Vertical network selection
Best Ad Network for App Install: Selection Guide
Evaluate best ad network for app-install through source transparency, controlled testing, complete measurement and accepted downstream value.
Purpose of this guide
A focused decision resource
Use this page when you need to evaluate ad-network requirements, controls and evidence for app install. The recommendations, examples and measurement rules are scoped to that decision. For a broader or adjacent decision, use App Install Ad Network.
Direct answer
What this page helps an advertiser decide
For mobile app install campaigns, begin with the business decision, not the delivery metric. Assign app install audience fit to a named owner and state what evidence changes a bid, budget, source status or pause decision. Keep the definition fixed through the observation window. The useful output is a documented network choice for mobile app install campaigns supported by matched campaign evidence and retained user value, while early clicks and visits remain supporting signals rather than the final proof.
Intent ownership
Search intent and cannibalization boundary
This canonical owns one distinct advertiser decision while broader strategy remains on established pillar URLs.
| Layer | Owner | Boundary |
|---|---|---|
| Primary page intent | Best Ad Network For App-Install | Owns the specific commercial decision for best ad network for app-install. Broad traffic purchase intent remains on /buy-website-traffic/ and parent strategy remains on /app-install-advertising/. |
| Parent intent | App Install Advertising | Definitions, broad category strategy and adjacent choices remain on the parent page. |
| Success definition | a documented network choice for mobile app install campaigns supported by matched campaign evidence and retained user value | Visits and clicks remain diagnostic until downstream acceptance is confirmed. |
Operating framework
A visual system for evidence-led campaign decisions
Connect eligibility, source, journey, measurement and rollback before the campaign buys scale.
A practical review of best ad network for app-install must account for stale rankings, unsupported winner claims, unequal campaign settings, hidden source mix, weak tracking, policy mismatch and choosing on front-end volume alone. Document each material difference instead of hiding it inside a blended average. If settings, eligibility or source mix cannot be matched, record that limitation in the decision memo. A narrow result that can be reproduced is more valuable than a broad claim that cannot survive a second test.
Before spending on best ad network for app-install, write the exact audience, country, device, format, destination and policy boundary. This prevents the campaign from drifting toward easier but less valuable delivery. During GEO and device comparison, compare like with like and preserve the original control. Any necessary exception should be visible in the final report with its reason and likely effect.
Operator guide
Build the decision from requirements to accepted value
Use the detailed checks below to keep the campaign measurable, comparable and reversible.
Define the exact best ad network for app-install decision
For the app install network shortlist scenario, isolate the smallest set of variables that can answer the question. Hold the accepted event, attribution window and destination logic steady. Change one bid, audience, source group or creative family at a time. If the result deteriorates, return to the last stable configuration rather than widening targeting to recover volume.
Operational fit belongs in the economics of best ad network for app-install. Count setup effort, moderation, reporting exports, tracking work, source review and troubleshooting alongside media cost. Evaluate policy and eligibility with the same seriousness as delivery volume. A channel that appears cheaper may be less efficient when the team cannot identify sources or reconcile outcomes without manual repair.
Match campaign conditions before comparing sources
Operational fit belongs in the economics of best ad network for app-install. Count setup effort, moderation, reporting exports, tracking work, source review and troubleshooting alongside media cost. Evaluate policy and eligibility with the same seriousness as delivery volume. A channel that appears cheaper may be less efficient when the team cannot identify sources or reconcile outcomes without manual repair.
For the GEO and device comparison scenario, isolate the smallest set of variables that can answer the question. Hold the accepted event, attribution window and destination logic steady. Change one bid, audience, source group or creative family at a time. If the result deteriorates, return to the last stable configuration rather than widening targeting to recover volume.
Build an equal evidence window for mobile app install campaigns
For the GEO and device comparison scenario, isolate the smallest set of variables that can answer the question. Hold the accepted event, attribution window and destination logic steady. Change one bid, audience, source group or creative family at a time. If the result deteriorates, return to the last stable configuration rather than widening targeting to recover volume.
Map the operational chain as eligible audience exposure to install and activation to retained user value. Preserve campaign, creative, source, device and GEO identifiers wherever the journey permits. Review install and activation attribution separately from unit economics and retention so one strong average cannot conceal a weak segment. Reconcile front-end activity with the accepted business record before declaring the test successful or increasing spend.
