Introducing our new voting intention methodology in Scotland

Since 2010, Ipsos’ approach to political polling for voting intention in Scotland had been based on a telephone quota sample using a mix of landline random digit dialling and mobile numbers. This approach worked well for many years, allowing us to accurately measure and understand public views of the political parties in Scotland, including at the most recent Scottish Parliament elections in 2021. We keep our methods under continual review, and are now introducing changes to our voting intention polling methodology, both for Great Britain and for Scotland specifically. For analysis on the reasons for these changes, see our fuller write-up.

We believe this is the right moment to transition to a new methodology and have carried out our latest voting intention polling on our online random probability KnowledgePanel©. The KnowledgePanel© was set up in the US in 1999 and in the UK in 2020, and is now present in another 7 European countries. It is based on probability principles, with addresses randomly selected from the Postcode Address File and invited to join the panel. Those who are digitally excluded are offered a tablet and restricted internet access free of charge to enable them to complete surveys online.

What are the benefits of a KnowledgePanel© approach?

A probability panel approach brings several benefits:

• Gold standard probability sampling approach minimises self-selection bias, only randomly selected households can join, and randomly selected individuals can complete a survey;
• Postal recruitment, alongside supplying tablets to those who are digitally excluded, ensures all households have a known and non-zero chance of being included, with design weights accounting for unequal probabilities of being selected (e.g. individuals in larger households have less of a chance of being invited to a survey);
• Rich panellist profiling;
• Collecting immediate post-election data on voting behaviour, mitigating against false recall;
• Collecting and processing complex data such as social grade (coded by professional coders), or voting eligibility information.

Voting intention on the KnowledgePanel

In addition to this change of mode, we have made further changes to our methods in Scotland to improve our estimates:

1. Reform UK. Up to and including the 2024 General Election, our General Election and Scottish Parliament constituency voting intention question only prompted for the Conservatives, Labour, Liberal Democrats and SNP in Scotland, with other smaller parties not prompted. Since then, though, given the 2024 election results, the changes since then and our analysis of the polls performance, we are now prompting Reform UK alongside other major parties. We are also now prompting Reform UK on our Scottish Parliament regional list voting intention question, alongside the parties already prompted for previously (Conservatives, Scottish Labour, Liberal Democrats, SNP and Scottish Green Party).
2. Past vote. Probability samples do not use quotas in the same way that opt-in surveys do. Instead, invited samples are usually ‘stratified’, meaning the sample is randomly selected to take part, but controls are imposed to ensure it is representative on key characteristics. Being able to collect voting information the day after the General Election means we are able to control the composition of our sample through past vote collected very near the time, ensuring it is balanced in terms of 2024 vote, but mitigating against issues related to false recall.
3. Weighting scheme. We have updated our longstanding weighting scheme which we have developed over years of conducting political research in Scotland. In addition to our existing approach of weighting by age and gender, Scottish Parliament region, qualifications, work status and work sector, social grade, we are now also weighting on area deprivation, ethnicity, number of cars in household and digital and print newspaper readership, have removed weights on tenure and country of birth, and have also updated sources used for some of the other targets (such as public sector workers).

Overall, we believe our KnowledgePanel is based on robust methodological principles, and the improvements made since the 2024 election help reduce biases we saw at the time. It is still the case that all surveys are subject to sources of error, and results should be interpreted in the round along with other sources of data. As always, we'll continue to review our new approach, and make more adjustments if necessary as we conduct more analysis.