations to be seamless and intuitive

I wanted the initial launch of bet matching to be loud and clear for mass adaptation. I wanted later iterations to be seamless and intuitive

Phase 1: Bold and upfront

Phase 1: Bold and upfront

Phase 1: Bold and upfront

Phase 2: Clear messaging

Phase 2: Clear messaging

Phase 2: Clear messaging

Phase 3: Subtle reminders

Phase 3: Subtle reminders

Phase 3: Subtle reminders

Phase 4: Fully integrated

Phase 4: Fully integrated

Phase 4: Fully integrated

What difference was made?

Matched bets

Matched bets

80%

80%

80%

+ 30%

+ 30%

Users saw an uptick in their number of bets being accepted

Users saw an uptick in their number of bets being accepted

Average handle

Average handle

60%

60%

60%

+ 20%

+ 20%

Betting more money was indicative of trust in bets being accepted

Betting more money was indicative of trust in bets being accepted

Churn rates

Churn rates

15%

15%

15%

- 35%

- 35%

User cohort numbers were relatively similar over time

User cohort numbers were relatively similar over time