Wagr
‘22-’23
Context
Wagr is a social sports
betting platform committed
to
transparency
1
,
sociability
3
and
delight
2
Anyone who sends a bet on
Wagr will always know who is
on the other side of the bet
Rather than betting against a house like traditional sports betting apps, Wagr only let people bet against other users
In 2022, I was on a
mission to
connect
more sports fans
together on the platform
While the company experienced a relatively successful launch, there was still opportunity to grow
By introducing an automated bet matching feature,
the platform saw
increased averaged handle
1
,
lowered churn
2
and
more daily active users
3
Designing an end-to-end feature that brings together sports fans
Step 1
Study the field
Most of Wagr's users were casual sports fans, placing light bets to enhance the watching experience rather than wagering large amounts of money
Wagr’s betting platform
Select side
Send bet
Friends
Crews
Accept
Deny
Win
Lose
Tie
Win $$$
Lose $$$
Lose $$$
Step 2
Identifying opportunites
Despite initial excitement around Wagr's social, transparent nature, a significant number of bets were going unanswered — signaling an opportunity to boost engagement
Bet rejection flow
Select side
Send bet
Friends
Crews
Deny
Win
Lose
Tie
Win $$$
Lose $$$
Lose $$$
Step 3
Zeroing in
To understand why bets were being rejected or ignored, I ran user research varying the bet amount, sender, and team — to see whether any of these factors influenced behavior
Wrong side
Did asking someone to back a team they didn't support affect acceptance rates?
Yes
Stranger danger
Did recognizing the bet sender affect acceptance rates?
No
Price too high
Did the proposed bet amount affect acceptance rates?"
No
The problem
Friendly fire
Sending out
a bet to someone who supports
the same team as you, pitting allies
against
each other as
rivals
Expanding who bets can be sent to
Select side
Send bet
Friends
Crews
Anyone
Accept
Deny
Win
Lose
Tie
Win $$$
Lose $$$
Lose $$$
The solution
Since Wagr users typically don't mind who
takes the other side of a bet,
as long as it isn't
the house,
an automated
bet-matching
feature that pairs
users with each other could
increase
in-app engagement
Step 4
Craft a game plan
Identifying areas in the app where bet matching would be most useful. What user flows from the current experience will be most impacted by the introduction of bet matching?
Home screen
Bet confirmation
Invite friends
Step 4
Execute the plan
Whilst introducing bet matching to an emerging user base like Wagr's, I aimed for a bolder, clearer initial release and seamless, intuitive interactions in later iterations
Introducing and explaining bet matching
Maximizing our odds of success
To support the success of bet matching, I refined key details across the experience. Since users gravitated toward trending matchups—not just upcoming ones—I added a ‘popular games’ section to surface high-interest games and increase engagement.
New game order
Browse games
Previous game order
Game 1
Start Time
8:00PM EST
Popularity
High
Game 2
Start Time
7:00PM EST
Popularity
Med
Game 3
Start Time
5:00PM EST
Popularity
Low
Select side
Place bet
What difference was made?
80%
of all bets being matched
Users saw a massive uptick in their number of bets being accepted
20%
increase in average handle
Betting more money was indicative of trust in bets being accepted
35%
reduction in churn rates
User activity stayed relatively consistent on the platform post-registration
Interested in more?
Wagr
‘22-’23
Context
Wagr is a social sports
betting platform committed
to
transparency
1
,
sociability
3
and
delight
2
Anyone who sends a bet on
Wagr will always know who is
on the other side of the bet
Rather than betting against a house like traditional sports betting apps, Wagr only let people bet against other users
In 2022, I was on a
mission to
connect
more sports fans
together on the platform
While the company experienced a relatively successful launch, there was still opportunity to grow
By introducing an automated bet matching feature, the platform
saw
increased averaged handle
1
,
lowered churn
2
and
more daily
3
active users
3
Designing an end-to-end feature that brings together sports fans
Step 1
Study the field
Most of Wagr's users were casual sports fans, placing light bets to enhance the watching experience rather than wagering large amounts of money
Wagr’s betting platform
Select side
Send bet
Friends
Crews (groups)
Accept bet
Reject bet
Win
Lose
Tie
Win $$$
Lose $$$
Lose $$$
Step 2
Identifying opportunites
Despite initial excitement around Wagr's social, transparent nature, a significant number of bets were going unanswered — signaling an opportunity to boost engagement
Bet rejection flow
Select side
Send bet
Friends
Crews (groups)
Reject bet
Win
Lose
Tie
Win $$$
Lose $$$
Lose $$$
Step 3
Zeroing in
To understand why bets were being rejected or ignored, I ran user research varying the bet amount, sender, and team — to see whether any of these factors influenced behavior
Wrong side
Did asking someone to back a team they didn't support affect acceptance rates?
Yes
Stranger danger
Did recognizing the bet sender affect acceptance rates?
No
Price too high
Did the proposed bet amount affect acceptance rates?"
