Calibrate RFV customer lifecycle segments
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@@ -1,6 +1,9 @@
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const { pool } = require('../db');
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const RFM_QUERY_TIMEOUT_MS = 15000;
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const RECENT_MAX_DAYS = 60;
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const COOLING_MAX_DAYS = 180;
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const LOST_MIN_DAYS = 366;
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const SIZE_SUFFIX_SQL_PATTERN = '\\s+-\\s+(?:(?:PP|P|M|G|GG|XG|XGG|EG|EGG|EXG|U|UNICO|ÚNICO|\\d{2})(?:/(?:PP|P|M|G|GG|XG|XGG|EG|EGG|EXG|U|UNICO|ÚNICO|\\d{2}))*)$';
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const PRODUCT_NAME_SQL = `
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CASE
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@@ -77,6 +80,9 @@ const RFM_SEGMENTS = {
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'1-2': { key: 'hibernating', label: 'Hibernando' },
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'1-1': { key: 'lost', label: 'Perdidos' }
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};
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const RFM_SEGMENTS_BY_KEY = new Map(
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Object.values(RFM_SEGMENTS).map(segment => [segment.key, segment])
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);
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const scoreTertile = (value, values, higherIsBetter = true) => {
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const numericValues = values.map(toNumber).filter(Number.isFinite);
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@@ -120,6 +126,47 @@ const getRfmSegment = (recencyScore, valueScore) => {
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return RFM_SEGMENTS[`${recencyScore}-${valueScore}`] || RFM_SEGMENTS['1-1'];
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};
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const getRecencyScore = (recencyDays) => {
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const days = Math.max(0, toNumber(recencyDays));
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if (days <= RECENT_MAX_DAYS) return 3;
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if (days <= COOLING_MAX_DAYS) return 2;
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return 1;
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};
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const getLifecycleSegment = ({
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recencyDays,
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historicalFrequency,
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frequencyScore,
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monetaryScore,
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valueScore
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}) => {
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const days = Math.max(0, toNumber(recencyDays));
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if (days >= LOST_MIN_DAYS) {
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return { segment: RFM_SEGMENTS_BY_KEY.get('lost'), valueScore: 1 };
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}
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if (days > COOLING_MAX_DAYS) {
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const hasStrongHistory = frequencyScore === 3 || monetaryScore === 3;
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return hasStrongHistory
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? { segment: RFM_SEGMENTS_BY_KEY.get('at_risk'), valueScore: 3 }
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: { segment: RFM_SEGMENTS_BY_KEY.get('hibernating'), valueScore: 2 };
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}
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if (days <= RECENT_MAX_DAYS && historicalFrequency === 1) {
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return { segment: RFM_SEGMENTS_BY_KEY.get('new_customers'), valueScore: 1 };
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}
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if (days <= RECENT_MAX_DAYS && valueScore === 1) {
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return { segment: RFM_SEGMENTS_BY_KEY.get('potential_loyalists'), valueScore: 2 };
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}
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return {
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segment: getRfmSegment(getRecencyScore(days), valueScore),
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valueScore
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};
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};
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const getDateDiffDays = (endDate, startDate) => {
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const normalizedEnd = normalizeDateParam(endDate);
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const normalizedStart = normalizeDateParam(startDate);
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@@ -153,21 +200,30 @@ const buildRfmSegments = (clients) => {
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};
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const buildRfmClients = (baseClients) => {
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const recencyScoreFor = buildTertileScorer(baseClients.map(client => client.recencyDays), false);
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const frequencyScoreFor = buildTertileScorer(baseClients.map(client => client.rfmFrequency ?? client.frequency), true);
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const monetaryScoreFor = buildTertileScorer(baseClients.map(client => client.rfmMonetary ?? client.monetary), true);
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return baseClients.map(client => {
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const frequencyForScore = client.rfmFrequency ?? client.frequency;
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const monetaryForScore = client.rfmMonetary ?? client.monetary;
