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Our technology reaches across 140+ industries to give you the scale of a panel combined with the depth of an expert network.



  • Cryptocurrency specialists advising on hedge fund projects 
  • Advertising professionals overseeing brand spend
  • Reddit users that visit Reddit for NSFW content
  • IT decision-makers evaluating cloud software services

Our RIM weighting analysis

RIM weighting is one of the many quantitative research tools we use to create your custom research strategy. 

Sometimes in B2B research, a very tight deadline or budget prevents you from using a respondent pool that’s a true 1:1 representation of your target population. In these circumstances, the expert use of RIM weighting becomes crucial to ensuring overall data quality. It’s also a very useful way to extrapolate a survey sample over a larger population.

As your B2B research partner, NewtonX will help determine the most important audience representation variables, so we can deploy RIM weighting where it’s most useful. When your surveys are complete, the RIM weighting calculation is used as part of your data analysis and synthesis process. With known biases corrected, your insights and recommendations are all highly relevant to your target audiences.

Strategy & Planning

  • Research strategy design
  • Screener design 
  • Interview guide questions
  • Survey questionnaire design: survey draft creation
  • Custom survey styling


  • Survey recruitment
  • Survey programming, coding, and hosting
  • Survey test (QA)
  • Survey fielding
  • Data consolidation & cleaning
  • Raw data extract

Data Analysis

  • Insight synthesis & analysis
  • RIM weighting (Random Iterative Method)
  • Crosstab analysis
  • Conjoint analysis


  • Automated charting
  • Manual charting
  • Top-line reports
  • High-level report or presentation
  • Extended full report or presentation draft
  • Key insights
  • Hypothesis testing
  • White labeling

What is RIM weighting?

brand price trade off research

What are the benefits of RIM weighting?

RIM offers several benefits in survey research and data analysis. These advantages make it a valuable technique for ensuring that survey results are representative and reliable:

Improved Representativeness

RIM weighting helps align the survey sample with the known population characteristics. By assigning appropriate weights to individual responses, it ensures that the survey data accurately reflects the demographics of the broader population. This leads to more representative and generalizable findings.

Reduced Non-Response Bias

In surveys, some groups of individuals may be less likely to respond than others, potentially introducing non-response bias. RIM weighting can mitigate this bias by giving higher weights to respondents from underrepresented groups, thus compensating for their lower response rates.

Enhanced Accuracy

By accounting for differences in demographics and other relevant variables, RIM weighting minimizes the risk of skewed results. This improved accuracy allows organizations to make data-driven decisions with greater confidence.

Better Subgroup Analysis

RIM weighting enables researchers to conduct more reliable subgroup analyses. Whether studying specific age groups, gender, or other demographics, this method ensures that the sample accurately represents each subgroup, leading to more meaningful insights.

Survey Data Harmonization

In cases where survey data is collected from multiple sources or at different time points, RIM weighting can harmonize and standardize the data to create a unified dataset for analysis. This is particularly useful for longitudinal studies or when merging data from various sources.

Informed Decision-Making

Organizations and policymakers rely on accurate survey data to make informed decisions. RIM weighting enhances the credibility of survey results, increasing the utility of research findings for decision-makers.

Valid Comparative Analysis

When conducting comparative analyses, such as assessing changes over time or differences between regions, RIM weighting ensures that the comparisons are valid and not distorted by sample imbalances.

Survey Efficiency

RIM weighting can be more cost-effective than conducting larger, more complex surveys to achieve representativeness. It allows researchers to work with existing data while still obtaining reliable results.

How does RIM weighting work?

research strategy

Good vs Bad RIM Weighting Efficiency

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Take it from the world’s leading companies.

NewtonX’s platform gives us continued confidence that we’re sourcing the highest quality data to drive critical business decisions.

Jason Talwar
Insights Executive with 15+ years of experience (Salesforce, Tableau, Microsoft)

I was really excited when we found NewtonX. Their Custom Recruiting has genuinely been a game changer for us in terms of data quality. Not only do I have much greater trust in the data, but the variation in the data means I can more easily provide actionable direction for our product and marketing teams without finding myself rationalizing away bad data.

Matt Harris Senior Customer Research & Insights Manager

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