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Metric and Definition | Query | Comments and Business Use | ||||||||||||||||||||||||||||||||||||||||||||
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Known Diner Sales (“KDS”) All sales that are made by recognizable guests, i.e. guests that have registered through the app (identified by their registered account id beginning with ‘us-east’) |
| This metric is used as a baseline to see loyalty sales penetration against system wide sales. | ||||||||||||||||||||||||||||||||||||||||||||
System Wide Sales (“SWS”) Total sales across TH |
| Note: Some forecasts may use Hyperion sales interchangeable in lieu of SWS sourced from STG.DERIVED_MASTER_TABLE_NEW. | ||||||||||||||||||||||||||||||||||||||||||||
Cheque Average sales value ($) of an individual transaction |
| Can calculate this on a system level or down to an individual guest level. Can filter on loyalty or non-loyalty. | ||||||||||||||||||||||||||||||||||||||||||||
Frequency Average loyalty guest visits in a given time period |
| Usually look at this metric for a week, month, or year. | ||||||||||||||||||||||||||||||||||||||||||||
White Label Delivery (“WL”) Delivery sales initiated from the TH mobile app |
| Included in known diner sales & digital sales. Sales of our internal app delivery platform. | ||||||||||||||||||||||||||||||||||||||||||||
Mobile Order & Pay (“MO&P”) |
| Included in known diner sales & digital sales. | ||||||||||||||||||||||||||||||||||||||||||||
Loyalty Scans Sales made by known diners and includes eat-in, takeout & drive thru |
| Included in known diner sales & digital sales. | ||||||||||||||||||||||||||||||||||||||||||||
3P Delivery Delivery sales initiated and fulfilled by third-party delivery providers, such as UberEats, SkipTheDishes and DoorDash |
| Included in digital sales | ||||||||||||||||||||||||||||||||||||||||||||
Kiosk Sales via Kiosk; can be split into registered and un-registered Kiosk sales using left(registered_account_id,7) = ‘us-east’ |
| Included in digital sales
| Catering Catering sales |
| Included in digital sales | Restaurants Reporting Any Menu Item (“RRAMI“) |
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WITH RESTAURANTS AS (
SELECT
TH_FISCAL_YEAR,
TH_FISCAL_WEEK,
PARTITION_DATE_KEY,
COUNT(DISTINCT REST_NO) AS RESTAURANTS
FROM STG.DERIVED_MASTER_TABLE_NEW
WHERE PARTITION_DATE_KEY BETWEEN 'START_DATE' AND 'END_DATE'
AND IS_PASS_THROUGH = 0
AND COUNTRY_NM = 'CANADA'
GROUP BY 1,2,3
ORDER BY 1)
SELECT
TH_FISCAL_YEAR,
TH_FISCAL_WEEK,
SUM(RESTAURANTS) AS RRAMI
FROM RESTAURANTS
GROUP BY 1,2 |
Scan & Pay (“S&P”)
Transactions where Scan & Pay feature was used
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SELECT
STOREDATE,
COUNT(DISTINCT TRANSACTIONID) AS TICKETS,
SUM(ITEMTOTALPRICE) AS SALES
FROM PRODRT.CURATED_TRANS_EVENTS_NEW
WHERE STOREDATE BETWEEN 'START_DATE' AND 'END_DATE'
AND IS_PASS_THROUGH = 0
AND COUNTRY_NM IN ('CANADA')
AND LEFT(REGISTEREDACCOUNTID,7) = 'us-east'
AND SCANANDPAY IS TRUE
GROUP BY 1 |
Often tracked as a % of registered transactions
Scan & Pay Penetration Formula: (Scan & Pay Transactions) / (Registered Transactions)
Loyalty Redemptions
Products that were redeemed using loyalty points
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CACHE TABLE DAILY_REDEMPTIONS AS
WITH TRANSACTIONS_WITH_OFFER_ID AS (
SELECT
LEFT(PERIOD_DT, 10) AS PERIOD_DT,
REGISTEREDACCOUNTID,
TRANSACTIONID,
EXPLODE(APPLIEDOFFERS) AS EXPLODED_OFFERS
FROM PRODRT.CURATED_TRANS_EVENTS_NEW
WHERE DATE_KEY >= '20230606'
AND COALESCE(REGISTEREDACCOUNTID,'') IS NOT NULL
AND APPLIEDOFFERS IS NOT NULL
AND COUNTRY_NM = 'CANADA')
SELECT
PERIOD_DT,
COUNT(DISTINCT TRANSACTIONID) AS TRXNS
FROM TRANSACTIONS_WITH_OFFER_ID AS A
INNER JOIN (SELECT DISTINCT OFFERID FROM DYDB.WEEKLYOFFERS
UNION ALL
SELECT DISTINCT OFFERID
FROM DYDB.OFFERS
WHERE CONTAINS(description, 'LOYALTY')
AND DESCRIPTION LIKE 'CA L%'
AND DESCRIPTION NOT IN ('CA LR Registered Default (same as L1)-LOYALTY', 'CA LU Unregistered (same as 102) ONE-TIME-LOYALTY') ) B
ON A.EXPLODED_OFFERS = B.OFFERID
LEFT JOIN DYDB.OFFERS AS C
ON A.EXPLODED_OFFERS=C.OFFERID
WHERE EXPLODED_OFFERS IS NOT NULL
AND C.OFFERID IS NOT NULL
GROUP BY 1 |
Used for tracking how many free items we’re giving away and the value of them.
Often viewed as a percentage of SWS or KDS.