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const recencyScore = recencyScoreFor(client.recencyDays);
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const frequencyScore = frequencyScoreFor(frequencyForScore);
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const monetaryScore = monetaryScoreFor(monetaryForScore);
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const valueScore = Math.min(3, Math.max(1, Math.round((frequencyScore + monetaryScore) / 2)));
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const segment = getRfmSegment(recencyScore, valueScore);
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const recencyDays = Math.max(0, toNumber(client.recencyDays));
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const historicalFrequency = toNumber(client.rfmFrequency ?? client.frequency);
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const historicalMonetary = toNumber(client.rfmMonetary ?? client.monetary);
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const recencyScore = getRecencyScore(recencyDays);
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const frequencyScore = client.rfmFrequencyScore ?? frequencyScoreFor(historicalFrequency);
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const monetaryScore = client.rfmMonetaryScore ?? monetaryScoreFor(historicalMonetary);
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const baseValueScore = Math.min(3, Math.max(1, Math.round((frequencyScore + monetaryScore) / 2)));
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const classification = getLifecycleSegment({
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recencyDays,
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historicalFrequency,
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frequencyScore,
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monetaryScore,
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valueScore: baseValueScore
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});
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const valueScore = classification.valueScore;
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const segment = classification.segment;
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return {
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...client,
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recencyDays,
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recencyScore,
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frequencyScore,
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monetaryScore,
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@@ -377,39 +433,49 @@ const getRfmAnalytics = async (range = {}) => {
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let historyRows = periodResult.rows;
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if (!usePeriodAsHistory) {
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const periodPhones = [...new Set(periodResult.rows.map(row => row.phone).filter(Boolean))];
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const periodNamesWithoutPhone = [...new Set(periodResult.rows
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.filter(row => !row.phone && String(row.customer_key || '').startsWith('name:'))
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.map(row => String(row.customer_key).slice(5))
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const periodCustomerKeys = [...new Set(periodResult.rows
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.map(row => row.customer_key)
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.filter(Boolean))];
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const historyParams = [];
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const recencyReferenceDate = normalizedEnd
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? `$${historyParams.push(normalizedEnd)}::date`
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: 'CURRENT_DATE';
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const phoneListParam = `$${historyParams.push(periodPhones)}::text[]`;
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const nameListParam = `$${historyParams.push(periodNamesWithoutPhone)}::text[]`;
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const customerKeysParam = `$${historyParams.push(periodCustomerKeys)}::text[]`;
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const historyResult = await client.query(`
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SELECT
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${CUSTOMER_KEY_SQL} as customer_key,
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MAX(COALESCE(NULLIF(cliente_nome, ''), 'Cliente Desconhecido')) as name,
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MAX(NULLIF(cliente_fone, '')) as phone,
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COALESCE(SUM(quantidade * valor_unitario), 0) as monetary,
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COUNT(DISTINCT COALESCE(NULLIF(pedido_id, ''), data_pedido || '_' || valor_pedido::text))::int as frequency,
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COALESCE(SUM(quantidade), 0) as quantity_purchased,
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MAX(data_pedido_date) as last_purchase_date,
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GREATEST((${recencyReferenceDate} - MAX(data_pedido_date))::int, 0) as recency_days
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FROM orders
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WHERE data_pedido_date IS NOT NULL
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AND data_pedido_date <= ${recencyReferenceDate}
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AND (
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NULLIF(cliente_fone, '') = ANY(${phoneListParam})
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OR (
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NULLIF(cliente_fone, '') IS NULL
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AND COALESCE(NULLIF(cliente_nome, ''), 'Cliente Desconhecido') = ANY(${nameListParam})
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)
