Years
2022
,
2021
,
2020
,
2019
,
2018

This Project addresses the topic of product and service information and labeling and marketing communications. This includes customer access to accurate and adequate information on the positive and negative economic, environmental, and social impacts of the products and services they consume – both from a product and service labeling and a marketing communications perspective. 

Fair and responsible marketing communications, as well as access to information about the composition of products, and their proper use and disposal, can help customers to make informed choices. 

The disclosed data can provide information about an organization’s impacts related to product and service labeling and marketing communications, and how it manages these impacts.

Collective Research


The scope for this project (topic and sector) was suggested by WikiRate's community.

Data Discovery is a monthly session where the WikiRate community gathers new ideas for four research sprints. 

The result is a new data insight released weekly to show how companies are impacting people and the planet.

Everyone is welcome to bring ideas of topics and companies to research. Together we’ll:

  • Gain perspective on the community's research interests
  • Be inspired by last month's results in a series of infographics
  • Pick ideas for companies and topics to research in the next month

This crowd-research project will remain active on the WikiRate platform. Do you want to help us with this or another project? You can sign up as a volunteer researcher or join our next meeting. Do not hesitate to contact us!

Export the data


Use the filters to explore the data.

At the bottom of the page, there are links to download the current answer results in CSV or JSON format.

Clicking on those links will provide an export URL that will allow you to download answers with the current filters.

CSV downloads will allow a maximum of 100 answers per request.

To download more answers than that, you will need to alter the filters. Learn more on exporting the data here.




Import Template: csv