Consumer Insights Tracker: Technical Report 2026

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Introduction

The Consumer Insights Tracker is the Food Standards Agency’s (FSA) tracking survey that monitors changes in consumers’ behaviour and attitudes in relation to food. Fieldwork is conducted on a monthly basis.

This technical report presents methodological details on the Consumer Insights Tracker; including how data is collected and analysed. It also provides information on the strengths and limitations of the methodology, to support interpretation of the data.

This technical report reflects the methodology up to the end of March 2026. At the time of publication, the sampling and weighting approach is under review, with a view to introducing ethnicity. This report will be updated annually to reflect key changes to the survey methodology. Please refer to the latest quarterly report for the most up to date high level overview of the method (including quotas and weights).

Overview of methodology

The Consumer Insights Tracker is conducted using a bespoke online survey approach, administered to members of the YouGov Plc UK panel. Fieldwork takes place monthly, typically over the first weekend of the month and lasts around 3 days in total. Approximately 2000 adults (aged 16 years and older) across England, Wales and Northern Ireland participate in the survey each month. This includes a pilot of around 50 responses for each wave. Respondents are excluded from taking the survey again for 6 months. The questionnaire completion time is approximately 10 minutes. The main body of questions remains broadly consistent for each wave, although there are ad hoc topics that are included at varying frequencies. Respondents are provided an incentive, in the form of points credited to their YouGov account, upon completion of the survey.

Findings are summarised by YouGov into a report and shared with the FSA. The FSA publishes findings on the Consumer Insights Tracker webpage and makes data tables available on the FSA’s data catalogue.

History of the Consumer Insights Tracker

In April 2020 the FSA established a new monthly survey (the COVID-19 Tracker) to monitor consumers’ attitudes and behaviour during the COVID-19 pandemic. This survey was designed to provide more regular and timely insights than the FSA’s official statistic survey, Food and You 2. In April 2022 the survey was renamed the Consumer Insights Tracker.

YouGov were appointed as the supplier of the Consumer Insights Tracker from July 2023. At this time, the FSA also took the opportunity to review the survey design and methodology for the Consumer Insights Tracker and the survey was relaunched in August 2023, following an independent review of the survey’s methods and content.

Due to a change in supplier and changes made to the survey design by the FSA, data collected from the two suppliers pre-and-post July 2023 should not be directly compared. More detail on the changes to the methodology can be found in the 2024 Technical Report whilst further details about the survey pre-July 2023 are available via a separate webpage.

In April 2025, several edits were made to the questionnaire to reduce duplication with Food and You 2, including:

• The removal of the food supply chain topic (Q13 and Q14)

• The removal of the questions related to confidence in the FSA to perform various functions (Q15)

• The removal of Q6 and Q8M (related to money saving behaviours), replacing them with a single redesigned question (Q6_NEW). Further revisions to the new question on behaviours to save money (Q6_NEW) were then made in May 2025. The changes included amending the options to be in line with the previous Q8M.

• The addition of two new questions on whether respondents recalled hearing anything about certain food safety topics (NEWC1 and NEWC2)

• Various changes to the response options for the consumer concerns question (Q12) were made including:

  • The removal of: ‘The healthiness of people’s diets in general’, ‘The safety of food produced in the UK’, ‘The safety of food imported from outside the UK’, ‘The quality of food produced in the UK’, ‘The quality of food imported from outside the UK’, ‘The information on food labels being accurate (e.g. ingredients, nutritional information, country of origin)’.

  • The addition of: ‘People being able to eat a healthy diet’, ‘Food waste in the food chain’, ‘Food fraud or crime (e.g. food not being what the label says it is)’, ‘Food poisoning (e.g. Salmonella and E. Coli)’, ‘The quality of food’, ‘Food hygiene when eating out or ordering takeaways’, ‘The amount of food packaging’, ‘The use of pesticides in food production’, ‘The amount of salt, sugar, fat, or calories in food’, and ‘Food allergen information (e.g. availability and accuracy)’.

