Metric and Definition | Query | Comments and Business Use |
|---|
Known Diner Sales (KDS“KDS”) - all 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’) | | Code Block |
|---|
SELECT TH_FISCAL_YEAR,
TH_FISCAL_WEEK,
SUM(AMOUNT) AS SALES,
COUNT(DISTINCT TICKET_ID) AS TRXNS,
COUNT(DISTINCT REGISTERED_ACCOUNT_ID) AS GUESTS
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'
AND LEFT(REGISTERED_ACCOUNT_ID,7) = 'us-east'
GROUP BY 1,2 |
| This metric is used as a baseline to see loyalty sales penetration to our against system wide sales. |
System Wide Sales (SWS“SWS”) - all Total sales across the systemTH | | Code Block |
|---|
SELECT
T1.TH_FISCAL_YEAR,
T1.TH_FISCAL_WEEK,
CAST(WEEK_START_DT AS DATE) AS WEEK_DT,
COUNT(DISTINCT REGISTERED_ACCOUNT_ID) AS GUESTS,
COUNT(DISTINCT T1.TICKET_ID) AS TRXNS,
SUM(T1.AMOUNT) AS SWS
FROM STG.DERIVED_MASTER_TABLE_NEW T1
WHERE
PARTITION_DATE_KEY BETWEEN '<START DATE>' AND '<END DATE>'
AND T1.IS_PASS_THROUGH = 0
AND T1.COUNTRY_NM = 'CANADA'
GROUP BY 1,2,3 |
| Note: Some forecasts may use hyperion Hyperion sales interchangeable instead in lieu of SWS sourced from STG.DERIVED_MASTER_TABLE_NEW. |
Cheque - average sales Average sales value ($) of an individual transaction | | Code Block |
|---|
SELECT
T1.TH_FISCAL_YEAR,
T1.TH_FISCAL_WEEK,
CAST(WEEK_START_DT AS DATE) AS WEEK_DT,
COUNT(DISTINCT T1.TICKET_ID) AS TRXNS,
SUM(T1.AMOUNT) AS SWS,
SUM(T1.AMOUNT)/COUNT(DISTINCT T1.TICKET_ID) AS CHEQUE
FROM STG.DERIVED_MASTER_TABLE_NEW T1
WHERE
PARTITION_DATE_KEY BETWEEN '<START DATE>' AND '<END DATE>'
AND T1.IS_PASS_THROUGH = 0
AND T1.COUNTRY_NM = 'CANADA'
GROUP BY 1,2,3 |
| Can calculate this on a system level or down to an individual guest level. Can filter on loyalty or non-loyalty. |
Frequency - average Average loyalty guest visits in a given time period | | Code Block |
|---|
SELECT
T1.TH_FISCAL_YEAR,
T1.TH_FISCAL_WEEK,
CAST(WEEK_START_DT AS DATE) AS WEEK_DT,
COUNT(DISTINCT T1.TICKET_ID) AS TRXNS,
COUNT(DISTINCT T1.REGISTERED_ACCOUNT_ID) AS GUESTS,
COUNT(DISTINCT T1.TICKET_ID)/COUNT(DISTINCT T1.REGISTERED_ACCOUNT_ID) AS FREQUENCY
FROM STG.DERIVED_MASTER_TABLE_NEW T1
WHERE
PARTITION_DATE_KEY BETWEEN '<START DATE>' AND '<END DATE>'
AND T1.IS_PASS_THROUGH = 0
AND T1.COUNTRY_NM = 'CANADA'
AND LEFT(REGISTERED_ACCOUNT_ID,7) = 'us-east'
GROUP BY 1,2,3 |
| Usually look at this metric for a week, month, or year. |
White Label Delivery (WL“WL”) Delivery sales initiated from the TH mobile app | | Code Block |
|---|
SELECT
TH_FISCAL_YEAR,
TH_FISCAL_WEEK,
SUM(AMOUNT) AS SALES
FROM STG.DERIVED_MASTER_TABLE_NEW
WHERE PARTITION_DATE_KEY BETWEEN '$START_DATE' AND 'END_DATE'
AND IS_PASS_THROUGH = 0
AND COUNTRY_NM = "CANADA"
AND ((SERVICE_MODE_CD = 'WHITE LABEL DELIVERY') OR (SERVICE_MODE_CD = 'DELIVERY' AND REGISTERED_ACCOUNT_ID LIKE 'us-east%'))
AND LEFT(REGISTERED_ACCOUNT_ID,7) = 'us-east'
GROUP BY 1,2 |
| Included in known diner sales & digital sales. Sales of our internal app delivery platform. |
Mobile Order & Pay (MO“MO&PP”) | | Code Block |
|---|
SELECT
TH_FISCAL_YEAR,
TH_FISCAL_WEEK,
SUM(AMOUNT) AS SALES
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"
AND SERVICE_MODE_CD IN ('MOBILE ORDER DRIVE THRU', 'MOBILE ORDER EAT IN', 'MOBILE ORDER TAKE OUT')
