TRC
1300 Virginia Drive
Suite 200
Fort Washington, PA 19034
Metro Area: Philadelphia (PA--NJ--DE--MD)
Phone: (215) 641-2200
Fax: (215) 641-2224
Email: admin@trchome.com
Personnel
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Richard Raquet, President |
Company Description
TRC is a research and analytics firm that pairs customized solutions with senior-level attention and the latest choice modeling approaches to help solve business problems. Success in marketing boils down to knowing how and why buyers make choices. Yet most market research studies fail to put these choices front and center. As a result they fail to capture what’s truly important to the consumer. That’s not actionable research. At TRC, we believe that the best types of research ask people to make hard decision to prioritize their needs and desires. We specialize in the tools and techniques (such as discrete-choice conjoint, product configurator or max-diff) for measuring these choices, and use them to help clients develop new products and services, and to segment customers and prospects.
Affiliations: AMA, CASRO, MRA
Market Research Specialties
Types of Research
Research Techniques & Services
Market Research Resources
White Paper
Product Configuration: A Research Approach for the Times
by Rajan Sambandam & Pankaj Kumar, TRC
The marketplace has shifted in the last decade with the ability of consumers to configure the product they want. This white paper explains the basics of configuration, an approach that mimics the real world of customer driven product design to obtain insight into consumer decision-making. Read White Paper »
White Paper
Product Configuration: Evidence for Effectiveness
by Rajan Sambandam & Pankaj Kumar, TRC
This white paper looks at the examples from one product configuration study, the kinds of information that can be derived and the possibilities provided by statistical analysis. Read White Paper »
White Paper
Non-Response Bias In Survey Sampling
by TRC
Market research accounts for many scenarios to ensure high quality of data. One of the most overlooked problems is non-response bias. TRC describes ways to reduce its effects through survey design and data adjustment in this white paper. Read White Paper »
White Paper
Cluster Analysis Gets Complicated
by Rajan Sambandam, TRC
Segmentation studies using cluster analysis have become commonplace. However, the data may be affected by collinearity, which can have a strong impact and affect the results of the analysis unless addressed. This article investigates what level presents a problem, why it's a problem, and how to get around it. Simulated data allows a clear demonstration of the issue without clouding it with extraneous factors. Read White Paper »
White Paper
How to Measure the Value of a Brand
by Rajan Sambandam, TRC
Brand name evokes an inherent value; finding a way to reliably measure that value is crucial in determining product development. A technique called discrete choice conjoint analysis is described in this paper by TRC. Read White Paper »
White Paper
Conjoint Analysis versus Self-Explicated Method: A Comparison
by Rajan Sambandam, TRC
Determining feature importance in a product can be divided into two techniques - top-down methods where a customer evaluates the whole product at once, and bottum-up methods where features are evaluated individually or in sets. The former method, Conjoint Analysis, is more common while the latter method, Self-Explicated Method, is not widely used but has practical advantages. TRC compares the two methods in this white paper. Read White Paper »
White Paper
Better Questions For Segmentation: Use of MAX-DIFF
by Rajan Sambandam, TRC
Using Maximum Difference Scaling as a method in designing surveys may ensure more useful results in your market research. It is a comparative method based on importance that sidesteps the problems associated with traditional importance scales. TRC explains the mechanics behind this method through a detailed example in this white paper. Read White Paper »
White Paper
Asymmetry in Product Features: Use of the Kano Method
by Rajan Sambandam, TRC
The presence or absence of product features strongly affect consumer satisfaction with the design. Comparing these features using asymmetry analysis can help identify satisfiers and dissatisfiers from among the features of a product. The Kano method is similar but results in categorizing each respondent's answers. TRC presents this essential method of deciding new product features in detail. Read White Paper »
White Paper
Want better product ideas? Try smart incentives
by Rajan Samandam, TRC
Idea generation from survey respondents is strongly dependent on incentive. Introducing competition strengthens the quantity and quality of creative responses. TRC provides examples of smart incentives in this white paper. Read White Paper »
White Paper
An alternative method of reporting customer satisfaction scores
by Rajan Sambandam and George Hausser of TRC
Though customer satisfaction evaluations are widely used, reporting of these scores has varied from one study to another. This is likely the result of each method’s advantages and disadvantages, as well as the personal preferences and habits of the researcher. In this article we review various reporting methods and outline our method with an example. Read White Paper »
White Paper
Database Scoring with Object Based Segmentation
by Rajan Sambandam, TRC