Compare source mix instead of blended averages
Map the operational chain as eligible audience exposure to install and activation to retained user value. Preserve campaign, creative, source, device and GEO identifiers wherever the journey permits. Review install and activation attribution separately from unit economics and retention so one strong average cannot conceal a weak segment. Reconcile front-end activity with the accepted business record before declaring the test successful or increasing spend.
Treat app install network shortlist as a bounded experiment. Set a daily ceiling, a total loss limit, a minimum evidence window and a rollback point before launch. New sources begin in an uncertain state and earn promotion through the same rule. When sample size is thin, keep the decision open rather than forcing a winner from unstable data.
Keep creative fairness without forcing identical assets
Treat app install network shortlist as a bounded experiment. Set a daily ceiling, a total loss limit, a minimum evidence window and a rollback point before launch. New sources begin in an uncertain state and earn promotion through the same rule. When sample size is thin, keep the decision open rather than forcing a winner from unstable data.
For the install and activation campaign test scenario, isolate the smallest set of variables that can answer the question. Hold the accepted event, attribution window and destination logic steady. Change one bid, audience, source group or creative family at a time. If the result deteriorates, return to the last stable configuration rather than widening targeting to recover volume.
Reconcile attribution before choosing a source
For the install and activation campaign test scenario, isolate the smallest set of variables that can answer the question. Hold the accepted event, attribution window and destination logic steady. Change one bid, audience, source group or creative family at a time. If the result deteriorates, return to the last stable configuration rather than widening targeting to recover volume.
Operational fit belongs in the economics of best ad network for app-install. Count setup effort, moderation, reporting exports, tracking work, source review and troubleshooting alongside media cost. Evaluate app install audience fit with the same seriousness as delivery volume. A channel that appears cheaper may be less efficient when the team cannot identify sources or reconcile outcomes without manual repair.
Include policy and operational fit in the decision
Operational fit belongs in the economics of best ad network for app-install. Count setup effort, moderation, reporting exports, tracking work, source review and troubleshooting alongside media cost. Evaluate app install audience fit with the same seriousness as delivery volume. A channel that appears cheaper may be less efficient when the team cannot identify sources or reconcile outcomes without manual repair.
For mobile app install campaigns, begin with the business decision, not the delivery metric. Assign policy and eligibility to a named owner and state what evidence changes a bid, budget, source status or pause decision. Keep the definition fixed through the observation window. The useful output is a documented network choice for mobile app install campaigns supported by matched campaign evidence and retained user value, while early clicks and visits remain supporting signals rather than the final proof.
Write a limited and reproducible conclusion
For mobile app install campaigns, begin with the business decision, not the delivery metric. Assign policy and eligibility to a named owner and state what evidence changes a bid, budget, source status or pause decision. Keep the definition fixed through the observation window. The useful output is a documented network choice for mobile app install campaigns supported by matched campaign evidence and retained user value, while early clicks and visits remain supporting signals rather than the final proof.
A practical review of best ad network for app-install must account for stale rankings, unsupported winner claims, unequal campaign settings, hidden source mix, weak tracking, policy mismatch and choosing on front-end volume alone. Document each material difference instead of hiding it inside a blended average. If settings, eligibility or source mix cannot be matched, record that limitation in the decision memo. A narrow result that can be reproduced is more valuable than a broad claim that cannot survive a second test.
Intent-specific audit
Four checks tied to this exact advertiser problem
These checks stop broad platform assumptions from distorting this specific search intent.
Confirm app install audience fit before launch
Use source transparency as an action layer. Define the evidence threshold, the person responsible for review, the permitted response and the condition that restores the previous configuration. Pair it with retained user value quality to confirm that improvement is not simply a change in traffic composition. Scale only after the accepted outcome remains stable through the required validation period.
Keep policy and eligibility visible
For mobile app install campaigns, begin with the business decision, not the delivery metric. Assign install and activation attribution to a named owner and state what evidence changes a bid, budget, source status or pause decision. Keep the definition fixed through the observation window. The useful output is a documented network choice for mobile app install campaigns supported by matched campaign evidence and retained user value, while early clicks and visits remain supporting signals rather than the final proof.
Validate retained user value quality independently
For the app install network shortlist scenario, isolate the smallest set of variables that can answer the question. Hold the accepted event, attribution window and destination logic steady. Change one bid, audience, source group or creative family at a time. If the result deteriorates, return to the last stable configuration rather than widening targeting to recover volume.
