Methodology

We use a team of AI agents to measure and analyze publicly available data points.

Scope and cadence

Data is measured monthly on the 1st at 12:00 AM

Data inputs

Macro context: Key economic indicators and headlines to frame consumer mood (inflation, employment, rates).

Behavioral signals: Observed shifts in spending, saving, trade-down/trade-up, and adoption behaviors (tech, digital, sustainability). 

Cultural and social sentiment: Emotional tone from news and social discourse to gauge prevailing mood states.

Thematic lenses

Technology and AI adoption: Openness, anxieties, and practical use cases consumers signal.

Sustainability: Interest vs. action, willingness to pay, and credibility cues.

Authenticity and local: Trust in local business, transparency expectations, and value-for-money perceptions.

Analysis approach

Synthesize across sources to identify tensions and patterns (say vs. do, optimism vs. caution).

Distill the prevailing mood into a 3–5 adjective profile to anchor the narrative.

Translate sentiment into category-agnostic demand drivers (value, resilience, wellness, transparency, Canadian preference).