SIGNAL.DUG v18

SIGNAL.DUG — M&A Intelligence

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Genre Heatmap

Publisher Heatmap

Time Window

24 weeks · Jan 2024 – Apr 2026 available

Genre Revenue Heatmap

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What am I looking at?

A weekly performance grid for every mobile gaming genre. Each row is a genre (sorted by latest-week revenue, largest at top). Each cell is one week — colored green (growing) to red (declining) by WoW revenue change. The right-side columns show: current revenue, 4-week average WoW%, and a sparkline trend. Switch between WoW% and absolute revenue using the dropdown.

How to use it: Scan for horizontal green streaks — that's sustained genre momentum, not a one-week spike. A red cell in a green streak is your entry signal (temporary dip in a healthy genre = studios on sale). Example: look at the top-ranked genre for multi-week color patterns to spot where sector momentum lives.

v2_genre_weekly

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Genre Rotation Quadrant

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What am I looking at?

Each bubble is a genre plotted by momentum velocity (X-axis: avg weekly growth over your selected window) and acceleration (Y-axis: is that growth speeding up or slowing down). Bubble size = genre revenue. Genres rotate through four quadrants over time, just like equity sectors.

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momentum x acceleration

Genre Sharpe Ratio

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What am I looking at?

The Sharpe ratio divides a genre's average weekly growth (mu) by its volatility (sigma). A high Sharpe means consistent, reliable growth — not a lucky spike. Genres are ranked by this risk-adjusted signal, not raw momentum.

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vol-adjusted momentum

Multi-Timeframe Relative Strength

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What am I looking at?

For each genre, this shows alpha — the genre's average WoW growth minus the overall market's average growth — at multiple timeframes. Green cells mean the genre is outperforming the market. Red means underperforming. The Composite column averages across all windows.

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genre alpha vs market

Genre Correlation Matrix

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What am I looking at?

A Pearson correlation matrix of excess returns (genre WoW% minus market WoW%) between every pair of genres. Market-wide seasonality is removed so you see true genre-specific co-movement. Red cells (near +1.0) mean two genres outperform and underperform together. Blue cells (near -1.0 or 0) mean they move independently — ideal for portfolio diversification.

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pairwise return correlations

Genre Power Structure

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What am I looking at?

Shows who controls each genre using CR3 (top-3 publisher revenue share). Walled Garden (CR3 > 60%) = entrenched incumbents, high premiums, hard to break in. Contested (30-60%) = a few leaders but room to acquire a meaningful position. Open Field (CR3 < 30%) = fragmented, multiple targets, lower premiums. Also shows the #1 publisher and total publisher count per genre.

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Publisher dominance by genre

Time Window

24 weeks

Genre

Publisher Revenue Heatmap

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What am I looking at?

A weekly revenue heatmap for the top 100 publishers by average revenue in the selected window. Each row is a publisher, each cell is one week — colored by WoW revenue change. The right-side summary shows window-average revenue, average WoW%, sparkline trend, and three M&A signals: MET (monetization efficiency — RPD trend), DRD (download-revenue divergence — harvest vs growth mode), and GSC (growth source — organic vs UA-driven). Gold ▲ markers flag revenue spikes >2.5x trailing average. Click any publisher name to see app-level breakdown.

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v2_publisher_weekly · US · iOS+Android · Clean Pipeline

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Publisher Sharpe Ratio

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What am I looking at?

Risk-adjusted revenue consistency for top publishers. A high Sharpe ratio means the publisher delivers stable, predictable revenue growth — safer acquisition targets. A low or negative Sharpe means volatile or declining revenue.

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Publisher Momentum (MRS)

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What am I looking at?

Multi-timeframe relative strength for publishers. Compares each publisher's WoW growth to the market average. LEADING = outperforming and accelerating. LAGGING = underperforming and decelerating. Use this to identify publishers with genuine momentum vs. those riding a fading wave.

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Publisher Genre Diversification

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What am I looking at?

How concentrated each publisher's revenue is across Tier-1 genre groups. A publisher with apps spanning multiple distinct genre families (e.g., Social Casino + Match & Merge + Strategy) represents a lower-risk acquisition with built-in portfolio diversification. A single-genre publisher carries concentration risk. Note: genres are collapsed to Tier-1 groups (e.g., Casino+Bingo+Poker+Solitaire = "Social Casino") to avoid inflating diversity counts from sub-genre overlap.

