Your platform tells you which campaign drove the most installs. That should tell you whether you made money. It doesn't.
For most betting operators, the answer is no.
The install number looks clean.
The CPA looks fine.
Then six months later the cohort has churned and the budget is already gone.
The gap is in what happens after acquisition. AppsFlyer, for example, does not natively connect to your game platform. That means someone on your data team has to stitch AppsFlyer device IDs to player IDs, then build their own logic for stakes, wins, voids, bonus cost, and settlement timing. That is not a platform feature. That is a custom project.
This article ranks three platforms - Intelitics, AppsFlyer, and Adjust - on how they actually close that gap.
Most analytics tools claim to measure marketing performance. The assumption is that any platform tracking clicks, installs, and first deposits gives you enough to make decisions. It does not.
A marketing measurement platform for betting operators connects every marketing dollar to downstream player revenue and long-term value across paid media, affiliates, influencers, and programmatic spend. The key word is downstream: not what happened at signup, but what that player was worth six months later.
Two problems make generic tools inadequate for this industry:
Every platform in this category claims to unify data and improve ROI. The criteria that actually separate betting-specific platforms from general-purpose tools come down to three questions.
Can it ingest first-party game platform data alongside paid media: Betting operators need revenue data from their game platform (GGR, NGR, player activity) connected to the marketing source that drove that player. A platform that only pulls from ad channels is measuring half the picture.
Can it predict player LTV early enough to act on it: The feedback loop in betting spans months or years. A platform that requires 90 days of player data before surfacing LTV signals is already too slow for in-flight campaign decisions.
Does it support the attribution models betting journeys actually require: A player may touch an affiliate link, a paid social ad, and a CTV spot before depositing. Last-click attribution misattributes value across all of them. The platform must support multi-touch models with configurable attribution windows by channel type.
The three platforms below cover different parts of the measurement problem and are not interchangeable. One is purpose-built for betting and gaming; two are general mobile attribution platforms that operators in the space commonly use.
Your affiliate manager needs player-level LTV by partner. Your CFO needs NGR by channel. Your performance team needs to know which creative drove a high-value cohort, not just a cheap install. Intelitics is the only platform in this list built to answer all three questions from a single source of truth.
The measurement model reflects how betting actually works: long player journeys, multi-state operations, NGR-based optimization, and affiliate relationships that require player-level LTV data, not click counts.
Best suited for operators with meaningful spend across multiple channels and partners who need a single platform to connect marketing decisions to downstream profit.
Your mobile acquisition team already knows AppsFlyer. It is one of the most widely deployed mobile measurement platforms globally, with strong SDK coverage and deep integrations across mobile ad networks.
Strengths for betting operators: Mobile attribution depth, fraud protection through Protect360 (processing roughly 1 trillion mobile events per month across 5.7 billion devices), deep linking, and a large partner ecosystem. Works well when the primary question is which mobile campaign drove this install.
Where it falls short for betting: Connecting app install data to NGR, GGR, or long-term player LTV requires significant custom data engineering. The platform does not natively ingest game platform revenue data, so operators must build identity stitching between AppsFlyer device IDs and player IDs in their gaming platform, then construct their own accounting logic for stakes, wins, voids, bonus cost, and settlement timing.
Attribution model support: Strong for last-click and probabilistic mobile attribution; multi-touch modeling available though it requires configuration.
Choose AppsFlyer when your measurement question centers on mobile app acquisition and your internal data team can build the revenue connection downstream. Avoid it when you need NGR-based attribution out of the box.
Adjust competes directly with AppsFlyer in most operator evaluations, with a stronger emphasis on data privacy and regulatory compliance across European and US markets.
Strengths for betting operators: Privacy-first architecture (operates its own physical servers rather than third-party cloud services, supports GDPR erasure requests via API/SDK), strong fraud prevention, and clean SDK implementation. Reliable for operators who need compliant mobile tracking across regulated jurisdictions.
Where it falls short for betting: Adjust does not connect marketing spend to player LTV or NGR without custom integration work. Operators must still build ledger logic for GGR/NGR, handle settlement-aware revenue events, and manage identity mapping between device IDs and player accounts.
Attribution model support: Last-click and multi-touch available with configurable attribution windows.
Choose Adjust when privacy-compliant mobile tracking in regulated markets is the primary requirement. Avoid it when you need a platform that connects spend to player value without a custom data engineering project.
