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Referenzabfragen für den Connect Customer Data Lake - Amazon Connect Connect-Kunde

Die vorliegende Übersetzung wurde maschinell erstellt. Im Falle eines Konflikts oder eines Widerspruchs zwischen dieser übersetzten Fassung und der englischen Fassung (einschließlich infolge von Verzögerungen bei der Übersetzung) ist die englische Fassung maßgeblich.

Referenzabfragen für den Connect Customer Data Lake

Dieses Thema enthält Athena-SQL-Abfragen (Trino Engine v3) zur Berechnung gängiger Connect Customer-Metriken aus Data-Lake-Tabellen. Alle Abfragen verwenden Bezeichner in doppelten Anführungszeichen und gehen von einem Datenbanknamen aus. connect_datalake Passen Sie den Datenbanknamen an Ihre Glue-Katalogkonfiguration an.

Ersetzen Sie <YOUR_INSTANCE_ID> in jeder Abfrage durch Ihre Connect Customer-Instanz-ID.

Kontakt- und Warteschlangenmetriken

Abbruchrate

Definition: Prozentsatz der Kontakte, die vom Kunden während der Warteschleife unterbrochen wurden. Rückrufe ausgeschlossen.

Quelltabelle: contact_statistic_record

SELECT "queue_id", CAST(SUM("is_abandoned") AS DOUBLE) / NULLIF(SUM("is_queued"), 0) * 100.0 AS "abandonment_rate_pct" FROM "connect_datalake"."contact_statistic_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id" ORDER BY "abandonment_rate_pct" DESC;

Contacts abandoned (Abgebrochene Kontakte)

Definition: Anzahl der Kontakte, die vom Kunden unterbrochen wurden, während er in der Warteschlange wartete.

Quelltabelle: contact_statistic_record

SELECT "queue_id", SUM("is_abandoned") AS "contacts_abandoned" FROM "connect_datalake"."contact_statistic_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id";

Contacts abandoned in X seconds (Kontakte, die innerhalb von X Sekunden abgebrochen wurden)

Definition: Anzahl der Kontakte, die innerhalb von X Sekunden, nachdem sie in die Warteschlange gestellt wurden, verlassen wurden.

Quelltabelle: contact_statistic_record

SELECT "queue_id", SUM( CASE WHEN "is_abandoned" = 1 AND "queue_time_ms" <= 30000 THEN 1 ELSE 0 END ) AS "contacts_abandoned_in_30s" FROM "connect_datalake"."contact_statistic_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id";

Average queue abandon time (Durchschnittliche Warteschlangenabbruchzeit)

Definition: Durchschnittliche Wartezeit von Kontakten in der Warteschlange, bevor sie den Vorgang abbrechen.

Quelltabelle: contact_statistic_record

SELECT "queue_id", AVG("abandon_time_ms") / 1000.0 AS "avg_queue_abandon_time_sec" FROM "connect_datalake"."contact_statistic_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "is_abandoned" = 1 AND "abandon_time_ms" IS NOT NULL AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id";

Durchschnittliche Warteschlangenantwortzeit

Definition: Durchschnittliche Zeit, in der Kontakte in der Warteschlange warteten, bis sie von einem Agenten beantwortet wurden.

Quelltabelle: contact_statistic_record

SELECT "queue_id", AVG("queue_answer_time_ms") / 1000.0 AS "avg_queue_answer_time_sec" FROM "connect_datalake"."contact_statistic_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "is_handled" = 1 AND "queue_answer_time_ms" IS NOT NULL AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id";

Serviceniveau

Definition: Anzahl und Prozentsatz der Kontakte, die innerhalb von X Sekunden beantwortet wurden.

Quelltabelle: contact_statistic_record

SELECT "queue_id", SUM(CASE WHEN "is_handled" = 1 AND "queue_answer_time_ms" <= 20000 THEN 1 ELSE 0 END) AS "contacts_answered_in_20s", SUM("is_queued") AS "contacts_queued", CAST(SUM(CASE WHEN "is_handled" = 1 AND "queue_answer_time_ms" <= 20000 THEN 1 ELSE 0 END) AS DOUBLE) / NULLIF(SUM("is_queued"), 0) * 100.0 AS "service_level_20s_pct" FROM "connect_datalake"."contact_statistic_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id";

Contacts queued (Kontakte in Warteschlange)

Definition: Anzahl der Kontakte, die in eine Warteschlange aufgenommen wurden.