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Publisher Rotation Quadrant

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What am I looking at?

A scatter plot of publisher momentum (x-axis) vs. acceleration (y-axis). Bubble size = revenue. Leading quadrant (top-right) = strong and getting stronger. Improving (top-left) = was declining, now reversing. Weakening (bottom-right) = was strong, now fading. Lagging (bottom-left) = declining and getting worse.

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RC Signal Board

Score Distribution

RichardClaude Signal Board

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What am I looking at?

A quantitative M&A target screen that scores every publisher in our universe on a 0-100 composite across four pillars:

Fundamentals (0-30) — Revenue scale (log-scaled), revenue stability (12w CV), monetization efficiency (rev/download — the strongest discriminator at 15x gap between acquired vs. universe), and revenue persistence (weeks above $100K — 3.6x discriminator).
Acquirability (0-30) — Lifecycle stage (Mature strongly preferred — data shows acquired studios trend flat, not growing), lifetime signal steadiness (87.8% benchmark), revenue predictability, and trough-to-peak consistency (revenue floor strength).
Strategic Value (0-25) — Genre tailwinds, alpha vs. genre peers, portfolio diversification (HHI), download momentum, and data track record depth.
Timing (0-15) — Signal quality (steady = gold), acceleration pattern, and momentum (reduced weight — does not discriminate between acquired and non-acquired per backtest analysis).

Grades: DEEP DIVE (≥68) = highest conviction, open a file. MONITOR (40-67) = track for signal changes. PASS (<40 or <$50K/week) = not actionable now.

Publishers owned by conglomerates, competitors, or already-acquired studios are excluded via the DQ filter. Revenue floor: $50K/week minimum.

— Column Guide —

Grade — DEEP DIVE / MONITOR / PASS. The L2 algorithmic verdict based on the composite score. L1 graduates only — publishers that didn't pass L1 quantitative screening are forced to PASS regardless of L2 score.
Score — 0-100 composite across all four pillars. The single number that ranks targets. 68+ = DEEP DIVE territory. Compare across publishers to prioritize your pipeline.
Weekly Rev — 4-week average US iOS+Android IAP revenue. This is the scale indicator — DoubleU targets are typically $200K-$2M/week. Below $50K/week = auto-PASS.
Trajectory — Revenue shape classification from 119-week time-series: HOCKEY_STICK (⬆ accelerating growth), STEADY_CLIMB (↗ consistent uptrend), PLATEAU (→ flat/stable), DECLINING (↘ gradual decay), SPIKE_DECAY (⬇ sharp post-peak drop). Acquired studios historically trend PLATEAU or STEADY_CLIMB — not growth rockets.
Urgency — 0-100 composite timing signal. Factors in lifecycle stage, trajectory momentum, competitive pressure, and window state. Higher = more time-sensitive. 55+ = flagged for immediate attention. Not a quality score — a "how soon do we need to move" score.
Window — Acquisition timing read: OPEN (favorable conditions, no red flags), NARROWING (window exists but competitive or market pressure building), CLOSING_FAST (act now or lose the opportunity), STABLE (no urgency signal either way).
Quality — Growth quality gate: ORGANIC (revenue growth driven by retention/monetization, not paid UA spikes — this is what DoubleU wants), MIXED (some paid signal detected), PAID (growth likely UA-driven — revenue may not survive post-acquisition UA cuts).
Durability — Revenue floor resilience grade: A (strong floor, low decay, high persistence — revenue survives downturns), B (moderate floor, some decay risk), C/D (weak floor, high decay — revenue could collapse post-deal). Acquired studios average B+ durability.

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Rev ≥ $50K

RC Score Distribution

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What am I looking at?

The grade distribution across all scored publishers. A healthy model should show a pyramid: few DEEP DIVE at the top, moderate MONITOR in the middle, and most publishers in PASS. If DEEP DIVE is too crowded, the threshold may need tightening.

How to use it: Check if the DEEP DIVE count matches your quarterly bandwidth. If you can only work 10 targets per quarter, filter by revenue range in the Signal Board to narrow your pipeline.

Count per grade bucket

Acquisition Radar — Why These Studios Get The Call

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What am I looking at?