  • Wording amends as follows: ‘Food availability/food shortages’ changed to ‘Food shortages’, ‘The sustainability of food and food production’ changed to ‘Food being produced sustainably’, ‘Ingredients and additives in food’ changed to ‘The use of additives in food (e.g. preservatives and colouring)’ and ‘Ultra-processed, or over-processing of food’ changed to ‘Ultra-processed food’.

Questionnaire design

Each wave of the survey is designed through collaboration between the FSA project team and YouGov. The survey asks respondents about their attitudes and behaviours in relation to a range of food-related topics that are of strategic interest to the FSA. Up to March 2026 this included the core topics of consumer concerns about food-related issues, food safety topics, trust in the FSA and attitudes and behaviours related to food affordability. Demographic information is already held by YouGov, so does not need to be collected as part of the questionnaire. An example of the survey questionnaire (from March 2026) is available in Annex 1^[1].

The survey is designed to be flexible, so in addition to covering these core topics, it includes other re-occurring topics. For example, in March 2026 additional questions were added on precision breeding. A full list of all the additional questions added over the past year (April 25-March 26) can be found in Annex 2. The survey is cross-sectional and offers a snapshot in time, with the findings for each wave reflecting the context at the time. Thus, it is important to reflect on the wider context when interpreting the findings for each wave.

Survey questions are written using plain English and neutral phrasing to reduce bias and encourage participation. The survey is structured in a way that flows logically, with similar topics grouped together, to reduce respondent fatigue. Questions that are sensitive in nature, which may incite an order effect^[2], or which relate to respondent demographics, are placed at the end of the survey where possible. Questions with multiple response options have their response options randomised so that the order these are presented does not affect how respondents answer. The same is done with the randomisation of questions that form question grids^[3]. Open-ended responses are reviewed to identify any nonsensical or low-quality answers, and attention-check questions are included to ensure respondents are actively engaged rather than providing random or disengaged responses.

Each month, the questionnaire is reviewed by the FSA project team. Any new questions or amendments to existing questions are developed by the FSA project team in collaboration with stakeholders at the FSA. Where possible, existing and cognitively tested questions (for example, from Food and You 2) are used to help design new survey questions. Once agreed they are sent to YouGov where they are reviewed by at least two experienced researchers, including at least one senior member responsible for sign-off. See the Quality Assurance section for further information about quality assurance in place for the survey design.

Pilot study

The online survey is piloted with approximately 50 respondents each month, before main fieldwork commences. This is to assess the respondent’s understanding of the questions, the survey logic, programming and the overall length of the survey. Once the pilot is completed any amends to the survey are made before main stage fieldwork.

Sampling

Sampling approach

All respondents who take part in the survey are drawn from the YouGov panel of over 400,000 active panel members who live in the UK. YouGov maintains an engaged panel of respondents who have specifically opted-in to participate in online research activities. This includes actively recruiting hard-to-reach respondents, such as younger people and those from ethnic minorities, via a network of partners with access to a wide range of online sources that cater to these groups. These partners have specific experience in recruiting these audiences for online activities. The sources include search engine optimization (SEO), affiliate networks, niche websites, and growth hacking techniques such as panellist refer-a-friend campaigns and social networks. All recruitment sources, for hard-to-reach audiences or anyone else, are monitored to ensure that respondents are always profiled, responsive and engaged in the survey experience.

The YouGov panel is large enough to select nationally representative samples that reflect the actual breakdown of the population on the key demographics of age, gender, region, social grade and education level.

