How to Analyze Postbacks and Optimize Affiliate Campaigns

If you work with iGaming traffic, you already know how important it is to track what happens after the click: did the user register, did they deposit, did they turn into a real player?

With postbacks, you get that data instantly. They help you see which channels actually bring revenue, react faster to changes, and increase ROI with informed decisions instead of guesswork.

Put simply: postbacks turn traffic buying from a blind experiment into a predictable and scalable process. And today — мы разберем, как использовать их правильно.

What Postbacks Really Are 

A postback is simply a real-time notification about what happens with the user you brought. A click is just a click — it doesn’t tell you whether the person stayed, registered, or turned into a paying player. With postbacks, you immediately see whether your traffic actually brings revenue, not just numbers in the advertising dashboard.

Once a player performs any meaningful action — registration, deposit, first bet — the partner program sends a signal to your tracker or ad platform. This signal includes the exact source of that user, so you know what really works: which campaign, which placement, which creative. The sooner you know the truth, the faster you scale what makes money and cut what wastes it. That’s why postbacks aren’t “another technical checkbox.” They are the foundation of profitable affiliate marketing — the bridge between traffic and results.

Which Data Inside Postbacks Matters Most

Postbacks can contain plenty of information, but only a few fields are responsible for the decisions that move your revenue up or down. When you focus on these parameters, you start seeing the true ROI of every traffic slice instead of judging by impressions and clicks alone.

sub_id — the real source of the money

sub_id shows where a converting user actually came from: a specific campaign, a single creative, a unique placement, or even one influencer. If two ads bring the same amount of clicks, but only one generates FTDs, sub_id reveals it instantly. Without this parameter, all traffic looks the same — and optimization becomes a guessing game.

GEO — different countries, different behavior

Every market behaves differently. You may get cheap clicks from Brazil but see much higher deposit rates from Canada. Postback data shows where the money is really coming from, not where the CTR looks nice. Sometimes scaling means not increasing volume, but shifting focus to the GEO where players pay.

Payout — the value behind each event

Registrations are great, deposits are better, but only paid actions show the real performance. Payout data tells you how much money each segment returns. Two channels may deliver the same number of FTDs, but one gives a 30% higher commission — that’s the traffic you scale first.

Event Status — understanding each step of the funnel

Signups, first deposits, repeated deposits — every stage tells a story. You may find creatives that bring a lot of registrations but zero paying users — that means the wrong message or audience mismatch. Tracking specific statuses shows where users fall off and where value is created.

Timestamp — when conversions actually happen

Time matters. Some campaigns perform better during commuting hours, others convert late at night. If you see that deposits peak in the morning for Mexico or drop every Friday evening in Germany, you use this to adjust budgets and bids for maximum return.

Device / OS — the platform influences profitability

Android and iOS users often behave differently. iOS traffic is usually more expensive, but many affiliates see 2–3x higher FTD value from it. Desktop users may have lower volume, but they often register and deposit faster. Device-level postbacks highlight which platforms deserve aggressive scaling.

Postback data gives you a clear view of the true profitability of every traffic segment. When you understand where your revenue comes from, optimization stops being a lottery — it becomes a strategy.

How to Analyze Postbacks for Optimization

Postbacks highlight where real revenue comes from. Start by comparing sub_ids: some bring signups, others deliver FTDs — scale only what drives deposits. Cut channels with clicks but no paid events. Check GEO performance at each step of the funnel: if players from one region drop after signup, review the angle or landing. Look at device data — iOS may cost more but return higher value. Timing also matters: if conversions peak during certain hours, shift spend to those windows. Every decision should follow the same logic: keep what pays, stop what doesn’t.

How Postbacks Help Improve Budgets and Bidding

1) Adjust bids based on FTDs, not clicks
Postbacks reveal where paid actions happen. Increase bids only on sources that consistently bring deposits.

2) Feed accurate conversion data into auto-bidding
Meta and Google optimize better when they receive real FTD signals, not just registrations or landing page views.

3) Shift budget from weak to strong sub_ids
If one segment drives revenue and another only spends — money should follow the profit.

4) Optimize ROI in real time
When payouts vs. traffic cost are visible immediately, it’s easy to scale winning combinations and freeze losing ones.

5) Prioritize creatives that generate deposits
A creative with fewer clicks but more FTDs deserves scaling — and postbacks prove it instantly.

Practical Examples You Can Apply

Example 1: Placement difference
sub_id=facebook_feed brings many clicks but almost no deposits.
sub_id=instagram_reels shows fewer clicks but strong FTDs.
→ Shift budget toward reels and pause feed traffic.

Example 2: Device matters
Android traffic comes cheaper, but iOS users deposit 3× more.
→ Keep Android for volume, scale iOS for profit.

Example 3: GEO timing insight
Mexico shows higher deposit rates in the morning than in the evening.
→ Adjust bidding schedule to peak hours and reduce late-night spend.

Example 4: Landing page behavior
Landing A drives many signups but poor FTD progression.
Landing B has fewer signups but a better deposit rate.
→ Send more high-intent traffic to Landing B.

Common Mistakes in Postback Analysis

1) Focusing only on clicks and registrations.
Signups don’t pay commissions. Deposits do. If you optimize for the wrong metric, you scale the wrong traffic.

2) No connection between postbacks and ad platform.
If conversion signals aren’t synced with Meta or Google, auto-bidding cannot optimize properly.

3) Analyzing too short time frames.
Paid players may convert later. Cutting a source after 20 minutes of testing means losing future FTDs.

4) Not splitting traffic by sub_id.
Aggregated data hides winners. Without segmentation, strong creatives drown in average results.

5) No clear optimization goal.
Some affiliates chase CR, others — volume. But the only goal that matters is ROI and payouts.

Without postbacks, affiliate marketing is guesswork. With postbacks, every decision is tied to real revenue: you scale what drives deposits, cut what burns the budget, and keep control over ROI at every step. Once you start analyzing sub_ids, GEO performance, devices, and timing, optimization becomes a repeatable process — not a gamble.

If you want a smooth way to test these strategies in a global GEO, take a look at Melbet Partners. It’s a solid program with fast tracking updates and flexible payout terms — a good match when you’re ready to grow responsibly.