Loyalty drag formula = $ value of redeemed items / SWS $
Monthly Active Users (“MAU”)
Number of guests that visited the app each month
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WITH EVENTS AS ( SELECT DATE , _TIMHORTONS.INTERACTION.ELEMENT.NAME , _TIMHORTONS.LOYALTY.ID AS GUEST_ID FROM loyalty.events.adobe_app_events WHERE EVENTTYPE IN ('app_open','app_launch') AND _TIMHORTONS.PLATFORM IN ('app') AND LEFT(_TIMHORTONS.LOYALTY.ID,7) = 'us-east' AND DATE <= CURRENT_DATE ) SELECT LAST_DAY(EVENTS.DATE) AS DTE -- List of Retaurants as of june 2024 ('100024', '100027', '100045', '100062', '100077', '100093', '100096', '100101', '100104', '100112', '100118', '100124', '100136', '100160', '100200', '100229', '100324', '100325', '100376', '100387', '100410', '100446', '100467', '100489', '100490', '100503', '100506', '100514', '100525', '100526', '100529', '100544', '100582', '100588', '100640', '100652', '100670', '100674', '100678', '100693', '100769', '100776', '100788', '100800', '100806', '100856', '100863', '100885', '100940', '100965', '100998', '101000', '101022', '101076', '101129', '101174', '101241', '101281', '101333', '101335', '101357', '101365', '101368', '101382', '101442', '101450', '101475', '101476', '101491', '101493', '101508', '101517', '101543', '101568', '101582', '101584', '101595', '101600', '101602', '101623', '101628', '101650', '101655', '101657', '101666', '101686', '101689', '101712', '101769', '101788', '101789', '101803', '101818', '101820', '101837', '101846', '101849', '101851', '101864', '101865', '101873', '101886', '101900', '101904', '101924', '101954', '101967', '101985', '101991', '101992', '101999', '102011', '102017', '102018', '102032', '102040', '102041', '102060', '102074', '102103', '102110', '102118', '102129', '102132', '102150', '102157', '102169', '102175', '102196', '102212', '102224', '102305', '102308', '102315', '102331', '102376', '102387', '102394', '102398', '102399', '102409', '102417', '102467', '102478', '102534', '102549', '102556', '102562', '102603', '102606', '102614', '102622', '102630', '102635', '102646', '102679', '102710', '102719', '102732', '102753', '102773', '102784', '102821', '102833', '102852', '102877', '102891', '102892', '102925', '102946', '102972', '102974', '102991', '103001', '103021', '103029', '103050', '103077', '103086', '103124', '103129', '103130', '103132', '103137', '103143', '103159', '103167', '103169', '103208', '103217', '103227', '103233', '103255', '103267', '103294', '103323', '103340', '103351', '103356', '103384', '103389', '103407', '103411', '103413', '103478', '103482', '103498', '103548', '103549', '103584', '103625', '103637', '103644', '103677', '103690', '103695', '103698', '103704', '103754', '103755', '103850', '103886', '103947', '103950', '103955', '104013', '104126', '104212', '104213', '104275', '104284', '104370', '104391', '104393', '104420', '104443', '104505', '104651', '104764', '104813', '104840', '104852', '104853', '104856', '104887', '104925', '104962', '104966', '104970', '104971', '105060', '105085', '105217', '105237', '105340', '105363', '105389', '105763', '105789', '105792', '105840', '105917', '106305', '106310', '106478', '106547', '106865', '106874', '106882', '107228', '107336', '107343', '107384', '107569', '107576', '107582', '107608', '107647', '107653', '108088', '108102', '108115', '108118', '108137', '108166', '108167', '108172', '108175', '108358', '108395', '108397', '108399', '108402', '108430', '108480', '108485', '108487', '108500', '108502', '108507', '108518', '109027', '109041', '109042', '109241', '109246', '109286', '109288', '109291', '109331', '109334', '109338', '109396', '109397', '109403', '109404', '109405', '109407', '109430', '109436', '109444', '109446', '109447', '109448', '109449', '109711', '109757', '109780', '109878', '109951', '109955', '120293', '101462', '101917', '102093', '102229', '103202', '103648', '104271', '104471', '106376') |
Catering
Catering sales
Code Block | ||
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SELECT
PARTITION_DATE_KEY,
SUM(ITEMTOTALPRICE)AS SALES,
FROM PRODRT.CURATED_TRANS_EVENTS_NEW
WHERE PARTITION_DATE_KEY BETWEEN 'START_DATE' AND 'END_DATE'
AND COUNTRY_NM = 'CANADA'
AND IS_PASS_THROUGH = 0
AND LEFT(REGISTEREDACCOUNTID,7) = 'us-east'
AND DININGTYPE = 'CT'
GROUP BY 1 |
Included in digital sales
Restaurants Reporting Any Menu Item (“RRAMI“)
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WITH RESTAURANTS AS (
SELECT
TH_FISCAL_YEAR,
TH_FISCAL_WEEK,
PARTITION_DATE_KEY,
COUNT(DISTINCT REST_NO) AS RESTAURANTS
FROM STG.DERIVED_MASTER_TABLE_NEW
WHERE PARTITION_DATE_KEY BETWEEN 'START_DATE' AND 'END_DATE'
AND IS_PASS_THROUGH = 0
AND COUNTRY_NM = 'CANADA'
GROUP BY 1,2,3
ORDER BY 1)
SELECT
TH_FISCAL_YEAR,
TH_FISCAL_WEEK,
SUM(RESTAURANTS) AS RRAMI
FROM RESTAURANTS
GROUP BY 1,2 |
Scan & Pay (“S&P”)
Transactions where Scan & Pay feature was used
Code Block | ||
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SELECT
STOREDATE,
COUNT(DISTINCT TRANSACTIONID) AS TICKETS,
SUM(ITEMTOTALPRICE) AS SALES
FROM PRODRT.CURATED_TRANS_EVENTS_NEW
WHERE STOREDATE BETWEEN 'START_DATE' AND 'END_DATE'
AND IS_PASS_THROUGH = 0
AND COUNTRY_NM IN ('CANADA')
AND LEFT(REGISTEREDACCOUNTID,7) = 'us-east'
AND SCANANDPAY IS TRUE
GROUP BY 1 |
Often tracked as a % of registered transactions
Scan & Pay Penetration Formula: (Scan & Pay Transactions) / (Registered Transactions)
Loyalty Redemptions
Products that were redeemed using loyalty points
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WITH TRANSACTIONS_WITH_OFFER_ID AS (
SELECT
LEFT(PERIOD_DT, 10) AS PERIOD_DT,
REGISTEREDACCOUNTID,
TRANSACTIONID,
EXPLODE(APPLIEDOFFERS) AS EXPLODED_OFFERS
FROM PRODRT.CURATED_TRANS_EVENTS_NEW
WHERE DATE_KEY >= '20230606'
AND COALESCE(REGISTEREDACCOUNTID,'') IS NOT NULL
AND APPLIEDOFFERS IS NOT NULL
AND COUNTRY_NM = 'CANADA')
SELECT
PERIOD_DT,
COUNT(DISTINCT TRANSACTIONID) AS TRXNS
FROM TRANSACTIONS_WITH_OFFER_ID AS A
INNER JOIN (SELECT DISTINCT OFFERID FROM DYDB.WEEKLYOFFERS
UNION ALL
SELECT DISTINCT OFFERID
FROM DYDB.OFFERS
WHERE CONTAINS(description, 'LOYALTY')
AND DESCRIPTION LIKE 'CA L%'
AND DESCRIPTION NOT IN ('CA LR Registered Default (same as L1)-LOYALTY', 'CA LU Unregistered (same as 102) ONE-TIME-LOYALTY') ) B
ON A.EXPLODED_OFFERS = B.OFFERID
LEFT JOIN DYDB.OFFERS AS C
ON A.EXPLODED_OFFERS=C.OFFERID
WHERE EXPLODED_OFFERS IS NOT NULL
AND C.OFFERID IS NOT NULL
GROUP BY 1 |
Used for tracking how many free items we’re giving away and the value of them.