For the Consumer Insights Tracker, a nationally representative sample of people in England, Wales and Northern Ireland was constructed for sampling and weighting. To qualify for the survey, respondents needed to meet two criteria:

• Be aged 16 years or older

• Live in England, Wales or Northern Ireland^[4]

Each month, eligible panellists (see further details below on sampling) are sent an email inviting them to take part. Rather than being invited to a specific survey, respondents are invited via ‘turbo sampling’. Invitations are sent when the system identifies people as a potential fit for a survey based on the current fieldwork requirements. The system then allocates respondents to a survey, taking into account quotas, priorities, and overall sample composition.

Only panellists who are invited can participate in the survey, and individuals can only respond once each time they are invited. Participants are given a brief introduction to the survey before responding. They are not made aware that the survey is being conducted on behalf of the FSA.

The sampling approach used for the Consumer Insights Tracker is quota sampling, with quotas taken from the 2021 Census. Quota sampling is a non-probability sampling method that involves dividing the population into sub-groups. The relative proportion of each sub-group as a percentage of the total sample is based on known characteristics of the overall population. Responses are collected until the ‘quota’ for each sub-group is reached. This is a standard sampling approach used in online panel surveys to capture a representative population on certain variables. The sample for the Consumer Insights Tracker is structured to be representative of the England, Wales and Northern Ireland population by the following variables:

• Age

• Gender

• Social grade

• Region

• Education level

At the time of writing, the sampling and weighting approach is under review, with a view to introducing ethnicity.

A sample boost is also applied in Northern Ireland (to achieve 100 respondents), to improve the representation of this group and to enable rudimentary demographic comparisons between countries. Weighting is later applied to ensure that sample sizes are proportionate to the country population value (weighting is further explained in the section below).

An exclusion criterion is also applied to the sample, which prevents any respondents from participating in the survey if they have done so in any of the six previous waves.

Sample size and weighting

The overall sample size for each wave is approximately 2,000. This is a pragmatic choice that provides an affordable, monthly survey that can be recruited over a few days, with reasonable numbers of respondents across key sub-groups of interest.

Weights are applied to the data to make it more representative of the population of England, Wales and Northern Ireland. Weighting involves adjusting the influence of individual respondents in a dataset to ensure that the results more accurately reflect the demographics of the target population. Data from the 2021 England and Wales Census from the Office for National Statistics (ONS) and the 2021 Northern Ireland Census from the Northern Ireland Statistics and Research Agency is used to do this, with weighting applied according to gender, age, education level, region, and social grade. Weighting on these variables is common practice across similar surveys of this nature, as it ensures that the data is representative of the target population, while also maximising weighting efficiency.

Random Iterative Method (RIM) weighting is used. RIM is used when there are a number of different standard weights that all need to be applied together. This weighting method calculates weights for each individual respondent from the targets and achieved sample sizes for all the quota variables. RIM weighting is an iterative process, whereby it recalculates the weights several times until the required degree of accuracy is reached. All weights are capped at six, and a YouGov internal weighting report is produced for each wave. If the weighting efficiency in the weight report is below 90% further fieldwork would be considered to increase the representation of certain groups and improve efficiency. However, due to the rigorous sampling approach used, required weighting adjustments are minimal and additional fieldwork is rarely required. The advantage of using a RIM weighting approach is that the weighting can include a greater number of variables, and it is not necessary to have targets for all the interlaced variables.

Weighting is applied at the end of the data processing phase on cleaned data (see the Quality Assurance section for further details on data cleaning).

The data is first weighted at a country level, for example, the England sample is weighted to be representative of people living in England. When the countries are combined into a single dataset, each country is weighted to reflect its share of the population (England 92%; Wales 5% and Northern Ireland 3%).

The table below provides the unweighted and weighted bases. The unweighted base shows the number of completed surveys and the weighted base shows the adjustments that have been made to correct for any sample bias. Every participant is given an overall weight based on the weighting of the demographic groups that they fall into. This is then used to ensure that different groups have proportionate influence on the results, in line with their representation in the wider population.

Data analysis

Data analysis for each question is conducted at the overall sample level, as well as across key demographic groups, using the weighted data. Analysis of changes across waves, as well as differences between demographic groups, are only reported when differences meet the criteria described below (see ‘Reporting conventions’).

