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The London Borough of Newham commissioned M·E·L Research to deliver a borough-wide residents’ survey to understand how people living in the borough perceive their local area, the services they receive, and the Council itself. The research was designed to provide robust evidence to support strategic decision-making, service improvement and communications planning.

Newham is one of London’s most diverse boroughs, with significant variation between neighbourhoods and demographic groups. The Council required reliable and representative insight that could capture the views of this diverse population and allow meaningful comparisons between different communities within the borough.

The survey aimed to explore several key areas:

A key requirement for the study was to understand how views varied geographically and demographically, enabling the Council to identify where experiences differed across neighbourhoods or resident groups. The research also aimed to benchmark residents’ views against wider UK sentiment where possible and to provide indicative comparisons with previous iterations of the survey.

Given the complexity and diversity of the borough, the Council required a robust sampling approach that could deliver representative insight while ensuring sufficient coverage across local areas and demographic groups.

M·E·L Research designed and delivered a large-scale quantitative survey using a face-to-face interviewing methodology to maximise representativeness and data quality.

Face-to-face interviewing was selected because it provides strong control over the sample composition and supports high engagement with respondents, allowing a broad range of topics to be explored within a single survey interview.

Face-to-face survey with residents

To ensure the sample reflected the borough’s population profile, quotas were applied at both ward and borough level:

For analysis and reporting, the data was organised geographically by Community Neighbourhood Areas (CNAs). These are locally recognised neighbourhood groupings made up of multiple COAs, enabling robust geographic analysis while maintaining a statistically controlled sample design.

Data weighting and statistical analysis

Although quotas ensured a diverse sample, data weighting was applied to the final dataset to ensure the results were fully representative of the borough population.

Weighting variables included:

The final sample of 1,523 residents delivered a maximum confidence interval of ±2.51 percentage points at the 95% confidence level for borough-level results.

Sub-group analysis was undertaken to compare views across different demographic groups and neighbourhoods. Statistical testing was used to identify significant differences between sub-groups and the borough average, ensuring that reported variations reflected genuine differences rather than sampling variation.

The research also included key driver analysis, examining the relationship between individual factors and overall satisfaction. This allowed the Council to identify which issues most strongly influenced residents’ perceptions of their local area and the Council’s performance.

Where relevant, results were also compared with Local Government Association (LGA) benchmark data, providing broader context for residents’ views.

M·E·L Research conducted detailed quantitative analysis of the survey data, including:

The results were presented in a comprehensive analytical report and presentation deck, combining data visualisation, interpretation and structured insight to support decision-making across the Council.

The outputs provided the Council with:

The research provided the Council with a detailed evidence base to inform service planning, policy development and engagement strategies across the borough.

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