Crypto iGaming moves quickly. Operators regularly update their campaigns, rewards, payment options and product features. Important developments also come from suppliers, regulators, payment companies and other businesses around the industry.
The information is spread across company websites, social channels, industry publications and promotional pages. I wanted a reliable way to follow meaningful changes without starting the research from zero every day.
What I built
I built a recurring AI-assisted competitive-intelligence process covering five direct competitors and the wider crypto-iGaming market.
AI browsing is used to search the market, open relevant sources and bring the findings together. Each research cycle checks a rolling two-day period. This helps capture announcements that may take time to appear in search results.
Direct company and regulatory sources are prioritised. Reliable industry publications can support developments reported by third parties, while affiliate pages are mainly used to discover possible leads.
Each finding is classified as confirmed, reported or observed. This creates a simple distinction between an official announcement, reliable outside reporting and something that can be seen directly on a live campaign or product page.
The process also remembers what has already been covered. Previously reported developments are left out unless something meaningful has changed.
Keeping the reports useful
Crypto and iGaming searches produce a large amount of noise. Routine bonuses, repeated campaigns, small game releases and recycled promotional articles can quickly fill a report without adding much business value.
I introduced a materiality filter to keep the focus on developments that may affect:
- Customer acquisition
- Retention and loyalty
- Product expectations
- Payments
- Market access
- Regulation
- Competitive positioning
The final output is a short weekday brief containing no more than five prioritised findings. Each item includes the source and an explanation of why it may matter commercially.
This gives the reader a manageable view of the market instead of another long collection of links.
What the research finds
Findings have included competitor campaigns built around recurring leaderboards, late-score payouts, loss protection, expanded VIP rewards and crypto-staking reward structures.
Wider market signals have also been identified, including supplier-led gamification, free-to-play product expansion, new sportsbook infrastructure and regulatory initiatives designed to help users find licensed platforms.
Some reports are driven by direct competitor activity. On quieter days, the strongest signals are often found among suppliers, regulators and adjacent operators.
This wider view matters because a supplier feature can quickly become available to several competitors, while regulatory or payment developments may affect an entire market at once.
The practical value
The process creates a consistent view of what is changing and why it deserves attention. Product, marketing, CRM and growth teams can use the findings as inputs for campaign planning, feature development, market selection and customer-retention work.
The accumulated research also creates useful history. Individual developments can be compared over time, making it easier to recognise repeated campaign mechanics, growing supplier trends and wider changes in customer expectations.
Source verification keeps the briefs grounded. When reliable evidence cannot be found, the development is excluded. A rolling research window helps capture late discoveries, while the existing report history prevents unnecessary repetition.
How much more value can it create?
The daily brief already turns fragmented market information into a short and usable business view. Its value can grow considerably as the research history becomes larger and more closely connected to planning.
Competitor mechanics can become ideas for controlled tests. Supplier announcements can help shape product priorities. Payment and regulatory signals can influence which markets deserve more attention. Repeated developments can reveal broader trends before they become obvious across the industry.
The more interesting questions concern action. Which competitor mechanic is strong enough to influence a test? Which regulatory signal should affect market priorities? When does a supplier announcement show that customer expectations are about to change?
Coverage can also improve over time. Some operator announcements appear only in closed communities, social channels or dynamic pages that are difficult to monitor consistently. Bringing more of these sources into the same process would increase the system’s reach and make the growing intelligence library even more useful.
For me, the project is a practical example of using AI to support everyday commercial work. It provides a disciplined way to follow a fast-moving market and creates an intelligence base that can continue supporting better campaigns, products and market decisions.