세그먼트별 맞춤 캠페인

// ============================================ // RFM 분석 기반 고객 세그멘테이션 시스템 // ============================================ class MAP_Customer_Segmentation { // RFM 점수 계산 (각 항목 1~5점) public function calculate_rfm($user_id) { $orders = wc_get_orders([ 'customer_id' => $user_id, 'status' => ['completed', 'processing'], 'orderby' => 'date', 'order' => 'DESC', 'limit' => -1, ]); if (empty($orders)) { return ['R' => 1, 'F' => 1, 'M' => 1, 'segment' => 'new_prospect']; } // Recency: 최근 주문으로부터 경과 일수 $last_order_date = $orders[0]->get_date_created(); $days_since = (time() - $last_order_date->getTimestamp()) / DAY_IN_SECONDS; if ($days_since $r_score = 5; elseif ($days_since $r_score = 4; elseif ($days_since $r_score = 3; elseif ($days_since $r_score = 2; else $r_score = 1; // Frequency: 총 주문 횟수 $order_count = count($orders); if ($order_count >= 20) $f_score = 5; elseif ($order_count >= 10) $f_score = 4; elseif ($order_count >= 5) $f_score = 3; elseif ($order_count >= 2) $f_score = 2; else $f_score = 1; // Monetary: 총 구매 금액 $total_spent = array_sum(array_map(function($o) { return $o->get_total(); }, $orders)); if ($total_spent >= 1000000) $m_score = 5; elseif ($total_spent >= 500000) $m_score = 4; elseif ($total_spent >= 200000) $m_score = 3; elseif ($total_spent >= 50000) $m_score = 2; else $m_score = 1; // 세그먼트 결정 $total = $r_score + $f_score + $m_score; $segment = $this->determine_segment($r_score, $f_score, $m_score, $total); // 사용자 메타에 저장 update_user_meta($user_id, '_rfm_r', $r_score); update_user_meta($user_id, '_rfm_f', $f_score); update_user_meta($user_id, '_rfm_m', $m_score); update_user_meta($user_id, '_rfm_segment', $segment); update_user_meta($user_id, '_rfm_updated', current_time('mysql')); return [ 'R' => $r_score, 'F' => $f_score, 'M' => $m_score, 'total' => $total, 'segment' => $segment, 'total_spent' => $total_spent, 'order_count' => $order_count, ]; } private function determine_segment($r, $f, $m, $total) { if ($total >= 13) return 'champion'; // 최우수 고객 if ($total >= 10 && $r >= 4) return 'loyal'; // 충성 고객 if ($r >= 4 && $f return 'new_customer'; // 신규 고객 if ($total >= 7 && $r >= 3) return 'potential'; // 잠재 충성 고객 if ($r $f >= 3) return 'at_risk'; // 이탈 위험 if ($r $f >= 4 && $m >= 4) return 'cant_lose'; // 놓치면 안 되는 고객 if ($r return 'lost'; // 이탈 고객 return 'regular'; // 일반 고객 } // 특정 세그먼트의 모든 고객 조회 public function get_segment_users($segment) { return get_users([ 'meta_key' => '_rfm_segment', 'meta_value' => $segment, 'fields' => ['ID', 'user_email', 'display_name'], ]); } // 전체 고객 RFM 일괄 업데이트 (주간 크론) public function batch_update_all() { $customers = get_users([ 'role' => 'customer', 'fields' => 'ID', ]); $stats = []; foreach ($customers as $user_id) { $result = $this->calculate_rfm($user_id); $stats[$result['segment']] = ($stats[$result['segment']] ?? 0) + 1; } update_option('_rfm_segment_stats', $stats); update_option('_rfm_last_batch', current_time('mysql')); return $stats; } }

// 행동 기반 세그멘테이션 (이메일 참여도, 구매 패턴) class MAP_Behavioral_Segmentation { // 이메일 참여도 기반 태깅 public function tag_by_engagement($user_id) { $tags = []; $opens_30d = $this->count_email_opens($user_id, 30); $clicks_30d = $this->count_email_clicks($user_id, 30); if ($opens_30d >= 10 && $clicks_30d >= 5) { $tags[] = 'highly_engaged'; } elseif ($opens_30d >= 3) { $tags[] = 'engaged'; } elseif ($opens_30d === 0) { $tags[] = 'disengaged'; } else { $tags[] = 'low_engaged'; } // 구매 패턴 태깅 $order_count = wc_get_customer_order_count($user_id); if ($order_count >= 5) $tags[] = 'repeat_buyer'; if ($order_count === 0) $tags[] = 'never_purchased'; // 평균 주문 금액 태깅 $avg_order = $this->get_avg_order_value($user_id); if ($avg_order >= 100000) $tags[] = 'high_value'; elseif ($avg_order >= 50000) $tags[] = 'mid_value'; else $tags[] = 'low_value'; // 관심 카테고리 태깅 $top_categories = $this->get_top_categories($user_id, 3); foreach ($top_categories as $cat) { $tags[] = 'interest_' . sanitize_title($cat); } // 태그 저장 update_user_meta($user_id, '_segment_tags', $tags); return $tags; } // 동적 세그먼트 쿼리 (복합 조건) public function query_segment($conditions) { global $wpdb; $query = "SELECT DISTINCT u.ID, u.user_email, u.display_name FROM {$wpdb->users} u INNER JOIN {$wpdb->usermeta} um ON u.ID = um.user_id"; $where = ["1=1"]; foreach ($conditions as $cond) { switch ($cond['type']) { case 'rfm_segment': $where[] = $wpdb->prepare( "u.ID IN (SELECT user_id FROM {$wpdb->usermeta} WHERE meta_key = '_rfm_segment' AND meta_value = %s)", $cond['value'] ); break; case 'has_tag': $where[] = $wpdb->prepare( "u.ID IN (SELECT user_id FROM {$wpdb->usermeta} WHERE meta_key = '_segment_tags' AND meta_value LIKE %s)", '%' . $cond['value'] . '%' ); break; case 'min_orders': $where[] = $wpdb->prepare( "u.ID IN (SELECT pm.meta_value FROM {$wpdb->postmeta} pm INNER JOIN {$wpdb->posts} p ON pm.post_id = p.ID WHERE pm.meta_key = '_customer_user' AND p.post_type = 'shop_order' AND p.post_status IN ('wc-completed','wc-processing') GROUP BY pm.meta_value HAVING COUNT(*) >= %d)", $cond['value'] ); break; case 'last_order_within': $where[] = $wpdb->prepare( "u.ID IN (SELECT pm.meta_value FROM {$wpdb->postmeta} pm INNER JOIN {$wpdb->posts} p ON pm.post_id = p.ID WHERE pm.meta_key = '_customer_user' AND p.post_type = 'shop_order' GROUP BY pm.meta_value HAVING MAX(p.post_date) >= DATE_SUB(NOW(), INTERVAL %d DAY))", $cond['value'] ); break; } } return $wpdb->get_results( $query . " WHERE " . implode(" AND ", $where) ); } }