get_customer_insights

com.ask-ai-data-connector/ask-ai · Verify this server

Get customer behavior and retention insights. All reports are per-store in multi-store mode — use the store param to target a specific store. Reports: new_vs_returning (revenue/orders/AOV split by first-time vs repeat buyers), repeat_metrics (repeat purchase rate, avg days between purchases, BOTH avgLifetimeValue and medianLifetimeValue, lifetimeValueSkewRatio + distribution note — LEAD WITH MEDIAN when describing 'the typical customer', use mean only when distribution is symmetric; if `lifetimeValueDistributionNote` is present the mean is misleading), cohorts (monthly acquisition cohorts — counts and aggregate repeat rate), retention_curve (per-cohort cumulative retention % AND LTV at month 1/3/6/12 — the canonical e-commerce LTV view; cohorts that haven't matured to a milestone show null for that milestone, not a fake-low value), by_category (repeat rate by Shopify product_type — requires product_type to be set, returns 'Uncategorized' if not), cohorts_by_first_purchase (cohorts by first product category), top_customers (ranked by LTV or order count), lapsed_high_value (high-spending customers who haven't ordered recently — per-store, ideal for targeted win-back campaigns; rows carry a Shopify-admin adminUrl (this dataset holds no names/emails by design) and customer tags, trade-frequency accounts are flagged likelyWholesale so they're excluded from consumer win-backs, and customers inactive beyond maxDaysInactive (default 365d) are treated as churned and excluded).