Quelltabelle: contact_statistic_record

SELECT "queue_id", SUM("is_queued") AS "contacts_queued" FROM "connect_datalake"."contact_statistic_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id";

Contacts handled (Bearbeitete Kontakte)

Definition: Anzahl der Kontakte, die mit einem Agenten verbunden sind.

Quelltabelle: contact_statistic_record

SELECT "queue_id", SUM("is_handled") AS "contacts_handled" FROM "connect_datalake"."contact_statistic_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id";

Contacts transferred in (Weitergeleitete Kontakte ein)

Definition: Kontakte, die in eine Warteschlange übertragen wurden.

Quelltabelle: contact_statistic_record

SELECT "queue_id", SUM("is_transferred_in") AS "contacts_transferred_in" FROM "connect_datalake"."contact_statistic_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id";

Contacts transferred out (Weitergeleitete Kontakte aus)

Definition: Kontakte, die aus einer Warteschlange übertragen wurden.

Quelltabelle: contact_statistic_record

SELECT "queue_id", SUM("is_transferred_out") AS "contacts_transferred_out", SUM("is_transferred_out_internal") AS "transferred_out_internal", SUM("is_transferred_out_external") AS "transferred_out_external" FROM "connect_datalake"."contact_statistic_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id";

Maximum queued time (Maximale Zeit in der Warteschlange)

Definition: Längste Zeit, die ein Kontakt damit verbracht hat, in der Warteschlange zu warten.

Quelltabelle: contact_record

SELECT "queue_id", MAX("queue_duration_ms") / 1000.0 AS "max_queued_time_sec" FROM "connect_datalake"."contact_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "queue_duration_ms" IS NOT NULL AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id";

Durchschnittliche Kontaktdauer

Definition: Durchschnittliche Zeit von der Kontaktaufnahme bis zur Unterbrechung der Verbindung.

Quelltabelle: contact_record

SELECT "queue_id", AVG( date_diff('millisecond', "initiation_timestamp", "disconnect_timestamp") ) / 1000.0 AS "avg_contact_duration_sec" FROM "connect_datalake"."contact_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "initiation_timestamp" IS NOT NULL AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id";

Leistungskennzahlen für Agenten

Average handle time (Durchschnittliche Bearbeitungszeit)

Definition: Durchschnittliche Zeit von der Kontaktverbindung bis zum Abschluss von ACW.

Quelltabelle: contact_statistic_record

SELECT "agent_id", AVG("handle_time_ms") / 1000.0 AS "avg_handle_time_sec" FROM "connect_datalake"."contact_statistic_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "is_handled" = 1 AND "handle_time_ms" IS NOT NULL AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "agent_id";

After contact work time (Kontaktnachbearbeitungszeit)

Definition: Gesamtzeit, die Agenten im Status ACW verbracht haben.

Quelltabelle: contact_statistic_record

SELECT "agent_id", SUM("after_contact_work_time_ms") / 1000.0 AS "total_acw_time_sec" FROM "connect_datalake"."contact_statistic_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "after_contact_work_time_ms" IS NOT NULL AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "agent_id";

Customer hold time (Kundenhaltezeit)

Definition: Gesamtzeit, die Kunden in der Warteschleife verbracht haben, nachdem sie eine Verbindung zum Agenten hergestellt haben.

Quelltabelle: contact_statistic_record

SELECT "agent_id", SUM("customer_hold_time_ms") / 1000.0 AS "total_hold_time_sec" FROM "connect_datalake"."contact_statistic_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "customer_hold_time_ms" IS NOT NULL AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "agent_id";

Agent idle time (Leerlaufzeit von Kundendienstmitarbeitern)

Definition: Zeit, die der Agent im Status „Verfügbar“ verbracht hat, ohne Kontakte zu bearbeiten.

Quelltabelle: agent_statistic_record

SELECT "user_id" AS "agent_id", SUM("agent_idle_time") / 1000.0 AS "total_idle_time_sec" FROM "connect_datalake"."agent_statistic_record" WHERE "published_date" >= TIMESTAMP '2026-06-09 00:00:00' AND "published_date" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "user_id";

Occupancy (Auslastung)

Definition: Prozentualer Anteil der Zeit, in der Agenten bei Kontakten aktiv waren, im Vergleich zu „verfügbar“ und „aktiv“.

