SQUADS
From engagement to conversion
Product: Squads (free-to-play game)
Company: LiveScore Group
Year: 2025
My contribution
I led this project end to end — from problem definition to stakeholder alignment and delivery
Gathered quantitative data to define the problem
Ran user research (on 1st iteration of the project)
Problem and user target definition
Opportunity shaping
Ideation across 3 possible approaches
Evaluative research — user testing
Proposed success metrics (Then shared with Insights for sign-off)
Gathered stakeholders and drove decision conversations
UX, UI, visual design, prototyping and animations
Who I worked with
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Product owner (delivery focus) who co-piloted on the project and handles dev team (capacity planning, epics, etc)
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Insights team (for modelling discussions, reporting & success metrics)
Promotions team (for budgeting)
Dev team (Included on early-stage ideation for effort-impact discussions, high-level constraints & feature mapping)
CRM (for feature rollout comms strategy and to collaborate with push notifications)
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Head of product
Product design director & Head of Product design
Marketing design (for sign-off visual direction)
What is SQUADS?
SQUADS is a football themed game that sits within LivescoreBet with two business objectives:
➡️ Retention tool to the overall platform. Users that play Squads have a 20% longer Lifetime Value than those who don't
Conversion, P2P (Pay to Play): Free to play users should be upsold to become paying customers by placing sports bets or playing casino games
➡️ How does it work
The user reveals 1 football player card every day, Monday to Friday. With the last player reveal, the user’s squad gets assigned a prize per goal. When any player on their squad scores a goal in a weekend match, the user gets paid withdrawable money.
2. A Vague brief
The brief was vague, the main concern was the upsell banner on the current experience not performing, and I was asked to explore ways to upsell users. There were mixed concepts and suggestions such as looking at retention, daily engagement and acquisition. My first task was to understand what problem we were actually trying to solve.
3. Understanding the Problem
After reviewing the game metrics, these were my findings:
❌ Retention to the game is not a problem. We retain 90% of unique users in the first month and 65% after 6 months.
❌ Daily engagement is not a problem. Users already have the habit of coming to the product every weekday, with an average of 4.1 out of 5 reveals a week.
✔ The upsell banner has effectively had flat performance since deployment, with only an average of 4% CTR, and out of that 4% only a 4.41% on average place a bet.
But what is the root problem that goes beyond
a poor banner performance?
I had questions as to who are our Squads players what are their behaviours. I’ve continued digging into metrics and this is what I found:
Who plays SQUADS?
The critical insight
80% of free to play users bet weekly—
but with our competitors
This insight brought further questions to the research
Why do users that play SQUADS daily choose our competitors to complete “jobs to be done”?
The causes are varied and complex. Some of these factors we have learned through more extensive research are: the industry is low loyalty, some of our competitors can afford to offer better odds, aggressive promotions, and users’ habit. These factors are outside our control.
So what do we have in our favour?
A strong retention, very good daily engagement, and therefore users who have the habit of coming into Squads almost every day (4.1/5 reveals a week). But:
What were users frustrations with Squads?
Qualitative insights from a previous iteration revealed two core pain points:
➡️ Lack of control over the players they receive — users want some level of strategy and knowledge application, although this needs to be balanced with low effort.
➡️ Dissatisfaction with prizes - which matches the metrics we’ve seen for these user cohorts. Most Tier 4 and 5 users, earn between £0.10 and £0.50 per goal.
4. The Opportunity
Connect Tier 4 and 5 users' unmet needs — perceived control over their squad and more meaningful rewards — to their existing betting habit, redirecting part of that weekly activity to LivescoreBet and unlocking higher wallet share from an already engaged but undermonetised audience.
Main success metric
As part of the opportunity, I identified and proposed the following success metric to align stakeholders on what we were optimising for:
Bet placement % uplift from Tier 4 & Tier 5 Squads players
5. Ideation
I evaluated three potential solutions against three criteria:
✅ User impact — does it address perceived control and reward dissatisfaction?
✅ Business viability — does it work within existing margins and technical constraints?
✅ Experience fit — does it embed the upsell naturally into the game?
Option 1: Wager to get a better cash per goal
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Make the existing prize allocation model visible and selectively enhance it for engaged users. By packaging the prize allocation model into levels and gamifying the experience: the more you bet that week within our product, the higher your prize per goal on Squads.
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Tackles user pain point on prize allocation
✅ Connects bet requirements with user game engagement
✅ Fast implementation — Just a few overriding rules to the model logic to enable these upsells, no dependency on other dev teams
✅ Potential to evolve into a tool for bonus optimisation, redistributing prize allocation away from 27% bonus abusers
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After modelling the numbers with the Insights team, offering a marketable prize range required lowering profit margins to a level that risked losses or otherwise required a review of bonus allocation from our promotions across the wider product.