A scatter plot mapping every publisher's RC Score (x-axis) against weekly revenue on a log scale (y-axis). Bubble size = revenue. The dashed green line marks the DEEP DIVE threshold (≥68).

Gold diamonds ◆ are studios that were actually acquired — plotted at their RC score as of deal announcement. The pattern: acquired studios cluster in the right half of the chart with scores of 60-85. Studios sitting in that zone today have the same quantitative profile as targets that got bought for $300M-$5B.

How to use it: Look for green bubbles (current DEEP DIVE) sitting near or overlapping the gold diamonds. Those publishers have the same fundamentals, stability, lifecycle stage, and momentum profile as studios that were acquired. That overlap is your pitch: "This publisher looks like Clipwire / SuperPlay / Plarium looked 6 months before they sold."

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Pillar Fingerprint — Top DEEP DIVE vs. Acquired Studios

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What am I looking at?

A radar chart comparing the average pillar profile of today's top DEEP DIVE publishers against the average profile of studios that were actually acquired. If the shapes overlap closely, the model is surfacing the right kind of targets. Gaps reveal where current targets differ from historical acquisitions.

How to use it: If current DEEP DIVE targets score lower on Fundamentals than acquired studios did, it means the pipeline is lighter-weight than what typically gets bought. If Strategic Value is higher, the market tailwinds are stronger now than when past deals closed.

Publisher

01 SCREENING & CONFIRMATION

L1 Screening Profile

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L1 Screening Profile

What: The first-pass quantitative filter that decides whether a publisher deserves deeper analysis. Every publisher in our Sensor Tower universe gets an L1 score (0-100) based on publicly observable signals — no enrichment data needed.

How it's computed: Four pillars scored independently:
• Scale (0-30) — Combined weekly revenue (log-scaled), genre rank, number of active apps. Larger studios score higher.
• Trajectory (0-30) — Revenue momentum (12-week trend), rank momentum, and maturity (weeks of data). Stable-to-rising studios preferred.
• Acquirability (0-25) — Ownership classification (independent preferred), revenue in buyable range ($200K-$2M/wk sweet spot), proven lifecycle maturity.
• Genre Fit (0-15) — Overlap with DoubleU's target genres (casual, mid-core, social casino adjacencies).

Publishers scoring ≥50 graduate to L2 enrichment. Below 50 = PASS at Layer 1.

The radar chart compares this publisher's pillar shape against the average DEEP DIVE and MONITOR publisher — so you can instantly see where it's strong or weak relative to the pipeline.

Dynamic example loaded in context above.

Score: — / 100

Why this publisher was flagged for review

              ● This publisher
              ● Avg DEEP DIVE
              ● Avg MONITOR
            

L2 Thesis Confirmation

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L2 Thesis Confirmation

What: A seven-point checklist that tests whether deeper enrichment data confirms or challenges the thesis that L1 flagged. Think of L1 as "this looks interesting" and L2 as "here's the evidence."

How it works: Each row runs an independent diagnostic:
• Revenue Trajectory — Does the 119-week shape (c1_trajectory_shape) confirm momentum? STEADY_CLIMB/HOCKEY_STICK = green. SPIKE_DECAY = red flag.
• Growth Quality — Is growth organic or UA-driven (c3_quality_gate)? ORGANIC = green = revenue survives post-deal UA cuts.
• Revenue Durability — Does the floor hold (c4_durability)? Grade A = revenue persists through downturns.
• Alpha vs Peers — Is this studio beating its genre (b1_rolling_alpha)? Positive sigma = outperforming.
• Acquisition Comps — Do genre-matching deals exist (d1_acquisition_match)? More comps = better valuation anchoring.
• Market Share Trend — Gaining or losing genre share (b2_market_share_slope)? GAINING = expanding moat.
• Mean Reversion Risk — Is current revenue unsustainably above historical mean (d3_mean_reversion)? |z| > 2 = elevated reversion risk.

Green = confirms thesis. Yellow = partial/ambiguous. Red = challenges thesis. The summary counts at top tell you the overall confidence level.

Does deeper data confirm L1's screening thesis? (US IAP only)

02 GENRE CONTEXT

Genre Landscape

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Genre Landscape

What: A per-genre breakdown of every market this publisher competes in. Tells you how big the genre is, how fast it's growing, how concentrated it is, and what slice this publisher owns.