Index of Multiple Deprivation (IMD) is one of the demographic factors calculated and reported for England, Wales and Northern Ireland. IMD is calculated using country-specific metrics, and then combined to give an overall measure of relative deprivation within a respondent’s specific region.

• England: The IMD ranks each English LSOA from 1 (most deprived) to 32,844 (least deprived).

• Wales: The Welsh equivalent (WIMD) ranks each Welsh LSOA from 1 (most deprived) to 1,909 (least deprived).

• Northern Ireland: The NI equivalent ranks each OA from 1 (most deprived) to 5,022 (least deprived).

Qualitative data (e.g., open ended responses) is analysed thematically. The FSA’s typical process includes developing initial coding frameworks from the raw data. Two researchers code a subset of responses, meeting to discuss problematic or missing codes. Following this, the coding framework is refined and the remaining responses coded. A subset (approximately 10% of responses) is coded by a second researcher to assess inter-coder reliability. Once coding is complete, code frequencies are reviewed, and emerging themes and key findings are identified.

Statistical reliability and confidence intervals

Confidence intervals do not strictly apply to quota samples. This is because confidence intervals rely on statistical theory which assumes a known probability of selection, which is not the case with quota sampling.

The table below offers a useful rule of thumb for assessing the statistical significance of the figures in the final dataset, but it should be interpreted with the understanding that these intervals are not exact measures of precision for quota samples. Since the data is generated from a quota sample, the actual confidence intervals are unknown.

Reporting conventions

The FSA project team work closely with YouGov each quarter to identify results of strategic importance for the FSA. Toplines typically focus on significant changes over time, an overview of each of the core topics from the Consumer Insights Tracker (e.g. food affordability, consumer concerns) and the rotating additional topics that featured that quarter.

The Consumer Insights Tracker uses t-tests to assess differences over time and between groups. However, there are known limitations when using t-tests on data collected using quota sampling:

• T-tests assume that samples are randomly selected from the population. In quota sampling, this assumption is violated because participants are selected based on specific characteristics to meet quotas. This non-random selection can introduce bias and affect the validity of the t-test results.

• When multiple comparisons are made, the probability of finding at least one statistically significant result by chance increases. In quota sampling, analysing multiple subgroups can inflate the Type I error rate (i.e. increase the likelihood of false positives).

Therefore, due to the quota sampling methodology used, these tests cannot be interpreted strictly. Users should be cautious when interpreting the results, considering the limitations and potential biases introduced by quota sampling.

Despite these limitations, these tests can help to highlight where there is the greatest evidence of a shift in behaviour or attitudes. The Consumer Insights Tracker only reports differences over time and between groups where the p value is <0.05. Results meeting this criterion are reported using arrows (↑ / ↓) on graphs.

The data for this project and other research that the FSA undertakes can be found on the FSA’s website, and in particular via the FSA data catalogue.

Quality assurance

Participant verification and engagement

Several checks are applied to ensure the quality of survey data. Checks for participant identification and authentication are conducted during panel registration, and through an initial welcome survey. These checks are designed to ensure that the survey is being completed by real respondents (i.e., not by chatbots), the demographic information provided is accurate, and the same individual cannot complete the survey multiple times. Some of these checks include:

• IP checks, including IP blacklists – checks on respondent’s IP addresses to ensure they have not been blacklisted from completing surveys.

• Digital fingerprinting – information collected about the software and hardware of a device for the purpose of identification.

• Double keying on panel registration and login – used to check for respondent errors in data entry.

• Email address verification, and testing for uniqueness – prevents respondents from signing up to the YouGov panel using multiple accounts.

• Contact detail de-duplication – prevents respondents from signing up to the panel using the same contact details multiple times.

• Country validation – checks to ensure that respondents on the UK panel live in the UK.

