As a long-time user, what I love most is the "set it and forget it" reliability of their attribution.

The Fraud Prevention Suite is the real MVP—it’s saved us thousands by auto-rejecting fake installs before they even hit our reports. Plus, the raw data callbacks are incredibly clean, making it seamless to sync with our internal BI tools. It basically turns a chaotic mess of marketing data into a clear, honest picture of our ROI. Review collected by and hosted on G2.com.

The biggest downsides for me are:

High Cost: The "pay-per-attribution" model is expensive and feels like a tax on your growth.

Too Complex: The setup isn't "plug-and-play." You need a solid technical background or a developer just to get the advanced tracking right.

Rigid Interface: It's powerful but feels less intuitive and "stiff" compared to newer, more user-friendly competitors. Review collected by and hosted on G2.com.

What I love most about Adjust is how it feels like a reliable partner rather than just a tool. It gives me a sense of security because I know my data is protected from fraud and every penny of my budget is well-spent. The interface is so intuitive that it makes my daily work much smoother and less stressful. It truly simplifies the complex world of data, allowing me to focus more on creative growth. To me, Adjust is the single source of truth that I can always count on. Review collected by and hosted on G2.com.

To be honest, Adjust is like a brilliant but strict mentor; its high level of detail can be quite overwhelming at first. Sometimes, navigating the complex settings feels like wandering in a vast forest without a clear map. I also feel a bit heavy-hearted about the cost, which can be a real burden for small teams just starting their journey. The technical documentation is so deep that it sometimes feels like a cold machine rather than a helping hand. I truly love the tool, but I wish it were a bit simpler and more affordable for everyone to reach. Review collected by and hosted on G2.com.

From my experience, the attribution technology works quite reliably in identifying legitimate user sources, which makes it easier to trust the data when evaluating different marketing channels. The UI/UX feels intuitive and fairly easy to navigate, so I didn’t have much trouble getting used to it even at the beginning. I also found the documentation to be detailed enough to follow along without confusion, which is helpful when trying to understand how everything works. As for the reporting feature, it’s simple to use but still provides the key information I need, so I can quickly review performance and make decisions without spending too much time digging around. Review collected by and hosted on G2.com.

There are times when the Adjust reports don’t load as smoothly as expected—they can occasionally be slow or even fail to load, which can be a bit frustrating when you need quick access to data. Also, the pricing feels somewhat on the higher side compared to similar tools, so it might not be the most cost-effective option depending on your budget and scale of use. Review collected by and hosted on G2.com.

I like how easy it is to integrate partners with Adjust and selectively share information when working with external agencies. The add-on features are reasonably priced, making it easy to get budget approval for upgrades. Review collected by and hosted on G2.com.

"Occasionally, we run into technical glitches that are difficult to fix, and sometimes we just have to accept them as they are." Review collected by and hosted on G2.com.

What I like most about Adjust is its accurate attribution and flexible reporting. I regularly use cohort analysis and raw data exports to track ROAS and retention across channels in one place. It saves me hours each week by eliminating manual data consolidation. An unexpected benefit is its debugging tools (like real-time logs and callback validation), which help quickly identify tracking issues. Review collected by and hosted on G2.com.

Reporting can be slow and limited for complex breakdowns, often forcing raw data exports, which slows decision-making. There are also noticeable discrepancies with ad network data (especially revenue), making validation time-consuming. Improving report speed, adding better reconciliation tools, and simplifying event/callback setup would significantly enhance the workflow. Review collected by and hosted on G2.com.

The most helpful part of Adjust is the reliability of its tracking links and deep-linking capabilities. It has vastly improved our workflow by providing a centralized view of all our campaign performances. The reporting tools are robust, allowing us to make data-driven decisions with high confidence. Review collected by and hosted on G2.com.

The learning curve can be somewhat steep for new users who are not familiar with mobile attribution. While the dashboard is powerful, it can feel a bit overwhelming at first due to the sheer amount of data and settings. I think the documentation could be improved with more step-by-step video tutorials for beginners. Review collected by and hosted on G2.com.

API is accessible and well-documented. You can pull any data you need and build automated reports the way it works for your team, not the way the platform wants you to. No need to rely on built-in dashboards or manual exports. Review collected by and hosted on G2.com.

Some features feel hidden behind sales calls. For example, there is an MCP server in beta which looks useful, but to actually get access you have to go through their sales team. Would be better if things like this were just available to try directly. Review collected by and hosted on G2.com.

I use Adjust to track the performance of my app campaigns on Google Ads, TikTok, and Mintegral, mainly focusing on CPI and ROAS.

From my experience, it helps me get a clearer view of performance when running multiple campaigns at the same time.

The main advantage of using Adjust, from my point of view, consists in getting insight into the performance of my campaigns, especially when there are multiple campaigns running simultaneously. Therefore, every day I review my CPI and ROAS metrics in Adjust, changing the budget or bid whenever necessary.

The key advantage lies in the ability to view everything in one dashboard instead of analyzing each ad platform individually, which takes much time and provides more precise results.

Data is updated quite rapidly. Hence, when something goes wrong (e.g., CPI increases drastically or ROAS goes down), I can react quickly. Review collected by and hosted on G2.com.

Initially, there were certain difficulties in understanding how to work with the dashboard since it took some time for me to figure out the way of reading the report and getting precise information.

Moreover, there are certain reports that are difficult to interpret and need additional preparation if you want to get more detailed information about your performance (e.g., performance per events/campaigns). Review collected by and hosted on G2.com.

Real-time data is the biggest win. When running sequenced A/B tests across paywall timing, pricing, and onboarding flows, I can spot underperforming variants and kill them fast instead of waiting for end-of-day reports. This saves budget especially when ROAS is tight.

Datascape makes reporting easy without technical skills. As a PO who also handles UA, I can build tables, filter by campaign/channel, and pull cohort data myself without writing SQL or exporting to Excel. That speed matters when you're a small team. Review collected by and hosted on G2.com.

Too much data without enough guidance on what matters. Adjust gives you a ton of metrics and dimensions, but doesn't do a great job telling you which ones actually matter for your use case. As a small team running utility apps, I don't need 50 breakdowns — I need the 5 that help me decide whether to scale or kill a campaign. A more opinionated default dashboard or "start here" view would go a long way. Review collected by and hosted on G2.com.

Adjust's real-time data accuracy and easy-to-use dashboard make attribution tracking straightforward for our mobile app. The SDK integration with Flutter was smooth, and we rely heavily on the cohort analysis and event tracking to measure campaign ROAS across Meta and Google channels. The fraud prevention features also give us confidence in our data quality, especially for markets like Vietnam where install fraud is common. Review collected by and hosted on G2.com.

The pricing structure is hard to justify for smaller teams — we're a startup with limited UA budget, and the cost feels high relative to our scale. Setting up purchase event mappings with RevenueCat was more complex than expected and required back-and-forth with support to get value and currency parameters forwarded correctly. We also experienced issues with deduplication when both Adjust and RevenueCat fire purchase events, which led to inflated ROAS numbers until we manually disabled one side. More out-of-the-box templates for common subscription app setups (trial → paid, credit IAP) would save significant integration time. Review collected by and hosted on G2.com.