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High Street Data Partnership

There are lots of silos of information about London’s High Streets and Town Centres. The aim of this partnership is to pool the resources of the London Boroughs, Business Improvement Districts, GLA and others to create a more joined up and effective approach to using and sharing High Street data.

Contact Julia Thomson for more information



What data is available now?

NOTE: if you can’t see the data that you are looking for then it may be that your Borough hasn’t signed the data sharing agreement yet. Contact the DataStore team for more information.

Mobility index – Feb 2020 to present

Anonymised and Aggregated data collected by Google has been provided to public authorities to inform their COVID-19 response. An index for each Borough against a baseline of Jan 2020 is provided for 6 common location types:

  • retail and recreation
  • grocery and pharmacy
  • parks
  • transit stations
  • workplaces
  • residential 

Footfall data – 1st July to 31st Oct 2020 (with context from July 2019)

Anonymised and Aggregated data by O2 has been purchased by the 24 Hour London team. The People Counts shows the number of people dwelling in each MSOA* area per hour, split by:

  • Resident – based on where the user has spent most of their evening and night time in the latest historical month available
  • Worker – based on where the user has spent most of their working hours predominantly based on February 2020 where available
  • Visitor (at least 30mins in location)

*MSOAs are roughly ward-sized areas. They vary in size across the ground, but contain around 10,000 residents.


Origin / Destination data – Oct 2020

Anonymised and Aggregated data by O2 has been purchased by the Strategic Coordination Group to understand how travel patterns have changed in the ‘new normal’. The counts by Borough (to/from other UK local authorities) are split by:

  • Commuters
  • Other

Spend data – 2018 to present

Card data from Mastercard has been has been purchased by the 24 Hour London team and aggregated to High Street / Town Centre level to show how spending patterns have changed over time.

  • total spend
  • number of transactions

Polling data

This dataset outlines the latest research on London public attitudes and behaviours in relation to the coronavirus outbreak. It includes the results of a tracker poll which asks respondents the same questions each week to monitor how responses change over time.


Update 12th Feb

Following feedback from users in the Boroughs, we’ve made the following changes and additions this week:

  1. Mastercard spend data
    • Updated to add December counts
    • High Streets and Town Centres tables now contain
      • Borough names (to filtering in Excel)
      • co-ordinates for each high street (so that they can be visualised in tools like PowerBI)
  2. Town Centre Boundaries – GIS file added
  3. Restrictions Timeseries – list of national and local restrictions, with start and end dates. Supplied as an experimental dataset to provide context for footfall and spend data timeseries
  4. Google Mobility by Borough – updates automatically every few days when Google publishes new data (NOTE: typically at least 4 days lag period)

Update 10th March

  1. A map showing the High Street Boundaries has been added https://data.london.gov.uk/dataset/gla-high-street-boundaries-map
  2. We have just added a ‘Mastercard high street excel explorer’ to help you explore the spend data by high streets – it has been designed to help those of you without much data analysis experience. It allows you to look at the spend across time and categories in one High Street, and also allows comparison to a reference High Street. I would encourage you all to download and take a look, and please give us feedback so we can fix any issues and/or make it even better. https://data.london.gov.uk/dataset/mastercard-high-street-excel-explorer
  3. Mastercard data for January is now available https://data.london.gov.uk/dataset/mastercard-retail-location-insights

Coming data releases

Camera counts

Researchers at the Alan Turing Institute have developed a system to count people-shaped objects from CCTV footage. NOTE: This does not involve facial recognition or tracking individuals over time or between locations. These counts of people will help Boroughs to identify pinch points and prioritise schemes to create more space for pedestrians if neccessary. Read more


TfL Station counts

TfL have taken data from their ticketing system (Oyster & Contactless Payment Card taps) to provide an indication of demand and how it has changed over time. Read more


StreetSpace schemes

Along with London’s boroughs TfL are creating more space for people to safely walk, cycle, scoot or wheel. Temporary cycle lanes and wider pavements are among the changes we’re making as part of Streetspace for London. Read more