2026
Real-Time Product & Launch Analytics in iGaming: How BetGames Transformed Decision Speed with Milo
In fast-moving industries like iGaming, product decisions must be informed instantly - not after days or weeks of waiting for reports. Game launches, promotional performance, and user cohort behaviours determine competitive positioning, monetization success, and long-term retention. For Ian, Chief Product Officer at BetGames, the problem wasn’t data scarcity - it was decision latency: the time between asking a product question and getting a meaningful answer. This case study explores how BetGames replaced lengthy reporting cycles with real-time AI-driven product analytics using Milo.
Faustas Rimkevičius
Growth Marketing
Customer Snapshot
Company: BetGames
Industry: iGaming (Live & RNG Games)
Role: Chief Product Officer
Core Focus: Launch performance, promotional impact, behavioural cohorts, product optimization
Technology Stack: Power BI + internal data warehouse (MS SQL, MySQL, etc)
Access Channels: Web, Slack, WhatsApp
BetGames operates in one of the most competitive entertainment markets. Success is measured in rapid iterations: each launch, campaign, and promotional push must be evaluated quickly to maintain growth and positioning.
Watch the case study's video here:
The Core Problem: Product Decisions Cannot Wait Two Weeks
“We work in a very competitive marketplace. We have to take quick decisions, and we can’t wait two weeks for reports.”
- Ian, Chief Product Officer, BetGames
Before Milo, product analytics at BetGames followed a traditional business intelligence (BI) pattern:
Submit an analytics request
Wait for BI to aggregate and build reports
Static dashboards reveal data slowly
Ask follow-up questions
Re-enter the reporting queue
This cycle introduced several constraints:
Launch Performance Lags
Evaluating how a game performed in its first 24 hours required manual pull-together of multiple dashboards and spreadsheets - delaying decisions on pricing, promotional pushes, or feature tweaks.
Cohort Analysis Complexity
Understanding user behavior across player segments over time (a technique known as cohort analysis, which groups users based on common characteristics to reveal behavior patterns) required extensive manual work.
Promotion Evaluation
Assessing whether a promotional campaign created value, volume, or both required stitching multiple data sources together - often too late to act.
Traditional BI pipelines simply couldn’t match the pace required in real markets. According to research on real-time business intelligence, systems that provide information as events occur deliver far greater operational agility and actionable insight than periodic reporting cycles.
BetGames needed an analytics approach capable of delivering answers in minutes - not days.
Why Milo: AI-Driven Product & Launch Intelligence
Milo is a conversational business intelligence platform that translates natural language questions into real-time data insights.
Instead of building dashboards first, product teams can ask Milo directly:
“How did the latest game launch perform in its first 24 hours compared to the previous launch?”
“Run a cohort analysis for this release.”
“Did this launch promotion drive value or volume?”
“What’s the performance trend in key regions?”
“What promotion types performed best by key region?”
Milo connects to BetGames’ existing stack - including Salesforce, Power BI, and warehouse data - and returns:
Launch metrics → Comparisons → Cohort breakdowns → Actionable insights within minutes.
This approach aligns with broader shifts toward decision intelligence platforms, a class of technologies identified by research firms like Gartner as critical for organizations that want to operationalize real-time decisions beyond static dashboards.
Solution in Action: From Question to Insight in Minutes
Real-World Scenario
A new game launches. The product team needs answers fast:
Is the launch outperforming the previous release?
Are high-value cohorts engaging early?
Is retention tracking above benchmarks?
Did the promotional mechanics influence value or volume?
Previously this required multiple reporting layers and manual cohorts.
Now, Ian sends a request in Slack or via web:
“How did the game launch in the first 24 hours versus the last launch? Give me some insight and run a cohort analysis.”
Behind the scenes, Milo:
Queries launch KPIs from connected systems
Benchmarks against historical data
Segments users into relevant cohorts
Highlights meaningful trends in value and engagement
Provides causal explanations for observed changes
Delivers the breakdown in minutes, not weeks
Ian describes the outcome succinctly:
“We can ask Milo anything at any point. The team can ask for insight. We don’t have to wait for BI. We have the information within a few minutes.”
This responsiveness transforms product operations - enabling quick iteration and competitive reactions during live market conditions.
From Static Reporting to Dynamic Product Intelligence
Traditional BI tools like Power BI are powerful for structured dashboards but require manual setup, fixed definitions, and pre-built views. Milo introduces conversational analytics - a flexible, context-aware layer that responds instantly to human queries.
Milo also incorporates features such as Role-Based Access Control (RBAC) to ensure secure, governed usage of data across departments. This functionality allows teams to manage who can see what - balancing accessibility with data security.
Before vs After: Product Analytics Transformation
Before
Two-week reporting latency
Manual cohort segmentation
Delayed launch comparisons
Hard BI dependency
Reactive optimization cycles
After with Milo
Launch comparisons in minutes
On-demand cohort analysis
Real-time promotional impact diagnostics
Self-service product intelligence
Faster iteration cycles
The shift wasn’t incremental - it was structural.
Measurable Impact
While specific internal KPIs remain confidential, BetGames experienced dramatic changes in insight velocity:
Time to launch insight: Reduced from weeks to minutes
BI backlog reduction: Product team self-serves most questions
Faster optimization: Immediate answers inform next steps
Competitive responsiveness: Decisions made in real time
In competitive game markets, speed = advantage.
Cultural Shift: Milo as an Extension of the Product Team
Ian puts it best:
“It’s like having another member of the product team.”
Milo augmented analytical capability rather than replaced analysts. The product team gained:
Instant validation of assumptions
Faster promotional iteration
Proactive cohort tracking
More confident portfolio decisions
Data conversations became part of daily workflows.
Related Resources
To explore how teams use AI analytics in their workflows:
How to Ask Data Questions in Slack - Practical guide for using AI analytics where teams communicate daily: https://www.milo.ai/blog/how-to-ask-data-questions-in-slack
BI Tools vs. AI Analytics: What Product Teams Need to Know - Comparison of traditional dashboards and conversational analytics: https://www.milo.ai/blog/bi-tools-vs.-ai-analytics-what-product-teams-need-to-know
Frequently Asked Questions (FAQ)
What is AI-powered product analytics?
AI-powered product analytics uses natural language and machine intelligence to analyze performance trends without manual dashboard creation.
How does Milo help with launch performance?
Milo benchmarks live launch data against historical launches and produces insights in minutes. Further, Milo delivers nuanced analyses such as user cohort analysis, feature usage reports etc., in near real time.
Does Milo perform cohort analysis?
Yes - Milo can segment user cohorts on demand, identifying retention and behavior trends.
Is Milo secure?
Milo is ISO27001 & SOC2 certified, supports enterprise governance controls, including RBAC, MFA and zero data retention to manage data accessibility securely.
Which industries benefit most?
High-velocity markets like iGaming, SaaS, fintech, and eCommerce benefit from real-time decision intelligence.
Conclusion: Product Decisions at Market Speed
For BetGames’ Chief Product & Business Officer, dashboards weren’t the real issue - it was latency.
With Milo, the product team moved from:
Two-week cycles → Real-time AI answers
Manual cohorts → Instant segmentation
Delayed execution → Immediate action
In competitive iGaming markets, speed determines success. With Milo, product intelligence moves at market speed.