How it's computed: Three enrichment layers merge per genre:
• a1_genre_size_growth — Total weekly genre revenue (US IAP) and 12-week growth rate. Shows market size and momentum.
• a2_genre_concentration — CR3 (top-3 publisher share), HHI (Herfindahl-Hirschman Index, 0-1 scale). FRAGMENTED (HHI < 0.10) = easier to gain share. CONCENTRATED (HHI > 0.25) = dominated by incumbents.
• a3_genre_tailwind — Whether the genre itself is expanding (STRONG/GROWING), flat (NEUTRAL/STABLE), or shrinking (DECLINING).

Pub Rev = market size × publisher share %. Mkt Share = this publisher's slice of the genre.

M&A context: DoubleU wants genres with (1) large market size, (2) growing tailwinds, and (3) fragmented concentration where a mid-size studio can gain share. A genre with $5M+/wk, STRONG tailwind, and HHI < 0.15 is a sweet spot.

Genres this publisher competes in · Data: US IAP

Genre	Market Size/wk	Growth 12w	Tailwind	CR3	HHI	Concentration	Pub Rev	Mkt Share

            CR3 = top-3 publisher revenue share.
            HHI = Herfindahl-Hirschman Index (0=perfect competition, 1=monopoly).
            Tailwind = 12-week genre revenue trend.
            ⚠ Genre data scope: US IAP revenue only
          

03 MARKET POSITION

04 GROWTH STORY

TIME WINDOW

Week 1 – 119

Revenue & Downloads — Per-App Breakdown

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Revenue & Downloads Chart

What: A 119-week dual-axis chart showing this publisher's entire revenue and download history, broken down per app.

How to read it:
• Stacked colored areas = each app's weekly US IAP revenue. The vertical stack shows you which apps generate the revenue and how that mix shifts over time.
• White line = total publisher revenue (sum of all apps).
• Gray bars (right axis) = total weekly downloads across all apps.

What to look for in M&A:
• Revenue concentration — If one color dominates the stack, the publisher is a single-app business. Higher risk.
• Revenue-download divergence — Revenue growing while downloads decline = strong monetization (ARPU improving). Downloads growing while revenue flat = poor monetization.
• Seasonal patterns — Regular spikes every 4-8 weeks may indicate promotional events or seasonal UA pushes.
• Cliff events — A sudden drop in one app's color band may indicate a platform change, competitor launch, or game issue.

Use the TIME WINDOW slider above to zoom into specific periods.

Stacked area = per-app revenue · White line = total · Bar = downloads

Rolling Alpha (Market Outperformance)

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Rolling Alpha

What: A time-series measure of how much this publisher's revenue growth outperforms (or underperforms) its genre average — expressed in standard deviations (σ).

How it's computed (b1_rolling_alpha): For each week, we calculate the publisher's revenue growth rate vs. the genre's average revenue growth rate, then normalize by genre standard deviation. Positive alpha = outperforming peers. Negative = underperforming.

The 4-week average (avg_4w) shown in the KPI strip smooths noise. The chart shows the full rolling history.

M&A context: Sustained positive alpha (> +0.5σ) means this studio has a competitive edge — better monetization, stronger retention, or superior product. Negative alpha with improving trend = turnaround candidate. Alpha that spiked then fell = one-time event, not sustainable advantage.

Revenue Forecast (13 Weeks)

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Revenue Forecast

What: A 13-week forward revenue projection based on historical trend analysis.

How it's computed (d2_revenue_forecast): Uses the publisher's trailing 119-week revenue series to fit a trend model (weighted moving average with decay). The forecast extrapolates the recent trajectory forward, with confidence bands widening as the horizon extends.

Key fields:
• forecast_13w — Projected weekly revenue 13 weeks from now.
• trend_direction — UP, FLAT, or DOWN based on the slope of the forecast.
• confidence — How stable the historical pattern is (higher = more reliable forecast).

M&A context: The forecast answers "what will revenue look like at close?" If forecast_13w is materially below current revenue, you may be buying at a peak. If it's above, there's organic growth runway. Always cross-check against trajectory shape — a SPIKE_DECAY with an UP forecast is contradictory and means the model hasn't caught the reversal yet.