Often viewed as a percentage of SWS or KDS.
Loyalty drag formula = $ value of redeemed items / SWS $
Monthly Active Users (“MAU”)
Number of guests that visited the app each month
Code Block | ||
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WITH EVENTS AS (
SELECT DATE
, _TIMHORTONS.INTERACTION.ELEMENT.NAME
, _TIMHORTONS.LOYALTY.ID AS GUEST_ID
FROM loyalty.events.adobe_app_events
WHERE EVENTTYPE IN ('app_open','app_launch')
AND _TIMHORTONS.PLATFORM IN ('app')
AND LEFT(_TIMHORTONS.LOYALTY.ID,7) = 'us-east'
AND _TIMHORTONS.LOYALTY.ID IN (SELECT DISTINCT registeredAccountId FROM loyalty.users.customer_base WHERE LEFT(loyaltyCustomerId,4) IN ('0463','0473'))
AND DATE <= CURRENT_DATE )
SELECT LAST_DAY(EVENTS.DATE) AS DTE
, COUNT(DISTINCT EVENTS.GUEST_ID) AS ACTIVE_USER
FROM EVENTS
GROUP BY 1
ORDER BY 1 DESC |
Used to track the unique number of guests who opened or launched the app per month. Limitation of the dataset is: (1) data only exists from Nov 1st, 2023, and (2) Prior to mm/dd/yyyy (TBD), dataset did not contain guests using app versions prior to 7.1.187.
Digital Sales
Pulled using the individual queries listed above.
Consists of WL, MO&P, Loyalty Scans, 3P Delivery, Kiosk & Catering.
Weekly Offer Redemptions
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WITH REDEMPTION_SUMMARY AS (
WITH OFFER_REDEMPTION_TRXNS AS (
WITH TRANSACTIONS_WITH_OFFER_ID AS (
SELECT
TH_FISCAL_YEAR,
TH_FISCAL_WEEK,
CAST(WEEK_START_DT AS DATE) AS WEEK_START_DT,
DATE_FORMAT(
CAST(
UNIX_TIMESTAMP(LEFT(WEEK_START_DT, 10), 'yyyy-MM-dd') AS TIMESTAMP
),
'yyyyMMdd'
) AS WEEK_START,
CAST(PERIOD_DT AS DATE) AS PERIOD_DT,
REGISTEREDACCOUNTID,
TRANSACTIONID,
EXPLODE(APPLIEDOFFERS) AS EXPLODED_OFFERS
FROM
PRODRT.CURATED_TRANS_EVENTS_NEW
WHERE
PARTITION_DATE_KEY BETWEEN 'START DATE' AND 'END DATE'
AND REGISTEREDACCOUNTID LIKE 'us-east%'
AND COUNTRY_NM = 'CANADA'
)
SELECT
DISTINCT A.TH_FISCAL_YEAR,
A.TH_FISCAL_WEEK,
A.WEEK_START_DT,
A.PERIOD_DT,
A.REGISTEREDACCOUNTID,
A.TRANSACTIONID,
C.NAME,
C.DESCRIPTION,
A.EXPLODED_OFFERS,
1 AS VOLUME
FROM
TRANSACTIONS_WITH_OFFER_ID A
INNER JOIN DYDB.WEEKLYOFFERS B ON A.EXPLODED_OFFERS = B.OFFERID
LEFT JOIN DYDB.OFFERS C ON A.EXPLODED_OFFERS = C.OFFERID
)
SELECT
WEEK_START_DT,
A.DESCRIPTION AS OFFER_DESCRIPTION,
A.EXPLODED_OFFERS AS OFFERID,
SUM(VOLUME) AS REDEMPTION_VOLUME
FROM
OFFER_REDEMPTION_TRXNS A
GROUP BY
1,
2,
3
)
SELECT
a.WEEK_START_DT AS WKDT,
OFFER_DESCRIPTION,
OFFERID,
SUM(REDEMPTION_VOLUME)
FROM
REDEMPTION_SUMMARY A
GROUP BY 1,2,3 |
Used to track the volume of redemptions for each offer in a given week.