Quelltabelle: agent_statistic_record

SELECT "user_id" AS "agent_id", CAST(SUM("agent_on_contact_time") AS DOUBLE) / NULLIF(SUM("agent_on_contact_time") + SUM("agent_idle_time"), 0) * 100.0 AS "occupancy_pct" FROM "connect_datalake"."agent_statistic_record" WHERE "published_date" >= TIMESTAMP '2026-06-09 00:00:00' AND "published_date" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "user_id";

Kundendienstmitarbeiter non-response (Nichtbeantwortung des Kundendienstmitarbeiters)

Definition: Anzahl der Kontakte, die an den Agenten weitergeleitet, aber nicht beantwortet wurden.

Quelltabelle: agent_queue_statistic_record

SELECT "user_id" AS "agent_id", "queue_id", SUM("agent_non_response") AS "agent_non_response_count" FROM "connect_datalake"."agent_queue_statistic_record" WHERE "published_date" >= TIMESTAMP '2026-06-09 00:00:00' AND "published_date" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "user_id", "queue_id";

Agent answer rate (Antwortrate des Kundendienstmitarbeiters)

Definition: Prozentsatz der weitergeleiteten Kontakte, die vom Agenten beantwortet wurden.

Quelltabelle: agent_queue_statistic_record

SELECT "user_id" AS "agent_id", CAST(SUM("contacts_handled") AS DOUBLE) / NULLIF(SUM("contacts_offered"), 0) * 100.0 AS "agent_answer_rate_pct" FROM "connect_datalake"."agent_queue_statistic_record" WHERE "published_date" >= TIMESTAMP '2026-06-09 00:00:00' AND "published_date" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "user_id";

Online time (Online-Zeit)

Definition: Gesamtzeit, in der Agent CCP auf einen anderen Status als Offline gesetzt wurde.

Quelltabelle: agent_statistic_record

SELECT "user_id" AS "agent_id", SUM("online_time") / 1000.0 AS "total_online_time_sec" FROM "connect_datalake"."agent_statistic_record" WHERE "published_date" >= TIMESTAMP '2026-06-09 00:00:00' AND "published_date" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "user_id";

Chat-Metriken

Durchschnittl. Zeit erste Reaktion Kundendienstmitarbeiter

Definition: Durchschnittliche Zeit, die ein Agent benötigt, um die erste Nachricht zu senden, nachdem er einen Chat-Kontakt erhalten hat.

Quelltabelle: contact_record

SELECT "queue_id", AVG("chat_contact_metrics_agent_first_response_time_ms") / 1000.0 AS "avg_agent_first_response_sec" FROM "connect_datalake"."contact_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "channel" = 'CHAT' AND "chat_contact_metrics_agent_first_response_time_ms" IS NOT NULL AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id";

Durchschnittl. Zeit Reaktion Kundendienstmitarbeiter

Definition: Durchschnittliche Zeit, die Agenten benötigen, um auf Kundennachrichten zu antworten.

Quelltabelle: contact_record

SELECT "queue_id", CAST(SUM("chat_agent_metrics_total_response_time_ms") AS DOUBLE) / NULLIF(SUM("chat_agent_metrics_num_responses"), 0) / 1000.0 AS "avg_agent_response_time_sec" FROM "connect_datalake"."contact_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "channel" = 'CHAT' AND "chat_agent_metrics_total_response_time_ms" IS NOT NULL AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id";

Durchschnittliche Gesamtzahl der Nachrichten

Definition: Durchschnittliche Gesamtzahl der Nachrichten pro Chat-Kontakt.

Quelltabelle: contact_record

SELECT "queue_id", AVG(CAST("chat_contact_metrics_total_messages" AS DOUBLE)) AS "avg_total_messages" FROM "connect_datalake"."contact_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "channel" = 'CHAT' AND "chat_contact_metrics_total_messages" IS NOT NULL AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id";

Abgebrochene Konversationen

Definition: Kontakte, bei denen der Chat von einem Agenten oder Kunden abgebrochen wurde.

Quelltabelle: contact_record

SELECT "queue_id", COUNT(*) AS "conversations_abandoned" FROM "connect_datalake"."contact_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "channel" = 'CHAT' AND ("chat_agent_metrics_conversation_abandon" = true OR "chat_customer_metrics_conversation_abandon" = true) AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id";

Metriken zur Konversationsanalyse

Durchschnittliche Gesprächszeit

Definition: Durchschnittliche kombinierte Gesprächszeit zwischen Agenten und Kunde pro Sprachkontakt.

