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The aim of this project is to develop a dashboard that illustrates the high-level performance of Tim Horton’s digital/loyalty program. Currently, executive leadership across Tim Horton’s seeks insights on digital health metrics at a higher frequency than the Digital & Loyalty Analytics team currently provides to them. Furthermore, the existing process to provide these metrics ad hoc requires significant manual intervention by the analytics team. Thus, the dashboard should display key metrics that the digital team already tracks, in one location. The end-users of the dashboard are anticipated to be high-level executives, who will monitor essential business metrics to effectively guide business activities, as well as members of the Digital Loyalty Analytics team and will be displayed on the Digital & Loyalty screens (therefore dashboard layout, perspective & dashboard should align to screen dimensions). However, based on the rate of uptake, users across the broader organization may utilize the dashboard on an ad hoc basis.
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The following outlines details of each of the requested dashboard views (of which there are four c.6 in total), and should inform the development of the underlying data models to power the use case. Note that the analysis should be limited to TH Canada and Canadian Loyalty Guests.
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The first time-series chart, KDS Penetration Over Time, is intended to illustrate, using superimposed line charts, the evolution of KDS penetration throughout the dashboard user’s selected time period, compared to past years over the same time period. Each line represents a different year’s KDS over the user’s selected reporting range. Within this chart, users should have the option to drill up or down on the reporting cadence (e.g., daily, weekly [fiscal], monthly, quarterly, annually). For example, if the user inputted the time range as [Start Date] 2023/01/01 to [End Date] 2023/10/01 and drilled down the reporting cadence to “weekly”, the chart would show weekly KDS penetration overtime for January to October, in 2021, 2022, and 2023.
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Project timeline overrun: as a high-priority project, with executive-level interest, adherence to the overall project timeline is the most significant risk of the project.
Inaccurate data: as the dashboard is anticipated to influence TH Digital & Loyalty decision-making, the accuracy of the data is paramount.
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Loyalty Dashboard Wishlist
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Issuance
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Total Points Issued
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Ability to filtered by
any period (day, week, month, campaign period)
province
top cities
restaurant
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Point Type
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Restaurant, FS/Partner, Marketing (split by Hockey Challenge, Word Challenge, Offers, Campaign), Support
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Earning Means
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App, Plastic, Digital Wallet
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Bonus Point Guardrail tracking
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Avg Issuance per guest
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Total Number of Non-Registered Points
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Ability to filtered by
any period (day, week, month, campaign period)
province
top cities
restaurant
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Redemption
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Total Points Burned
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Ability to filtered by
any period (day, week, month, campaign period)
province
top cities
restaurant
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Points Burned by Tier
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Average Redemption Per guest
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Type of Point Burned
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Restaurant, FS/Partner
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Number of points burned as a % of total points in system
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Guest View
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Number of Guests that Earned
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Ability to filtered by
any period (day, week, month, campaign period)
province
top cities
restaurant
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Number of New Guests that Earned (past 30 days)
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Number of Guests that Burned
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Number of New Guests that Burned (P30 days)
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Total Number Non-Registered Guests
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Total Number Non-Registered Guests that Earned
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Total Number of Guests Scanning with Plastic (any plastic)
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Total Number of Guest Scanning with Digital
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Total # of features guest has engaged with (meaning scan, Scan & Pay, MPO, delivery, game, catering,
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Avg cheque
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Ability to filtered by
any period (day, week, month, campaign period)
province
top cities
restaurant
Plastic vs. Digital Earn
New (last 30 days) vs. Ongoing
Frequency/value segments
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Avg visits
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Offer users
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Game interactions (HC, WC, RUTW)
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Ability to filtered by
guests that play in any period (day, week, month, campaign period)
ever played
new players in a certain time
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Scan & Pay Penetration’s
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ability to filter between by guest, by transaction
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Never redeemed
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amount, % of total redeemers, % of all guest
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Balances
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Bankers
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% and number of points
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Set to redeem
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% and number of points
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Expiry/Inactive/Fraud
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Total Points Expiring
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per month
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Number of Guests with Expiring Points
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per month
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Total Points Deactivated (when live)
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per month
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Number of Guests with Inactive Points (when live)
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