Our Approach

Every client is different with unique challenges and objectives. Because there is no one-size-fits-all solution, we don’t offer a one-size-fits-all approach. Instead, we tailor our approach using the most appropriate tools & techniques for each client to ensure we meet the needs and objectives of the research goal. Below is a sampling of how we develop our approach that you can expect when working with us.

1. Objectives Assessment

VI will examine the objectives of your project and identify desired goals and outcomes. These could include:

• Testing Marketing Copy to increase engagement, retention rates, or conversion.
• Researching Pricing to identify price sensitivity, friction points, or profit optimization.
• Testing Product Variations to identify what features customers value that can be added to the product to increase sales.
• Identifying Content Gaps that are contributing to high bounce rates.
• Evaluating UI and site design to improve user experience on the site.
• Performing Loyalty Analysis to determine what factors lead to repeat purchases, advocacy, and support of the brand.

2. Behavioral Science Principles

VI will identify which behavioral science principles might apply to designing the research methodology. These include principles from social sciences and behavioral economics:

• Recognition-Primed Decision-Making: A model of how individuals make quick, yet effective, decisions (when speed of decision is important) amidst uncertainty.
• Loss Aversion: The tendency for individuals to avoid losses in favor of acquiring gains of equivalent perceived value.
• Cognitive Priming: Exposing individuals to a concept, medium, or idea activates thoughts on the topic that influences responses to subsequent stimuli.
• Endowment Effect: The tendency for individuals to assign a higher monetary value to an item they own than they would assign to the same item if someone else owned it.
• Scarcity: A perceived limited supply of a good can cause increased perceived value of the good.

3. Data Collection Methodology

After understanding which behavioral science principles would enrich the market research, VI will design a data collection methodology around these principles using the appropriate techniques. These techniques may include:

• A/B Testing: Presenting different versions of the same concept to separate groups and measuring the differences in behavior, reaction, or other quantifiable response. This method is commonly used to test marketing copy, websites, imagery, and other concepts.
• Pairwise Comparison: Systematically presenting a pair of features to individuals to identify which feature of each pair is most important relative to the other feature. Pairwise comparison allows for simplification of complex, feature-rich concepts that results in a weighted, ordered ranking of each feature.
• Multivariate Testing: Presenting the same version of a concept with subtle changes of the concept’s elements to separate groups and measuring the differences in behavior, reaction, or other quantifiable response.
• Observational Study: Allowing the test group to interact with a concept or product to draw inferences from monitoring how the group interacts with the concept or product.    
• Semantic Comparison: Measuring the effect of one or more stimuli on an individual in varying contexts. This is most useful when the marketing copy or image concept is the same, but changing the copy surrounding the concept might change how the user interacts with or feels towards the concept.

4. Survey Programming

Depending on the size of the research and the design of the methodology, VI will conduct research programming via online surveys, phone surveys, 1-on-1 interviews, focus groups, and/or other methods.

5. Data Analysis Methodology:

Upon completion of data collection, VI will perform both qualitative and quantitative analysis to derive information and insights from the survey results. Common data analysis methods employed include:

• Regression: Analyze the relationship of one or more variables with the outcome variable.
• Pareto Analysis: Identify the key factors that contribute in highest proportion to the outcome.
• Sentiment Analysis: Through artificial intelligence (AI) and natural language processing (NLP) or through categorical processing, extract quantitative sentiment information from qualitative data.
• Principle Component Analysis: Preserve as much information as possible while reducing the number of variables into a smaller data set that adequately characterizes the key factors of the data.
• Behavioral Mapping: Analyze how different behavior factors and actions lead to different positive and negative outcomes.

6. Review of insights

A preliminary review of the insights will be shared with you after VI performs initial data analysis. This typically includes high-level topics and key takeaways that are expected to be proven by more in-depth analysis.

7. Presentation of insights

After detailed data analysis has been completed, the final deliverable in the form of an Insight Presentation and data collection package will be presented and delivered to you.