# Competitor Benchmark Report

> Build a Google Ads competitive benchmark report from auction insights, industry data, and the user's own performance - surfacing where competitors are ahead, where there's room to move, and which gaps are worth closing. Use this skill when a user asks for competitor analysis, mentions auction insights, wants to know how they stack up, asks "who are my biggest competitors" in Google Ads, wants industry benchmarks, or asks about competitive bidding strategy. Trigger on phrases like "auction insights", "competitor benchmark", "how do I compare", "competitive analysis", "industry benchmarks", "who's outbidding me", "competitor share", or any request about Google Ads competitive position.

- Skill: `kochellenk-afk/competitor-benchmark-report` (Agent Skill)
- Install (CLI): `npx skillmds@latest add kochellenk-afk/competitor-benchmark-report`
- Raw SKILL.md: https://api.skillmd.com/api/skills/kochellenk-afk/competitor-benchmark-report/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Docs & Writing
- Author: kochellenk-afk (https://skillmd.com/u/kochellenk-afk)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/kochellenk-afk/competitor-benchmark-report

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# Competitor Benchmark Report

A skill for analyzing competitive position in Google Ads using auction insights, industry benchmarks, and account performance.

## What this skill does

Combines three data sources to produce a competitive picture:

1. **Auction insights** - who's bidding against the user, at what overlap and impression share
2. **Industry benchmarks** - typical CTR, CPC, conv. rate, CPA for the user's vertical
3. **The user's own performance** - where they sit vs. competitors and vs. industry typical

Output:
- Top 5 competitors by overlap rate, with characterization (heavy bidders, niche players, brand-defenders)
- Performance vs. each competitor on each campaign
- Performance vs. industry benchmark (above/below)
- Three competitive gap categories with action items
- Strategic recommendations: where to push, where to defend, where to retreat

## Required inputs

1. **Auction insights export** - at the campaign level, ideally for the highest-spend campaigns
2. **The user's own campaign performance** - same period as auction insights
3. **Industry/vertical** - for benchmark comparison; ask if not provided
4. **Geographic market** - benchmarks vary by country
5. **Brand vs. non-brand designation** for each campaign - interpretation differs

If auction insights data is missing, tell the user:

> "I need the Auction Insights report to do this analysis. In Google Ads, go to a campaign → Auction insights tab → Download. Export at the campaign level for your top 3–5 highest-spend campaigns, then attach. Without this, I can only give you industry benchmark comparison, not who specifically is outbidding you."

If the user can't access auction insights for technical reasons, fall back to the benchmark-only mode (skip the competitor sections, focus on industry comparison).

## Workflow

### Step 1: Validate and characterize competitors

For each campaign's auction insights data, look at:

- **Overlap rate** - how often a competitor's ad appeared when yours did
- **Position above rate** - how often they showed above you
- **Top of page rate** - how often they showed at the top
- **Outranking share** - how often they ranked higher than you
- **Abs. top of page rate** - absolute top placement rate

Group competitors by behavior (read `references/competitor-archetypes.md`):

| Archetype | Signal |
|---|---|
| **Heavy bidder** | High top-of-page rate (>50%), high overlap |
| **Niche player** | Low overlap (<10%) but high outrank when present |
| **Brand defender** | Only appears in brand auctions; low overlap on non-brand |
| **Aggregator/marketplace** | Wide overlap across many ad groups, mid position |
| **Test-and-retreat** | Variable presence over time, suggests testing |

### Step 2: Per-campaign competitive position

For each user campaign, build a matrix:

| Competitor | Overlap rate | Position above us | Top of page % | Archetype |
|---|---|---|---|---|

Sort by overlap rate descending.

### Step 3: Industry benchmark comparison

Compare the user's campaign metrics to industry typicals. Read `references/industry-benchmarks.md` for the lookup table by vertical.

For each metric (CTR, CPC, conv. rate, CPA), classify the user's campaign:

- **Above benchmark** (top quartile)
- **At benchmark** (50th percentile range)
- **Below benchmark** (bottom quartile)

The user wants to know which metrics are dragging their competitive position. A campaign at-benchmark on CTR but below-benchmark on conv. rate has a landing page or audience-quality issue, not an auction issue.

### Step 4: Competitive gap categorization

Group findings into three buckets:

**Push opportunities** - where the user can gain ground:
- Auctions where the user's avg position is winnable with modest bid increases
- Competitors with declining presence (if time-series data available)
- Keywords where the user's CTR beats benchmarks but IS lost to rank is high - they're efficient enough to bid more

**Defend** - where the user must protect existing position:
- Brand auctions where competitors have any overlap (always defend)
- Top-converting non-brand keywords where a competitor escalated recently
- Categories where dropping IS by 10+ points would compound (recent share losses)

**Retreat** - where the user shouldn't fight:
- Auctions where overlap with a heavy bidder is high AND the user's CPA is already over target
- Categories where a niche specialist dominates and the user is generalist (or vice versa)
- Geographic or audience segments where structural cost disadvantages exist

### Step 5: Strategic recommendations

3–5 specific recommendations. Each:
- Action (specific, not "review")
- Expected business impact
- Timeline
- Resource cost

Examples:
- "Push: increase Long Tail Search bids 15% to overtake Competitor B (currently outranks you on 35% of overlapping queries). Estimated: +28 conversions/week, ~$8K incremental spend, 2-week implementation."
- "Defend: add Competitor X's brand variants as exact-match negatives on non-brand campaigns immediately - they're pulling 12% of your branded auction volume."
- "Retreat: pause keyword cluster Y where Competitor C's ecosystem advantage is structural. Reallocate $3K/month to Push #1."

### Step 6: Output

A markdown report structured as:

```
# Competitive Benchmark Report - [Period]

## Headline finding
[One paragraph summary of competitive position]

## Top 5 competitors
[Table sorted by overlap]

## Per-campaign competitive matrix
[One section per top-spend campaign]

## Industry benchmark comparison
[Table of user metrics vs. benchmarks]

## Competitive gap analysis
### Push opportunities
### Defend priorities
### Retreat areas

## Strategic recommendations
[3–5 prioritized actions]
```

If the user needs this for a stakeholder presentation, generate as a PowerPoint deck (pptx skill) with one slide per section. If it's for internal record-keeping, Word doc (docx skill).

## What this skill must NOT do

- Don't name competitors that the auction insights data didn't include. The data anonymizes some entrants ("Other"); don't speculate beyond what's shown.
- Don't recommend bid escalation against heavy bidders without confirming the user's unit economics support it. More CPC × stable conv. rate = worse CPA. Always check.
- Don't treat industry benchmarks as targets to beat. They're context, not goals. A campaign 30% below benchmark CTR may still be hitting the user's actual business goals.
- Don't recommend defending every losing auction. Some auctions are correctly losses - fighting them harms the account.
- Don't assume competitors with high overlap are direct competitors. Sometimes a marketplace or comparison site overlaps highly without being a real threat.
- Don't make claims about competitors' strategies you can't substantiate. "They're testing a new product" is speculation; "their position-above rate jumped 20% in the last month" is fact.

## Reference files

- `references/competitor-archetypes.md` - how to characterize competitors from auction insights signals
- `references/industry-benchmarks.md` - vertical-specific CTR/CPC/CPA/conv. rate benchmarks