Quelltabelle: contact_lens_conversational_analytics

SELECT AVG("talk_time_total_ms") / 1000.0 AS "avg_talk_time_sec" FROM "connect_datalake"."contact_lens_conversational_analytics" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "channel" = 'VOICE' AND "instance_id" = '<YOUR_INSTANCE_ID>';

Durchschnittliche Nicht-Gesprächszeit

Definition: Durchschnittliche Haltezeit plus Ruhezeit pro Sprachkontakt.

Quelltabelle: contact_lens_conversational_analytics

SELECT AVG("non_talk_time_total_ms") / 1000.0 AS "avg_non_talk_time_sec" FROM "connect_datalake"."contact_lens_conversational_analytics" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "channel" = 'VOICE' AND "instance_id" = '<YOUR_INSTANCE_ID>';

Stimmungsbewertung

Definition: Allgemeine Stimmungswerte für Agenten und Kunden.

Quelltabelle: contact_lens_conversational_analytics

SELECT AVG("sentiment_overall_score_agent") AS "avg_agent_sentiment", AVG("sentiment_overall_score_customer") AS "avg_customer_sentiment", AVG("sentiment_end_score_agent") AS "avg_agent_end_sentiment", AVG("sentiment_end_score_customer") AS "avg_customer_end_sentiment" FROM "connect_datalake"."contact_lens_conversational_analytics" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>';

Durchschnittliche Kundendienstmitarbeiterunterbrechungen

Definition: Durchschnittliche Anzahl von Agentenunterbrechungen pro Kontakt.

Quelltabelle: contact_lens_conversational_analytics

SELECT AVG(CAST("interruptions_agent_count" AS DOUBLE)) AS "avg_agent_interruptions" FROM "connect_datalake"."contact_lens_conversational_analytics" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "channel" = 'VOICE' AND "instance_id" = '<YOUR_INSTANCE_ID>';

Kennzahlen für KI-Agenten

Erfolgsquote beim Aufrufen von KI-Agenten

Definition: Rate erfolgreicher Aufrufe von KI-Agenten.

Quelltabelle: ai_agent

SELECT "ai_agent_name", SUM(CASE WHEN "invocation_success" = true THEN 1 ELSE 0 END) AS "success_count", COUNT(*) AS "total_invocations", CAST(SUM(CASE WHEN "invocation_success" = true THEN 1 ELSE 0 END) AS DOUBLE) / NULLIF(COUNT(*), 0) * 100.0 AS "success_rate_pct" FROM "connect_datalake"."ai_agent" WHERE "creation_timestamp" >= CAST('2026-06-09' AS TIMESTAMP) * 1000 AND "instance_id" = '<YOUR_INSTANCE_ID>' AND "ai_agent_id" IS NOT NULL GROUP BY "ai_agent_name";

AI-Übergaberate

Definition: Rate der KI-Sitzungen, die an menschliche Agenten eskalierten.

Quelltabelle: ai_session

SELECT SUM(CASE WHEN "is_handed_off" = true THEN 1 ELSE 0 END) AS "ai_handoffs", COUNT(*) AS "ai_involved_contacts", CAST(SUM(CASE WHEN "is_handed_off" = true THEN 1 ELSE 0 END) AS DOUBLE) / NULLIF(COUNT(*), 0) * 100.0 AS "handoff_rate_pct" FROM "connect_datalake"."ai_session" WHERE "creation_timestamp" >= CAST('2026-06-09' AS TIMESTAMP) * 1000 AND "instance_id" = '<YOUR_INSTANCE_ID>' AND "ai_session_id" IS NOT NULL;

KI-Qualitätswerte

Definition: Durchschnittliche Werte für Torerfolg, Treue und Vollständigkeit.

Quelltabelle: ai_session

SELECT AVG("goal_success_rate") AS "avg_goal_success_rate", AVG("faithfulness_score") AS "avg_faithfulness_score", AVG("completeness_score") AS "avg_completeness_score" FROM "connect_datalake"."ai_session" WHERE "creation_timestamp" >= CAST('2026-06-09' AS TIMESTAMP) * 1000 AND "instance_id" = '<YOUR_INSTANCE_ID>' AND "goal_success_rate" IS NOT NULL;

Genauigkeit des KI-Tools

Definition: Genauigkeitswerte für die Verwendung, Auswahl und Nutzung von KI-Tool-Parametern.

