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Reduce friction when analyzing your workforce

Use predictive synthetic data to gain efficiency and scalability when analyzing global employee bases

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Map quantitative inputs

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Identify sub-segments

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Assess boosts coverage

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Implement new workflows

Rely on predictive data to reduce sample sizes

Significantly reduce your sample requirements when collecting data by applying predictive augmentation

Smart
Use reliable predictive intelligence that is trained and monitored on your data
Flexible
Works with any workflow, whether in-house, with agency or digital panels
Economic
Reduce sample sizes needed to run an quantitative survey
Powerful
Analyze segments once considered too hard or slow-to-reach
Technical validation

Boosting consumer research about smart speakers

Fairgen's synthetic niche dataset performed better than 2x across segments, questions, and answers — and it was trained on only 44% of the ground truth.

  • Can we trust synthetic data?
    Absolutely - and we can prove it. Bestfit's pioneer data augmentation solution can generate near-real synthetic results into niche segments. As long as based on a model trained on your general audience survey. Technical validation is a key part of every workflow in Bestfit.
  • Can anyone sign up?
    Yes. Currently, any organization can apply online by scheduling an introductory call with our team. Be among the first to deliver unprecedented granularity using reliable and explainable AI technology,
  • What is the impact of BestFIt on Insights teams?
    Insights teams can make better niche go-to-market decisions by having fast and affordable access to data that was before too hard, or impossible, to get. It provides insides teams with the ability to zoom in on sub-segments and gain more trust when reading these groups. ‍ Researchers can immediately expand coverage across niche markets, while gaining fast access do data and without the need of costly traditional data collection boosts. ‍ Access to once "impossible-to-reach" segments is an added value: by extrapolating results while maintaining high confidence levels, niche segments once considered too small, or too hard-to-reach for fieldwork boosts, can now be analyzed.
  • How is the technical validation process for BestFit?
    In short, you will run several parallel testing processes that will compare the efficiency of synthetic data versus real data. The primary method used by our clients is "Backtesting", using as a base existing datasets. By the end of it, our predictive technology's accuracy and coherence both on aggregated and granular results can be determined. ‍ The process is simple: you will provide a fraction of an existing dataset for Bestfit to be trained on, so we can mimic a situation where you have scarce data. Let's say 10% of it. The remaining of it will be used as the ground truth and Bestfit will generate a synthetic dataset that was trained on only 10% of it. We will then compare its reliability against samples of the "ground truth". ‍ We guarantee a reliable and coherent augmentation that will perform significantly better than what our models were trained on.
  • Can Bestfit handle any type of data?
    Yes. Bestfit is equipped to handle any quantitative (close-ended) data points that can be exported in a columnar format (single and multiple choice questions, rankings, NPS, continuous open-ended, ratings, and more). Bestfit automatically recognizes field types and conditional relationships between questions.
  • Can Bestfit augment qualitative questions?
    No. Bestfit's can augment only quantitative fields.
  • How is it different than reweighting?
    In a nutshell, Bestfit will reduce your niche segment's margin of error while classic reweighting techniques will not. When applying different weights for specific segments in a quantitative surveys there is no impact on confidence intervals for that group.

Interested in learning more?

We are looking forward to onboarding you into the world of augmented synthetic respondents.

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