AnswerLab

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Our Process

Our flexible, customizable process ensures unique, relevant solutions for every project.

1. Identify Goals and Define Questions

We start every project by researching your industry, your current website, and your competition. With a thorough understanding of your online marketing objectives and challenges, we then focus on clarifying your goals and making sure your team is bought into the questions we're trying to answer. Our projects kick off with one or two facilitated sessions. The goals of these sessions are to:

 

2. Develop a Custom Solution

There are no off-the-shelf "research packages" at AnswerLab. We apply the most cost-effective methodologies that will yield the highest quality results. For example, for decisions that require insight into preferences and attitudes of consumers, we recommend large-sample, online studies so you can be confident in the findings.

 

For decisions focused only on behavior and usability, we often recommend one-on-one usability studies in a lab setting. Six to ten users can typically uncover most tactical usability problems.


Learn more about our research types and our methodologies.

3. Incorporate Appropriate Tools

AnswerLab develops and implements your research with best-of-breed partners that provide software, panels, and facilities. We hold our partners to the same quality standards that we set for our own work.

 

4. Deliver Actionable and Reliable Answers

You've trusted us as a research partner, and we owe it to you to produce actionable, business-relevant recommendations. We don't just give you a data dump of facts and figures. We analyze the results and distill information in order to get directly to the “meat” of the topic researched. Every chart and graph must pass our “So what?” test before being shown to a client. With AnswerLab, you’ll never need to do analysis on your own.


We put a great deal of care into ensuring our findings are grounded in solid research, from following strict guidelines for questionnaire design to relying on multiple data points to help eliminate the effects of random errors. These methods provide accurate and reliable results.

 

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