• Location verification (e.g. post code) – crosschecks respondents against other location metrics to ensure that respondents are not signing up to the panel using erroneous postcodes.

• Machine Learning based cookie checks, and checks against Cookie blacklists – uses browser-based cookies (e.g. to prevent respondents from completing the same survey multiple times).

• Email confirmation and activation code – checks to ensure that respondents are using a valid email address.

• Data validation checks – checking for inconsistencies that indicate inauthentic behaviour or indications that responses have been written by large language models or AI chatbots. The survey also includes attention checks with those failing them removed from the data.

Panel composition

The YouGov panel is recruited through organic growth, targeted advertising, and recruitment strategies aimed at underrepresented demographic groups, including younger individuals and those from ethnic minorities. YouGov actively recruit these ‘seldom heard’ respondents via a network of partners with access to diverse sources.

YouGov regularly review the composition of their panel against publicly available UK population benchmarks. While the panel will not mirror the population exactly, their processes allow YouGov to draw large, robust samples that are fully representative through carefully designed sampling and weighting.

Data cleaning and quality checks

As mentioned above, following the survey closing, those who fail the attention check questions or have answered under a certain time period^[5] are removed from the data. Additionally, inconsistent, incoherent or incomplete responses are removed from the dataset in a process of data cleaning.

The cleaned data is used to produce data tables. The YouGov team carry out a thorough review of the data tables to check for accuracy. This includes:

• Checking that all questions from the survey have been included.

• Checking that the total sample size matches the target sample.

• Checking that base sizes and text for each question are correct.

• Checking that percentages for each question sum to 100% (if single code), and that ‘net’ figures have been calculated correctly.

• Checking that crossbreaks have been calculated correctly.

• Checking that the data has been weighted correctly.

• Comparing data with previous waves and investigating the reasons behind any large shifts in results to ensure they are not the result of data errors.

When outputs are provided to the FSA, the FSA project team also conduct quality assurance checks before data is published; including spot checks against multiple data sources (for example, previous publications and data tables) and significance testing to ensure the same results can be found using alternative methods. Any discrepancies are highlighted and discussed with YouGov. Prior to publication, reports are reviewed and signed-off by at least two researchers at the FSA.

Survey design

The survey is designed to ensure that data collected is robust, reliable, and fit for purpose. Where appropriate, questions are informed by other existing studies.

Prior to fieldwork, the survey undergoes a thorough review process. This includes:

• Ensuring that any new questions align with the research objectives.

• Checking question wording to minimise bias, leading language, or ambiguity.

• Reviewing question order and routing logic to ensure a coherent respondent journey and to reduce order effects.

• Testing response options to ensure they are exhaustive, mutually exclusive, and appropriate for analysis.

• Senior sign-off of questions from both the FSA and YouGov teams.

The survey is piloted (to 50 respondents) prior to launch to identify any issues with question interpretation, technical functionality, or completion time, and any necessary amendments are made before full fieldwork begins.

Reporting

Survey findings are reported in a clear, accurate, and transparent way to ensure they are accessible and appropriately interpreted. Reporting includes a quarterly slide deck and an annual written report.

Reporting is typically produced through an iterative drafting process, incorporating feedback from the FSA at each stage.

At each draft stage, the report is checked to ensure:

• All reported figures, percentages, and charts accurately match the final weighted data tables.

• Base sizes are correct and clearly labelled for each question and subgroup.

• Statistical significance testing has been applied consistently and reported correctly where used.

• Any limitations, caveats, or methodological considerations are clearly explained.

• Terminology, definitions, and question wording are used consistently throughout the report.

• Trends, changes over time or other notable findings are appropriately and proportionately described for users who may not be familiar with the data

Final reports are reviewed and signed off by at least two researchers (at both YouGov and the FSA) to ensure they meet required quality and governance standards before being published or shared externally.

