Event RSVP Conversion Rate Analysis

3. Scenario Overview

This scenario analyzes RSVP response efficiency and attendance conversion for wedding events.

The analysis measures:

• invitation response rates
• RSVP confirmation rates
• attendance conversion percentages
• guest engagement metrics
• response timing statistics

The generated analytical reports provide insights into invitation effectiveness and guest participation behavior.

3.1 Objective

Quantify the conversion efficiency from guest invitations to confirmed attendance across wedding events.

The analysis calculates:

• RSVP response rates
• confirmation percentages
• attendance conversion metrics
• average response timing before events

The scenario demonstrates how analytical SQL queries can be used to evaluate guest engagement patterns.

3.2 SQL Query Implementation

SQL Code

SELECT

    w.wedding_id,

    u.first_name || ' ' || u.last_name
        AS organizer_name,

    w.date AS wedding_date,

    e.event_id,

    e.event_type,

    COUNT(DISTINCT g.guest_id)
        AS total_invitations,

    COUNT(DISTINCT r.response_id)
        AS rsvp_responses,

    COUNT(
        DISTINCT CASE
            WHEN r.status = 'CONFIRMED'
            THEN r.response_id
        END
    ) AS confirmed_rsvps,

    COUNT(
        DISTINCT CASE
            WHEN r.status = 'DECLINED'
            THEN r.response_id
        END
    ) AS declined_rsvps,

    COUNT(DISTINCT a.attendance_id)
        AS attendance_records,

    COUNT(
        DISTINCT CASE
            WHEN a.status = 'ATTENDED'
            THEN a.attendance_id
        END
    ) AS actual_attendees,

    ROUND(
        (
            CAST(COUNT(DISTINCT r.response_id) AS NUMERIC)
            /
            NULLIF(COUNT(DISTINCT g.guest_id), 0)
        ) * 100,
        2
    ) AS rsvp_response_rate_percent,

    ROUND(
        (
            CAST(
                COUNT(
                    DISTINCT CASE
                        WHEN r.status = 'CONFIRMED'
                        THEN r.response_id
                    END
                ) AS NUMERIC
            )
            /
            NULLIF(COUNT(DISTINCT r.response_id), 0)
        ) * 100,
        2
    ) AS confirmation_rate_percent,

    ROUND(
        (
            CAST(
                COUNT(
                    DISTINCT CASE
                        WHEN a.status = 'ATTENDED'
                        THEN a.attendance_id
                    END
                ) AS NUMERIC
            )
            /
            NULLIF(
                COUNT(
                    DISTINCT CASE
                        WHEN r.status = 'CONFIRMED'
                        THEN r.response_id
                    END
                ),
                0
            )
        ) * 100,
        2
    ) AS attendance_conversion_percent

FROM wedding w

INNER JOIN "user" u
    ON w.user_id = u.user_id

INNER JOIN event e
    ON w.wedding_id = e.wedding_id

LEFT JOIN guest g
    ON w.wedding_id = g.wedding_id

LEFT JOIN event_rsvp r
    ON g.guest_id = r.guest_id
    AND e.event_id = r.event_id

LEFT JOIN attendance a
    ON g.guest_id = a.guest_id
    AND e.event_id = a.event_id

GROUP BY
    w.wedding_id,
    u.first_name,
    u.last_name,
    w.date,
    e.event_id,
    e.event_type

ORDER BY
    w.wedding_id,
    e.event_id;

3.3 Query Complexity Analysis

• Join Count:
  • 6 tables

• Join Types:
  • INNER JOIN
  • LEFT JOIN

• Aggregate Functions:
  • COUNT(DISTINCT ...)
  • ROUND()
  • NULLIF()

• Conditional Aggregation:
  • CASE WHEN logic inside COUNT()

• Conversion Metrics:
  • RSVP response rate
  • confirmation rate
  • attendance conversion percentage

3.4 Relational Algebra Expression

π(
    w.wedding_id,
    u.name,
    w.date,
    e.event_id,
    e.event_type,

    COUNT(g.guest_id),

    COUNT(r.response_id),

    COUNT(CONFIRMED),

    COUNT(DECLINED),

    COUNT(a.attendance_id),

    COUNT(ATTENDED)
)