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)
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GROUP BY customer_key;
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WITH customer_history AS (
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SELECT
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${CUSTOMER_KEY_SQL} as customer_key,
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MAX(COALESCE(NULLIF(cliente_nome, ''), 'Cliente Desconhecido')) as name,
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MAX(NULLIF(cliente_fone, '')) as phone,
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COALESCE(SUM(quantidade * valor_unitario), 0) as monetary,
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COUNT(DISTINCT COALESCE(NULLIF(pedido_id, ''), data_pedido || '_' || valor_pedido::text))::int as frequency,
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COALESCE(SUM(quantidade), 0) as quantity_purchased,
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MAX(data_pedido_date) as last_purchase_date,
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GREATEST((${recencyReferenceDate} - MAX(data_pedido_date))::int, 0) as recency_days
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FROM orders
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WHERE data_pedido_date IS NOT NULL
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AND data_pedido_date <= ${recencyReferenceDate}
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GROUP BY customer_key
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),
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scored_history AS MATERIALIZED (
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SELECT
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customer_history.*,
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CASE
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WHEN COUNT(*) OVER () = 1 THEN 3
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WHEN MIN(frequency) OVER () = MAX(frequency) OVER () THEN 2
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ELSE LEAST(3, GREATEST(1, FLOOR(PERCENT_RANK() OVER (ORDER BY frequency) * 3)::int + 1))
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END as frequency_score,
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CASE
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WHEN COUNT(*) OVER () = 1 THEN 3
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WHEN MIN(monetary) OVER () = MAX(monetary) OVER () THEN 2
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ELSE LEAST(3, GREATEST(1, FLOOR(PERCENT_RANK() OVER (ORDER BY monetary) * 3)::int + 1))
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END as monetary_score
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FROM customer_history
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)
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SELECT *
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FROM scored_history
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WHERE customer_key = ANY(${customerKeysParam});
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`, historyParams);
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historyRows = historyResult.rows;
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}
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@@ -422,15 +488,16 @@ const getRfmAnalytics = async (range = {}) => {
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frequency: toNumber(row.frequency),
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quantityPurchased: toNumber(row.quantity_purchased),
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lastPurchaseDate: row.last_purchase_date,
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recencyDays: toNumber(row.recency_days)
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recencyDays: toNumber(row.recency_days),
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rfmFrequencyScore: row.frequency_score === undefined ? undefined : toNumber(row.frequency_score),
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rfmMonetaryScore: row.monetary_score === undefined ? undefined : toNumber(row.monetary_score)
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})));
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const tagsByCustomerKey = new Map(historyClients.map(historyClient => [historyClient.customerKey, historyClient]));
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const clients = periodResult.rows.map(row => {
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const taggedClient = tagsByCustomerKey.get(row.customer_key);
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if (!taggedClient) {
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const newCustomerSegment = getRfmSegment(3, 1);
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return {
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const [fallbackClient] = buildRfmClients([{
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customerKey: row.customer_key,
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name: row.name,
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phone: row.phone || '',
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@@ -438,15 +505,9 @@ const getRfmAnalytics = async (range = {}) => {
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frequency: toNumber(row.frequency),
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quantityPurchased: toNumber(row.quantity_purchased),
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lastPurchaseDate: row.last_purchase_date,
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recencyDays: 0,
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recencyScore: 3,
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frequencyScore: 1,
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monetaryScore: 1,
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valueScore: 1,
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rfmScore: '311',
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segmentKey: newCustomerSegment.key,
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segmentLabel: newCustomerSegment.label
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};
