CPG Beverage Personas

What this is

Purchase and digital on the same person

Most beverage datasets give you what people bought, or what they looked at. This one carries both for the same individual across seven surfaces, which is what makes research-to-purchase questions answerable at all.

Why it is different

Why it is different

What is in each profile

306 features, grouped by prefix

Category

Per category: events, spend, share, top brand and brand HHI, across thirteen categories.

Brand

Events, purchase events and spend per tracked brand, plus cohort-level brand_hhi, brand_top_share and brand_distinct.

Crossover

crossover_type, crossover_conversion_rate, and the prospect, converted and habit brand sets.

Purchase and interest

Baskets, spend, repeat rate and active months, alongside searches, product views and per-surface engagement.

Time and seasonal

Nineteen day and day-part columns for media scheduling, plus peak month, trend, lapse and reactivation flags.

How teams use it

What it supports

Sample query

Research-to-purchase crossover by market

SELECT
    identity_market,
    crossover_type,
    COUNT(DISTINCT user_id)                      AS profiles,
    ROUND(AVG(brand_hhi), 3)                     AS brand_concentration,
    ROUND(AVG(brand_distinct), 1)                AS brands_per_person,
    ROUND(AVG(crossover_conversion_rate), 3)     AS conversion_rate
FROM cpg_personas_v3
WHERE engagement_active_months >= 3
GROUP BY identity_market, crossover_type
HAVING COUNT(DISTINCT user_id) >= 20
ORDER BY profiles DESC;

Conditioning on active months matters: brand concentration is censored by observation length, so someone seen for a single month looks perfectly loyal.

Specifications

What ships

Privacy & provenance