How to Build Effective MMP Reporting Dashboards (2025)

Most MMP dashboards show everything and reveal nothing.

You log in to see 47 metrics, 12 charts, and endless rows of campaign data. Five minutes later, you're still trying to answer a simple question: are my campaigns working?

Effective dashboards don't show all available data. They surface the specific insights needed to make decisions.

Here's how to build MMP reporting dashboards that actually drive better growth outcomes.

The Problem with Default Dashboards

MMPs provide powerful reporting capabilities, but out-of-the-box dashboards are generic.

They're designed to work for any app in any vertical with any business model. That means they include metrics that don't matter for your specific use case and bury the ones that do.

Common issues with default dashboards:

• Too many metrics with no clear priority
• No time-based comparisons (are things getting better or worse?)
• Missing context (is 30% D7 retention good for your category?)
• No audience segmentation (executive view vs growth team view)
• Disconnected from decision-making workflows

The fix isn't more data. It's more focused data structured around the decisions you need to make.

Dashboard Design Principles

Before building dashboards, establish core principles:

Principle 1: Audience-Specific

Different stakeholders need different views:

Executive dashboard: High-level metrics, trends, and efficiency ratios Growth team dashboard: Campaign performance, cohort analysis, and optimization levers Finance dashboard: Spend, CAC, payback period, and unit economics Product dashboard: User quality by source, retention, and in-app behavior

Don't try to build one dashboard for everyone. Build multiple focused dashboards.

Principle 2: Decision-Oriented

Every metric should connect to a decision.

If you track "impressions" but never use that number to make budget or creative decisions, remove it. If you track "Day 1 retention by source" and use it to pause low-quality campaigns, keep it prominent.

Ask: "If this metric changes significantly, what action would I take?" If the answer is "nothing," remove it.

Principle 3: Hierarchy and Flow

Structure dashboards top-to-bottom in order of importance:

1. Executive summary: 3-5 top-level metrics
2. Trends: Week-over-week and month-over-month changes
3. Channel breakdown: Performance by source
4. Detailed analysis: Campaign, creative, and cohort-level data

Users should get answers to high-level questions (Is performance improving?) in 3 seconds without scrolling.

Principle 4: Time Comparisons Over Absolutes

Showing "1,000 installs" is less useful than showing "1,000 installs (�15% vs last week)."

Always include time-based context:

• Week-over-week change
• Month-over-month change
• Year-over-year for seasonality

Trends matter more than point-in-time snapshots.

Essential Metrics for Every Dashboard

While specific metrics vary by business model, certain core metrics belong in nearly every MMP dashboard:

Top-Level Metrics (Executive Summary)

Total installs: Absolute count with WoW/MoM change Cost per install (CPI): Blended and by channel Return on ad spend (ROAS): Revenue divided by ad spend Day 7 retention: Percentage of users retained after 7 days Fraud rejection rate: Percentage of installs rejected as fraudulent

These five metrics give a complete snapshot of acquisition health.

Channel Performance Metrics

Installs by source: Volume from each channel (Facebook, TikTok, Google, ASA) CPI by source: Cost efficiency comparison Retention by source: Day 1, Day 7, Day 30 retention rates LTV by source: Projected or realized lifetime value LTV:CAC ratio: Profitability indicator

This shows which channels deliver the best users, not just the most users.

Cohort and User Quality Metrics

Cohort retention curves: Retention over time for each acquisition cohort Cumulative revenue per user: Revenue curves by cohort Conversion rate by source: Percentage of users completing key actions Engagement metrics: Session frequency, time in app, feature usage

These metrics reveal user quality differences across campaigns.

Campaign Optimization Metrics

Campaign-level CPI: Drill-down within each channel Creative performance: CPI and retention by creative variant Targeting performance: Results by audience segment A/B test results: Statistical comparison of variants

For hands-on growth teams making daily optimization decisions.

Dashboard Structure Templates

Template 1: Executive Dashboard

Purpose: Weekly review for leadership Update frequency: Weekly Audience: CEO, CFO, Head of Growth

Structure:

[Header: Week Overview]
- Total Installs: 12,450 (�8% WoW)
- Blended CPI: $4.25 (�5% WoW)
- ROAS: 2.3x (�0.2 WoW)
- D7 Retention: 32% (� flat WoW)

[Chart: Install Trend]
Line chart showing daily installs over past 90 days

[Table: Channel Summary]
Source | Installs | CPI | D7 Retention | LTV | LTV:CAC
Facebook | 5,200 | $4.50 | 30% | $18.50 | 4.1x
TikTok | 4,100 | $3.80 | 28% | $14.20 | 3.7x
Google | 2,150 | $5.20 | 38% | $22.10 | 4.3x
ASA | 1,000 | $3.50 | 42% | $24.00 | 6.9x

[Chart: Cohort Performance]
Retention curves for weekly cohorts over past 8 weeks

This gives executives everything they need in 30 seconds: overall performance, trends, and channel efficiency.