Conceptual design, happy journey
Option 2: Wager to swap any player for a guaranteed forward← Selected
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Users who place a qualifying bet unlock a transfer window to swap any player for a guaranteed forward.
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Addresses the lack of control over players users receive, allowing a level of knowledge application by choosing which player from their squad they want to transfer out.
Embeds the upsell strategy trhough a gamified approach, connecting the user engagement with the game to the business need for a higher wallet share from Squads players.
The transfer window element fits naturally with user behaviour, bringing traffic during prime time for both the business and the users’ weekly activity
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Implementation may involve dependency on a second dev team
Option 3: Dynamic contextual banners
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Repurpose promo banners and make them relevant to users’ player reveals, using logic to display the right promotion or betting market based on users’ betting behaviour and the Squads player revealed that day.
I presented this option strategically last, after stakeholders were already invested in Options 1 and 2 — making them more flexible on implementation timelines. -
Fast implementation — presented as a pragmatic short-term option
User research and metrics on different promo campaigns showed better user uptake of promotions when relevant to user behaviour and timing.
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This may have optimised banner performance but failed to address root user pain points
Does not fully leverage the opportunity identified
6.The solution
Option 2 was selected. Here is how it worked:
The mechanic:
1️⃣ Users place a bet on any player market between Monday and Saturday 3pm
2️⃣ This unlocks a transfer window on Saturday 12pm–3pm
3️⃣ During that window, users swap any player from their squad for a guaranteed forward
Why every design decision was deliberate:
Perceived control— Users choose which player to transfer out, introducing a level of strategy and knowledge application within the game, as expressed by users during research.
Reward value — A guaranteed forward gives users a statistically higher chance of earning prize money, since forwards score more goals than defenders or midfielders.
The transfer window timing was the most considered decision. Our data showed Saturday afternoon is peak sports betting time — users already had the habit of betting then, just with competitors. Rather than creating a new behaviour, we redirected an existing one. Users coming to complete their transfer were on our platform at the exact moment they would typically open a competitor platform.
The betting requirement connected the two habits identified in the opportunity statement — playing Squads daily and betting weekly — creating a direct relationship between them within our platform for the first time.
7 Breaking it down into an MVP
Before stakeholder alignment, I worked with the PM on a feature map to define MVP scope and ran an early feasibility check with the dev team across all three solutions. This surfaced a key dependency: the in-app reminder feature required building a new API, which would have delayed the entire release. We moved it to V2 and used CRM push notifications as a pragmatic alternative — reaching users who had opted in to notifications at the start of the transfer window.
8 Success metrics
The feature is currently in development. These are the metrics defined upfront to evaluate success:
🎯 North star metric
Bet placement rate uplift from Tier 4 and 5 Squads users, through qualifying bets (£5 on any player market), measured across several weekends and compared to the same period the previous season to minimise seasonality factors.
🔎 Hypothesis: A higher percentage of Tier 4 and 5 Squads users will place at least one qualifying bet with LivescoreBet per week after the feature launches, compared to their pre-launch baseline, — redirecting existing betting behaviour toward LivescoreBet, and capturing part of the wallet share that research showed was going to competitors. The motivation is the direct connection between betting and gaining a strategic advantage in the game — a guaranteed forward player that addresses the users' stated pain point of player quality.
🥈 Supporting metric – WoW retention: % of the unique user cohort, filtered by tier, who engaged with the transfer mechanic in week 1 since launch, and re-engaged in each subsequent weeks — tracking whether the same users return repeatedly rather than comparing new unique users each week.
🔎 Hypothesis: Users who engage with the transfer mechanic in week 1 will incorporate placing a qualifying bet into their weekly routine, returning to the mechanic consistently in subsequent week. This is driven by the recurring structure of the game — a new squad every week, and a new opportunity to gain a strategic advantage — transforming a one-time incentive into a habitual behaviour that increases LivescoreBet's share of their weekly betting activity over time.
🥉 Secondary metric: – Bet placement uplift from Squads users across Tier 1- 5 on Saturdays during the transfer window (12pm-3pm), measured across a minimum of 8 Saturdays post-launch vs the same 8 Saturdays the previous season, to smooth out match week variance.
🔎 Hypothesis: By bringing users back to the platform during Saturday 12–3pm — a window our data identified as peak sports betting time — we expect to see a measurable uplift in bet placement across different betting markets during that specific window. Rather than creating a new behaviour, the transfer window redirects an existing habit: users who were already placing bets on Saturday afternoons.
👁️ Guardrail metric: Squads engagement rate and betting activity among Tier 4 and 5 users exposed to the transfer mechanic who did not complete the qualifying bet, tracked week on week from feature launch vs pre-launch baseline.
🔎 Hypothesis: Users who are exposed to the upsell mechanic but do not convert will maintain their existing Squads engagement and betting activity levels. A drop in either would indicate the mechanic is perceived as too aggressive, risking churn from both the game and the platform among the users we are trying to convert.