Tie unit economics and retention to the final memo
Treat install and activation campaign test as a bounded experiment. Set a daily ceiling, a total loss limit, a minimum evidence window and a rollback point before launch. New sources begin in an uncertain state and earn promotion through the same rule. When sample size is thin, keep the decision open rather than forcing a winner from unstable data.
Buyer framework
Six controls before the campaign buys scale
Each control must lead to an observable decision rather than a decorative report.
App Install Audience Fit
Source governance matters because mobile app install campaigns can change as budgets, bids and inventory conditions move. Classify sources as new, uncertain, promising, reduced or excluded. Apply one promotion rule and one exclusion rule across the test. Recheck app install audience fit after every material scale step, because a winning average may weaken when the source portfolio expands.
Evidence → owner → action → rollbackPolicy And Eligibility
Treat install and activation campaign test as a bounded experiment. Set a daily ceiling, a total loss limit, a minimum evidence window and a rollback point before launch. New sources begin in an uncertain state and earn promotion through the same rule. When sample size is thin, keep the decision open rather than forcing a winner from unstable data.
Evidence → owner → action → rollbackSource Transparency
Map the operational chain as eligible audience exposure to install and activation to retained user value. Preserve campaign, creative, source, device and GEO identifiers wherever the journey permits. Review source transparency separately from retained user value quality so one strong average cannot conceal a weak segment. Reconcile front-end activity with the accepted business record before declaring the test successful or increasing spend.
Evidence → owner → action → rollbackInstall And Activation Attribution
A practical review of best ad network for app-install must account for stale rankings, unsupported winner claims, unequal campaign settings, hidden source mix, weak tracking, policy mismatch and choosing on front-end volume alone. Document each material difference instead of hiding it inside a blended average. If settings, eligibility or source mix cannot be matched, record that limitation in the decision memo. A narrow result that can be reproduced is more valuable than a broad claim that cannot survive a second test.
Evidence → owner → action → rollbackRetained User Value Quality
Use retained user value quality as an action layer. Define the evidence threshold, the person responsible for review, the permitted response and the condition that restores the previous configuration. Pair it with app install audience fit to confirm that improvement is not simply a change in traffic composition. Scale only after the accepted outcome remains stable through the required validation period.
Evidence → owner → action → rollbackUnit Economics And Retention
Source governance matters because mobile app install campaigns can change as budgets, bids and inventory conditions move. Classify sources as new, uncertain, promising, reduced or excluded. Apply one promotion rule and one exclusion rule across the test. Recheck unit economics and retention after every material scale step, because a winning average may weaken when the source portfolio expands.
Evidence → owner → action → rollbackWorkflow
An eight-step campaign operating sequence
Move from business definition to controlled scale without losing the source-to-outcome record.
- 01
Define the accepted event
The measurement plan should connect raw delivery to a documented network choice for mobile app install campaigns supported by matched campaign evidence and retained user value. Record eligible exposure, source distribution, landing continuity, conversion status and downstream acceptance in separate layers. Use policy and eligibility to diagnose where value is gained or lost. Do not let a lower cost per click override evidence that the final business event is weaker or less repeatable.
- 02
Verify eligibility and policy fit
For the GEO and device comparison scenario, isolate the smallest set of variables that can answer the question. Hold the accepted event, attribution window and destination logic steady. Change one bid, audience, source group or creative family at a time. If the result deteriorates, return to the last stable configuration rather than widening targeting to recover volume.
- 03
Map the complete user journey
Source governance matters because mobile app install campaigns can change as budgets, bids and inventory conditions move. Classify sources as new, uncertain, promising, reduced or excluded. Apply one promotion rule and one exclusion rule across the test. Recheck install and activation attribution after every material scale step, because a winning average may weaken when the source portfolio expands.
- 04
Create decision cells
Before spending on best ad network for app-install, write the exact audience, country, device, format, destination and policy boundary. This prevents the campaign from drifting toward easier but less valuable delivery. During app install network shortlist, compare like with like and preserve the original control. Any necessary exception should be visible in the final report with its reason and likely effect.
