When launching in a new market or geography, iGaming operators face a familiar challenge: “We have no player history here yet, so how can we personalize effectively?”. Teams typically take immediate steps, such as analyzing what competitors offer, hiring people with local market experience, or applying insights from similar geographies.
However, this early approach is often built on assumptions rather than actual data, which slows your growth in the new market. When players encounter offers, messaging, or game recommendations that don’t resonate with their preferences, they’re less likely to deposit, engage, or return, directly impacting retention rates and player lifetime value.
This article provides a practical, step-by-step plan for operators entering new markets who want to start personalizing accurately from week one -even without historical data-. While you won’t achieve fully automated personalization immediately, you can create experiences that feel relevant from day one and build a foundation for sophisticated AI-driven personalization, as your presence on the market matures.
Step 1. Ensure proper data collection
If you’ve been operating without personalization until now, you might be tracking basic analytics but not capturing the specific behavioral signals needed for personalization. Before launching in your new market, verify you’re collecting:
- User information: registration details, profile fields, device type.
- Payment activity: deposits, withdrawals, transaction patterns.
- Bonus activity: what users view, claim, and actually use.
- Gaming activity: game categories, frequency, preferences, and session length.
These are the first signals you’ll eventually use to personalize, even if you’re just storing and labelling them for now. Make sure your data is stored securely, in compliance with all relevant privacy laws, and that players know what’s being tracked and why.
Step 2. Learn from competitors and market specifics
If there are competitors who’ve been doing for years what you’re just starting, it’s worth taking a closer look at how they approach personalization. You won’t discover all their secrets, of course, but good market research can give you insights into product positioning, localization needs, cultural nuances, and user experience expectations. You can analyze the top games and categories they promote, their bonus strategies for different player types, their tone of voice and messaging style, the payment options and limits they offer, seasonality patterns (active hours, days, and months), the local holidays, sports events, and cultural moments they tap into.
It’s important to remember that what works for your competitors won’t automatically work for you. However, by studying their reasoning, the “why” behind their personalization choices, you can better understand your own opportunities. For example, if you notice that a competitor highlights certain games during local holidays, it reflects timing and the emotional connection they’re creating with players. They might be tapping into national pride or seasonal spending habits. If their bonus messages sound warmer or more conversational in some regions, it might reflect a cultural preference for friendliness over formality.
Step 3. Use test acquisition campaigns as early insights
The next step forward is to interpret the information you gathered, look beyond the numbers, and understand why things happen. Why do users choose certain games or payment methods? Why do some respond to bonuses while others scroll past? Your first week of acquisition testing is like your first real audience study. It’s your chance to understand who engages, how they behave and what they value most in your product.
To make sense of this early data, use your test acquisition campaigns as your first source of insight. Measure conversions and user behaviors, then compare what works and what doesn’t.
Even limited test traffic can reveal valuable behavioral signals long before you have statistically significant datasets:
- Which user cohorts react best to which value propositions?
- What micro-patterns might signal your most valuable users?
- Where can you begin building early personalization rules?
Step 4. Introduce hybrid personalization after the first month
After four weeks, you can start implementing hybrid personalization, which is a mix of human expertise and early data-driven insights. You can combine what you know about the market with early behavioral signals from your users. Getting to a fully personalized experience usually requires these key phases:
Phase 1: Manual Review (Months 1-3). The first 1-3 months focus heavily on traffic and funnel optimization; understanding which channels deliver quality players and where users drop off. While deep product personalization may not be the priority yet, manual VIP detection is critical (and helps define the most effective acquisition channels). This phase usually involves human review; a person manually identifies who has VIP potential, what recommendations to show, and which actions to take. Essentially, a human is doing what AI will eventually automate: pattern recognition and decision-making.
Phase 2: Early Models (Month 2-4). Once you have some volume, switch to models to handle detection (identifying player types) and recommendations. Even with minimal information -like acquisition channel or which creative a player clicked- you can deliver dynamic promo that aren’t fully personalized but already adapt to behavior signals.
Phase 3: Sophisticated Automation (Month 4+). With more volume, you can add use cases that only work on a scale, like behavioral profiling. You continue improving and deepening personalization as data accumulates.
It’s like training an AI: if you immediately ask it to create a full player strategy, you’ll get nonsense; but if you guide it step-by-step, feeding data and giving context gradually, results improve. That’s exactly how AI-powered personalization in new markets should evolve: start with guided, partially manual processes; then let the system learn and take over.
Step 5. Test and adapt
Even if your personalization setup feels basic, you can start running small tests. Try different combinations of promos, adjust your offers, and experiment with communication timing. A/B testing your messaging or bonus timing can reveal patterns that spreadsheets can’t show. Each test helps you learn more about what resonates with your players, and, over time, these small experiments add up and will guide you from early assumptions toward a more mature personalization approach.
To Sum Up
Full-scale personalization doesn’t happen the moment you enter a new market, and that’s okay. However, you don’t need half a year to start making your product feel personal either. By collecting the right data, learning from your first users, observing competitors and blending expert intuition with early automation, you can already make a noticeable difference within the first month. Each small, data-informed decision moves you closer to personalization that feels human.
These small steps can help you focus on quality acquisition and keep players engaged through the second month. That, in turn, speeds up your payback, frees up resources to scale faster and turns early retention into your first real growth engine.