Real-Time Commercial Analytics in iGaming: How BetGames Eliminated BI Bottlenecks with AI
In commercial organizations, speed compounds revenue. Campaigns launch weekly. Pipeline stages move daily. Regional performance can shift overnight. If insight arrives late, opportunity closes early. For Gary Francis, Head of Commercial at BetGames, the challenge wasn’t data availability. It was decision latency - the gap between asking a question and getting a usable answer. This case study explores how BetGames transformed commercial analytics from static dashboards and BI queues into real-time, AI-powered decision intelligence using Milo.
Faustas Rimkevičius
Growth Marketing
Customer Snapshot
Company: BetGames
Industry: iGaming (Live & RNG Games)
Commercial Scope: Global partner campaigns, pipeline performance, revenue optimization, game performance
Role: Head of Commercial
Technology Stack: Salesforce + Power BI + internal data warehouse (MSSQL + MySQL)
Access Channels with Milo: Slack, WhatsApp, Web
BetGames supplies gaming content (games) to thousands of brands worldwide. Campaign performance, regional growth, and partner pipelines move continuously. In this environment, commercial leaders must make revenue driving decisions in real time.
Watch the full video of Gary Francis, Head of Commercial at BetGames:
The Core Problem: BI Reporting Cycles vs Revenue Velocity
“In commercials, speed is everything. Campaigns, revenue, launches. If you don't see what's happening right now, you're already behind.”
- Gary Francis, Head of Commercial, BetGames
Before implementing Milo, the commercial workflow depended on traditional BI processes:
Submit a reporting request to the BI team
Wait 5–10 days for updates
Review static dashboards
Submit clarification or follow-up request
Re-enter the queue
While Power BI provided structured reporting, it was not built for dynamic, conversational iteration. Any change - new metric view, filtered breakdown, updated comparison - required manual intervention. This created three structural issues:
1. Commercial Meetings Based on Outdated Data
Pipeline reviews were often conducted using data that was already several days old or by using multiple different tools in parallel (PowerBI, Salesforce and Excel). Campaign pivots were reactive rather than proactive.
2. BI Team Bottleneck
The BI function became a dependency layer for minor adjustments. Commercial agility was limited by backlog capacity.
3. Lost Momentum
When reporting cycles stretch across a week, optimization cycles stretch with them. Revenue acceleration slows.
Organizations investing in decision intelligence capabilities improve operational responsiveness and business performance. Delayed analytics introduce systemic friction in revenue operations.
BetGames needed to eliminate that friction - without replacing their existing infrastructure.
Why Milo: Agentic GenBI for Commercial Decision Intelligence
Milo sits on top of existing systems and turns plain-English questions into actionable insight.
Instead of dashboards-first analytics, Milo enables conversation-first intelligence.
Gary now asks:
“How are campaigns running since last week?”
“How’s the pipeline looking since the last meeting?”
“What changed in this region?”
“Why did performance dip in Q4 accounts?”
Milo connects across:
Salesforce (pipeline, deal progression, partner engagement)
Power BI (historical reporting layer)
Internal data warehouse systems (MS SQL, MySQL, etc.)
It returns:
What changed + Why it changed → within minutes.
This aligns with findings from McKinsey & Company, which reports that embedding AI into commercial workflows significantly increases productivity and shortens decision cycles.
Milo doesn’t just surface numbers. It interprets drivers.
Solution in Action: From Question to Insight in Minutes
Real-World Scenario
A campaign launched last week. A regional sales review is scheduled in 45 minutes.
Previously, the process might involve:
Exporting Power BI dashboards
Requesting filtered views
Waiting for manual updates
Pulling Spreadsheet reports (MS Excel) manually
Now, Gary sends a message in Slack or WhatsApp:
“How are campaigns performing since last Monday? What changed in the pipeline?”