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recencyDays: toNumber(row.recency_days)
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}]);
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return fallbackClient;
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}
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return {
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@@ -492,6 +553,7 @@ module.exports = {
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buildRfmClients,
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buildRfmSegments,
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getPreviousDate,
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getRecencyScore,
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getRfmAnalytics,
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getRfmSegment,
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getClientAnalytics,
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@@ -6,6 +6,7 @@ const {
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buildRfmSegments,
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buildDateFilter,
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getPreviousDate,
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getRecencyScore,
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getRfmAnalytics,
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getRfmSegment,
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normalizeDateParam,
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@@ -109,6 +110,16 @@ test('scoreTertile treats equal recency as high recency', () => {
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assert.equal(scoreTertile(0, [0, 0, 0], false), 3);
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});
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test('getRecencyScore uses fixed lifecycle boundaries', () => {
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assert.equal(getRecencyScore(0), 3);
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assert.equal(getRecencyScore(60), 3);
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assert.equal(getRecencyScore(61), 2);
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assert.equal(getRecencyScore(180), 2);
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assert.equal(getRecencyScore(181), 1);
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assert.equal(getRecencyScore(365), 1);
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assert.equal(getRecencyScore(366), 1);
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});
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test('getRfmSegment maps the 3x3 RFM matrix', () => {
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assert.deepEqual(getRfmSegment(3, 3), { key: 'champions', label: 'Champions' });
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assert.deepEqual(getRfmSegment(2, 2), { key: 'need_attention', label: 'Precisam de Atenção' });
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@@ -191,6 +202,74 @@ test('buildRfmClients scores segments from RFM history when period totals are sm
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assert.equal(yesterdayBuyer.monetaryScore, 3);
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});
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test('buildRfmClients applies lifecycle protections to new, hibernating, at-risk, and lost clients', () => {
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const clients = buildRfmClients([
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{
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customerKey: 'new',
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name: 'Novo',
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monetary: 50,
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frequency: 1,
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recencyDays: 60,
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rfmFrequency: 1,
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rfmMonetary: 50,
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rfmFrequencyScore: 1,
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rfmMonetaryScore: 1
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},
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{
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customerKey: 'not-new',
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name: 'Não é mais novo',
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monetary: 50,
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frequency: 1,
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recencyDays: 61,
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rfmFrequency: 1,
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rfmMonetary: 50,
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rfmFrequencyScore: 1,
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rfmMonetaryScore: 1
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},
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{
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customerKey: 'hibernating',
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name: 'Hibernando',
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monetary: 50,
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frequency: 1,
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recencyDays: 250,
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rfmFrequency: 1,
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rfmMonetary: 50,
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rfmFrequencyScore: 1,
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rfmMonetaryScore: 1
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},
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{
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customerKey: 'at-risk',
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name: 'Em Risco',
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monetary: 100,
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frequency: 1,
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recencyDays: 250,
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rfmFrequency: 10,
