Session 13 – Specific issues raised in the questionnaires The Potential Use of Credit/Debit Card Data for Tourism Statistics – Considerations Michel Dubreuil Destination Canada UNWTO/DG GROW Workshop Measuring the economic impact of tourism in Europe: The Tourism Satellite Account (TSA) Brussels, Belgium 29-30-November 2017 1 Incorporating more data sources to enhance the robustness of the Tourism Statistical Program Application Add-ons Build on already existing Social Media applications to collect info on Use of social media info to capture travellers. info travellers’ origin, destination, and characteristics. Mobile & cellular info Mobile & cellular information on Payment & Credit Cards travellers’ mobility & hotspots. Use of payment and credit cards information to enhance admin and Self-response survey data. Tourism data collection Stats & Info Self-response electronic questionnaire. Assisted & promoted data collection Data collection supported by Admin info interviewers or promoted by Administrative data Administrative data supporting traveller & tourism stakeholders. various regulatory activities. Gathering information on tourism spending and its key correlates Credit/Debit cards offer significant potential benefits for tourism statistics… • Equivalent to an electronic cash register • Visibility of actual transactions by travellers • Timely • Details about • types of commodities purchased • locations of spending at subnational/regional levels 3 … but it is not without challenges • Data acquisition issues • Negotiating access to credit/debit card transaction data • Costs • Confidentiality and privacy issues • Public perceptions • Data interpretation and integration issues • Lack of visibility over travellers’ characteristics • Share (%) and type of spending captured by credit/debit card transactions • Travel ≠ Tourism 4 Tourism is a subset of travel • Credit/Debit card transactions will not discriminate between types of travelers • In Canada, 1 in 12 travelers is a crew member (airline, cruise, trucking) Number of non-resident travellers entering Canada in 2016 Arrivals Share of Same-day & Total Traveler characteristics overnight travelers & crews Mostly tourism trips Travel ≠ Tourism Non-resident travelers 30.1 million from United Stated 23.9 million from other countries 6.2 million Other travelers Non-Resident Crews 2.8 million 8.6% from United Stated 2.0 million 7.8% from other countries 0.8 million 11.5% Source: Statistics Canada , CANSIM Table 427-0001 5 Credit card spending patterns differ in their characteristics compared to other modes of payments Spending using VISA credit cards represent s40% of total inbound expenditure VISA Reported total spending by Distribution of spending by Share of commodity commodity – VISA versus ITS ITS $848 16.8% Lodging Lodging $4,891 38.9% 17.3% $674 Restaurants 13.3% Million CAD Million $3,131 Restaurants 24.9% 21.5% $149 2.9% Entertainment Entertainment $1,122 8.9% 13.3% $3,386 66.9% Others* Others* $3,440 27.3% 98.4% $5,058 100.0% Total Total $12,584 100.0% 40.2% VISA Spending ITS Spending VISA Share ITS Share Total inbound international travel spending by non-resident travelers in Canada. May to September 2016 * Others include retails, transportation in Canada and other expenditures 6 Source: Travel Industry Association of Canada, VISA & TIAC 2016 Summer Travel Snapshot; Statistics Canada , International Travel Survey (ITS), 2016 Q2 & Q3 Case study: German leisure tourists to Canada Size of Travel Party associated Payment Method Credit Card Used to payment transactions 62% 1 person 31% 48% Credit 49% Cards 18% 2 people 47% Others 0% 3 people 13% 6% Debit/Bank Cards 4 people 7% Average 42% VISA’s party size Cash share 5 or more 2.02 30.5% 2% people 3% Other Leisure Tourists to Canada (n=306) 7 Source: Destination Canada, Global Tourism Watch (GTW) 2016 Base: Long-haul pleasure travellers (past 3 years) who visited Canada, U.S., Australia QRT10a. Thinking back to purchases made during this trip, including yourself, how many people’s expenditures were you paying for? QRT10b. Approximately what percentage of your purchases did you make during your trip with each of the following payment methods? Your best guess is fine. Base: Long-haul pleasure travellers (past 3 years) who used a credit card for purchases QRT10c. Which credit cards did you use to make purchases on this trip? German transactions using a Visa credit card May-September 2016 • VISA captured an estimated 25% of all reported travel spending by Germans in Canada, similar but lower than the share for leisure travel (30.5%) • Spending distribution is similar to total inbound international travel spending Global VISA VISA Reported total Distribution of spending Share of Share of spending by commodity by commodity – VISA versus ITS ITS ITS $18 16.5% Lodging $188 43% 9.6% 17.3% $12 Restaurants 10.6% $103 23% 11.4% 21.5% US$85m Million CAD $4 3.5% (CAD$ 110) Entertainment 14.0% $28 6% 13.3% $77 Others* 69.4% 63.0% $122 28% 98.4% $110 Total 100.0% 25.0% $441 100% All Travels VISA 40.2% Share VISA Spending ITS Spending Leisure VISA’s share 30.5% 8 Source: Travel Industry Association of Canada, VISA & TIAC 2016 Summer Travel Snapshot; Statistics Canada , International Travel Survey (ITS), 2016 Q2 & Q3; Destination Canada , GTW 2016 Outlook for integrating credit/debit cards in tourism statistics • Offers real (administrative) and very rich data, but the challenge will be to develop methods to: • map this data onto total travel spending and • assign traveler characteristics • Short term outlook • Develop early indicators of travel spending • Benchmarking and spending dispersion across local geographies by country of origin • Seasonal spending trends by commodities • Long Term outlook • Develop indicators of travel characteristics for credit/debit card spending data • Develop methods to identify, organize and integrate transaction data into tourism statistics and into TSA 9 Short Term Outlook Develop indicators of travel spending Credit/debit card data will provide us with the ability to ask questions on travel spending not previously possible • By country of origin • Spending category: can be aggregated to a level consistent with TSA commodity aggregations • Geography: Data available at • national, • provincial/territorial, • tourism region, • census sub-division and • neighborhood levels (Postal Code’s Forward Sorting Area (FSA)) • Timing: weekly, monthly, quarterly 10 Thank you Merci 11 .