05 QUALITY & CONTEXT

06 APP PORTFOLIO

App Portfolio — Current Snapshot

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App Portfolio — Current Snapshot

What: A per-app breakdown of everything this publisher owns — each app's revenue, downloads, genre rank, week-over-week change, percent of peak, trajectory, revenue share, and maturity (total weeks tracked).

Key columns:
• Rev/wk — Latest 4-week average US IAP revenue for this app.
• Rank — App's rank within its genre by revenue.
• WoW% — Week-over-week revenue change. Consistent negatives = declining app.
• Peak% — Current revenue as a % of all-time peak. 80%+ = near-peak, healthy. <50% = well past peak.
• Trajectory — GROWING/STABLE/DECLINING classification for this specific app.
• Share — This app's % of the publisher's total revenue. If one app > 70%, it's a single-app business (concentration risk).
• Wks — Weeks of data history. More weeks = more mature, more predictable.

Genre competitors expand below each app showing the top 5 publishers in that genre — your target is highlighted in cyan.

Concentration indicator: DIVERSIFIED (no app > 60%), MODERATE (one app 60-80%), SINGLE_APP (one app > 80%). DoubleU prefers DIVERSIFIED or MODERATE — less key-person/key-game risk.

Coverage % at bottom = sum of app-level revenue ÷ publisher total. If < 80%, some revenue is coming from apps not in our tracking universe.

Portfolio Analytics

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Portfolio Analytics

What: Six analytical views that decompose the publisher's app portfolio into actionable acquisition intelligence. This section answers: where does revenue come from, how concentrated is it, what's the trajectory of each app, who are the competitors, and is there cannibalization risk?

Sub-panels:
• Revenue Attribution — Stacked area chart showing which apps drive revenue over time. Answers "who's carrying the business?"
• Concentration Risk (HHI) — HHI trend over time. Rising HHI = becoming more dependent on fewer apps. Falling = diversifying.
• Per-App Lifecycle — Each app classified as GROWING/STABLE/DECLINING with lifecycle stage and peak distance.
• Competitive Gap Analysis — Rank velocity showing which apps are climbing or falling in their genres.
• Genre Share Per App — 12-week trend of each app's market share within its genre. Rising share = gaining competitive position.
• Cannibalization Risk — Checks if multiple apps from this publisher compete in the same genre (cannibalizing each other's downloads).

Per-app trajectory modeling · Revenue attribution · Concentration risk · Competitive gaps

Revenue Attribution — Who's Driving Growth?

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Revenue Attribution

What: A stacked area chart showing each app's revenue contribution over time.

How to read it: Each colored band = one app. The total height = publisher total. If one band dominates, revenue depends on a single game. A healthy portfolio shows multiple bands growing together.

M&A signal: If the top app's band is shrinking while total stays flat, newer apps are successfully replacing legacy revenue — good succession signal. If the top band shrinks and nothing replaces it, the business is in decay.

Concentration Risk — HHI Over Time

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Concentration Risk (HHI)

What: The Herfindahl-Hirschman Index applied to this publisher's app-level revenue, tracked over time.

How it's computed: HHI = sum of squared revenue shares. If one app has 100% of revenue, HHI = 1.0 (monopoly). If 4 apps each have 25%, HHI = 0.25.

Thresholds: HHI < 0.25 = diversified. 0.25-0.50 = moderate concentration. > 0.50 = single-app dependent.

M&A signal: Falling HHI over time = new apps gaining revenue share = healthier business. Rising HHI = revenue concentrating into fewer apps = increasing key-game risk. DoubleU prefers HHI < 0.40.

Per-App Lifecycle & Trajectory Classification

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Per-App Lifecycle

What: Each app classified by lifecycle stage and revenue trajectory.

Trajectory types: GROWING (revenue trending up), STABLE (flat, predictable), DECLINING (revenue eroding). Computed from 12-week revenue slope.

Lifecycle stages: LAUNCH (<12 weeks), GROWTH (rising + young), MATURE (stable + 26+ weeks), LATE (declining + old).

M&A signal: A healthy acquisition target has most revenue in MATURE/STABLE apps (predictable cash flows) with at least one GROWING app (future upside). All-DECLINING portfolios = value trap.

Competitive Gap Analysis — Rank Velocity

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Competitive Gap Analysis

What: How fast each app is climbing or falling in its genre rank — and who the nearest competitors are.