AND LEFT(REGISTERED_ACCOUNT_ID,7) = 'us-east'
GROUP BY 1 |
| Included in known diner sales & digital sales. |
Loyalty Scans - this Sales made by known diners and includes eat-in, takeout & drive thru | | Code Block |
|---|
SELECT
TH_FISCAL_YEAR,
TH_FISCAL_WEEK,
SUM(AMOUNT) AS SALES
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"
AND SERVICE_MODE_CD IN ('TAKEOUT', 'EATIN','DRIVETHRU')
AND LEFT(REGISTERED_ACCOUNT_ID,7) = 'us-east'
GROUP BY 1,2 |
| Included in known diner sales & digital sales. |
Other Registered Sales - Catering, Kiosk & Curbside Pick Up | | Code Block |
|---|
SELECT
TH_FISCAL_YEAR,
TH_FISCAL_WEEK,
SUM(AMOUNT) AS SALES
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"
AND SERVICE_MODE_CD IN ('KIOSK', 'KIOSK TAKEOUT', 'CATERING', 'CURB SIDE PICK UP')
AND LEFT(REGISTERED_ACCOUNT_ID,7) = 'us-east'
GROUP BY 1,2 |
| 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 | | Code Block |
|---|
SELECT
a.PARTITION_DATE_KEY,
SUM(A.AMOUNT) AS SALES
FROM STG.DERIVED_MASTER_TABLE_NEW A
INNER JOIN TLOG.TLOG_SALE_TICKET_TENDERS B
ON A.TICKET_ID = B.TICKET_ID
WHERE A.PARTITION_DATE_KEY BETWEEN 'START_DATE' AND 'END_DATE'
AND IS_PASS_THROUGH = 0
AND COUNTRY_NM = 'CANADA'
AND TENDER_NAME IN ("UBER EATS CREDIT","Credit Uber Eats","Uber Eats Credit","CRÉDIT UBER EATS","SKIP CREDIT","Skip Credit","CRÉDIT de DoorDash","CRÉDIT DE DOORDASH","DoorDash Credit","DOORDASH CREDIT","Crédit de DoorDash","Doordash")
GROUP BY 1 |
| Included in digital sales |
Unregistered Kiosk | Code Block |
|---|
Sales via Kiosk by guests who did not scan for loyalty | | Code Block |
|---|
SELECT
PARTITION_DATE_KEY,
SUM(AMOUNT) AS SALES
FROM STG.DERIVED_MASTER_TABLE_NEW
WHERE PARTITION_DATE_KEY BETWEEN '$1_START_DATE' AND '$2_END_DATE'
AND SERVICE_MODE_CD IN ('KIOSK', 'KIOSK TAKEOUT')
AND IS_PASS_THROUGH = 0
AND COUNTRY_NM = "CANADA"
AND LEFT(COALESCE(REGISTERED_ACCOUNT_ID,''),7) <> 'us-east'
GROUP BY 1 |
| Included in digital sales |
Unregistered Catering Catering sales by unregistered guests | | Code Block |
|---|
SELECT
PARTITION_DATE_KEY,
SUM(AMOUNT) AS SALES
FROM STG.DERIVED_MASTER_TABLE_NEW
WHERE PARTITION_DATE_KEY BETWEEN 'START_DATE' AND 'END_DATE'
AND SERVICE_MODE_CD IN ('CATERING', 'CURB SIDE PICK UP')
AND IS_PASS_THROUGH = 0
AND COUNTRY_NM = "CANADA"
AND LEFT(COALESCE(REGISTERED_ACCOUNT_ID NOT LIKE,''),7) <> 'us-east%east'
GROUP BY 1 |
| Included in digital sales |
RRAMI (Restaurants Reporting Any Menu Item (“RRAMI“) | | Code Block |
|---|
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 |
|---|
SELECT
PARTITION_DATE_KEY,
COUNT(DISTINCT TRANSACTIONID) AS TICKETS,
SUM(ITEMTOTALPRICE) AS SALES
FROM PRODRT.CURATED_TRANS_EVENTS_NEW
WHERE PARTITION_DATE_KEY >= 20230801
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 | | Code Block |
|---|
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“MAU”) - Amount Number of guests that visited the app each month | Pulled currently from Amplitude using unique guests that triggered the ‘Session Start’ event. Will switch to Adobe in October 2023 using the same event. | Used to track amount of guests who visit the app. |
