Best Practices

Recommended setup

Match dimensions to your reporting hierarchy

Adjust supports full campaign hierarchy: network → campaign → adgroup → creative. Only go as deep as you actually use — adding creative-level dimensions to a high-level report inflates row counts without adding useful signal.

Use additional metrics for custom events

If you've set up app-specific events in Adjust (like "level_complete" or "subscription_start"), add them in the Additional metrics field. These won't appear in the standard metric picker but are fully supported by the API.

Separate cohort and non-cohort reports

Cohort metrics measure a user group's behavior over time from their install date, while standard metrics reflect activity in the report period. Mixing them in one report often produces confusing results — create separate data flows for each use case.

Data refresh and scheduling

Account for attribution windows

Adjust attribution windows can be up to 7 days (or longer for view-through). Data for recent dates may still be incomplete. Include a few days of overlap in your start date to catch late-attributed installs on subsequent refreshes.

Append historical data, don't re-pull everything

Once data older than your attribution window is settled, it won't change. Use Coupler.io's Append transformation to add new date ranges on top of existing data rather than re-exporting your full history each run.

Performance optimization

Limit dimension combinations for large date ranges

Adding 4–5 dimensions to a 90-day report across many networks can generate thousands of rows and slow down the API response. For long-range historical pulls, use fewer dimensions or split into multiple data flows by time period.

Use country_code instead of country for joins

If you're joining Adjust data with other sources (like ad spend from Facebook or Google), use `country_code` rather than `country` as the join key — standardized ISO codes are far more reliable than country name strings across platforms.

Common pitfalls

Don't mix revenue and all_revenue in the same analysis without understanding the difference. revenue covers IAP only; all_revenue adds ad revenue on top. Using both in a single report without labeling them clearly leads to double-counting errors in dashboards.

Do

• Select only the dimensions relevant to your analysis
• Use network_cost_diff to monitor discrepancies between Adjust and network reporting
• Create separate data flows for campaign-level and creative-level reporting
• Use country_code as a join key when combining with other data sources

Don't

• Mix cohort and non-cohort metrics in the same report
• Pull full historical data on every refresh — use Append for incremental updates
• Forget that paid_installs excludes organic — use installs if you need the full picture
• Run multiple large Adjust data flows simultaneously — you may hit rate limits