Quelltabelle: ai_tool

SELECT "ai_tool_name", AVG("ai_tool_parameter_accuracy") AS "avg_parameter_accuracy", AVG("ai_tool_selection_accuracy") AS "avg_selection_accuracy", AVG("ai_tool_utilization_accuracy") AS "avg_use_accuracy" FROM "connect_datalake"."ai_tool" WHERE "creation_timestamp" >= CAST('2026-06-09' AS TIMESTAMP) * 1000 AND "instance_id" = '<YOUR_INSTANCE_ID>' AND "ai_tool_id" IS NOT NULL GROUP BY "ai_tool_name";

Flow-Metriken

Gestartete Flows

Definition: Anzahl der Flows, deren Ausführung begonnen hat.

Quelltabelle: contact_flow_events

SELECT "flow_resource_id", "flow_type", COUNT(*) AS "flows_started" FROM "connect_datalake"."contact_flow_events" WHERE "start_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "start_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "flow_resource_id", "flow_type";

Prozentsatz des Ablaufergebnisses

Definition: Prozentsatz jedes Flow-Ergebnistyps.

Quelltabelle: contact_flow_events

WITH flow_counts AS ( SELECT "flow_resource_id", "flow_outcome", COUNT(*) AS "outcome_count", SUM(COUNT(*)) OVER (PARTITION BY "flow_resource_id") AS "total_completed" FROM "connect_datalake"."contact_flow_events" WHERE "start_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "start_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "end_timestamp" IS NOT NULL AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "flow_resource_id", "flow_outcome" ) SELECT "flow_resource_id", "flow_outcome", "outcome_count", CAST("outcome_count" AS DOUBLE) / "total_completed" * 100.0 AS "outcome_pct" FROM flow_counts ORDER BY "flow_resource_id", "outcome_pct" DESC;

Durchschnittliche Flow-Zeit

Definition: Durchschnittliche Dauer der Flow-Ausführungen.

Quelltabelle: contact_flow_events

SELECT "flow_resource_id", AVG( date_diff('millisecond', "start_timestamp", "end_timestamp") ) / 1000.0 AS "avg_flow_time_sec" FROM "connect_datalake"."contact_flow_events" WHERE "start_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "start_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "end_timestamp" IS NOT NULL AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "flow_resource_id";

Bewertungsmetriken

Durchgeführte Evaluationen

Definition: Anzahl der eingereichten Bewertungen.

Quelltabelle: contact_evaluation_record

SELECT COUNT(DISTINCT "evaluation_id") AS "evaluations_performed" FROM "connect_datalake"."contact_evaluation_record" WHERE "evaluation_submitted_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "evaluation_submitted_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "item_type" = 'Form' AND "to_delete" = false AND ("evaluation_type" IS NULL OR "evaluation_type" != 'calibration') AND "instance_id" = '<YOUR_INSTANCE_ID>';

Durchschnittliches Bewertungsergebnis

Definition: Durchschnittliche Bewertungspunktzahl aller eingereichten Bewertungen.

Quelltabelle: contact_evaluation_record

SELECT AVG("score") AS "avg_evaluation_score_pct" FROM "connect_datalake"."contact_evaluation_record" WHERE "evaluation_submitted_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "evaluation_submitted_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "item_type" = 'Form' AND "to_delete" = false AND ("evaluation_type" IS NULL OR "evaluation_type" != 'calibration') AND "instance_id" = '<YOUR_INSTANCE_ID>';

Automatische Fehlschläge in Prozent

Definition: Prozentsatz der Bewertungen, die zu einem automatischen Fehlschlagen geführt haben.

Quelltabelle: contact_evaluation_record

SELECT CAST( COUNT(DISTINCT CASE WHEN "automatic_fail" = true THEN "evaluation_id" END) AS DOUBLE ) / NULLIF(COUNT(DISTINCT "evaluation_id"), 0) * 100.0 AS "automatic_fail_pct" FROM "connect_datalake"."contact_evaluation_record" WHERE "evaluation_submitted_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "evaluation_submitted_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "item_type" = 'Form' AND "to_delete" = false AND ("evaluation_type" IS NULL OR "evaluation_type" != 'calibration') AND "instance_id" = '<YOUR_INSTANCE_ID>';

Metriken für ausgehende Kampagnen

Kontakte zur Kampagne

Definition: Anzahl der ausgehenden Kampagnenkontakte.

