Measurement and Forecasting Methodology
This page explains three things: how we forecast demand, how we rank the job list by impact, and how we measure AI visibility.
How demand is forecast
Horizon
Every tracked keyword gets a weekly forecast 26 weeks, or 6 months, ahead.
Seasons and events
With more than two years of data, yearly seasonality is included. Recurring calendar events are added to the forecast.
Range
A forecast is shown as a range with lower and upper bounds, not a single number. A wide range shows the uncertainty on screen.
Threshold
Keywords with less than 30 weeks of data get no forecast. The unfinished current week is left out so a partial week does not look like a drop.
Label
Forecasts always carry a “Forecast” label and a dashed line, never mixed with measured values.
Season versus real growth
The trend verdict compares the last 12 weeks with the same 12 weeks last year. Movement that repeats every year counts as seasonal, not as growth.
How the job list is ranked
Each job gets an impact score: the traffic it can bring, multiplied by the likelihood that the fix works, divided by the effort it takes (hours). The list is ranked by this score; the high, medium and low impact labels come from it. Pages that are doing well stay on the list with a “Leave as is” verdict, so you also see where not to spend effort.
impact = traffic impact × likelihood of recovery ÷ effort
The Four Ps Framework
Brand visibility in AI platforms isn't just about being present. Where, how, and with what impact matters too. We measure visibility across four dimensions:
Presence
Does the brand appear?
- · Mention Rate
- · Citation Rate
- · Share of Voice
- · Visibility Momentum
Scope Trends: AI Visibility · Scope Citation · Perception Radar
Prominence
How prominently featured?
- · Position
- · First-paragraph appearance
- · Citation ordering
Coming soon: in-answer position mapping
Portrayal
How framed, how accurate?
- · Sentiment
- · Framing
- · Hallucination Rate
- · Factual Inaccuracy Rate
Scope Trends: Algi Radar sentiment + Pulse
Persuasion
Does visibility drive action?
- · Recommendation Strength
- · Post-Citation CTR
- · Downstream conversion
Coming soon: click tracking pipeline
Two-Tier Quality Classification
Not all measurements carry equal weight. Data for budget allocation and data for trend spotting have different reliability needs. So we tag each metric across two tiers:
Reliable enough for budget allocation and strategic decisions
- Query volume
- Broad, diverse set
- Intent types
- 4/4
- Test frequency
- Weekly+
- Platform coverage
- Most AI traffic
Suitable for trend spotting, not decision-critical
- Query volume
- ≥50
- Intent types
- ≥2
- Test frequency
- Monthly/Quarterly
- Platform coverage
- 1+
Critical: "A single response is not a measurement." AI answers are non-deterministic, so results are reported as ranges (e.g., 22% ±4). Scope Trends computes coverage_confidence + noise_floor for every dimension.
Data Sources · Transparency
The source types we measure are documented:
SERP + AI Search
Google SERP · Google AI Overviews · ChatGPT · Claude · Scope AI Search · Gemini
Brand Monitoring
X · Reddit · YouTube · local complaint and forum platforms · open knowledge bases
Site Signals
Google Search Console · PageSpeed Insights · Own crawler (Scope Crawl)
AI Evaluators
Scope AI
Methodology update: 2026-08-13 · First release.