Custom Research & Insights
Business intelligence data has never been more readily available; but data without strategic purpose is just noise. Pacific Market Research combines a thoughtful, powerful mix of active research and observational techniques to collect data. And we synthesize our findings through advanced, storytelling-inspired analysis that gives you richer, more actionable results and recommendations.
The intelligence that decisions deserve.
In the current business environment, technology has afforded business leaders access to unprecedented sources and amounts of data. However, a wealth of data does not necessarily provide the complete tactical information necessary to make strategic decisions. In this noisy playing field, how do you gain true insight and, in turn, produce better strategies? We’re confident that the answer is to combine research that asks questions and research that observes — leading more directly from data to insights to action.
Every Pacific custom research engagement is different. Based on your unique needs, goals and opportunities, we may recommend that you use survey research data (more active), pursue observational research techniques (more passive) or combine the two. By taking this flexible approach, we’re able to tell a more holistic story — one that’s insightful, but also allows for more actionable uses of data for real-world applications. We also apply advanced analytical techniques to your data in order to go beyond simple descriptions of data points and into hidden relationships among variables, which is critical to moving research and insights into actionable territory.
Survey Research Techniques (Active Data)
Our survey-based work includes, but is not limited to:
Our “new school” approach to segmentation uses a sophisticated model grounded in behavioral science that recognizes that decision-making goes beyond demographics and psychographics and into needs-based choices that manifest in one’s lifestyle.
We provide an understanding of how — and at what level – each of your product features, benefits or communication points contributes to overall product/service selection. This helps you determine the optimal combinations of product features and attributes to influence customer decision-making.
Too often, current cross-cultural and multicultural research treats people as data points only. We use psychological and sociological approaches to understand the factors that contribute to differences, giving you more insightful, actionable results.
Contemporary Brand Tracking
Common brand tracking’s Achilles heel is that yesterday’s data tells an incomplete story — so we offer a more considered approach that allows for real-time action, along with measuring emotional resonance to your brand.
We believe that creative testing based on typical rational tests is highly limited. Our tests observe consumer impact from emotional, rational and reptilian points of view, which provides a better, more holistic predictor of in-market success. One example is our use of predictive markets, which draws from the Iowa Electronics Markets and its success at predicting presidential elections to test ideas through an element of gamification. In this technique, a convenience sample of respondents is allowed to “buy and sell shares” in an idea to evaluate its worth.
Win-loss research is especially effective if you have a high-dollar product or service with a strong consultative selling component, or if you are in a market where the buyer may be less educated about your product or the category in general.
Attitude, Awareness & Usage (AA&U)
We use AA&U studies to measure changes happening in consumer attitudes, awareness and usage levels for your product and competitive products.
Observational Research (Passive Data)
Pacific Market Research offers a variety of contemporary techniques, including:
Measuring human emotional response is difficult (and sometimes impossible) to achieve with cognitive questioning only. We can supplement with biometric approaches, such as galvanic skin response, when appropriate.
Sometimes, the best way to truly grasp the impact of a design — whether physical, such a retail space layout or product package, or informational, like website copy — is to conduct experiments that measure how changes in the choice environment influence decision-making.
Ethnography (in-person and mobile)
When performing qualitative research, observational techniques tend to be the most insightful. Why? Because these methods don’t force people to have to “perform” or appeal to social desirability. The subjects can just be themselves.
Social Media Listening and Analysis
Observing conversations online expands the nature of ethnography, which is more individual in nature, to create understanding at a mass level.
Imagine viewing an experience through the eyes of your customer in an actual, not virtual, environment. With wearables, you see real, authentic interactions uncolored by observers, contrived situations and other distractions that introduce bias and affect customer decision-making.
Identifying opinion leaders and influencers is key to creating effective strategy segmentation. We help you achieve this by observing people’s behavior and applying network theory and analysis in order to determine the primary influencers for brands, products, topics, politicians/candidates and others.
Transaction Data Research
TDR is the use of time-dimensional data to describe an event occurring at the transactional level, from purchase details or payment records to customer touches and other actions. This data, typically used in concert with other measures, helps create a full view of consumer actions.
This simple but often very helpful method splits a group of people into one or more smaller groups, each of which is sent a different message or component of creative work to evaluate which has the highest conversion rate.
Simple data description still has its place, but the full value of innovative custom research can only be realized through more sophisticated techniques. Pacific Market Research uses advanced analytics to dissect hidden relationships and patterns within the data, unveiling findings that cannot be seen with simpler traditional analyses like cross-tabulation. This future-focused approach helps us deliver insights and strategies that can drive tangible business improvements and form the foundation of long-term success.
We offer an extensive array of advanced analytical tools, and we’re continually evolving with emerging trends. Our techniques include, but aren’t limited to:
Conjoint Analysis/Discrete Choice
Conjoint analysis seeks to determine the optimal configuration of items or concepts. It’s common in product development, such as determining the optimal computer configuration for a computer manufacturing company. With this technique, respondents are presented with various combinations of components (hard drives, RAM, etc.) and asked to choose their favorite combinations. The conjoint then prioritizes the importance of each component.
This analysis describes how dependent variables interact with independent variables. It’s especially useful for determining which factors or attributes drive loyalty, satisfaction and other important consumer metrics.
With our advanced product simulators, you can dynamically change product components to see how these influence key segments and demographics.
Maximum Difference Scaling (MaxDiff)
We use this indirect approach to determine consumer preference for and importance of various product characteristics.
This technique helps determine the specific combination of products and services that appeals to the greatest number of customers.
These studies examine the parity between consumer expectations and reality. For example, a survey about car satisfaction might ask if the buyer is satisfied with the gas mileage, seats or air conditioning. Gap/opportunity analysis quantifies the difference between what the buyer expects in his ideal car versus actual reality.
By breaking down secondary data to determine the demographic and psychographic profiles of ideal customers, CHAID helps identify high-opportunity segments.
Cluster analysis groups a set of consumers in such a way that consumers in the same group are more similar to each other than to those in other groups. This allows us to identify and better understand important differences between consumer segments.