Segmentation created from company databases are often lacking the rich segmentation schemes formed by attitudinal surveys. A new approach is Object based segmentation that uses database variables at the basis for forming attitudinal segments, leaving both markets classifiable with clear demographic segments. TRC compares traditional segmentation analysis with Object based. Read White Paper »
White Paper
Product Configurator
by Rajan Sambandam, TRC
To help customers purchase the right product, companies often use product configurators - tools that let customers design their purchase before ordering. This method is employed as a market research technique, similar to conjoint analysis but without some of the constrictions. This white paper from TRC explains an appropriate use of the product configurator method. Read White Paper »
White Paper
Identifying Feature Importance: A Comparison of Methods
by TRC
Understanding what customers want is fundamental to the new product development process as well as to the process of keeping existing products fresh and relevant. To be successful in this area we need to be able to correctly identify what features are important to consumers. Feature importance can be measured using a variety of methods of differing effectiveness. In this paper we will deal with the following methods: Importance Scales, Pick data, Pairwise Comparisons, and Max-Diff. Read White Paper »
White Paper
Segmentation Success
by Michael Sosnowski, TRC
This paper explains the basic building blocks of the segmentation process and its implementation. Read White Paper »
Case Study
Market Segmentation: One Method, Four Examples
by Rajan Sambandam, TRC
Effective market segmentation requires an understanding of the market and the skilled art of finding the appropriate segments. TRC gives four examples of this method's application with results. Read Case Study »
White Paper
Understand Choice in Banking: Use of Discrete Choice Conjoint Analysis
by TRC
Conjoint analysis provides incentive for survey respondents to determine which features must not be omitted in their final purchase. The method closely mirrors decision-making in the real world, and as shown by TRC in this white paper, is applicable to many situations including how customers choose their bank. Read White Paper »
White Paper
Monadic Price Testing vs. Price Laddering
by TRC
Compares two popular pricing methods to understand the difference in take rate information. Read White Paper »
White Paper
TURF: New Methods for Implementation
by Westley Ritz, TRC
TURF is a long-established and quite useful marketing research tool, but not everyone is familiar with how it works, or with the latest developments that can make TURF even more effective. The purposes of this paper are twofold: (1) to explain the technique and (2) to describe the latest methods for implementation. Read White Paper »
White Paper
Deriving Value from Research: the Use of Conjoint Analysis for Product Development
by Rajan Sambandam, TRC
Marketing research has been used by firms over the last several decades to provide information for decision making. Over time, increasingly sophisticated statistical methods have been developed and deployed in the service of this goal. This article focuses on one such method - conjoint analysis - and its application to product development. Read White Paper »
White Paper
New Product Development: Stages and Methods
by Rajan Sambandam, TRC
TRC identifies the best methods for each stage of the product development process, from Idea Generation through Feature Development, Product Development and Product Testing. Read White Paper »
Case Study
Improving Claim Satisfaction: A Case Study
by TRC
A case study on applying full-service market research to help an insurance company improve their client satisfaction with claim handling. Read Case Study »
Case Study
Improving Call Satisfaction: A Case Study
by TRC
TRC presents a case study of analyzing and improving a call center as an on-going data collection process. Read Case Study »
White Paper
Survey of Analysis Methods Part I
by Rajan Sambandam, TRC
Practical marketing research deals with two major problems: identifying key drivers and developing segments. In this two-part series TRC looks at key driver analysis and segmentation. Read White Paper »
White Paper
Survey of Analysis Methods Part II
by Rajan Sambandam, TRC
This is Part II of a series looking at aspects of practical marketing research: identifying key drivers and developing segments. This content describes specific segmentation methods: cluster analysis, neural networks, self-organizing map (SOM), and mixture models. Included is a discussion on ideas for developing good segments. Read White Paper »
Service
Identifying the Key Drivers of Brand Image
by TRC
Measuring brand image requires looking at direct effects as well as indirect effects of a company's performance. TRC compares traditional multiple regression with SatiscanTM, a method that can review all possible path models. Read Service »
Service
Validating Satiscan Using A Split Sample Approach
by TRC
TRC's SatiscanTM model is tested for validity using call center data and a split sample approach. This shows that SatiscanTM produces similar models when run on random halves of an energy industry dataset. Read Service »
Service
Satiscan and Regression Analysis: A Comparison
by TRC
The comparison shows the advantages of SatiscanTM, an analytical method from TRC, over regression in identifying the correct and cost efficient action steps. Read Service »