Behind the scenes, Milo:
Queries live CRM and performance data
Compares against historical baselines (Point-in-Time)
Identifies material shifts in conversion or revenue
Detects movement in deal stages
Explains contributing factors
Returns a structured response in minutes
As Gary describes it:
“The best thing about Milo is that I can use Slack or WhatsApp. It’s like having a senior analyst in my pocket.”
This shift from static dashboards to conversational analytics removes friction entirely.
Eliminating BI Bottlenecks Without Replacing BI
It’s important to clarify: Milo did not replace the BI team.
The BI team still governs infrastructure, modelling, and foundational reporting standards.
Milo:
Leverages existing data architecture
Respects governance controls
Enables commercial self-service
Reduces ad-hoc reporting burden
This reflects a broader industry evolution identified by Forrester toward AI-assisted decision platforms that sit above traditional BI layers.
Rather than removing BI, Milo increases its leverage.
Before vs After: Commercial Analytics Transformation
Before
5–10 day turnaround for report changes
Static dashboards and Spreadsheets
BI tickets for small adjustments
Limited ability to iterate live in meetings
Slower campaign optimization cycles
Reactive revenue strategy
After with Milo
Ask questions in Slack, WhatsApp or WebApp
Live pipeline visibility
Immediate campaign diagnostics
Contextual explanations
Faster revenue decision-making
Independent commercial self-service
The shift wasn’t incremental. It was structural.
Measurable Impact
While the biggest change was cultural and operational, the quantitative impact was clear:
Time to insight: Reduced from 10 days+ to minutes
BI dependency: Removed for commercial ad-hoc analysis
Optimization cycle: Significantly accelerated
Meeting quality: Based on live data, not snapshots
Speed in analytics translates directly into revenue responsiveness.
Cultural Shift: From Reporting to Revenue Intelligence
Milo changed how commercial teams think about data.
Instead of preparing slides before meetings, Gary explores insight during meetings.
Instead of sending follow-up emails for updated breakdowns, he asks additional questions in real time.
Instead of waiting for revised dashboards, optimization happens immediately.
As Gary summarizes:
“Now we don’t have to wait anymore. No BI team, no BI tickets. It’s near enough instant.”
This is more than convenience. It’s commercial acceleration.
Related Resources
To understand the broader architecture and governance behind Milo:
Role-Based Access Control in Milo
https://www.milo.ai/blog/role-based-access-control-in-miloMaking AI Work with Legacy Systems
https://www.milo.ai/blog/making-ai-work-with-legacy-systemsExtending Generative BI to Existing Infrastructure
https://www.milo.ai/blog
These explain how Milo integrates securely into enterprise BI environments without requiring costly replatforming.
Frequently Asked Questions (FAQ)
What is real-time commercial analytics?
Real-time commercial analytics enables revenue teams to access live pipeline, campaign, and product performance insights without waiting for scheduled reports or dashboard updates.
How is Milo different from traditional BI tools?
Tools like Power BI provide structured dashboards. Milo provides AI-driven, conversational analytics that explains performance drivers instantly. Milo gives you an answer.
Does Milo integrate with Salesforce?
Yes. Milo’s data layer connects directly to Salesforce and logically connects its data with other data sources, enabling real-time contextual pipeline analysis and deal performance tracking.
Is Milo secure?
Milo supports role-based access control (RBAC), governance layers, and auditability, aligning with enterprise-grade requirements.
Does Milo replace BI teams?
No. It complements BI by reducing ad-hoc reporting load while leveraging existing infrastructure.
Which industries benefit most?
Industries with high commercial velocity - such as iGaming, SaaS, fintech, and eCommerce - see the strongest impact.
Conclusion: From Reporting Delays to Revenue-Speed Decisions
For BetGames’ Head of Commercial, the issue wasn’t data availability.
It was delay.
By implementing Milo, the commercial team transitioned from:
Static dashboards → Conversational AI analytics
BI queues → Instant answers
Reactive decisions → Revenue-speed execution
In competitive markets, speed compounds.
With Milo, insight moves at the pace of revenue.