Offer Challenge
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with TRXN_OFFER_CHALLENGES_REDEMPTIONS as ( WITH EXPLODED AS ( SELECT TH_FISCAL_YEAR, TH_FISCAL_WEEK, DATE_FORMAT( CAST( UNIX_TIMESTAMP(LEFT(WEEK_START_DT, 10), 'yyyy-MM-dd') AS TIMESTAMP ), 'yyyyMMdd' ) AS WEEK_START_MAPPING, CAST(PERIOD_DT AS DATE) AS PERIOD_DT, REGISTEREDACCOUNTID, loyaltyCustomerId, TRANSACTIONID, EXPLODE(APPLIEDOFFERS) AS EXPLODED_OFFERS, REST_TYP_NM, OPS_DIV_NM FROM PRODRT.CURATED_TRANS_EVENTS_NEW -- 1. Challenge duration: 26/09 to 02/10 WHERE DATE_KEY BETWEEN '${myapplication.Offer_Start_Date}' AND '${myapplication.Offer_End_Date}' AND COUNTRY_NM = 'CANADA' AND REGISTEREDACCOUNTID IS NOT NULL AND TRANSACTIONID IS NOT NULL -- AND REST_TYP_NM = "STANDARD" ) SELECT DISTINCT A.TH_FISCAL_YEAR, A.TH_FISCAL_WEEK, A.WEEK_START_MAPPING, A.PERIOD_DT, A.REGISTEREDACCOUNTID, A.loyaltyCustomerId, A.TRANSACTIONID, A.REST_TYP_NM, A.OPS_DIV_NM, B.DESCRIPTION, 1 AS REDEMPTIONS FROM EXPLODED AS A LEFT JOIN DYDB.OFFERS AS B ON A.EXPLODED_OFFERS = B.OFFERID WHERE EXPLODED_OFFERS = '76290e2e-1783-442f-8ff6-a2b16900a34e' ), points_issued as ( Select *, WEEKOFYEAR(to_date(partition_date_key, "yyyyMMdd")) AS WEEK_START, regexp_extract(barcode, '(\\d+)|(\\d+)', 0) as lid From prodrt.curated_points_events as points where partition_date_key BETWEEN '${myapplication.Offer_Start_Date}' AND '${myapplication.Offer_End_Date}' and tag = 'PRODUCT_CHALLENGED_COMPLETED' ), completed as( Select a.TH_FISCAL_YEAR as TH_FISCAL_YEAR, a.TH_FISCAL_WEEK as TH_FISCAL_WEEK, a.WEEK_START_MAPPING as WEEK_START_MAPPING, a.PERIOD_DT as PERIOD_DT, DATE_FORMAT( CAST( UNIX_TIMESTAMP(LEFT(PERIOD_DT, 10), 'yyyy-MM-dd') AS TIMESTAMP ), 'yyyyMMdd' ) as transaction_dt, a.REGISTEREDACCOUNTID as REGISTEREDACCOUNTID, a.loyaltyCustomerId as loyaltyCustomerId, a.TRANSACTIONID as TRANSACTIONID, a.REST_TYP_NM as REST_TYP_NM, a.OPS_DIV_NM as OPS_DIV_NM, a.DESCRIPTION as DESCRIPTION, a.REDEMPTIONS as REDEMPTIONS, b.transactionID as completion_transactionID, b.pointsEarned as pointsEarned, b.restaurant as restaurant, b.partition_date_key as offer_completion_dt, b.WEEK_START as offer_completion_week, b.lid as lid from TRXN_OFFER_CHALLENGES_REDEMPTIONS a left join points_issued b on a.loyaltyCustomerId = b.lid and b.WEEK_START = a.TH_FISCAL_WEEK ) Select TH_FISCAL_YEAR, TH_FISCAL_WEEK, WEEK_START_MAPPING, REGISTEREDACCOUNTID, loyaltyCustomerId, offer_completion_week, count( distinct( case when offer_completion_dt is not NULL and transaction_dt <= offer_completion_dt then TRANSACTIONID end ) ) as trnx_before_completion, count(distinct(TRANSACTIONID)) as total_trnx, count( distinct ( case ,when COUNT(DISTINCT EVENTS.GUEST_ID) AS ACTIVE_USER FROM lid is not Null then lid EVENTS GROUP BY 1end ORDER BY 1 DESC |
Used to track the unique number of guests who opened or launched the app per month. Limitation of the dataset is: (1) data only exists from Nov 1st, 2023, and (2) Prior to mm/dd/yyyy (TBD), dataset did not contain guests using app versions prior to 7.1.187.
Digital Sales
Pulled using the individual queries listed above.
Consists of WL, MO&P, Loyalty Scans, 3P Delivery, Kiosk & Catering.
Weekly Offer Redemptions
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WITH REDEMPTION_SUMMARY AS ( WITH OFFER_REDEMPTION_TRXNS AS ( WITH TRANSACTIONS_WITH_OFFER_ID AS ( SELECT TH_FISCAL_YEAR, ) ) as completed from completed group by 1, 2, 3, 4, 5, 6 |
Count of guests who completed a specific Offer Challenge
Games
NHL Hockey Challenge & Tims Word Challenge
Code Block | ||
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SELECT YEAR(TIMESTAMP) AS YR TH_FISCAL_WEEK, CAST(WEEK_START_DT AS DATEMONTH(TIMESTAMP) AS WEEK_START_DT,MTH DATE_FORMAT( , COUNT(DISTINCT GUESTS) AS GUESTS FROM CAST( -- WORD CHALLENEGE PLAYERS SELECT DISTINCT TIMESTAMP, UNIX_TIMESTAMP(LEFT(WEEK_START_DT, 10), 'yyyy-MM-dd') AS TIMESTAMP_TIMHORTONS.LOYALTY.ID AS GUESTS FROM loyalty.events.adobe_app_events WHERE ), TRIM(_TIMHORTONS.INTERACTION.PATH) IN ('/timswordchallenge') AND TRIM(_TIMHORTONS.INTERACTION.ELEMENT.NAME) = 'yyyyMMddplay' AND _TIMHORTONS.PLATFORM IN ('app') ASAND WEEK_START, LEFT(_TIMHORTONS.LOYALTY.ID,7) = CAST(PERIOD_DT AS DATE) AS PERIOD_DT, REGISTEREDACCOUNTID, 'us-east' AND _TIMHORTONS.LOYALTY.ID IN (SELECT DISTINCT registeredAccountId FROM loyalty.users.customer_base WHERE LEFT(loyaltyCustomerId,4) IN ('0463','0473')) AND TRANSACTIONID, DATE >= DATE '2023-11-01' UNION EXPLODE(APPLIEDOFFERS) AS EXPLODED_OFFERS -- HOCKEY PLAYERS SELECT DISTINCT FROM TIMESTAMP,_TIMHORTONS.LOYALTY.ID AS GUESTS FROM PRODRTloyalty.events.CURATEDadobe_TRANSapp_EVENTS_NEWevents WHERE WHERE TRIM(_TIMHORTONS.INTERACTION.PATH) = '/hockey_challenge' AND PARTITION_DATE_KEY BETWEEN 'START DATE'TRIM(_TIMHORTONS.INTERACTION.ELEMENT.NAME) IN ('submit_picks') AND 'END DATE' _TIMHORTONS.PLATFORM AND REGISTEREDACCOUNTID LIKE 'us-east%' IN ('app') AND AND COUNTRY_NMLEFT(_TIMHORTONS.LOYALTY.ID,7) = 'CANADAus-east' AND ) _TIMHORTONS.LOYALTY.ID IN (SELECT DISTINCT registeredAccountId FROM loyalty.users.customer_base WHERE DISTINCT A.TH_FISCAL_YEAR, LEFT(loyaltyCustomerId,4) IN ('0463','0473')) AND A.TH_FISCAL_WEEK, A.WEEK_START_DT, A.PERIOD_DT, DATE >= DATE '2023-11-01' ) GROUP BY 1,2 ORDER BY 1 DESC, 2 |
Count of guests who played Games (NHL Hockey Challenge and Tims Word Challenge).
