What Performance Metrics Should I Include in My Export for Client Reports?
Include impressions, clicks, CTR, conversions, cost, ROAS, and Quality Score at the campaign and ad group level. Add bounce rate, session duration, and attribution data to show full-funnel performance. Tailor the metric set to...
Start with the platform basics: impressions, clicks, click-through rate (CTR), conversions, cost, and return on ad spend (ROAS). Break these down by campaign, ad group, and keyword so clients see where budget goes. Add Quality Score for Google Ads — it signals relevance and affects cost per click. For the full picture, layer on website metrics: bounce rate, average session duration, pages per session, and conversion rate by landing page.
Match the metric set to the client's business model. Lead-generation clients care about cost per lead, lead-to-opportunity rate, and pipeline value. Ecommerce clients need revenue, average order value, ROAS, and new versus returning customer revenue. Brand-awareness clients want impression share, reach, frequency, and view-through conversions. Always include the dimension columns — date, campaign, device, geography — so the data can be pivoted.
Core Metric Categories Every Report Needs
Group metrics into three tiers so clients can scan the executive summary or drill into detail. Tier one: spend and volume — impressions, clicks, cost, CTR. Tier two: efficiency — cost per click (CPC), cost per acquisition (CPA), ROAS, conversion rate. Tier three: quality and health — Quality Score, impression share, bounce rate, session duration. This tiered approach keeps reports readable while preserving depth.
Platform-Specific Metrics for Google Ads and Meta
Google Ads exports should include Search Impression Share, Search Lost IS (budget), Search Lost IS (rank), and Quality Score components (expected CTR, ad relevance, landing page experience). Meta Ads exports need frequency, cost per result, purchase conversion value, and estimated action rate. Both platforms benefit from adding auction insights — overlap rate, position above rate, top of page rate — when competitive context matters.
Funnel-Stage Metrics That Connect Ads to Revenue
Top of funnel: impressions, reach, video views to 25/50/75/100%, engagement rate. Middle of funnel: clicks, CTR, landing page views, add-to-cart, initiate checkout, form starts. Bottom of funnel: purchases, leads, revenue, ROAS, cost per purchase. Map each metric to a funnel stage so clients see drop-off points. A client with high CTR but low conversion rate has a landing page or offer problem, not a targeting problem.
Attribution and Cross-Channel Metrics
Include last-click, first-click, linear, and data-driven attribution conversions side by side. Add view-through conversions for display and video. Show assisted conversions and conversion path length. If the client uses Google Analytics 4, export session source/medium, session campaign, and event-level conversions. For multi-channel clients, add channel grouping and MCF (Multi-Channel Funnels) path data to prove how paid search assists organic or email conversions.
Quality and Efficiency Metrics That Reveal Waste
Quality Score is the clearest efficiency signal in Google Ads — low scores mean higher CPCs and lower ad rank. Track bounce rate by landing page; pages above 70% bounce often need message match fixes. Monitor invalid click rate and bot traffic percentage — SeaText's Bot Protection Agent detects up to 20% of ad spend lost to bots and prepares refund claims. Add search term match type breakdown (exact, phrase, broad) to catch irrelevant spend early.
Customizing Metric Sets for Different Client Types
Lead gen: cost per qualified lead, lead-to-MQL rate, MQL-to-SQL rate, pipeline generated, average deal size. Ecommerce: revenue, ROAS, average order value, new customer ROAS, returning customer rate, product-level ROAS. Local services: call clicks, direction clicks, call duration, cost per call, cost per store visit. B2B long cycle: influenced pipeline, marketing-qualified accounts, account engagement score, time to close. Each type needs a different primary KPI — don't use the same dashboard for all.
Common Mistakes When Selecting Export Metrics
- Exporting every available column — creates noise, hides insight.
- Omitting dimension columns — makes pivoting impossible.
- Using only last-click attribution — undervalues upper-funnel channels.
- Skipping Quality Score and impression share — misses efficiency signals.