Quelltabelle: contact_record

SELECT "campaign_id", COUNT(*) AS "campaign_contacts" FROM "connect_datalake"."contact_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "campaign_id" IS NOT NULL AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "campaign_id";

Mensch hat geantwortet

Definition: Ausgehende Kampagnenanrufe, die mit einem Live-Kunden verbunden sind.

Quelltabelle: contact_record

SELECT "campaign_id", COUNT(*) AS "human_answered" FROM "connect_datalake"."contact_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "campaign_id" IS NOT NULL AND "answering_machine_detection_status" = 'HUMAN_ANSWERED' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "campaign_id";

Fallmetriken

Erstellte Fälle

Definition: Gesamtzahl der in einem Zeitraum erstellten Fälle.

Quelltabelle: case_events

SELECT COUNT(DISTINCT "case_id") AS "cases_created" FROM "connect_datalake"."case_events" WHERE "event_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "event_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "event_type" = 'CASE.CREATED' AND "instance_id" = '<YOUR_INSTANCE_ID>';

Durchschnittliche Falllösungszeit

Definition: Durchschnittliche Zeit von der Erstellung des Falls bis zum Abschluss.

Quelltabelle: case_events

SELECT AVG( date_diff('hour', "created_timestamp", "last_closed_timestamp") ) AS "avg_resolution_time_hours" FROM "connect_datalake"."case_events" WHERE "last_closed_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "last_closed_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "created_timestamp" IS NOT NULL AND "instance_id" = '<YOUR_INSTANCE_ID>';

Bot-Metriken

Ergebnisse der Bot-Konversation

Definition: Prozentuale Aufschlüsselung der Ergebnisse von Bot-Konversationen.

Quelltabelle: bot_conversations

WITH bot_outcomes AS ( SELECT "bot_id", "bot_conversation_outcome", COUNT(*) AS "cnt", SUM(COUNT(*)) OVER (PARTITION BY "bot_id") AS "total" FROM "connect_datalake"."bot_conversations" WHERE "bot_conversation_start_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "bot_conversation_start_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "bot_id", "bot_conversation_outcome" ) SELECT "bot_id", "bot_conversation_outcome", "cnt", CAST("cnt" AS DOUBLE) / "total" * 100.0 AS "outcome_pct" FROM bot_outcomes;

Allgemeine Abfragemuster

Die folgenden Muster zeigen, wie Sie mehrere Data-Lake-Tabellen kombinieren können, um umfassende Dashboards und Berichte zu erhalten.

Tägliches Übersichts-Dashboard

Definition: Umfassende tägliche Kennzahlen zur Warteschlange, einschließlich des Servicelevels.

Quelltabelle: contact_statistic_record

SELECT "queue_id", SUM("is_queued") AS "contacts_queued", SUM("is_handled") AS "contacts_handled", SUM("is_abandoned") AS "contacts_abandoned", AVG(CASE WHEN "is_handled" = 1 THEN "queue_answer_time_ms" END) / 1000.0 AS "avg_answer_time_sec", AVG(CASE WHEN "is_handled" = 1 THEN "handle_time_ms" END) / 1000.0 AS "avg_handle_time_sec", CAST(SUM(CASE WHEN "is_handled" = 1 AND "queue_answer_time_ms" <= 20000 THEN 1 ELSE 0 END) AS DOUBLE) / NULLIF(SUM("is_queued"), 0) * 100.0 AS "sl_20s_pct" FROM "connect_datalake"."contact_statistic_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY "queue_id" ORDER BY "contacts_queued" DESC;

Stündliche Trendanalyse

Definition: Stündliches Kontaktvolumen und Trends beim Servicelevel.

Quelltabelle: contact_statistic_record

SELECT date_trunc('hour', "disconnect_timestamp") AS "hour", "queue_id", SUM("is_queued") AS "contacts_queued", SUM("is_handled") AS "contacts_handled", SUM("is_abandoned") AS "contacts_abandoned", CAST(SUM("is_abandoned") AS DOUBLE) / NULLIF(SUM("is_queued"), 0) * 100.0 AS "abandon_rate_pct", AVG(CASE WHEN "is_handled" = 1 THEN "handle_time_ms" END) / 1000.0 AS "aht_sec" FROM "connect_datalake"."contact_statistic_record" WHERE "disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND "disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND "instance_id" = '<YOUR_INSTANCE_ID>' GROUP BY date_trunc('hour', "disconnect_timestamp"), "queue_id" ORDER BY "hour";

Mit Kontaktlinsen angereicherte Kontaktlinsen

Definition: Bereichern Sie Kontaktdatensätze mit Kontaktlinsenanalysen.

