Market Insights

Description

Based on all acquiring transactions in the Nordics, we've developed a service that allows merchants and business intelligence users to identify ongoing market trends in real-time. With a vast number of dynamic filters, users can tailor the insights to their business and turn the analytics into actionable insights.

Users can see weekly, monthly, and quarterly developments in card turnover, number of transactions, and number of cards, and compare user-defined time periods with historical figures. The correlation between card spending and the number of cards is also included. Using this data, the service can visualize the effects of tourism, trends in card area origin and the use of business cards, giving deep insights into spending patterns for the user's chosen segments.

The area of residence of a card is estimated from the consumer's previous transaction patterns, which can be used to identify the distribution of cardholders for a specific industry or merchant area. All these insights enable benchmarking with historic and current market trends, information on business expansion opportunities, and improved targeted marketing, all without increased consumer survey costs.

The different resources are explained in a short description with the different possibilities you get with this API, and some hypotheses for how you could maybe use the different data, which is possible to extract.

 

Resources

A list of resources bellow maps the API’s endpoint hierarchy. Find out more details on information pages made for each resource.

• Indexes
• Historical Comparison
• Correlations
• Share of Turnover
• Average Spend

 

Filters

Here you can see some more details about different filters (name of filter in API in parentheses).

• Week number (transaction_week) - Filter by week number.

• Month (transaction_month) - Filter by month.

• Quarter (transaction_quarter) - Filter by quarter.

• Year (transaction_year) - Filter by year.

• Merchant country (merchant_country_a3) - Filter by a country from where a merchant is from.

• Merchant region (merchant_region_code) - Filter by a region from where a merchant is from.

• Merchant municipality (merchant_municipality_code) - Filter by a municipality from where a merchant is from.

• Estimated residence country (estimated_residence_country_a3) - Filter by a country from where we estimate a consumer is from.

• Estimated residence region (estimated_residence_region_code) - Filter by a region from where we estimate a consumer is from.

• Estimated residence municipality (estimated_residence_municipality_code) - Filter by an municipality from where we estimate a consumer is from.

• Category (category_code) - Filter by a category.

  • The aggregated data consists of many transactions. These transactions are categorized based on the type of merchant where the transaction occurred. For example, if a merchant owns a grocery store, the transaction made in the store will belong under the Supermarkets category.

• Vertical (vertical) - Filter by a vertical.

  • The verticals are an abstraction level on top of the category filter.

• Online / Physical (online_physical) - Filter by Online or Physical.

  • The aggregated data consists of many transactions. These are categorized as those which took place online (ECOM) or physically in the store (POS).

• Business / Private (business_private) - Filter by Business or Private consumers.

  • The aggregated data consists of many transactions. Some transactions were made with credit cards owned by businesspeople, others by private persons. Filter out what's needed to narrow down your search.

• Domestic / International (domestic_international) - Filter by Domestic or International card spending.

  • The aggregated data consists of many transactions. If the credit card was issued in a country which matches the country where we estimate a merchant is from, we categorize such a transaction as Domestic. If there is a mismatch between these two values, the transaction is categorized as International.

• Issuer Country (issuer_country_a3) - Filter by cards issued in specific country.

• Regional Local (is_regional_local) - Narrow your search by looking at regional local or not regional local (same as non-local) transactions.

  • Regional local transactions correspond to the estimated residence region of a card matching the region of a merchant, and not regional local transactions are the case in which we estimate the cardholder to come from another region than the location of the merchant.

• Municipality Local (is_municipality_local) - Narrow your search by looking at municipality local or not municipality local transactions.

  • Municipality local transactions correspond to the estimated residence municipality of a card matching the municipality of a merchant, and not municipality local transactions are the case in which we estimate the cardholder to come from another municipality than the location of the merchant.

• Group By (group_by) - Specify how the response should be grouped.

  • This will make it possible for the client to decide how the response is grouped. See more in general

 

Important notes on the data

• We unfortunately don't have all merchants as customers, so these numbers serve only as indicators of the whole market trend. This is to be remembered throughout the dashboard.

• It's important to note that one cardholder may possess multiple cards, thus the number of cards doesn't necessarily reflect the number of consumers.

• Some weeks can be pay week one year and not the other year, which could lead to wrong conclusions on trends, so be aware of holidays, pay weeks, seasonality, incomplete periods etc.

• The area of residence of a card is only an estimate based on previous transaction patterns. Therefore, this should only be used as an indicator.

• The residence area of some cards can't be estimated if they have had too few transactions in the past 6 months, so only the estimable cards are accounted for in this analysis.

Go to API