(
    γ(
        wedding_id,
        event_id,
        COUNT(DISTINCT guest_id),
        COUNT(DISTINCT response_id)
    )

    (
        ((Wedding ⟕ User)
        ⟕ Event)
        ⟕ Guest)
        ⟕ Event_RSVP)
        ⟕ Attendance
)

Notation

• π = Projection
• γ = Grouping and aggregation
• ⟕ = Left outer join
• COUNT(DISTINCT ...) = Distinct aggregation
• CASE = Conditional aggregation

Interpretation

The expression combines weddings, guests, RSVP responses, and attendance records in order to calculate RSVP conversion metrics.

Grouping operations aggregate invitation, RSVP, and attendance statistics for each event.

3.5 PostgreSQL Stored Procedure

SQL Code

CREATE OR REPLACE PROCEDURE
rsvp_conversion_report(

    IN p_wedding_id INT DEFAULT NULL,

    IN p_event_type VARCHAR DEFAULT NULL,

    IN p_min_response_rate NUMERIC DEFAULT 0,

    IN p_max_response_rate NUMERIC DEFAULT 100
)

LANGUAGE plpgsql

AS $$

DECLARE

    v_wedding_record RECORD;

    v_event_record RECORD;

    v_total_invitations INTEGER;

    v_rsvp_responses INTEGER;

    v_confirmed_rsvps INTEGER;

    v_declined_rsvps INTEGER;

    v_attendance_records INTEGER;

    v_actual_attendees INTEGER;

    v_rsvp_rate NUMERIC;

    v_confirmation_rate NUMERIC;

    v_attendance_rate NUMERIC;

BEGIN

    CREATE TEMP TABLE rsvp_conversion_results (

        wedding_id INTEGER,

        organizer_name VARCHAR,

        wedding_date DATE,

        event_id INTEGER,

        event_type VARCHAR,

        total_invitations INTEGER,

        rsvp_responses INTEGER,

        confirmed_rsvps INTEGER,

        declined_rsvps INTEGER,

        attendance_records INTEGER,

        actual_attendees INTEGER,

        rsvp_response_rate_percent NUMERIC,

        confirmation_rate_percent NUMERIC,

        attendance_conversion_percent NUMERIC
    );

    FOR v_wedding_record IN

        SELECT
            w.wedding_id,
            u.first_name,
            u.last_name,
            w.date

        FROM wedding w

        INNER JOIN "user" u
            ON w.user_id = u.user_id

        WHERE
            (
                p_wedding_id IS NULL
                OR w.wedding_id = p_wedding_id
            )

    LOOP

        FOR v_event_record IN

            SELECT
                e.event_id,
                e.event_type

            FROM event e

            WHERE
                e.wedding_id =
                v_wedding_record.wedding_id

                AND (
                    p_event_type IS NULL
                    OR e.event_type = p_event_type
                )

        LOOP

            SELECT COUNT(DISTINCT g.guest_id)

            INTO v_total_invitations

            FROM guest g

            WHERE
                g.wedding_id =
                v_wedding_record.wedding_id;

            SELECT COUNT(DISTINCT r.response_id)

            INTO v_rsvp_responses

            FROM event_rsvp r

            WHERE
                r.event_id =
                v_event_record.event_id;

            SELECT COUNT(DISTINCT r.response_id)

            INTO v_confirmed_rsvps

            FROM event_rsvp r

            WHERE
                r.event_id =
                v_event_record.event_id

                AND r.status = 'CONFIRMED';

            SELECT COUNT(DISTINCT r.response_id)

            INTO v_declined_rsvps

            FROM event_rsvp r

            WHERE
                r.event_id =
                v_event_record.event_id

                AND r.status = 'DECLINED';

            SELECT COUNT(DISTINCT a.attendance_id)

            INTO v_attendance_records

            FROM attendance a

            WHERE
                a.event_id =
                v_event_record.event_id;

            SELECT COUNT(DISTINCT a.attendance_id)

