inquiry playbook

Buffer Analytics Inquiry & Baseline Playbook #

This reference establishes the standard analytical methodologies, inquiry types, and SQL formulas used to evaluate social post performance, diagnose anomalies, and benchmark content growth.

1. Outlier & Distribution Analysis (Mean vs. Median) #

When evaluating day-of-week, topic, or channel performance, always compare the Median to the Mean to ensure viral spikes (e.g., 40k+ impression posts) do not distort baseline expectations.

Methodology #

• Calculate COUNT, AVG (Mean), MEDIAN, and MAX per cohort.
• Identify skew: If Mean > 3 * Median, performance is driven by rare outliers rather than a repeatable baseline.

SQL / Python Template #

SELECT
    day_of_week,
    COUNT(*) AS post_count,
    ROUND(AVG(impressions), 0) AS mean_impressions,
    MAX(impressions) AS max_impressions,
    ROUND(AVG(reactions), 1) AS mean_reactions
FROM v_posts_summary
WHERE status = 'sent' AND service = 'linkedin'
GROUP BY day_of_week;

2. Time-Series & Growth Tracking (Quarter-over-Quarter) #

Determine whether reach, engagement rate, and audience response are compounding over time.

Methodology #

• Group posts by year_month or quarter.
• Track Posting Frequency against Average Reach to detect content fatigue or audience dilution.

SQL Template #

SELECT
    service,
    strftime('%Y-%m', sent_at) AS year_month,
    COUNT(*) AS posts_published,
    ROUND(SUM(impressions), 0) AS total_impressions,
    ROUND(AVG(impressions), 0) AS avg_impressions_per_post,
    ROUND(AVG(reactions), 1) AS avg_reactions,
    ROUND(AVG(engagement_rate), 2) AS avg_engagement_rate
FROM v_posts_summary
WHERE status = 'sent'
GROUP BY service, year_month
ORDER BY service, year_month;

3. Geographic Sweet-Spot Inference #

Since raw follower country geolocation is paywalled on basic tiers, infer geographic capture by mapping UTC publishing hours to global developer activity zones.

Time Zones & Developer Activity Windows #

• 11:00 – 15:00 UTC (Transatlantic Sweet Spot):
  • UK / Europe: 12:00 – 16:00 (afternoon dwell time).
  • US East Coast: 07:00 – 10:00 EDT (morning commute / start-of-day feed check).
  • Brazil / LATAM: 08:00 – 11:00 BRT (morning startup).
• 17:00 – 21:00 UTC (US West Coast / Evening Catchup):
  • US West Coast: 10:00 – 14:00 PDT.

4. Multi-Platform Top-Performer Trait Profiling #

Extract the top 5–10 posts per platform and analyze their common structural DNA:

5. Behavioral & Effort Allocation Bias Detection #

Detect whether performance differences across days or formats are caused by the calendar day or by author effort:

• Effort Bias: Major long-form blog series and keynote decks are deliberately published on specific days (e.g. Mondays/Thursdays), giving those days an artificial performance advantage over casual mid-week check-ins.
• Cadence vs. Saturation: Posting >5 times a week can dilute median impressions per post, whereas 1–2 high-effort posts per week maximize reach per asset.