Ads & paid
AuraScore 77/100

Commercial Real Estate Paid Search Audit and Lead Efficiency Report

Evaluate search campaign efficiency, negative keyword leakage, and asset-class CPA performance for commercial brokerage advertising.

Use this template when conducting a quarterly performance and budget hygiene audit on Google and Bing search ads for commercial properties. It uncovers negative keyword waste, bid misalignments, and geotargeting inefficiencies across asset classes.

Template

Role: Senior Paid Search Director specializing in Commercial Real Estate (CRE) acquisition and institutional leasing.

Context

  • Brokerage Name: {{brokerage_name}}
  • Core Asset Classes: {{target_asset_classes}}
  • Monthly Search Ad Spend: {{monthly_ad_spend}}
  • Baseline Cost-Per-Lead Benchmarks: {{current_cpl_benchmarks}}
  • Geographic Footprint: {{geotargeting_footprint}}
  • Conversion Infrastructure: {{conversion_tracking_setup}}

Task

Generate a rigorous search advertising audit report for {{brokerage_name}} that pinpoints spend inefficiencies, optimizes bidding for high-intent tenant/investor keywords, and provides an actionable restructuring roadmap to lower acquisition costs across {{target_asset_classes}}.

Method

  1. Analyze current keyword thematic clusters against {{target_asset_classes}}, separating tenant representation, buyer representation, and landlord listing queries.
  2. Audit negative keyword lists to detect budget leakage from residential searches, DIY leasing queries, and low-intent informational terms.
  3. Evaluate the {{geotargeting_footprint}} settings to ensure radius targeting and location exclusions match physical property corridors without cannibalization.
  4. Assess bid strategies (tCPA vs. Maximise Conversions) against {{current_cpl_benchmarks}} and total spend velocity of {{monthly_ad_spend}}.
  5. Inspect the {{conversion_tracking_setup}} for primary conversions (offering memorandum downloads, broker calls, tour bookings) versus unverified micro-conversions.
  6. Review Ad Copy relevancy and Responsive Search Ad (RSA) asset strength regarding capitalization rates, square footage, and zoning specifics.
  7. Calculate potential budget recovery from eliminated waste and model the reallocated pipeline yield.

Constraints

  • Focus exclusively on commercial real estate dynamics (triple-net, industrial, retail, office, multi-family syndication).
  • MUST provide quantitative budget reallocation percentages totaling exactly 100%.
  • MUST NOT recommend broad match bidding without strict brand and residential negative keyword lists.
  • Limit recommendations to changes deployable within a 30-day implementation sprint.

Output format

Structure the report under these explicit section headers:

  1. Executive Summary & Waste Diagnostics (max 200 words)
  2. Keyword & Search Term Architecture Audit (bulleted findings by asset class)
  3. Geotargeting & Bidding Strategy Evaluation
  4. Conversion Tracking & Attribution Review
  5. 30-Day Paid Search Remediation & Budget Reallocation Plan (table format with Current vs. Proposed % split)

Self-review

  • Confirm that all referenced asset classes from {{target_asset_classes}} receive tailored analysis.
  • Verify that commercial vs. residential keyword intent separation is explicitly addressed.
  • Ensure all recommended metrics align with {{monthly_ad_spend}} and realistic commercial lead volumes.
AuraScore breakdown
77/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering8/12 · Adequate

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

marketing
marketing-ads
real-estate-construction
paid-search
cre-marketing
google-ads