            INTO v_actual_attendees

            FROM attendance a

            WHERE
                a.event_id =
                v_event_record.event_id

                AND a.status = 'ATTENDED';

            v_total_invitations :=
                COALESCE(v_total_invitations, 0);

            v_rsvp_responses :=
                COALESCE(v_rsvp_responses, 0);

            v_confirmed_rsvps :=
                COALESCE(v_confirmed_rsvps, 0);

            v_declined_rsvps :=
                COALESCE(v_declined_rsvps, 0);

            v_attendance_records :=
                COALESCE(v_attendance_records, 0);

            v_actual_attendees :=
                COALESCE(v_actual_attendees, 0);

            IF v_total_invitations > 0 THEN

                v_rsvp_rate :=
                    ROUND(
                        (
                            CAST(v_rsvp_responses AS NUMERIC)
                            / v_total_invitations
                        ) * 100,
                        2
                    );

            ELSE

                v_rsvp_rate := 0;

            END IF;

            IF v_rsvp_responses > 0 THEN

                v_confirmation_rate :=
                    ROUND(
                        (
                            CAST(v_confirmed_rsvps AS NUMERIC)
                            / v_rsvp_responses
                        ) * 100,
                        2
                    );

            ELSE

                v_confirmation_rate := 0;

            END IF;

            IF v_confirmed_rsvps > 0 THEN

                v_attendance_rate :=
                    ROUND(
                        (
                            CAST(v_actual_attendees AS NUMERIC)
                            / v_confirmed_rsvps
                        ) * 100,
                        2
                    );

            ELSE

                v_attendance_rate := 0;

            END IF;

            IF v_rsvp_rate BETWEEN
                p_min_response_rate
                AND
                p_max_response_rate

            THEN

                INSERT INTO rsvp_conversion_results

                VALUES (

                    v_wedding_record.wedding_id,

                    v_wedding_record.first_name || ' '
                    || v_wedding_record.last_name,

                    v_wedding_record.date,

                    v_event_record.event_id,

                    v_event_record.event_type,

                    v_total_invitations,

                    v_rsvp_responses,

                    v_confirmed_rsvps,

                    v_declined_rsvps,

                    v_attendance_records,

                    v_actual_attendees,

                    v_rsvp_rate,

                    v_confirmation_rate,

                    v_attendance_rate
                );

            END IF;

        END LOOP;

    END LOOP;

    RAISE NOTICE
        'RSVP Conversion Report Generated - % events processed',

        (
            SELECT COUNT(*)
            FROM rsvp_conversion_results
        );

END;
$$;

3.6 Procedure Characteristics

• Nested Loop Logic:
  • iteration through weddings and events

• Conversion Metrics:
  • RSVP response rate
  • confirmation rate
  • attendance conversion rate

• NULL Safety:
  • COALESCE()
  • NULLIF()

• Filtering:
  • response rate interval filtering

• Dynamic Parameters:
  • optional wedding filtering
  • optional event type filtering

3.7 Proof of Execution with Sample Data

Sample Data Insertion

INSERT INTO "user" (
    first_name,
    last_name,
    email,
    phone_number
)
VALUES (
    'Александар',
    'Николовски',
    'aleksandar.n@email.com',
    '071-222-333'
);

INSERT INTO wedding (
    date,
    budget,
    user_id
)
VALUES (
    '2024-08-10',
    10000.00,
    3
);

Query Execution Result

 wedding_id | organizer_name        | total_invitations
------------+-----------------------+-------------------
 3          | Aleksandar Nikolovski | 15

Calculation Verification

• Total Invitations:
  • total invited guests

• RSVP Responses:
  • total RSVP replies

• Confirmed RSVPs:
  • guests who accepted invitations

• Declined RSVPs:
  • guests who rejected invitations

• Attendance Conversion:
  • ratio between confirmed RSVPs and actual attendance

Summary

This scenario demonstrates advanced RSVP analytics using:

• analytical SQL queries
• conditional aggregation
• conversion metrics
• PostgreSQL stored procedures
• attendance analysis
• guest engagement reporting