Limitation: Data only available from Nov 1, 2023.
Total Sales and Ticket Count by Tender Type
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WITH LOYALTY_TENDERS AS ( WITH A.REGISTEREDACCOUNTID,TENDERS AS ( A.TRANSACTIONID, SELECT C.NAME, C.DESCRIPTION, REPLACE(UPPER(TRIM(TENDER_NAME)), '.', '') AS TENDER_NAME, A.EXPLODED_OFFERS, TICKET_ID 1 AS VOLUME FROM loyalty.tlog.tlog_sale_ticket_tenders FROM WHERE TRANSACTIONSPARTITION_WITHDATE_OFFER_IDKEY ABETWEEN 20230101 AND 20230731 INNER JOIN DYDB.WEEKLYOFFERS B ON A.EXPLODED_OFFERS = B.OFFERIDAND LEFT(REST_NO,2) = 10 ), LEFT JOIN DYDB.OFFERSLOYALTY CAS ON A.EXPLODED_OFFERS = C.OFFERID ( ) SELECT SELECT WEEK_START_DT, A.DESCRIPTIONTICKET_ID AS OFFER_DESCRIPTION,TICKET_ID FROM A.EXPLODED_OFFERS AS OFFERID,STG.DERIVED_MASTER_TABLE_NEW SUM(VOLUME) ASWHERE REDEMPTION_VOLUME FROMPARTITION_DATE_KEY BETWEEN 20230101 AND 20230731 OFFER_REDEMPTION_TRXNS A AND COUNTRY_NM GROUP= BY'CANADA' 1, AND IS_PASS_THROUGH = 2, 0 3 ) SELECT a.WEEK_START_DT AS WKDT, OFFER_DESCRIPTION, OFFERID, SUM(REDEMPTION_VOLUME) FROM REDEMPTION_SUMMARY A GROUP BY 1,2,3 |
Used to track the volume of redemptions for each offer in a given week.
Offer Challenge
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with TRXN_OFFER_CHALLENGES_REDEMPTIONS as ( WITH EXPLODED AS ( AND LEFT(REGISTERED_ACCOUNT_ID,7) = 'us-east' ) SELECT A.* FROM TENDERS A INNER JOIN LOYALTY B ON SELECTA.TICKET_ID = B.TICKET_ID ) SELECT CASE TH_FISCAL_YEAR, WHEN TH_FISCAL_WEEK, DATE_FORMAT( UPPER(TENDER_NAME) IN ('CASH', 'COMPTANT', 'EFECTIVO', 'US CASH', 'CANADIAN CASH', 'CDN CASH', 'ROUNDED CASH', 'ROUNDED COMPTANT') THEN 'CASH' CAST( UNIX_TIMESTAMP(LEFT(WEEK_START_DT, 10), 'yyyy-MM-dd') AS TIMESTAMPWHEN UPPER(TENDER_NAME) IN ('DEBIT CARD', 'DEBIT', 'CARTE DEBIT', 'DEBITO', 'DÉBIT', 'DO DEBIT') THEN 'DEBIT' WHEN UPPER(TENDER_NAME) IN ('VISA', 'MASTERCARD', 'MASTER CARD', 'AMEX', 'AMERICAN EXPRESS', 'CREDIT CARD', 'CREDIT CARDS', 'yyyyMMdd' ) AS WEEK_START_MAPPING, CAST(PERIOD_DT AS DATE) AS PERIOD_DT,'DISCOVER', 'M/C', 'DISCOVER CARD', 'DIGITAL AMEX', 'DIGITAL DISCOVER', 'DIGITAL MASTER CARD', 'DIGITAL MASTERCARD', 'DIGITAL AMERICAN EXPRESS', 'DIGITAL VISA', 'DO VISA', 'DO MASTERCARD') THEN 'CREDIT' WHEN UPPER(TENDER_NAME) IN REGISTEREDACCOUNTID('TIM CARD', 'DIGITAL TIM loyaltyCustomerId, TRANSACTIONID, EXPLODE(APPLIEDOFFERS) AS EXPLODED_OFFERS,CARD', 'CARTE TIM', 'MOBILE TIM CARD', 'DIGITAL CARTE TIM', 'TIM CARTE', 'TIMS GIFT CARD', 'DIGITAL TIMS GIFT CARD', 'CARTE-CADEAU TIM', 'DIGITAL CARTE-CADEAU TIM') THEN 'TIMCARD' WHEN REST_TYP_NM, UPPER(TENDER_NAME) LIKE '%SKIP%' THEN 'SKIP' OPS_DIV_NM WHEN UPPER(TENDER_NAME) FROM LIKE '%UBER%' THEN 'UBER' PRODRT.CURATED_TRANS_EVENTS_NEW -- 1. Challenge duration: 26/09 to 02/10 WHEN UPPER(TENDER_NAME) LIKE '%DOOR%' THEN 'DOORDASH' WHERE WHEN DATE_KEY BETWEEN '${myapplication.Offer_Start_Date}' AND '${myapplication.Offer_End_Date}' AND COUNTRY_NM = 'CANADA' AND REGISTEREDACCOUNTID IS NOT NULL AND TRANSACTIONID IS NOT NULL -- AND REST_TYP_NM = "STANDARD" ) SELECT DISTINCT A.TH_FISCAL_YEAR,UPPER(TENDER_NAME) IN ('SCAN AND PAY VISA', 'SCAN AND PAY MASTERCARD', 'SCAN AND PAY TIMCARD', 'SCAN AND PAY AMEX', 'SCAN AND PAY DISCOVER', 'SCAN AND PAY TIM CARD', 'NUMERISEZ ET PAYEZ – VISA', 'SCANTOPAY', 'NUMERISEZ ET PAYEZ – MASTERCARD', 'NUMERISEZ ET PAYEZ – CARTE TIM', 'NUMÉRISEZ ET PAYEZ – VISA', 'NUMÉRISEZ ET PAYEZ – MASTERCARD', 'NUMÉRISEZ ET PAYEZ – CARTE TIM', 'NUMERISEZ ET PAYEZ – AMEX', 'NUMÉRISEZ ET PAYEZ – AMEX', 'SCAN AND PAY TIMS GIFT CARD', 'NUMERISEZ ET PAYEZ CARTE-CADEAU TIM') THEN 