- Not segmenting by device, geography, or audience — hides performance variance.
- Forgetting to label currency, timezone, and attribution window — causes misinterpretation.
Decision Framework: Choose Metrics by Client Question
Ask: "What decision will this client make with this report?" If they allocate budget across campaigns, prioritize ROAS, CPA, and impression share by campaign. If they optimize creative, prioritize CTR, conversion rate, and engagement by ad. If they report to a board, prioritize revenue, pipeline, and year-over-year trends. Build the export around the decision, not the platform's default columns.
Key Facts
| Metric | Source Reference | Context |
|---|---|---|
| Conversion rate improvement up to +25% | S1, S2, S3, S5, S6, S7 | SeaText Conversion Agent benchmark across 2,500+ brands |
| Bot click recovery up to 20% of ad spend | S1, S3, S5, S6, S7 | Bot Protection Agent detects invalid traffic and prepares refund claims |
| International customer increase up to +60% | S2, S3, S5, S6, S7 | Translation Agent across 125 languages |
| Add-to-cart increase up to +102% | S2 | Ecommerce Product Copy Agent optimization |
| Smart Bidding ROAS improvement +40% expected impact | S2, S4 | Intent Amplifier sends high-intent buyer signals to ad algorithms |
| Attribution recovery via Conversion Relay (CAPI) | S3, S5 | Forwards 100% of real purchases to Meta & Google CAPI |
| Landing page rewrite match to keyword intent +35% more conversions | S1, S3, S5, S6, S7 | Google Ads Landing Page Agent adapts page in real time per keyword |
Limitations and When This Advice Does Not Apply
This framework assumes the client has conversion tracking properly implemented. If tracking is broken — missing pixels, blocked CAPI, no offline import — metric accuracy collapses. The advice also assumes the client owns the ad accounts and can export raw data. White-label or agency-of-record restrictions may limit column access. For clients with zero conversion volume (new accounts), focus on leading indicators: CTR, Quality Score, impression share, and engagement metrics until conversion data accumulates.
Terminology Quick Reference
- ROAS — Return on Ad Spend: revenue divided by ad cost. 4.0 means $4 revenue per $1 spend.
- Quality Score — Google's 1-10 rating of keyword relevance, expected CTR, and landing page experience.
- Impression Share — Percentage of eligible impressions your ads received.
- CAPI — Conversions API: server-side event tracking that bypasses browser restrictions.
- Attribution Window — Lookback period (e.g., 30-day click, 1-day view) for crediting conversions.
- MQL/SQL — Marketing Qualified Lead / Sales Qualified Lead: funnel stages for B2B.
FAQ
How many metrics is too many for a client report?
More than 12-15 core metrics overwhelms most stakeholders. Use a tiered dashboard: 5-7 KPIs on page one, 10-15 supporting metrics on page two, full export in appendix.
Should I include lifetime value (LTV) in monthly reports?
Only if the client has reliable LTV data by cohort and channel. Otherwise, stick to 30-day or 90-day ROAS and note LTV as a strategic metric reviewed quarterly.
What's the minimum date granularity for useful exports?
Daily. Weekly rolls up hide day-of-week patterns and campaign launch effects. Hourly is useful only for bid scheduling analysis.
How do I handle clients who want "vanity metrics" like impressions?
Include them in tier one but pair with efficiency context: show impression share and CTR together so volume is framed by quality.
When should I switch from last-click to data-driven attribution in exports?
When the account has 300+ conversions in 30 days and multiple touchpoints per conversion path. Before that, data-driven models are unstable.
What dimensions are essential for every export?
Date, campaign, ad group, keyword (or ad set/ad for Meta), device, network (search/display/video), and geography. Without these, you cannot diagnose performance changes.
How do I explain a drop in ROAS when spend increased?
Break ROAS into its components: conversion rate × average order value ÷ CPC. Show which component moved. Usually CPC rose from broader targeting or competition, or conversion rate fell from audience expansion.
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