Digital Sales | Pulled using the individual queries listed above. | Consists of all known diner sales (WL, MO&P, Loyalty Scans, Other Registered Sales) along with 3P Delivery, Unregistered Kiosk & Unregistered Catering. |
Weekly Offer Redemptions | | Code Block |
|---|
WITH REDEMPTION_SUMMARY AS (
WITH OFFER_REDEMPTION_TRXNS AS (| Code Block |
|---|
| WITH EVENTS AS (
SELECT DATE
, _TIMHORTONS.INTERACTION.ELEMENT.NAME
WITH, TRANSACTIONS_WITH_OFFER__TIMHORTONS.LOYALTY.ID AS (GUEST_ID
FROM loyalty.events.adobe_app_events
WHERE SELECTEVENTTYPE TH_FISCAL_YEAR,IN ('app_open','app_launch')
AND TH_FISCAL_WEEK,
_TIMHORTONS.PLATFORM IN ('app')
AND CASTLEFT(WEEK_START_DT AS DATE) AS WEEK_START_DT,
_TIMHORTONS.LOYALTY.ID,7) = 'us-east'
AND DATE <= DATE_FORMAT(
CURRENT_DATE )
SELECT LAST_DAY(EVENTS.DATE) AS DTE
CAST( , UNIX_TIMESTAMP(LEFT(WEEK_START_DT, 10), 'yyyy-MM-dd') AS TIMESTAMP
COUNT(DISTINCT EVENTS.GUEST_ID) AS ACTIVE_USER
FROM EVENTS
GROUP ),BY 1
ORDER BY 'yyyyMMdd'
) AS WEEK_START,
CAST(PERIOD_DT AS DATE) AS PERIOD1 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 all known diner sales (WL, MO&P, Loyalty Scans, Other Registered Sales) along with 3P Delivery, Unregistered Kiosk & Unregistered Catering. |
Weekly Offer Redemptions | | Code Block |
|---|
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 REGISTEREDACCOUNTIDAS OFFER_DESCRIPTION,
A.EXPLODED_OFFERS AS TRANSACTIONIDOFFERID,
EXPLODE(APPLIEDOFFERS) AS EXPLODED_OFFERS
SUM(VOLUME) AS REDEMPTION_VOLUME
FROM
OFFER_REDEMPTION_TRXNS A
PRODRT.CURATED_TRANS_EVENTS_NEW
GROUP BY
1,
WHERE 2,
PARTITION_DATE_KEY BETWEEN 'START DATE' AND 'END DATE'
AND REGISTEREDACCOUNTID LIKE 'us-east%'
AND COUNTRY_NM = 'CANADA'
)
SELECT3
)
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 | | Count of guests who completed a specific Offer Challenge |
Games NHL Hockey Challenge & Tims Word Challenge | | Code Block |
|---|
| SELECT YEAR(TIMESTAMP) AS YR
DISTINCT A.TH_FISCAL_YEAR, MONTH(TIMESTAMP) A.TH_FISCAL_WEEK,
AS MTH
A.WEEK_START_DT, A.PERIOD_DT, COUNT(DISTINCT GUESTS) AS GUESTS FROM A.REGISTEREDACCOUNTID,
A.TRANSACTIONID,
C.NAME,(
-- WORD CHALLENEGE PLAYERS
SELECT DISTINCT TIMESTAMP, _TIMHORTONS.LOYALTY.ID AS GUESTS
FROM C.DESCRIPTION,loyalty.events.adobe_app_events
WHERE A.EXPLODED_OFFERS,
TRIM(_TIMHORTONS.INTERACTION.PATH) IN ('/timswordchallenge')
AND 1 AS VOLUME TRIM(_TIMHORTONS.INTERACTION.ELEMENT.NAME) = 'play'
FROMAND TRANSACTIONS_WITH_OFFER_ID A
_TIMHORTONS.PLATFORM IN ('app')
AND INNER JOIN DYDB.WEEKLYOFFERS B ON A.EXPLODED_OFFERS = B.OFFERID
LEFT(_TIMHORTONS.LOYALTY.ID,7) = 'us-east'
AND LEFT JOIN DYDB.OFFERS C ON A.EXPLODED_OFFERS = C.OFFERID
)
DATE >= DATE '2023-11-01'
UNION
-- HOCKEY PLAYERS
SELECT DISTINCT WEEK_START_DT,TIMESTAMP,_TIMHORTONS.LOYALTY.ID AS A.DESCRIPTION AS OFFER_DESCRIPTION,GUESTS
FROM A.EXPLODED_OFFERS AS OFFERID,loyalty.events.adobe_app_events
WHERE SUM(VOLUMETRIM(_TIMHORTONS.INTERACTION.PATH) AS= REDEMPTION_VOLUME
'/hockey_challenge'
AND FROM OFFER_REDEMPTION_TRXNS A
GROUP BY
TRIM(_TIMHORTONS.INTERACTION.ELEMENT.NAME) IN ('submit_picks')
AND 1, _TIMHORTONS.PLATFORM 2,
IN ('app')
AND 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 LEFT(_TIMHORTONS.LOYALTY.ID,7) = 'us-east'
AND 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. |