Understanding the Grades in Your Marketing Audit Report

This document provides detailed information on the visual representation and calculation of scores within the Marketing Audit Report. The aim is to offer clarity on how different performance levels are evaluated and displayed using a colour-coded scheme and weighted scoring system.

Overall Score Calculation

Your overall score is an average of five equally weighted sections:

Colour Scheme Scores are visually represented using the following colour scheme:

Business Information Section

The Business Information section is divided into several sub-categories, each with a specific weightage:

Reviews Section

Reviews Section

Reviews help measure both customer sentiment and overall reputation strength in the Marketing Audit Report. A strong rating matters, but review volume also affects how credible that rating appears to prospects.

Reviews are evaluated using these sources:

Google Reviews: 75% Facebook Reviews: 25%

The report considers positive review signals from both platforms when calculating the Reviews score.

Important: A perfect star rating does not always result in a perfect Reviews score when the total number of

reviews is very low. This helps the report reflect business credibility more accurately and prevents inflated scores based on limited review volume.

If your report does not reflect the latest review analysis, refresh the report to load the most current audit results.

Listings Grade: Measuring Your Digital Footprint

This score evaluates the accuracy and impact of your business listings across the internet. It considers:

A higher grade indicates a strong, consistent online presence, which can improve your discoverability and credibility with potential customers.

Website Performance

The Website Performance section includes several metrics with the following weightage:

SEO Section

The SEO Section consists of 9 Heat Map points with varying weightage:

Before you begin

“Understanding the Grades in Your Marketing Audit Report” is part of the Reporting → Reporting Dashboard area in Adaptive AI. Use the central reporting view and saved reporting settings. Reports are only useful when their date range, time zone, filters, source records, and attribution rules match the question being asked. The objective is not merely to save a setting; it is to confirm the result works for the staff member or customer who will depend on it.

• Define the business question and the exact metric, record type, status, owner, campaign, or channel needed to answer it.
• Set the account time zone, reporting date range, comparison period, and filters before interpreting totals or trends.
• Confirm the underlying contacts, appointments, opportunities, messages, payments, or events are being recorded consistently.
• Identify attribution windows, bot filtering, exclusions, and status definitions that can change what the report counts.
• Choose a small set of known source records that can be compared directly with the report output.

Verify the result

After completing the instructions in this guide, use a controlled test before treating the setup as finished. A saved screen or success message confirms configuration, but only an end-to-end test confirms the business outcome.

1. 1Run the report with the intended filters and compare several results with their underlying source records.
2. 2Change one filter at a time and confirm the totals respond in a way that matches the documented definition.
3. 3Check the same reporting period after export and verify columns, time zones, statuses, and totals remain consistent.
4. 4Confirm users with the intended role can access the report without seeing data outside their responsibility.
5. 5Record the report definition and date so later comparisons use the same rules rather than a visually similar configuration.

Troubleshooting checklist

If the result differs from what you expected, preserve the current state and isolate one variable at a time. Start with the checks below before deleting the configuration or rebuilding it from scratch.

• Clear hidden filters and verify the date range, time zone, owner, pipeline, status, and channel when expected records are missing.
• Allow for processing delay when the underlying event occurred recently, then compare event and report timestamps.
• Check whether bot filtering, attribution rules, deleted records, test activity, or duplicate contacts explain a count difference.
• Compare a single known record end to end before treating an aggregate mismatch as a reporting defect.
• Confirm the selected report version or migrated widget uses the same metric definition as the report being replaced.

Best practices

• Use a small set of documented decision-making metrics instead of dashboards filled with unrelated numbers.
• Name saved reports for the audience, metric, period, and filter scope so similar reports are not confused.
• Separate test activity from production reporting and establish consistent rules for won, lost, canceled, spam, and duplicate records.
• Review source-data quality before optimizing a campaign or team based on the dashboard.
• Annotate major launches, tracking changes, and outages so unusual trends can be interpreted later.