'SCANANDPAY' A.TH_FISCAL_WEEK, A.WEEK_START_MAPPING, A.PERIOD_DT, A.REGISTEREDACCOUNTID, A.loyaltyCustomerId, A.TRANSACTIONID, A.REST_TYP_NM, A.OPS_DIV_NM, B.DESCRIPTION, WHEN UPPER(TENDER_NAME) IN ('HST', 'HST1', 'TVQ', 'TPS', 'GST', 'TAX', 'PST', 'HST TAXABLE SALES', 'SALES TAX' 'HST 1', 'H.S.T.1', 'H.S.T', 'HST 13% TAXABLE SALES', 'GST TAXABLE SALES', 'TAX 1', 'HST 1', 'GST# 75696 6891 RT0001', 'HST # 897258141', 'HST5%', 'HST8%', 'QST', 'SALES TAX', 'MEAL PLAN CARD - PREPAID TAX', 'CARTE PLAN REPAS - TAX PREPAYEE', 'GST # 121071781RT0001', 'TVH', 'TVH1', 'VAF', 'H.S.T.') THEN 'TAX' 1 AS REDEMPTIONS FROM WHEN ((UPPER(TENDER_NAME) LIKE '%ROUND%') OR (UPPER(TENDER_NAME) LIKE '%ARRONDIS %')) THEN 'ROUND UP' EXPLODED AS A ELSE 'OTHER' END AS LEFT JOIN DYDB.OFFERS AS B ON A.EXPLODED_OFFERS = B.OFFERID WHERE TENDER, COUNT(DISTINCT TICKET_ID) AS TRXNS FROM LOYALTY_TENDERS GROUP BY 1 |
Total sales $ and ticket count organized by tender type (debit, credit, cash, Tims Card, tax) for a given restaurant
Discounting
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With base as( select EXPLODED_OFFERS = '76290e2e-1783-442f-8ff6-a2b16900a34e' TH_FISCAL_YEAR, ), period_dt, points_issued as ( state_nm, Select detail_type, *ops_div_nm, WEEKOFYEAR(to_date(partition_date_ticket_details_key, "yyyyMMdd")) AS WEEK_START ticket_details_pos_no, regexp_extract(barcode, '(\\d+)|(\\d+)', 0) as lid From a.ticket_details_pos_nm, B.discount_key, prodrtB.curated_points_events as pointsdiscount_cd, B.discount_nm, where C.coupon_key, partition_date_key BETWEEN '${myapplication.Offer_Start_Date}'C.coupon_cd, AND '${myapplication.Offer_End_Date}'C.coupon_offr_nm, D.Category, and tag = 'PRODUCT_CHALLENGED_COMPLETED' SUM(amount) as amt, ), completed as( count(distinct(ticket_id)) as TRXNS Select from aSTG.THDERIVED_MASTER_FISCALTABLE_YEARNEW as TH_FISCAL_YEAR,a left join loyalty.tlog.dim_discount b on a.THticket_FISCALdetails_WEEKkey as= TH_FISCAL_WEEK,b.discount_key left join atlog.WEEKdim_START_MAPPINGcoupon as WEEK_START_MAPPING, a.PERIOD_DT as PERIOD_DT, DATE_FORMAT(c on a.ticket_details_key = c.coupon_key left join loyalty.analytics.clearview_mapping_discount_types d CAST( on a.ticket_details_pos_nm = d.ticket_details_pos_nm where UNIX_TIMESTAMP(LEFT(PERIOD_DT, 10), 'yyyy-MM-dd') AS TIMESTAMPamount < 0 and quantity ),> 0 AND COUNTRY_NM = 'yyyyMMddCANADA' -- and rest_no = 100387 ) as transaction_dt, -- and date_key >= 20240101 a.REGISTEREDACCOUNTID as REGISTEREDACCOUNTID,GROUP BY 1, a.loyaltyCustomerId as loyaltyCustomerId, 2, a.TRANSACTIONID as TRANSACTIONID3, 4, a.REST_TYP_NM as REST_TYP_NM, 5, a.OPS_DIV_NM as OPS_DIV_NM 6, 7, a.DESCRIPTION as DESCRIPTION, 8, a.REDEMPTIONS as REDEMPTIONS9, 10, b.transactionID as completion_transactionID, 11, b.pointsEarned as12, pointsEarned, 13, b.restaurant as restaurant, 14, b.partition_date_key as offer_completion_dt, b.WEEK_START as offer_completion_week, b.lid as lid from TRXN_OFFER_CHALLENGES_REDEMPTIONS a left join points_issued b on a.loyaltyCustomerId = b.lid and b.WEEK_START = a.TH_FISCAL_WEEK ) Select TH_FISCAL_YEAR, TH_FISCAL_WEEK, WEEK_START_MAPPING, REGISTEREDACCOUNTID, loyaltyCustomerId, offer_completion_week, count( distinct( case when offer_completion_dt is not NULL and transaction_dt <= offer_completion_dt then TRANSACTIONID end ) ) as trnx_before_completion, count(distinct(TRANSACTIONID)) as total_trnx, count( distinct ( case when lid is not Null then lid end ) ) as completed from completed group by 1, 2, 3, 4, 5, 6 |
Count of guests who completed a specific Offer Challenge
Games
NHL Hockey Challenge & Tims Word Challenge
