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NTTS 2017 conference Session: Structured Big Data - Producing official statistics from new structured data sources Official statistics on B2C e-commerce.

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Presentation on theme: "NTTS 2017 conference Session: Structured Big Data - Producing official statistics from new structured data sources Official statistics on B2C e-commerce."— Presentation transcript:

1 NTTS 2017 conference Session: Structured Big Data - Producing official statistics from new structured data sources Official statistics on B2C e-commerce based on individuals’ credit card payment information David Suárez and Luis Padial Department of Statistics and KM, CNMC Brussels, March 15, 2017

2 Introduction Definition for e-commerce: Any purchase made online, regardless of the payment method used. Its basic characteristic consists of a purchase order, which needs to be carried out via an electronic means, no matter the actual payment mechanism involved.

3 Introduction In the EU, official e-commerce statistics are based mainly on survey data collection: survey on ‘ICT usage in households and by individuals’ survey on 'ICT usage and e-commerce in enterprises' both annually conducted by National Statistical Offices of the Member States.

4 Introduction Any alternative to surveys? In Spain, the National Authority on Markets and Competition (CNMC) collects quarterly data on B2C e-commerce using as data source individuals’ credit card payment information. For this purpose, CNMC reached an agreement with the Spanish card payment entities to collect their raw data which the CNMC process to make the results publically available.

5 Methods Data source: partnership with main market stakeholders (Spanish credit/debit cards entities)

6 Methods Thus, CNMC keeps a census of all the e-commerce transactions carried out through virtual PoS that have Spain as their point of origin and/or destination and whose payment is carried out through the card payment entities. A virtual PoS is any software tool that sends card payment requests to the financial entities and expressly identifies the transaction as e-commerce.

7 CNMC e-commerce data available:
Methods CNMC e-commerce data available: e-commerce indicators Turnover (revenues) Number of transactions Segmentation (2 axis) Geographical segmentation according to origin and destination of the transactions (3 groups plus countries of origin/destination). Branch of economic activity involved in the transaction (the CNAE code: National Classification of Economic Activities is used for this classification, 93 groups).

8 Methods CNMC e-commerce data available: Geographical segmentation according to origin and destination of the transactions Spanish commercial transactions with foreign countries Foreign commercial transactions with Spain Transactions within Spain

9 Results QUARTERLY TREND IN E-COMMERCE TURNOVER AND YEAR-ON-YEAR VARIATION (millions of euros and percentage)

10 Results THE TEN AREAS OF ACTIVITY WITH THE HIGHEST PERCENTAGE OF E-COMMERCE TURNOVER (2Q2016, percentage)

11 Results QUARTERLY TREND IN E-COMMERCE TRANSACTIONS AND YEAR-ON-YEAR VARIATION (millions of transactions and percentage)

12 Results E-COMMERCE TURNOVER SEGMENTED GEOGRAPHICALLY (2Q2016, percentage)

13 Results E-COMMERCE TURNOVER FROM SPAIN TO FOREIGN LOCATIONS BY GEOGRAPHICAL AREA (2Q2016, percentage)

14 Results available at: http://data.cnmc.es
14

15 Conclusions Pros: Quarterly e-commerce indicators: unique monitor market. Richness of the data source: complementing survey data. Cons: E-commerce paid for via bank transfer or cash on delivery not included. However, not an issue. Innovative payment methods (mobile payments or others) are gaining traction: need to stay updated.


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