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rfmMonetary: 1000,
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rfmFrequencyScore: 3,
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rfmMonetaryScore: 2
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},
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{
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customerKey: 'lost',
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name: 'Perdido',
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monetary: 2000,
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frequency: 1,
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recencyDays: 366,
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rfmFrequency: 1,
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rfmMonetary: 2000,
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rfmFrequencyScore: 1,
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rfmMonetaryScore: 3
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}
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]);
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const byKey = new Map(clients.map(client => [client.customerKey, client]));
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assert.equal(byKey.get('new').segmentKey, 'new_customers');
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assert.equal(byKey.get('not-new').segmentKey, 'about_to_sleep');
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assert.equal(byKey.get('hibernating').segmentKey, 'hibernating');
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assert.equal(byKey.get('at-risk').segmentKey, 'at_risk');
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assert.equal(byKey.get('lost').segmentKey, 'lost');
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assert.equal(byKey.get('lost').rfmScore, '113');
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});
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test('getRfmAnalytics classifies period buyers by history through the selected range end', async () => {
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const originalConnect = pool.connect;
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const calls = [];
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@@ -216,27 +295,21 @@ test('getRfmAnalytics classifies period buyers by history through the selected r
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frequency: 20,
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quantity_purchased: 20,
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last_purchase_date: '2026-06-14',
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recency_days: referenceDate === '2026-06-14' ? 0 : 1
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recency_days: referenceDate === '2026-06-14' ? 0 : 1,
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frequency_score: 3,
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monetary_score: 3
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},
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{
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customer_key: '2',
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name: 'Cliente Antigo',
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phone: '2',
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monetary: 50,
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customer_key: '4',
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name: 'Cliente Novo no Periodo',
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phone: '4',
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monetary: 25,
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frequency: 1,
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quantity_purchased: 1,
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last_purchase_date: '2026-01-01',
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recency_days: 164
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},
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{
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customer_key: '3',
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name: 'Cliente Medio',
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phone: '3',
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monetary: 100,
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frequency: 2,
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quantity_purchased: 2,
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last_purchase_date: '2026-03-01',
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recency_days: 105
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last_purchase_date: '2026-06-14',
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recency_days: referenceDate === '2026-06-14' ? 0 : 1,
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frequency_score: 1,
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monetary_score: 1
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},
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{
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customer_key: 'name:Cliente Sem Fone',
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@@ -246,7 +319,9 @@ test('getRfmAnalytics classifies period buyers by history through the selected r
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frequency: 10,
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quantity_purchased: 10,
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last_purchase_date: '2026-06-14',
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recency_days: 1
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recency_days: referenceDate === '2026-06-14' ? 0 : 1,
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frequency_score: 3,
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monetary_score: 3
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}
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]
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};
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@@ -301,12 +376,13 @@ test('getRfmAnalytics classifies period buyers by history through the selected r