Use of artificial intelligence

AI (Microsoft Copilot, with enterprise encryption) is used to support aspects of reporting, including content review and refinement. For example, it is used to help identify errors and typos in reports. It is also used to help when designing new question wording, including suggestions to improve clarity and brevity. Any AI suggestions are reviewed by a human for accuracy. AI can support thematic analysis by helping to review open-ended responses and identify emerging themes. However, it is not currently used this way for the Consumer Insights Tracker.

Ethics

YouGov takes a number of steps to ensure the highest ethical standards are upheld as part of this survey in line with the GSR ethical assurances for social research. This covers four main items:

1. Informed consent and right to withdraw: Before beginning the survey, respondents are presented with an introduction page explaining the survey topic. This ensures that all participants understand the nature of the survey at the outset and enables anyone who does not wish to continue to voluntarily exit at this point. All panellists have double opted into responding to online surveys. This means that they have agreed to take surveys with YouGov and have then agreed to participate in the Consumer Insights Tracker, when invited. Respondents are able to withdraw from the panel generally at any time and also have the option to withdraw from the survey whilst it is in progress.

2. Accessibility: YouGov takes steps to aid participation through its systems and capabilities by servicing all devices and channels in an accessible way. This includes optimising surveys to be conducted on a range of devices, configuring the way text and image-based questions are displayed to respondents to avoid any accessibility-related issues (e.g. through the use of screen reader support) and using plain, simple language.

3. Avoiding personal harm: YouGov has a duty of care to panellists and steps are taken to avoid causing personal harm. Examples are signposting sensitive topics at the beginning of the survey (if relevant, depending on topics), providing links to trusted support organisations respondents can contact if required, and providing the option to skip or ‘prefer not to say’ to questions relating to sensitive information and/or special category data under the GDPR.

4. Safeguarding personal data: All personal data collected on respondents is anonymised. The data YouGov shares with the FSA is completely anonymous, non-identifiable and only reported at an aggregate level. GDPR principles and other applicable local privacy and security obligations are adhered to by both YouGov and the FSA when conducting this research.

Strengths and limitations

Strengths of approach

The FSA’s project team carefully weigh up the strengths and limitations of all methodologies before deciding the most appropriate methodology for an individual piece of research.

The approach for the Consumer Insights Tracker offers several strengths including:

• Reliable, representative tracking: A large, nationwide online panel, enables data to be gathered that is representative of the population aged 16 years and over in England, Wales and Northern Ireland on specific variables, to track changes over time and to collect a wide range of demographic information. A boosted sample of 100 is collected in Northern Ireland which allows for the comparison of each country across England, Wales and Northern Ireland.

• Speed of delivery: An online panel approach means that the survey can be administered to participants quickly, particularly in comparison to other modes such as telephone or face-to-face methods. As participants are pre-screened for eligibility for the panel, this means that surveys can be administered quicker than methods that require recruitment and screening processes. In addition, online surveys can be completed at any time of day (according to respondent preference).

• Cost effectiveness: The combination of speedier delivery and a less resource-intensive approach by eliminating the need for human interviewers contribute to online surveys being significantly more cost effective than other survey methodologies. In addition, because YouGov already holds many of the key demographic indicators on panellists, this saves questionnaire space (and therefore survey cost) by not needing to ask these questions.

• Flexibility in survey design: Online surveys provide greater flexibility in terms of the types of questions which can be included. Questions involving images, videos or audio clips can be included, which is not always possible, for example when using a telephone methodology.

• Reduction in certain forms of bias: As online surveys do not require an interviewer to be present, they can help to reduce the effects of social desirability bias among respondents. Sampling bias can also be reduced online, compared to face-to-face approaches, where the interviewer may be more restricted by location when conducting the survey, although other forms of sampling bias may be present in online surveys (see limitations below). Additionally, using a bespoke survey approach means respondents are only asked the questions in the Consumer Insights Tracker, reducing certain types of bias associated with approaches where respondents are asked to complete multiple surveys.