Quelltabelle: contact_record verknüpft mit contact_lens_conversational_analytics

SELECT cr."contact_id", cr."queue_id", cr."agent_id", cr."agent_interaction_duration_ms" / 1000.0 AS "interaction_sec", cl."talk_time_agent_ms" / 1000.0 AS "agent_talk_sec", cl."talk_time_customer_ms" / 1000.0 AS "customer_talk_sec", cl."sentiment_overall_score_agent", cl."sentiment_overall_score_customer" FROM "connect_datalake"."contact_record" cr JOIN "connect_datalake"."contact_lens_conversational_analytics" cl ON cr."contact_id" = cl."contact_id" AND cr."instance_id" = cl."instance_id" WHERE cr."disconnect_timestamp" >= TIMESTAMP '2026-06-09 00:00:00' AND cr."disconnect_timestamp" < TIMESTAMP '2026-06-10 00:00:00' AND cr."instance_id" = '<YOUR_INSTANCE_ID>' AND cr."channel" = 'VOICE';

Einhaltung des Zeitplans für Agenten (Aktivitätsebene)

Definition: Vergleicht den tatsächlichen Aktivitätsstatus eines Agenten (vonagent_statistic_record) mit seinen geplanten Schichtaktivitäten (aus Planungstabellen) für jedes Zeitintervall eines Tages. Ermittelt pro Intervall die Einhaltung: IN (der Agent hat getan, was für ihn geplant war) oder OUT (er hat nicht getan).

Ausgabespalten: Agent, Datum, Beginn, Ende, geplante Aktivität, Aktuelle Aktivität, Status der Einhaltung, Dauer

Quelltabellen:

  • staff_shifts— Der Agent wechselt für den Tag (letzte, nicht gelöschte Version)

  • staff_shift_activities— Geplante Aktivitätsblöcke innerhalb jeder Schicht

  • shift_activities— Suche nach Aktivitätsnamen (ordnet ARN einem menschenlesbaren Namen zu)

  • agent_statistic_record— Aktueller Agentenstatus pro Intervall

  • users— Agentenname und ARN-Auflösung

Adhärenzlogik (vereinfacht):

  • Geplantes „Öffnen“ — der Agent ist AKTIV, wenn der Status „Verfügbar“, „In Kontakt“ oder „ACW“ lautet

  • Geplante „Pause“ — Der Agent ist ZUGESCHALTET, wenn der Status Pause oder Mittagessen lautet

  • Geplantes „Meeting“ — Der Agent ist ANGEMELDET, wenn der Status „Schulung“ oder „Besprechung“ lautet