Template 2: Growth Team Dashboard

Purpose: Daily campaign monitoring and optimization Update frequency: Real-time or daily Audience: Growth marketers, UA managers

Structure:

[Today's Performance]
- Installs (today): 1,845
- Spend (today): $7,830
- CPI (today): $4.24

[Active Campaign Performance]
Campaign | Status | Installs | CPI | D1 Retention | Action
FB_Prospecting_Jan | Active | 450 | $4.10 | 35% |  Performing
TT_Lookalike_v2 | Active | 380 | $3.95 | 29% | � Low retention
Google_Search | Active | 220 | $6.50 | 42% |  High quality
FB_Retargeting | Active | 180 | $3.20 | 38% |  Scale up

[Fraud Alerts]
- TikTok campaign "TT_Lookalike_v2": 35% fraud rejection rate (investigate)

[Creative Performance - Last 7 Days]
Creative | Impressions | Installs | CPI | D1 Retention
Creative_A | 450K | 920 | $3.80 | 38%
Creative_B | 380K | 680 | $4.20 | 31%
Creative_C | 290K | 450 | $5.10 | 28%

Action: Scale Creative_A, pause Creative_C

This dashboard is action-oriented. Every section connects to a specific optimization decision.

Template 3: Cohort Analysis Dashboard

Purpose: Understanding user quality and LTV by source Update frequency: Weekly Audience: Growth team, product team, finance

Structure:

[Cohort Retention Comparison]
Chart: Retention curves for cohorts by source
Lines: Facebook, TikTok, Google, ASA, Organic

[Revenue by Cohort]
Chart: Cumulative revenue per user over 90 days
Segmented by acquisition source

[Weekly Cohort Summary]
Week | Source | Cohort Size | D7 Ret | D30 Ret | Revenue/User (D30) | Projection
Jan 1-7 | Facebook | 3,200 | 32% | 18% | $12.50 | $38.20
Jan 1-7 | TikTok | 2,800 | 28% | 14% | $9.80 | $28.50
Jan 1-7 | Google | 1,400 | 39% | 24% | $16.20 | $48.60

[Payback Analysis]
Source | CAC | D30 Revenue | Days to Payback
Facebook | $4.50 | $12.50 | 42 days
TikTok | $3.80 | $9.80 | 48 days
Google | $5.20 | $16.20 | 38 days

This reveals which sources deliver sustainable, profitable growth.

Template 4: Finance Dashboard

Purpose: Budget tracking and unit economics Update frequency: Daily spend updates, weekly cohort updates Audience: CFO, finance team, investors

Structure:

[Spend Summary]
- MTD Spend: $235,000 / $300,000 budget (78%)
- Projected Month-End Spend: $298,500
- Variance: $1,500 under budget

[Unit Economics]
- Blended CAC: $4.25
- LTV (90-day): $42.50
- LTV:CAC: 10.0x
- Payback Period: 45 days

[Spend by Channel]
Channel | MTD Spend | % of Total | CPI | LTV:CAC | ROI
Facebook | $105,000 | 45% | $4.50 | 8.9x | 789%
TikTok | $78,000 | 33% | $3.80 | 7.5x | 650%
Google | $42,000 | 18% | $5.20 | 9.3x | 830%
ASA | $10,000 | 4% | $3.50 | 13.7x | 1270%

[Cohort Payback Tracking]
Cohort | CAC | D30 Rev | D60 Rev | D90 Rev | Payback Status
Dec Week 1 | $4.30 | $11.20 | $24.80 | $41.50 |  Paid back
Dec Week 2 | $4.45 | $10.90 | $23.50 | $39.20 |  Paid back
Dec Week 3 | $4.60 | $11.40 | $24.10 | In progress | Tracking

Finance-focused dashboards emphasize budget pacing, unit economics, and payback.

Building Dashboards in Your MMP

AppsFlyer Dashboards

AppsFlyer offers customizable dashboards with drag-and-drop widgets.

Key features:

• Cohort reports
• Retention analysis
• Revenue tracking
• Fraud rejection visibility
• Custom grouping dimensions

Best practices:

• Create separate dashboards for different audiences
• Use "Favorites" to save commonly used report configurations
• Set up scheduled email reports for weekly stakeholder updates
• Export to Google Sheets or Data Locker for advanced analysis

Adjust Dashboards

Adjust provides dashboard builder with Growth Copilot (AI-powered natural language queries).

Key features:

• Ask questions in plain English ("What's my CPI from Facebook this week?")
• Customizable metric cards
• Cohort visualization
• Fraud analytics dashboard
• SKAdNetwork-specific reports

Best practices:

• Use Growth Copilot for ad-hoc analysis
• Create templated dashboards for recurring reporting needs
• Integrate with BI tools via Adjust's data export features
• Leverage Adjust's built-in benchmarks for context

Branch Dashboards

Branch dashboards focus on deep link performance and user routing.