• Exclusion period: Participants are excluded from taking the survey again for 6 months. Having a long exclusion period means they are less likely to become familiar with survey questions, or to experience survey fatigue. It also allows up to 6 months of data to be combined, to provide a large base size for further analysis opportunities without the risk of duplicated participants.

Limitations of approach

Some of the limitations of the approach include:

• Opt-in sampling bias: Panellists on opt-in panels can be more engaged in current issues, which means they are more motivated to opt-into panel surveys. This means precise measures for some attitudes and behaviours reflecting the total population can be difficult to obtain. It is therefore beneficial to regularly validate and compare the results of online opt-in surveys using other robust methodologies such as random probability surveys. The FSA often use multiple methodologies to understand the complexities of a single topic.

• Representation: Some groups are underrepresented in online opt-in panels. This is particularly true of those who do not have internet access (who are excluded) or those who are not comfortable going online, who also tend to be older and in lower socio-economic groups. Additionally, young working-class men are difficult to reach across many methodologies, including opt-in online panels. These issues can be remedied in part through quotas and weighting, if the groups being underrepresented are identified. Other methodologies, such as postal or face-to-face surveys, can be more suitable when capturing the views of those who are digitally excluded, but these methodologies typically take longer to deliver and are more expensive.

• Generalisability: Due to quota sampling approach and the limitations mentioned above (representation, bias), the findings from the Consumer Insights Tracker are not generalisable to the entire population. Findings should be treated as indicative, and any demographic differences should not be interpreted as applying to all members of those groups in the wider population. This means that while the tracker provides valuable insights, the results should be interpreted within this context and supplemented with additional research methods to ensure a comprehensive understanding.

• Topics and complexity: Online surveys, and in general surveys that are self-administered, are useful for an overall read on issues or for exploring topics that are well understood by respondents. However, it becomes more difficult to explore in depth, complex issues where respondents do not have a good understanding of the topic. Such topics can benefit from an interviewer who can provide explanations or are better explored through qualitative research.

• Detailed demographic analysis: Due to sample size, it is not always possible to review detailed demographic cross-breaks, such as region or granular details of income with the Consumer Insights Tracker which has a sample of approximately 2,000 per month. This only allows for analysis by broad demographic characteristics such as gender, age group, income group, or the presence of children in the household. However, by combining six months of data, a sample size of 12,000 is created. This greater sample size increases the number of individuals of each demographic cross-break, thus allowing the comparison of those that do not meet the required number in the monthly figures.

How the Consumer Insights Tracker differs from Food and You 2

Alongside the Consumer Insights Tracker, the FSA collects evidence on consumers’ attitudes and behaviours through its Official Statistics survey, Food and You 2. While both surveys aim to understand consumer perceptions, attitudes and behaviours in relation to food, they are designed for different purposes and cover some different topic areas. Food and You 2 provides more methodologically robust evidence and is therefore better suited for producing population-level estimates or carrying out in-depth sub-group analysis. Whereas the Consumer Insights Tracker is designed to provide a regular ‘temperature check’ on key issues and allows the FSA to gather timely evidence on new or emerging issues. The table below provides further detail on the differences between these two consumer surveys.

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1. Questionnaires from other months are published alongside the quarterly reports or are available on request from the FSA Analytics Unit.

2. An order effect occurs when a question earlier in a survey influences respondents’ answers to later questions in the survey.

3. Question grids are tabular questions that asks respondents to evaluate one or more row items using the same set of column choices.

4. The sample does not include respondents from Scotland. The FSA is the independent government department working to protect public health and consumers’ wider interests in relation to food in England, Wales and Northern Ireland. Food Standards Scotland is the independent public body with responsibility for food policy and implementation in Scotland. Food Standards Scotland conduct their own consumer monitoring.

5. Those with a completion time of 1/3 under the median are removed from the final survey sample.