  • Andernfalls — AUS

WITH latest_shift_versions AS ( -- Get the latest (non-deleted) shift version per shift_id SELECT shift_id, MAX(shift_version) AS max_version FROM "connect_datalake"."staff_shifts" WHERE is_deleted = false AND CAST(shift_start_timestamp AS DATE) = DATE '2026-06-10' -- SET REPORT DATE GROUP BY shift_id ), latest_shifts AS ( SELECT ss.shift_id, ss.agent_arn, ss.shift_start_timestamp, ss.shift_end_timestamp FROM "connect_datalake"."staff_shifts" ss INNER JOIN latest_shift_versions lsv ON ss.shift_id = lsv.shift_id AND ss.shift_version = lsv.max_version WHERE ss.is_deleted = false ), -- Get scheduled activity blocks with human-readable activity names scheduled_blocks AS ( SELECT ls.agent_arn, ssa.activity_start_timestamp, ssa.activity_end_timestamp, sa.shift_activity_name, CASE WHEN sa.shift_activity_name IN ('Work', 'Overtime') THEN 'Open' WHEN sa.shift_activity_name IN ('Break', 'Lunch') THEN 'Break' WHEN sa.shift_activity_name = 'Training' THEN 'Meeting' WHEN sa.shift_activity_name = 'PTO' THEN 'PTO' ELSE sa.shift_activity_name END AS scheduled_activity_label FROM "connect_datalake"."staff_shift_activities" ssa INNER JOIN latest_shifts ls ON ssa.shift_id = ls.shift_id INNER JOIN latest_shift_versions lsv ON ssa.shift_id = lsv.shift_id AND ssa.shift_version = lsv.max_version INNER JOIN "connect_datalake"."shift_activities" sa ON ssa.shift_activity_arn = sa.shift_activity_arn WHERE ssa.is_deleted = false ), -- Get actual agent state intervals for the day actual_states AS ( SELECT u.user_arn AS agent_arn, u.first_name, u.last_name, asr.interval_start_time, asr.interval_end_time, asr.agent_status_name, asr.online_time, asr.agent_idle_time, asr.agent_on_contact_time, asr.non_productive_time, CASE WHEN asr.agent_on_contact_time IS NOT NULL AND asr.agent_on_contact_time > 0 THEN 'On Inbound Call' WHEN asr.agent_idle_time IS NOT NULL AND asr.agent_idle_time > 0 THEN 'Available' WHEN asr.non_productive_time IS NOT NULL AND asr.non_productive_time > 0 THEN COALESCE(asr.agent_status_name, 'Non-Productive') WHEN asr.online_time IS NOT NULL AND asr.online_time > 0 THEN 'Available' ELSE COALESCE(asr.agent_status_name, 'Offline') END AS actual_activity_label FROM "connect_datalake"."agent_statistic_record" asr INNER JOIN "connect_datalake"."users" u ON asr.user_id = u.user_id WHERE asr.interval_start_time >= TIMESTAMP '2026-06-10 00:00:00' -- SET REPORT DATE (UTC) AND asr.interval_start_time < TIMESTAMP '2026-06-11 00:00:00' ), -- Join actual states with scheduled blocks activity_timeline AS ( SELECT act.first_name || ' ' || act.last_name AS agent_name, act.interval_start_time, act.interval_end_time, act.actual_activity_label, act.agent_status_name, COALESCE(sb.scheduled_activity_label, 'Open') AS scheduled_activity FROM actual_states act LEFT JOIN scheduled_blocks sb ON act.agent_arn = sb.agent_arn AND act.interval_start_time < sb.activity_end_timestamp AND act.interval_end_time > sb.activity_start_timestamp ) SELECT agent_name AS "AGENT", CAST(interval_start_time AS DATE) AS "DATE", DATE_FORMAT(interval_start_time, '%H:%i:%s') AS "BEGIN", DATE_FORMAT(interval_end_time, '%H:%i:%s') AS "END", scheduled_activity AS "SCHEDULED ACTIVITY", actual_activity_label AS "ACTUAL ACTIVITY", CASE WHEN scheduled_activity = 'Open' AND actual_activity_label IN ('Available', 'On Inbound Call', 'On Outbound Call', 'Call Ringing', 'Aftercall (ACW)') THEN 'IN' WHEN scheduled_activity = 'Break' AND agent_status_name IN ('Break', 'Lunch') THEN 'IN' WHEN scheduled_activity = 'Meeting' AND agent_status_name IN ('Training', 'Meeting') THEN 'IN' ELSE 'OUT' END AS "ADHERENCE STATE", CAST(DATE_DIFF('second', interval_start_time, interval_end_time) / 3600 AS VARCHAR) || ':' || LPAD(CAST((DATE_DIFF('second', interval_start_time, interval_end_time) % 3600) / 60 AS VARCHAR), 2, '0') || ':' || LPAD(CAST(DATE_DIFF('second', interval_start_time, interval_end_time) % 60 AS VARCHAR), 2, '0') AS "DURATION" FROM activity_timeline ORDER BY interval_start_time ASC;

Bewährte Methoden

  • Löschen von Partitionen — Verwenden Sie immer Partitionsfilter (disconnect_timestamppublished_date, odercreation_timestamp), um die Scankosten zu minimieren.

  • Deduplizierung — Connect Customer liefert Datensätze mindestens einmal. Wird für Primärschlüssel verwendetDISTINCT, wenn genaue Zählungen erforderlich sind.

  • Zeitzonen — Alle Zeitstempel sind in UTC. AT TIME ZONEBeantragen Sie lokale Berichterstattung.

  • Millisekunden — Die meisten Felder für die Dauer werden in Millisekunden gespeichert. Teilen Sie für Sekunden durch 1000,0.

  • Instanz-ID-Filter — In Umgebungen mit mehreren Instanzen wird immer nach instance_id gefiltert.

  • Real-time Metriken — Verwenden Sie die GetCurrentMetricData API, um echte Echtzeit-Metriken zu erhalten. Der Data Lake stellt nur historische Daten zur Verfügung.