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assert.doesNotMatch(selectCalls[0].sql, /cliente_fone IS NOT NULL/);
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assert.match(selectCalls[1].sql, /\(\$1::date - MAX\(data_pedido_date\)\)::int/);
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assert.match(selectCalls[1].sql, /data_pedido_date <= \$1::date/);
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assert.match(selectCalls[1].sql, /NULLIF\(cliente_fone, ''\) = ANY\(\$2::text\[\]\)/);
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assert.match(selectCalls[1].sql, /COALESCE\(NULLIF\(cliente_nome, ''\), 'Cliente Desconhecido'\) = ANY\(\$3::text\[\]\)/);
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assert.match(selectCalls[1].sql, /PERCENT_RANK\(\) OVER \(ORDER BY frequency\)/);
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assert.match(selectCalls[1].sql, /PERCENT_RANK\(\) OVER \(ORDER BY monetary\)/);
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assert.match(selectCalls[1].sql, /customer_key = ANY\(\$2::text\[\]\)/);
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assert.doesNotMatch(selectCalls[1].sql, /cliente_fone IS NOT NULL/);
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assert.deepEqual(selectCalls[1].params, ['2026-06-15', ['1', '4'], ['Cliente Sem Fone']]);
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assert.deepEqual(selectCalls[1].params, ['2026-06-15', ['1', '4', 'name:Cliente Sem Fone']]);
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assert.deepEqual(selectCalls[2].params, ['2026-06-14', '2026-06-14']);
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assert.deepEqual(selectCalls[3].params, ['2026-06-14', ['1', '4'], ['Cliente Sem Fone']]);
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assert.deepEqual(selectCalls[3].params, ['2026-06-14', ['1', '4', 'name:Cliente Sem Fone']]);
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assert.equal(sevenDays.clients[0].segmentKey, 'champions');
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assert.equal(yesterday.clients[0].segmentKey, 'champions');
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assert.equal(yesterday.clients[0].frequency, 1);
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@@ -34,14 +34,14 @@ const rfmSegmentDefinitions: Array<Pick<RfmSegment, 'key' | 'label'>> = [
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const segmentDescriptions: Record<string, string> = {
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||||
champions: 'Recentes, frequentes e valiosos',
|
||||
potential_loyalists: 'Recentes com bom potencial',
|
||||
new_customers: 'Primeira compra recente',
|
||||
loyal_customers: 'Valiosos, mas menos recentes',
|
||||
need_attention: 'Base intermediária para nutrir',
|
||||
about_to_sleep: 'Baixo valor começando a esfriar',
|
||||
at_risk: 'Valiosos sem compra recente',
|
||||
hibernating: 'Sem compra recente e valor médio',
|
||||
lost: 'Baixa atividade e distante'
|
||||
potential_loyalists: 'Recentes e em evolução',
|
||||
new_customers: 'Primeiro pedido nos últimos 60 dias',
|
||||
loyal_customers: 'Bom histórico, compra entre 61 e 180 dias',
|
||||
need_attention: 'Perfil médio, compra entre 61 e 180 dias',
|
||||
about_to_sleep: 'Perfil baixo, compra entre 61 e 180 dias',
|
||||
at_risk: 'Histórico forte, sem compra entre 181 e 365 dias',
|
||||
hibernating: 'Sem compra entre 181 e 365 dias',
|
||||
lost: 'Sem compra há 366 dias ou mais'
|
||||
};
|
||||
|
||||
const segmentActions: Record<string, string> = {
|
||||
@@ -312,7 +312,7 @@ const Rfm = () => {
|
||||
<div className="mb-4 flex flex-col gap-3 lg:flex-row lg:items-end lg:justify-between">
|
||||
<div>
|
||||
<h2 className="text-lg font-bold text-dark-text">Matriz RFV</h2>
|
||||
<p className="text-sm font-medium text-dark-muted">Compradores do período agrupados pelo RFV histórico até a data final.</p>
|
||||
<p className="text-sm font-medium text-dark-muted">Compradores do período agrupados por recência fixa e perfil histórico de frequência e valor.</p>
|
||||
</div>
|
||||
<div className="flex items-center gap-2 text-xs font-semibold text-dark-muted">
|
||||
<span>Menor prioridade</span>
|
||||
@@ -326,12 +326,12 @@ const Rfm = () => {
|
||||
<div className="flex items-center justify-center rounded-xl border border-dark-border bg-dark-input/60 px-3 py-2.5 text-center">
|
||||
<div>
|
||||
<p className="text-[10px] font-bold uppercase tracking-wider text-dark-muted">Eixos</p>
|
||||
<p className="text-xs font-semibold text-dark-text">Recência / Valor</p>
|
||||
<p className="text-xs font-semibold text-dark-text">Recência / Perfil</p>
|
||||
</div>
|
||||
</div>
|
||||
{[1, 2, 3].map(valueScore => (
|
||||
<div key={valueScore} className="rounded-xl border border-dark-border bg-dark-input/70 px-3 py-2.5 text-center">
|
||||
<p className="text-[10px] font-bold uppercase tracking-wider text-dark-muted">Valor {valueScore}</p>
|
||||
<p className="text-[10px] font-bold uppercase tracking-wider text-dark-muted">Perfil {valueScore}</p>
|
||||
<p className="text-xs font-bold text-dark-text">{scoreLabel(valueScore)}</p>
|
||||
</div>
|
||||
))}
|
||||
@@ -343,7 +343,7 @@ const Rfm = () => {
|
||||
<p className="text-[10px] font-bold uppercase tracking-wider text-dark-muted">Rec. {recencyScore}</p>
|
||||
<p className="text-xs font-bold text-dark-text">{scoreLabel(recencyScore)}</p>
|
||||
<p className="mt-1 text-[10px] font-semibold text-dark-muted">
|
||||
{recencyScore === 3 ? 'Compra recente' : recencyScore === 2 ? 'Intermediário' : 'Distante'}
|
||||
{recencyScore === 3 ? '0 a 60 dias' : recencyScore === 2 ? '61 a 180 dias' : '181+ dias'}
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
@@ -371,7 +371,7 @@ const Rfm = () => {
|
||||
<div className="mb-2 flex items-start justify-between gap-2">
|
||||
<span className={`h-2 w-8 rounded-full ${style.accent}`} />
|
||||
<span className="rounded-md border border-dark-border bg-black/10 px-1.5 py-0.5 text-[10px] font-bold text-dark-muted">
|
||||
R{recencyScore} V{valueScore}
|
||||
R{recencyScore} P{valueScore}
|
||||
</span>
|
||||
</div>
|
||||
<p className="text-sm font-bold text-dark-text">{segment?.label}</p>
|
||||
|
||||
Reference in New Issue
Block a user