Rank velocity: Measured in positions/week. Positive = climbing (gaining market position). Negative = falling. Computed from 12-week rank regression.

M&A signal: Apps with positive rank velocity are taking share from competitors — these are the growth engines. Apps falling in rank are losing to competitors and may need UA investment post-acquisition. Cross-reference with the genre's CR3 — in a concentrated genre, climbing rank is harder and more valuable.

Genre Share Per App — 12-Week Trend

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Genre Share Per App

What: A trend chart showing each app's share of its genre's total revenue over the last 12 weeks.

How it's computed: Each week: app revenue ÷ total genre revenue × 100. Plotted as time series.

M&A signal: Rising share = the app is winning in its genre, even if the genre itself is flat. Falling share + stable genre = losing to competitors. Falling share + growing genre = getting left behind in a growing market (worst case).

Cannibalization Risk & Cross-App Dynamics

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Cannibalization Risk

What: Checks whether this publisher has multiple apps competing in the same genre — which could mean they're cannibalizing their own downloads and ad impressions.

How it's detected: If 2+ apps share a primary genre, they're flagged. More overlap = higher risk that UA spend on one app steals users from the other.

M&A signal: Cannibalization isn't always bad — it can mean genre dominance (multiple hits in the same category). But post-acquisition, DoubleU would consolidate UA spend, so understanding which apps overlap helps plan the integration. If apps are in different genres = pure diversification play = zero cannibalization risk.

07 DEAL SIGNAL

Acquisition Comps

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Acquisition Comps

What: A list of historical mobile gaming acquisitions that match this publisher's genre footprint, with deal values and overlap scoring.

How it's computed (d1_acquisition_match): We maintain a database of ~50 mobile gaming acquisitions with known deal values and genre tags. For each comp, we count how many genres overlap with the target publisher:
• STRONG (2+ genre overlap) — Highly comparable. These comps should anchor your valuation.
• MODERATE (1 genre overlap) — Partially comparable. Use for range-building.
• WEAK (0 overlap, same broad category) — Loosely comparable at best.

Median deal value is calculated from 2+ overlap comps first (more relevant). Falls back to all comps if insufficient strong matches.

M&A context: When you pitch to the CEO, you need to say "similar studios sold for $X-$YM." These comps give you that anchor. The more STRONG matches, the more defensible your valuation range. 3+ strong comps = solid comparable basis. 0-1 = you'll need to build the valuation case from DCF instead.

Urgency Factor Breakdown

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Urgency Factor Breakdown

What: A decomposition of the urgency score (0-100) into its five contributing factors. Tells you why a target is time-sensitive.

Five factors (d4_window_score):
• Lifecycle (0-25) — Where is the publisher in its lifecycle? Mature publishers with stable revenue score highest (best acquisition timing). Early-stage or declining score lower.
• Trajectory (0-25) — Is the revenue shape favorable right now? PLATEAU and STEADY_CLIMB score high. SPIKE_DECAY scores low (already past the window).
• Competitive (0-20) — Are competitors or acquirers circling this publisher's genre? High genre M&A activity = pressure to move.
• Alpha Streak (0-15) — How long has the publisher been outperforming? Long positive alpha streaks increase urgency because the outperformance makes the studio more visible to other buyers.
• Scale (0-15) — Is the publisher in the $200K-$2M/week sweet spot? Studios in DoubleU's target range score higher urgency.

Window states derived: OPEN (total ≥ 40, no red factors), NARROWING (40-55 with a red factor), CLOSING_FAST (55+ with multiple pressure signals).

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Global Market Leaderboard

152 markets · Statista + Sensor Tower · Apr 2026

#	Market	Rev 2024	Rev 2025E	YoY	Fwd CAGR	ARPU	Pen %	Signal

Opportunity Quadrant

Bubble = ARPU · X = Revenue · Y = Forward Growth

MIN REV:

ARPU Ranking 2024 - Top 25

Revenue per user

ARPU vs Penetration

High ARPU + Low Pen = premium underpenetrated

Revenue Curve 2019-2028

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CIQ Deal Comps

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CIQ Comp Explorer

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Cap 20x

Deals shown

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Median EV/Rev

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Median EV/EBITDA

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Median deal EV

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