Key features:

• Link-level analytics
• Deep link attribution
• Channel comparison
• Audience syncing performance

Best practices:

• Create separate views for paid acquisition vs organic/referral
• Track deep link conversion funnels
• Monitor link click-to-install rates
• Use Branch's Quick Links dashboard for campaign tracking

Exporting to BI Tools

Native MMP dashboards work for most use cases, but exporting to BI tools offers advantages:

When to Use BI Tools

Combine multiple data sources: MMP + revenue + product analytics + customer support Advanced calculations: Custom LTV models, cohort forecasting, contribution margin analysis Automated reporting: Scheduled PDF reports or Slack notifications Historical trends: Multi-year trend analysis beyond MMP's data retention

Popular BI Tool Integrations

Looker: Native integrations with Adjust, AppsFlyer, Singular Tableau: Connect via API or data warehouse exports Mode Analytics: SQL-based analysis on exported MMP data Google Data Studio: Free option with connector support

Most MMPs support BigQuery, Redshift, or Snowflake exports for BI tool integration.

Dashboard Maintenance

Dashboards decay without maintenance.

Monthly Review

Once per month, audit your dashboards:

• Are all metrics still relevant?
• Do stakeholders use all sections?
• Are there new questions that need new metrics?
• Can any metrics be removed?

Remove unused metrics. Add new ones based on evolving business needs.

Version Control

When you change dashboard structure, save the old version.

If stakeholders are used to a specific layout, sudden changes create confusion. Give advance notice and offer training on new dashboard formats.

Documentation

Document what each metric means and how it's calculated.

"D7 Retention" seems obvious but might be calculated as:

• Users who return exactly on Day 7
• Users who return any time during Day 7
• Users who return by Day 7 (D0-D7)

Clarify definitions to prevent misinterpretation.

Common Dashboard Mistakes

Mistake 1: Too Many Metrics

If your dashboard has 30+ metrics, no one knows which ones matter.

Limit to 8-12 core metrics. Create separate detailed dashboards for deep dives.

Mistake 2: No Benchmarks or Context

Showing "25% Day 7 retention" is meaningless without context.

Add benchmarks: "25% D7 retention (category avg: 22%, our goal: 28%)"

Mistake 3: Static Time Periods

Dashboards that only show "last 7 days" miss trends.

Include multiple time comparisons: last 7 days, last 30 days, WoW change, MoM change.

Mistake 4: No Clear Action Items

Data without action is just noise.

Include recommendations directly in dashboards: "TikTok CPI up 25% WoW � Review creative fatigue"

Mistake 5: Ignoring Mobile Optimization

Growth teams check dashboards on mobile during commutes or between meetings.

Ensure dashboards are mobile-responsive or create mobile-specific views.

Automation and Alerts

Don't rely on manual dashboard checks to catch issues.

Set Up Automated Alerts

Configure alerts for:

• CPI increases >20% day-over-day
• Retention drops >15% week-over-week
• Fraud rejection rates >30%
• Daily spend exceeding budget
• Campaign delivery issues (zero installs for 24+ hours)

Alerts notify you immediately when something breaks, rather than discovering it during weekly reviews.

Scheduled Reports

Set up automated weekly reports sent to stakeholders every Monday morning.

This creates accountability and ensures consistent visibility even when people don't proactively check dashboards.

FAQs

What metrics should be in an MMP dashboard?

Essential metrics include total installs, cost per install (CPI), retention rates (D1, D7, D30), lifetime value (LTV), return on ad spend (ROAS), fraud rejection rate, and channel-specific performance. Focus on 5-8 core metrics rather than overwhelming dashboards with 20+ data points.

How often should I check my MMP dashboard?

Daily for active campaigns to catch performance issues early. Weekly for strategic reviews and budget reallocation. Monthly for cohort analysis and LTV trends. Set up automated alerts for significant changes in key metrics.

Should I build dashboards in my MMP or export to BI tools?

Use native MMP dashboards for daily campaign monitoring. Export to BI tools (Looker, Tableau, Mode) when you need to combine MMP data with revenue, product analytics, or other business data for comprehensive analysis.

How many dashboards should I create?

Create separate dashboards for each audience: executive dashboard, growth team dashboard, finance dashboard, and cohort analysis dashboard. Most teams need 3-5 focused dashboards rather than one catch-all view.

What's the best way to share dashboards with stakeholders?

For technical stakeholders, provide direct MMP access with role-based permissions. For non-technical stakeholders, schedule automated weekly email reports with key metrics and trends. For executives, create simplified summary views with high-level insights only.

---

Effective MMP dashboards don't show all available datathey surface the right data to support specific decisions. By building audience-specific dashboards with clear hierarchies, time comparisons, and actionable insights, you transform raw attribution data into strategic growth intelligence.