No
The problem
Friendly fire
Sending out
a bet to someone
who suports the same team as you,
pitting allies
against each
other as
rivals
Expanding who bets can be sent to
Select side
Send bet
Friends
Crews
Anyone
Accept bet
Reject bet
Win
Lose
Tie
Win $$$
Lose $$$
Lose $$$
The solution
Since Wagr users typically don't
mind who takes the other side of
a bet,
as long as it isn't the
house,
an automated
bet-
matching feature that pairs
increase
in-app engagement
users with each other could
Step 4
Craft a game plan
Identifying areas in the app where bet matching would be most useful. What user flows from the current experience will be most impacted by the introduction of bet matching?
Home screen
Bet confirmation
Invite friends
Step 4
Execute the plan
Whilst introducing bet matching to an emerging user base like Wagr's, I aimed for a bolder, clearer initial release and seamless, intuitive interactions in later iterations
Introducing and explaining bet matching
Maximizing our odds of success
To support the success of bet matching, I refined key details across the experience. Since users gravitated toward trending matchups—not just upcoming ones—I added a ‘popular games’ section to surface high-interest games and increase engagement.
New game order
Browse games
Previous game order
Game 1
Start Time
8:00PM EST
Popularity
High
Game 2
Start Time
7:00PM EST
Popularity
Med
Game 3
Start Time
5:00PM EST
Popularity
Low
Select side
Send bet
What difference was made?
80%
of all bets being matched
Users saw a massive uptick in their number of bets being accepted
20%
increase in average handle
Betting more money was indicative of trust in bets being accepted
35%
reduction in churn rates
User activity stayed relatively consistent on the platform post-registration
Interested in more?
Wagr
‘22-’23
Context
Wagr is a social sports
betting platform committed
to
transparency
1
,
sociability
3
and
delight
2
Anyone who sends a bet on
Wagr will always know who is
on the other side of the bet
Rather than betting against a house like traditional sports betting apps, Wagr only let people bet against other users
In 2022, I was on a
mission to
connect
more sports fans
together on the platform
While the company experienced a relatively successful launch, there was still opportunity to grow
By introducing an automated bet matching feature,
the platform saw
increased averaged handle
1
,
lowered churn
2
and
more daily active users
3
Designing an end-to-end feature that brings together sports fans
Step 1
Study the field
Most of Wagr's users were casual sports fans, placing light bets to enhance the watching experience rather than wagering large amounts of money
Wagr’s betting platform
Select side
Send bet
Friends
Crews (groups)
Accept bet
Reject bet
Win
Lose
Tie
Win $$$
Lose $$$
Lose $$$
Step 2
Identifying opportunites
Despite initial excitement around Wagr's social, transparent nature, a significant number of bets were going unanswered — signaling an opportunity to boost engagement
Bet rejection flow
Select side
Send bet
Friends
Crews (groups)
Reject bet
Win
Lose
Tie
Win $$$
Lose $$$
Lose $$$
Step 3
Zeroing in
To understand why bets were being rejected or ignored, I ran user research varying the bet amount, sender, and team — to see whether any of these factors influenced behavior
Wrong side
Did asking someone to back a team they didn't support affect acceptance rates?
Yes
Stranger danger
Did recognizing the bet sender affect acceptance rates?
No
Price too high
Did the proposed bet amount affect acceptance rates?"
No
The problem
Friendly fire
Sending out
a bet to someone who supports
the same team as you, pitting allies
against
each other as
rivals
Expanding who bets can be sent to
Select side
Send bet
Friends
Crews (groups)
Anyone
Accept bet
Reject bet
Win
Lose
Tie
Win $$$
Lose $$$
Lose $$$
The solution
Since Wagr users typically don't mind who
takes the other side of a bet,
as long as it isn't
the house,
an automated
bet-matching
feature that pairs
users with each other could
increase
in-app engagement
Step 4
Craft a game plan
Identifying areas in the app where bet matching would be most useful. What user flows from the current experience will be most impacted by the introduction of bet matching?
Home screen
Bet confirmation
Invite friends
Step 4
Execute the plan
Whilst introducing bet matching to an emerging user base like Wagr's, I aimed for a bolder, clearer initial release and seamless, intuitive interactions in later iterations
Introducing and explaining bet matching
Maximizing our odds of success
To support the success of bet matching, I refined key details across the experience. Since users gravitated toward trending matchups—not just upcoming ones—I added a ‘popular games’ section to surface high-interest games and increase engagement.
New game order
Browse games
Previous game order
Game 1
Start Time
8:00PM EST
Popularity
High
Game 2
Start Time
7:00PM EST
Popularity
Med
Game 3
Start Time
5:00PM EST
Popularity
Low
Select side
Send bet
What difference was made?
80%
of all bets being matched
Users saw a massive uptick in their number of bets being accepted
20%
increase in average handle
Betting more money was indicative of trust in bets being accepted
35%
reduction in churn rates
User activity stayed relatively consistent on the platform post-registration
Interested in more?