Baseline Visibility Snapshot (Onboarding)

Baseline Visibility Snapshot (Onboarding)

1. 01

   Freeze a 90-day historical baseline before any new tracking configuration goes live

   Pull existing position data for the client's top 50 revenue keywords so the first monthly report shows movement against a fixed reference point, not a blank slate. Agencies that skip this step end up defending a flat line in month two.

2. 02

   Separate branded from non-branded queries and report them on different lines

   Branded terms inflate aggregate visibility and hide the non-branded gains that justify a retainer. Keep the two sets in distinct dashboard groups from day one.

3. 03

   Map each tracked keyword to a landing page and a commercial intent tier

   A keyword without an assigned URL cannot be actioned by the delivery team. Tag terms as informational, comparison, or transactional so prioritization survives staff turnover.

4. 04

   Record competitor domains at the group level, not as a flat list

   Grouping rivals by segment (direct, adjacent, marketplace) lets a platform like AccuRanker or Nozzle surface share-of-voice shifts that a flat competitor list obscures.

5. 05

   Add AI citation prompts alongside classic SERP keywords in the same workspace

   Nightwatch and LLMrefs both track brand mentions across ChatGPT, Gemini, and Perplexity next to traditional rankings. Starting both tracks at onboarding avoids a mid-contract rebuild when the client asks about AI visibility.

6. 06

   Set the check frequency per keyword tier and document the rationale

   Daily checks on 500 low-intent terms burn API credits; weekly checks on ten revenue terms miss volatility. Write the tiering rule into the client file so it is auditable.

7. 07

   Confirm white-label and access settings before the client sees anything

   TrackRight and Nightwatch support full white-label reporting, while several AI visibility tools do not. Verify branding, user seats, and export permissions at setup, not the week a report is due.