- 05
Launch a bounded test
Operational fit belongs in the economics of best ad network for app-install. Count setup effort, moderation, reporting exports, tracking work, source review and troubleshooting alongside media cost. Evaluate unit economics and retention with the same seriousness as delivery volume. A channel that appears cheaper may be less efficient when the team cannot identify sources or reconcile outcomes without manual repair.
- 06
Classify sources consistently
The measurement plan should connect raw delivery to a documented network choice for mobile app install campaigns supported by matched campaign evidence and retained user value. Record eligible exposure, source distribution, landing continuity, conversion status and downstream acceptance in separate layers. Use app install audience fit to diagnose where value is gained or lost. Do not let a lower cost per click override evidence that the final business event is weaker or less repeatable.
- 07
Validate downstream quality
The measurement plan should connect raw delivery to a documented network choice for mobile app install campaigns supported by matched campaign evidence and retained user value. Record eligible exposure, source distribution, landing continuity, conversion status and downstream acceptance in separate layers. Use policy and eligibility to diagnose where value is gained or lost. Do not let a lower cost per click override evidence that the final business event is weaker or less repeatable.
- 08
Scale one reversible variable
Source governance matters because mobile app install campaigns can change as budgets, bids and inventory conditions move. Classify sources as new, uncertain, promising, reduced or excluded. Apply one promotion rule and one exclusion rule across the test. Recheck source transparency after every material scale step, because a winning average may weaken when the source portfolio expands.
Measurement model
Measure the complete path, not the cheapest activity
Delivery layer
Map the operational chain as eligible audience exposure to install and activation to retained user value. Preserve campaign, creative, source, device and GEO identifiers wherever the journey permits. Review app install audience fit separately from source transparency so one strong average cannot conceal a weak segment. Reconcile front-end activity with the accepted business record before declaring the test successful or increasing spend.
Journey layer
Use policy and eligibility as an action layer. Define the evidence threshold, the person responsible for review, the permitted response and the condition that restores the previous configuration. Pair it with install and activation attribution to confirm that improvement is not simply a change in traffic composition. Scale only after the accepted outcome remains stable through the required validation period.
Acceptance layer
Use source transparency as an action layer. Define the evidence threshold, the person responsible for review, the permitted response and the condition that restores the previous configuration. Pair it with retained user value quality to confirm that improvement is not simply a change in traffic composition. Scale only after the accepted outcome remains stable through the required validation period.
Economics layer
Operational fit belongs in the economics of best ad network for app-install. Count setup effort, moderation, reporting exports, tracking work, source review and troubleshooting alongside media cost. Evaluate install and activation attribution with the same seriousness as delivery volume. A channel that appears cheaper may be less efficient when the team cannot identify sources or reconcile outcomes without manual repair.
Evidence scorecard
Evidence required for each control
Score only evidence that can change a real campaign action.
| Control | Evidence | Decision |
|---|---|---|
| App Install Audience Fit | Build the scorecard around decisions the team is prepared to execute. App Install Audience Fit requires a defined owner, evidence window and stop rule; source transparency confirms whether the change survives beyond the front-end metric. Unknown values should stay unknown until measured. Estimating missing evidence merely to complete a table creates false confidence and weakens later optimization. | Keep, reduce, test, exclude or scale under the documented rule. |
| Policy And Eligibility | Finish with a dated decision memo for mobile app install campaigns. State the tested scope, evidence window, excluded variables, source distribution, accepted result and rollback trigger. Explain how policy and eligibility affected the conclusion and what new evidence would overturn it. This keeps the outcome useful after inventory, policy, pricing or campaign conditions change. | Keep, reduce, test, exclude or scale under the documented rule. |
| Source Transparency | For the GEO and device comparison scenario, isolate the smallest set of variables that can answer the question. Hold the accepted event, attribution window and destination logic steady. Change one bid, audience, source group or creative family at a time. If the result deteriorates, return to the last stable configuration rather than widening targeting to recover volume. | Keep, reduce, test, exclude or scale under the documented rule. |
| Install And Activation Attribution | Use install and activation attribution as an action layer. Define the evidence threshold, the person responsible for review, the permitted response and the condition that restores the previous configuration. Pair it with unit economics and retention to confirm that improvement is not simply a change in traffic composition. Scale only after the accepted outcome remains stable through the required validation period. | Keep, reduce, test, exclude or scale under the documented rule. |
| Retained User Value Quality | The measurement plan should connect raw delivery to a documented network choice for mobile app install campaigns supported by matched campaign evidence and retained user value. Record eligible exposure, source distribution, landing continuity, conversion status and downstream acceptance in separate layers. Use retained user value quality to diagnose where value is gained or lost. Do not let a lower cost per click override evidence that the final business event is weaker or less repeatable. | Keep, reduce, test, exclude or scale under the documented rule. |
| Unit Economics And Retention | Operational fit belongs in the economics of best ad network for app-install. Count setup effort, moderation, reporting exports, tracking work, source review and troubleshooting alongside media cost. Evaluate unit economics and retention with the same seriousness as delivery volume. A channel that appears cheaper may be less efficient when the team cannot identify sources or reconcile outcomes without manual repair. | Keep, reduce, test, exclude or scale under the documented rule. |
Practical scenarios
Four practical ways to use this framework
Adapt the framework to a bounded business problem without changing the underlying evidence rules.