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SELECT YEAR(TIMESTAMP) AS YR , MONTH(TIMESTAMP) AS MTH , COUNT(DISTINCT GUESTS) AS GUESTS FROM ( -- WORD CHALLENEGE PLAYERS SELECT DISTINCT TIMESTAMP, _TIMHORTONS.LOYALTY.ID AS GUESTS FROM loyalty.events.adobe_app_events WHERE TRIM(_TIMHORTONS.INTERACTION.PATH) IN ('/timswordchallenge') AND TRIM(_TIMHORTONS.INTERACTION.ELEMENT.NAME) = 'play' AND _TIMHORTONS.PLATFORM IN ('app') AND LEFT(_TIMHORTONS.LOYALTY.ID,7) = 'us-east' AND DATE15 |
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loyalty.analytics.clearview_mapping_discount_types |
This table is manually mapped by grouping ticket_detail_POS_nm into categories
Combo Discount, Combo Discount (BG Bundle), Tims Rewards, Targeted Offers, Campaign, In-restaurant, Other, Settlement, and Uncategorized
This mapping was last updated in March 2024; any unmapped fields would show up as null and would be considered as “Other”
Discounts on offerids
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-- Total Summary
with clean_loyalty_transactions as(
with FILTERED as(
WITH SEPERATED AS (
-- Filter for Exploded offers for offer ids and explode the disc amt with corresponding PLU
with zipped as (
-- explode offers and combine the Discount amount with offer
SELECT
*,
arrays_zip(discountAmounts, appliedOffers) as comb -- EXPLODE(APPLIEDOFFERS) AS EXPLODED_OFFERS
FROM
PRODRT.CURATED_TRANS_EVENTS_NEW
WHERE
partition_date_key >= 20201201
-- to_date(partition_date_key, "yyyyMMdd") BETWEEN DATE '$Start_Date' AND DATE '$End_Date'
AND LEFT(REGISTEREDACCOUNTID, 7) = 'us-east'
AND APPLIEDOFFERS IS NOT NULL
AND COUNTRY_NM = 'CANADA'
)
select
DISTINCT transactionId,
loyaltyCustomerId,
registeredAccountId,
state_nm,
ticketId,
period_dt,
th_fiscal_week,
th_fiscal_year,
week_start_dt,
explode(Comb) as test
from
zipped
)
SELECT
*,
test ['discountAmounts'] AS DISC_AMT,
test ['appliedOffers'] AS APPLIED_OFFER
FROM
SEPERATED
)
select
FILTERED.*,
O.NAME,
O.DESCRIPTION,
1 as VOLUME
From
FILTERED
inner JOIN DYDB.OFFERS O ON O.OFFERID = FILTERED.APPLIED_OFFER
)
SELECT
TH_FISCAL_YEAR,
th_fiscal_week,
date(week_start_dt) as wk_start_dt,
state_nm,
APPLIED_OFFER,
DESCRIPTION,
SUM(DISC_AMT) AS DISCOUNT_DOLLARS,
SUM(VOLUME) AS REDEMPTION_VOLUME
FROM
clean_loyalty_transactions
GROUP BY
1,2,3,4,5,6 |
Tims Word Challenge Player Levels
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SELECT LEVEL, COUNT(DISTINCT ID) AS USERS FROM ( SELECT _TIMHORTONS.LOYALTY.ID, MAX(DATE(TIMESTAMP)) AS DTE , COALESCE(MAX(CAST(SUBSTRING(_TIMHORTONS.INTERACTION.ELEMENT.VALUE,18,CHARINDEX('-',REPLACE(_TIMHORTONS.INTERACTION.ELEMENT.VALUE,'"','-'),18)-18) AS INT)),0) LEVEL FROM loyalty.events.adobe_app_events WHERE EVENTTYPE = 'element_clicked' AND DATE(TIMESTAMP) >= DATE '2023-11-01' AND UNION -- HOCKEY PLAYERS SELECT _TIMHORTONS.INTERACTION.PATH = '/timswordchallenge' AND DISTINCT TIMESTAMP,_TIMHORTONS.INTERACTION.LOYALTY.ID AS GUESTS FROM loyalty.events.adobe_app_events WHERE TRIM(_TIMHORTONS.INTERACTION.PATH) = '/hockey_challenge' AND TRIM(_TIMHORTONS.INTERACTION.ELEMENT.NAME) IN ('submit_picks') ANDELEMENT.NAME = 'play' AND _TIMHORTONS.LOYALTY.ID IN (SELECT DISTINCT registeredAccountId FROM loyalty.users.customer_base WHERE LEFT(loyaltyCustomerId,4) IN ('0463','0473')) GROUP BY 1 ) GROUP BY 1 ORDER BY 1 |
Points Issued by Channel
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WITH OFFER_BASE AS ( _TIMHORTONS.PLATFORM IN ('app')SELECT AND LEFT(_TIMHORTONS.LOYALTY.ID,7) = 'us-east' AND MONTH_DT, DATE >= DATE '2023-11-01' ) GROUP BY 1,2 ORDER BY 1 DESC, 2 |
Count of guests who played Games (NHL Hockey Challenge and Tims Word Challenge).
Limitation: Data only available from Nov 1, 2023.