Your current platform probably reports CPA and install volume cleanly. The gap is in what happens after the install: whether those players deposited, whether they stayed, and whether the channel that drove them was actually profitable.
|
Metric |
Intelitics |
AppsFlyer |
Adjust |
|
CPA / CAC |
✓ |
✓ |
✓ |
|
First deposit |
✓ |
✓ |
✓ |
|
NGR / GGR |
✓ |
Requires custom build |
Requires custom build |
|
Predictive LTV |
✓ (within 72 hrs) |
Limited |
Limited |
|
CAC:LTV ratio |
✓ |
Manual |
Manual |
|
Contribution margin |
✓ |
No |
No |
|
Affiliate player-level LTV |
✓ |
No |
No |
CPA (cost per acquisition) measures the marketing cost to acquire a single player; CAC (customer acquisition cost) is the fully loaded cost across all channel spend. CPA is the standard betting industry metric, though in isolation it says nothing about whether the player acquired was worth acquiring.
GGR (gross gaming revenue) is total wagers minus winnings paid. NGR (net gaming revenue) is GGR minus bonuses, promotions, and taxes, which represents actual profit from player activity.
Generic mobile measurement platforms can record a revenue number on an event, though they do not ship with a native schema for:
Operators typically end up building a canonical gaming fact table in a data warehouse, then deciding what to down-convert into MMP-friendly events. That is a custom engineering project, not a platform feature.
Generic MMP cohort LTV is observation-based: it becomes meaningfully stable only after D7 to D30 for optimization, with true value categories requiring D60 to D90 or longer depending on the payback curve. Betting operator LTV is frequently measured in multi-month or multi-year terms from first deposit.
Predictive LTV compresses that feedback loop. AI models trained on early behavioral signals (game choices, deposit patterns, engagement frequency) generate a forecast of long-term player revenue within 72 hours of acquisition, early enough to redirect budget before a low-quality cohort scales.
The CAC:LTV ratio is the finance-grade expression of whether acquisition is profitable and the metric that bridges the CMO-CFO conversation. A platform that cannot produce it natively requires manual calculation or custom warehouse logic.
The right platform matches the operator's primary acquisition complexity and data infrastructure, not the longest feature list. Three scenarios cover most operator situations.
You are running paid media across Google, Meta, TikTok, and programmatic, managing a network of affiliates and influencers, operating in multiple states or regions, and need a single platform that connects all of it to player LTV and NGR without building a custom data pipeline.
Intelitics handles the full stack: paid media, affiliates, game platform data, predictive LTV, and finance-ready reporting in one place, with implementation under 30 days via pre-built integrations to GiG, Playtech, White Hat Gaming, and hundreds of ad channel connectors.
Your primary acquisition channel is mobile app installs, your internal data team is strong enough to build the revenue layer downstream, and the primary measurement question is which mobile campaigns and creatives drove installs and early engagement. AppsFlyer and Adjust are both mature, well-integrated options here.
The choice between them often comes down to existing vendor relationships and privacy compliance requirements by market. AppsFlyer's Protect360 fraud suite leads on scale; Adjust's privacy-first architecture leads on GDPR and CCPA compliance.
You are expanding into regulated European or US markets where GDPR and CCPA compliance are non-negotiable, and the primary concern is maintaining tracking continuity without relying on third-party cookies or device IDs. Adjust's ePrivacy certification since 2015 and GDPR erasure request workflows make it purpose-built for this scenario.
Compliance tracking alone does not answer the revenue measurement question. Operators in this scenario still need a revenue intelligence layer to connect mobile attribution to NGR and player LTV.
Tracking gaps, corrupted attribution data, and broken commission calculations with affiliates are not edge cases during a platform migration. They are the most common outcomes of a poorly managed cutover.
Your game platform integration is the hardest part of the migration, not the ad channel connections. Generic attribution tools connect to Meta and Google easily; connecting to GiG, Playtech, or White Hat Gaming requires either a pre-built connector or a custom engineering project.
Ask for a specific integration list, not a general "we can integrate with anything" claim. Identity stitching between MMP device IDs and player IDs in the gaming platform requires backend logic and mapping, and settlement-aware revenue logic (handling late-arriving bet settlement data, bonus cost, adjustments, refunds, voids, chargebacks) must be built if the platform does not natively support it.
Intelitics has pre-built integrations with major gaming platforms and hundreds of ad channel connectors, which eliminates the custom engineering project.
The cutover window is the highest-risk period. Validate these specifics in writing before signing:
Your CFO will ask for NGR by channel, contribution margin by cohort, and CAC:LTV by region at the first leadership review. A platform that can only answer marketing questions will not survive it.
Validate that the platform produces NGR-based attribution, contribution margin by channel, CAC:LTV by cohort, and region-level segmentation for multi-state operators as core outputs, not custom report requests.
Intelitics is built to bridge the CMO-CFO gap with finance-grade metrics as a core output, not an add-on.
Most operators are not measuring the wrong things. They are measuring the right things with the wrong tools. CPA and install volume are not useless; they are just incomplete without the revenue layer that connects them to actual player value.
Three steps to move forward:
If you are running multi-channel acquisition across paid media and affiliates and need a single platform that connects spend to player value without a custom data engineering project, schedule a demo with Intelitics to see how operators connect every marketing dollar to predicted revenue and profit.