App Install Network Shortlist
Map the operational chain as eligible audience exposure to install and activation to retained user value. Preserve campaign, creative, source, device and GEO identifiers wherever the journey permits. Review install and activation attribution separately from unit economics and retention so one strong average cannot conceal a weak segment. Reconcile front-end activity with the accepted business record before declaring the test successful or increasing spend.
Install And Activation Campaign Test
Map the operational chain as eligible audience exposure to install and activation to retained user value. Preserve campaign, creative, source, device and GEO identifiers wherever the journey permits. Review retained user value quality separately from app install audience fit so one strong average cannot conceal a weak segment. Reconcile front-end activity with the accepted business record before declaring the test successful or increasing spend.
Geo And Device Comparison
Use unit economics and retention as an action layer. Define the evidence threshold, the person responsible for review, the permitted response and the condition that restores the previous configuration. Pair it with policy and eligibility to confirm that improvement is not simply a change in traffic composition. Scale only after the accepted outcome remains stable through the required validation period.
Retained User Value Quality Review
Operational fit belongs in the economics of best ad network for app-install. Count setup effort, moderation, reporting exports, tracking work, source review and troubleshooting alongside media cost. Evaluate app install audience fit with the same seriousness as delivery volume. A channel that appears cheaper may be less efficient when the team cannot identify sources or reconcile outcomes without manual repair.
Stop rules
Write the stop rules before the campaign starts
Build the scorecard around decisions the team is prepared to execute. App Install Audience Fit requires a defined owner, evidence window and stop rule; source transparency confirms whether the change survives beyond the front-end metric. Unknown values should stay unknown until measured. Estimating missing evidence merely to complete a table creates false confidence and weakens later optimization.
The measurement plan should connect raw delivery to a documented network choice for mobile app install campaigns supported by matched campaign evidence and retained user value. Record eligible exposure, source distribution, landing continuity, conversion status and downstream acceptance in separate layers. Use policy and eligibility to diagnose where value is gained or lost. Do not let a lower cost per click override evidence that the final business event is weaker or less repeatable.
Operational fit belongs in the economics of best ad network for app-install. Count setup effort, moderation, reporting exports, tracking work, source review and troubleshooting alongside media cost. Evaluate source transparency with the same seriousness as delivery volume. A channel that appears cheaper may be less efficient when the team cannot identify sources or reconcile outcomes without manual repair.
Failure modes
What to prevent before more budget enters the campaign
Measurement drift
Map the operational chain as eligible audience exposure to install and activation to retained user value. Preserve campaign, creative, source, device and GEO identifiers wherever the journey permits. Review policy and eligibility separately from install and activation attribution so one strong average cannot conceal a weak segment. Reconcile front-end activity with the accepted business record before declaring the test successful or increasing spend.
Source-mix illusion
For the GEO and device comparison scenario, isolate the smallest set of variables that can answer the question. Hold the accepted event, attribution window and destination logic steady. Change one bid, audience, source group or creative family at a time. If the result deteriorates, return to the last stable configuration rather than widening targeting to recover volume.
Irreversible scale
Before spending on best ad network for app-install, write the exact audience, country, device, format, destination and policy boundary. This prevents the campaign from drifting toward easier but less valuable delivery. During retained user value quality review, compare like with like and preserve the original control. Any necessary exception should be visible in the final report with its reason and likely effect.