Total Sales and Ticket Count by Tender Type
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WITH LOYALTY_TENDERS AS ( WITH TENDERS AS (SUM(CASE WHEN A.TAG IS NULL AND LEFT(A.EXPLODED.OFFERID,11) = 'EARN_POINTS' THEN A.EXPLODED.TIMSPOINTSEARNED ELSE 0 END) AS BASE, SELECT SUM(CASE WHEN REPLACE(UPPER(TRIM(TENDER_NAME)), '.', '') AS TENDER_NAME, TICKET_ID FROM loyalty.tlog.tlog_sale_ticket_tendersLEFT(A.EXPLODED.OFFERID,11) <> 'EARN_POINTS' AND A.EXPLODED.OFFERID IS NOT NULL AND A.TAG IS NULL THEN A.EXPLODED.TIMSPOINTSEARNED ELSE 0 END) AS OFFERS WHERE PARTITION_DATE_KEY BETWEEN 20230101 AND 20230731 AND LEFT(REST_NO,2) = 10 FROM (SELECT ), LOYALTY AS ( LAST_DAY(TO_DATE(PARTITION_DATE_KEY, 'yyyyMMdd')) AS MONTH_DT, SELECT TICKET_ID AS TICKET_ID FROM STG.DERIVED_MASTER_TABLE_NEWTAG, WHERE PARTITION_DATE_KEY BETWEEN 20230101 AND 20230731 TRANSACTIONID, AND COUNTRY_NM = 'CANADA' AND IS_PASS_THROUGH = 0 POINTSEARNED, AND LEFT(REGISTERED_ACCOUNT_ID,7) = 'us-east' ) SELECTcoalesce(cast(isCustomerServiceVisit as string), '') as A.*ISCUSTOMERSERVICEVISIT, FROM TENDERS A INNER JOIN LOYALTY B EXPLODE(APPLIEDOFFERDETAILS) AS EXPLODED ON A.TICKET_ID = B.TICKET_ID ) SELECT CASE WHEN UPPER(TENDER_NAME) IN ('CASH', 'COMPTANT', 'EFECTIVO', 'US CASH', 'CANADIAN CASH', 'CDN CASH', 'ROUNDED CASH', 'ROUNDED COMPTANT') THEN 'CASH'FROM PRODRT.CURATED_POINTS_EVENTS A WHEN UPPER(TENDER_NAME) IN ('DEBIT CARD' WHERE TO_DATE(PARTITION_DATE_KEY, 'DEBITyyyyMMdd',) 'CARTE DEBIT', 'DEBITO', 'DÉBIT', 'DO DEBIT') THEN 'DEBIT'BETWEEN DATE '2024-05-01' AND DATE '2024-05-31' --UPDATE THIS WHENAND UPPER(TENDER_NAMELEFT(BARCODE, 4) IN= ('VISA', 'MASTERCARD', 'MASTER CARD', 'AMEX', 'AMERICAN EXPRESS', 'CREDIT CARD', 'CREDIT CARDS', 'DISCOVER', 'M/C', 'DISCOVER CARD', 'DIGITAL AMEX', 'DIGITAL DISCOVER', 'DIGITAL MASTER CARD', 'DIGITAL MASTERCARD', 'DIGITAL AMERICAN EXPRESS', 'DIGITAL VISA', 'DO VISA', 'DO MASTERCARD') THEN 'CREDIT' 0463' AND COALESCE(PARTNERID, '') = '' AND ISCUSTOMERSERVICEVISIT IS NOT TRUE WHEN UPPER(TENDER_NAME) IN ('TIM CARD', 'DIGITAL TIM CARD', 'CARTE TIM', 'MOBILE TIM) CARD',A 'DIGITAL CARTE TIM', 'TIM CARTE', 'TIMS GIFT CARD', 'DIGITAL TIMS GIFT CARD', 'CARTE-CADEAU TIM', 'DIGITAL CARTE-CADEAU TIM') THEN 'TIMCARD' GROUP BY 1 ), ALL_OTHER AS ( WHEN UPPER(TENDER_NAME) LIKE '%SKIP%' THENSELECT 'SKIP' WHEN UPPER(TENDER_NAME) LIKE '%UBER%' THEN 'UBER' LAST_DAY(TO_DATE(PARTITION_DATE_KEY, 'yyyyMMdd')) AS MONTH_DT, SUM(CASE WHEN B.TAG IN UPPER(TENDER_NAME) LIKE '%DOOR%' THEN 'DOORDASH'('DAYPART_CHALLENGED_COMPLETED','PRODUCT_CHALLENGED_COMPLETED','FREQUENCY_CHALLENGED_COMPLETED') THEN B.POINTSEARNED ELSE 0 END) AS CHALLENGES, SUM(CASE WHEN UPPER(TENDER_NAMELEFT(TAG, 4) IN= ('RUTR'SCAN ANDTHEN PAYPOINTSEARNED VISA', 'SCAN AND PAY MASTERCARD', 'SCAN AND PAY TIMCARD', 'SCAN AND PAY AMEX', 'SCAN AND PAY DISCOVER', 'SCAN AND PAY TIM CARD', 'NUMERISEZ ET PAYEZ – VISA', 'SCANTOPAY', 'NUMERISEZ ET PAYEZ – MASTERCARD', 'NUMERISEZ ET PAYEZ – CARTE TIM', 'NUMÉRISEZ ET PAYEZ – VISA', 'NUMÉRISEZ ET PAYEZ – MASTERCARD', 'NUMÉRISEZ ET PAYEZ – CARTE TIM', 'NUMERISEZ ET PAYEZ – AMEX', 'NUMÉRISEZ ET PAYEZ – AMEX', 'SCAN AND PAY TIMS GIFT CARD') THEN 'SCANANDPAY'ELSE 0 END) AS RUTW, SUM(CASE WHEN LEFT(B.TAG, 6) = 'HOCKEY' THEN B.POINTSEARNED ELSE 0 END) AS HOCKEY, SUM(CASE WHEN B.ISCUSTOMERSERVICEVISIT = 'true' THEN B.POINTSEARNED ELSE 0 END) AS GUEST_CARE, SUM(CASE WHEN UPPER(B.TAG) = 'WORD_CHALLENGE_LEVEL' THEN B.POINTSEARNED ELSE 0 END) AS WORD_CHALLENGE, WHEN UPPER(TENDER_NAMESUM(B.POINTSEARNED) IN ('HST', 'HST1', 'TVQ', 'TPS', 'GST', 'TAX', 'PST', 'HST TAXABLE SALES', 'SALES TAX' 'HST 1', 'H.S.T.1', 'H.S.T', 'HST 13% TAXABLE SALES', 'GST TAXABLE SALES', 'TAX 1', 'HST 1', 'GST# 75696 6891 RT0001', 'HST # 897258141', 'HST5%', 'HST8%', 'QST', 'SALES TAX', 'MEAL PLAN CARD - PREPAID TAX', 'CARTE PLAN REPAS - TAX PREPAYEE', 'GST # 121071781RT0001', 'TVH', 'TVH1', 'VAF', 'H.S.T.') THEN 'TAXAS TOTAL_POINTS FROM PRODRT.CURATED_POINTS_EVENTS B WHERE TO_DATE(PARTITION_DATE_KEY, 'yyyyMMdd') BETWEEN DATE '2024-05-01' AND DATE '2024-05-31' --UPDATE THIS AND LEFT(BARCODE, 4) = '0463' WHEN AND ((UPPER(TENDER_NAMECOALESCE(PARTNERID, '') LIKE= '%ROUND%') OR (UPPER(TENDER_NAME) LIKE '%ARRONDIS %')) THEN 'ROUND UP' ELSE 'OTHER' END AS TENDER, COUNT(DISTINCT TICKET_ID) AS TRXNS FROM LOYALTY_TENDERS GROUP BY 1 |
'
GROUP BY 1
)
SELECT
A.MONTH_DT,
BASE,
OFFERS,
CHALLENGES,
RUTW,
HOCKEY,
GUEST_CARE,
WORD_CHALLENGE,
TOTAL_POINTS
FROM OFFER_BASE A
LEFT JOIN ALL_OTHER B
ON A.MONTH_DT = B.MONTH_DT |