Access High-Quality Data with Hanover

You make important decisions based on data and you need to be able to rely on it. However, increases in bot responses and junk data means you risk skewed insights.

Hanover takes multiple steps to ensure any insights we provide are based on clean, accurate data. Our commitment to data quality means you get results you can rely on, every time.

1 + Million

Surveys Deployed Annually

How do we do it?

Our approach blends hands-on expertise with AI technology to ensure a thorough data cleaning process without sacrificing timeliness or urgency. This includes our proprietary data validation tool that evaluates data for poor quality and fraudulent results to ensure the insights you receive are accurate and actionable.

Hanover’s commitment to data quality

We work with top providers in the field to source respondents and actively monitor the quality of results to ensure data is credible.

If we don’t think we can provide an adequate sample size for your project, we will work with you to adjust the scope and design a new approach — one that will produce quality data that fully answers your questions.

Make Decisions Based on Verified, Credible Data

How Hanover ensures data quality

Design

Method

Research methods are developed by subject matter experts to ensure accurate and actionable results.

Scope

The research scope is kept narrow to gather sufficient data to answer the key research objectives and follow industry best practices to reduce drop-off, fatigue, and response bias.

Collection

Sample Size

Sampling plans are created so that respondents match the client’s target audience in terms of characteristics and overall distribution.

Language

Questions are translated into the native language of respondents to ensure accurate responses.

Quality Control

Respondent Validity

Each respondent is given a data quality score that evaluates respondent characteristics (e.g., age, seniority level) and those who fall below the threshold are removed.

Data Quality

We include an additional layer of security via a proprietary tool to detect poor quality or fraudulent responses by looking across a wide range of quality measures.

Data Validation

Our experts personally review the data — particularly open-ended question data — to flag nonsensical and out-of-context responses and to consider additional logic traps that were not programmed into the survey that can invalidate the data.

Data Weighing

Data can be weighted to adjust results based on the impact of certain variables or to filter out biased responses for results that better reflect the target audience.

Vendors

Suppliers are regularly assessed to monitor the quality of their data and are suspended or blacklisted when they fail to uphold Hanover’s data quality standards.