Unsupported winner claims
Source governance matters because mobile app install campaigns can change as budgets, bids and inventory conditions move. Classify sources as new, uncertain, promising, reduced or excluded. Apply one promotion rule and one exclusion rule across the test. Recheck app install audience fit after every material scale step, because a winning average may weaken when the source portfolio expands.
Limits and compliance
Use realistic expectations and responsible controls
Traffic-quality controls can reduce risk but cannot eliminate every invalid interaction. Approval, inventory, delivery and results depend on campaign details, policy, GEO, format, bid, creative, destination, tracking and optimization. No page should be interpreted as a guarantee of traffic quality, conversions, ROI, ranking, approval or business performance.
For the retained user value quality review scenario, isolate the smallest set of variables that can answer the question. Hold the accepted event, attribution window and destination logic steady. Change one bid, audience, source group or creative family at a time. If the result deteriorates, return to the last stable configuration rather than widening targeting to recover volume.
Frequently asked questions
Questions about best ad network for app-install
What should advertisers evaluate in a best ad network for app-install?
The measurement plan should connect raw delivery to a documented network choice for mobile app install campaigns supported by matched campaign evidence and retained user value. Record eligible exposure, source distribution, landing continuity, conversion status and downstream acceptance in separate layers. Use retained user value quality to diagnose where value is gained or lost. Do not let a lower cost per click override evidence that the final business event is weaker or less repeatable.
How much budget should a first best ad network for app-install test use?
For mobile app install campaigns, begin with the business decision, not the delivery metric. Assign unit economics and retention to a named owner and state what evidence changes a bid, budget, source status or pause decision. Keep the definition fixed through the observation window. The useful output is a documented network choice for mobile app install campaigns supported by matched campaign evidence and retained user value, while early clicks and visits remain supporting signals rather than the final proof.
Which metric matters most for best ad network for app-install?
Finish with a dated decision memo for mobile app install campaigns. State the tested scope, evidence window, excluded variables, source distribution, accepted result and rollback trigger. Explain how app install audience fit affected the conclusion and what new evidence would overturn it. This keeps the outcome useful after inventory, policy, pricing or campaign conditions change.
How should traffic quality be checked?
Use policy and eligibility as an action layer. Define the evidence threshold, the person responsible for review, the permitted response and the condition that restores the previous configuration. Pair it with install and activation attribution to confirm that improvement is not simply a change in traffic composition. Scale only after the accepted outcome remains stable through the required validation period.
Why is source-level reporting important?
Treat app install network shortlist as a bounded experiment. Set a daily ceiling, a total loss limit, a minimum evidence window and a rollback point before launch. New sources begin in an uncertain state and earn promotion through the same rule. When sample size is thin, keep the decision open rather than forcing a winner from unstable data.
How long should the evidence window run?
Use install and activation attribution as an action layer. Define the evidence threshold, the person responsible for review, the permitted response and the condition that restores the previous configuration. Pair it with unit economics and retention to confirm that improvement is not simply a change in traffic composition. Scale only after the accepted outcome remains stable through the required validation period.
When should a source be paused?
Build the scorecard around decisions the team is prepared to execute. Retained User Value Quality requires a defined owner, evidence window and stop rule; app install audience fit confirms whether the change survives beyond the front-end metric. Unknown values should stay unknown until measured. Estimating missing evidence merely to complete a table creates false confidence and weakens later optimization.
Can best ad network for app-install guarantee conversions?
The measurement plan should connect raw delivery to a documented network choice for mobile app install campaigns supported by matched campaign evidence and retained user value. Record eligible exposure, source distribution, landing continuity, conversion status and downstream acceptance in separate layers. Use unit economics and retention to diagnose where value is gained or lost. Do not let a lower cost per click override evidence that the final business event is weaker or less repeatable.
How should a winning cell be scaled?
Operational fit belongs in the economics of best ad network for app-install. Count setup effort, moderation, reporting exports, tracking work, source review and troubleshooting alongside media cost. Evaluate app install audience fit with the same seriousness as delivery volume. A channel that appears cheaper may be less efficient when the team cannot identify sources or reconcile outcomes without manual repair.
What belongs in the final decision memo?
Treat install and activation campaign test as a bounded experiment. Set a daily ceiling, a total loss limit, a minimum evidence window and a rollback point before launch. New sources begin in an uncertain state and earn promotion through the same rule. When sample size is thin, keep the decision open rather than forcing a winner from unstable data.
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