Marketing Mix Analysis
A GEE statistical technique was applied to 10 brands over a 5-year period for a large manufacturer. The analysis provided marketing intelligence to the company by showing the impact of various promotions, radio and TV, and other advertising spend on sales. We also built a prediction simulator that allows the company to input an amount of money into one of several types of spend and see the predicted sales that would result from that spend.
Statistical Consulting: From Data Collection to Communicating Your Results
Many professors, market research firms, and researchers have consulted with us to assist them in developing survey instruments, determining the appropriate sample size for their studies, conducting quantitative (descriptive and inferential statistics) and qualitative analyses, writing relevant, useful reports, creating illuminating tables and figures, designing PowerPoint presentations, and build interactive, customized front end-data collection to back-end reports. Our capabilities run the entire gamut of statistical analyses–our expertise includes descriptive and inferential statistics, cluster analysis, discriminant analysis, time-series/ARIMA models, mixed models, structural equation models (SEM)/path analysis, survival analysis, conjoint analysis, MANOVA/ANOVAs, linear/ordinal/multinominal/logistic regression, as well as confirmatory and exploratory factor analysis.
We seek to empower your company to become more autonomous, to use your data more creatively, and ultimately, to create more meaningful results.
Developed an Interactive Presentation for Sales Team
A large financial services company sought a customized solution for their sales representatives to sell life insurance to wealthy individuals. We built an Excel engine where they could work with different assumptions (e.g., growth rates, interest rates, market volatility). The engine produced VaR calculations, for example, which ranked maximum loss not to exceed some given probability over a given period of time. The engine was an interactive model with interactive graphs, where customized assess risk scenarios could be generated on the fly. We included training to their team to use these models. The end result was an effective, flexible, scalable, presentation for their customers and sales team.
Segmented Retail Operations
A large eye wear manufacturer came to us with a large data-set on the preferences and sensitivity of individuals to price of glasses, style of glasses, children and adult glasses, size and location of the stores, internal and external labs, gender and age of the client, and several other client and retail factors. We conducted a cluster analysis to help the company group individuals and retail factors so they could design and fill the stores with the most marketable products. In cluster analysis, the goal is to use the data to group individuals into clusters or segments and also to help determine markets. We used K-means clustering which found a clusters’ center, then grouped customers around that center, and hierarchical clustering which treated each customer as a separate cluster then grouped them into larger and larger clusters. Additionally, we created an excel engine so the client could continue to add observations and determine their particular cluster.
What Product Should I Sell?
A South American Ice cream manufacturer conducted a survey in several countries on perceptions of flavors, texture, taste, appearance, and overall satisfaction of various flavors. Hundreds of inferential statistics and follow-up statistics were conducted to help the manufacturer decide what ice cream to sell next.
We created a ratings profile for different types of ice cream. The goal of their business strategy was to use customer satisfaction as a way to compete in the competitive ice cream business while keeping existing consumers loyal and targeting new customers. Hooray for researchers of ice cream producers!
Maintaining the Right to Sell Your Product: Assisted a Prosthetic Manufacturer in Determining Failure Rate
A midsize prosthetic manufacturer was in jeopardy of being prohibited to sell their products in an entire country. The company hired us to conduct survival analyses to determine whether the amount of defects was consistent with the industry. Survival analysis in this context involved modeling the time to replacement of the prosthetic and how long it lasts. The accuracy of the analyses was critical, both for the company’s own survival and for the patients who potentially had to undergo another surgery. Upon examining the data-sets and analysis from this industry’s National Joint Replacement Registry, we found many inconsistencies both in a country and across countries’ registries, and recalculated the revision rates and hazard ratios (the number of repeat surgeries that needed to be performed). While the company was under an extremely tight timeline, we provided them with statistically sound findings to refute the previous analyses. Today, the company remains doing business in that country.
Leadership Survey Analysis
A company sought to assess the leadership qualities of CEO’s with communication skills, financial performance, IT strategy, and overall company alignment, and questionnaire construction is the key success factor of your survey. During the initial phases of the construction, we will understand your goal in developing the survey, the research design, your timing and budget. We consider the type of questions (closed: multiple choi
ce, yes/no, Likert types items, or open-ended: sentence completion), the placement of the survey items on the survey, and the tone of the survey questions. Further, we can provide various methods of data collection (i.e., mail, telephone, email, in-person), as well as a thorough analysis and reporting of the findings. We can analyze your survey or construct one to your specifications, and we can automate the entire process so you can create an updated report with graphs in a moment’s notice.
Survey Instrument Validation
A survey instrument developer needed to assess the reliability of their instrument, and to certify a validation report. The data was statistically evaluated to determine the reliability. The reliability was measured using the Cronbach Alpha, which basically measured how well a set of items (or variables) measured a single unidimensional latent construct. In addition, the Standard Error of Measurement (SEM) was calculated which refers to the standard deviation of test scores that would have been obtained from a single participant had that participant been tested repeatedly.
In any type of market research, the analyses should take into account different types of error, such as reliability and validity. Reliability basically refers to the consistency in which participants respond to a set of questions (i.e., the Cronbach alpha cited above, test-retest, Spearman-Brown, or split-half). Validity refers to measuring what you say you are measuring such as content, criterion, construct, convergent, divergent, and nomological validity. When developing an instrument or analyzing yours, we take into account both reliability and validity.
Retaining State Funding: Determine ROI for a Nonprofit Organization
A state-wide not-for-profit organization sought to retain their State funding and needed to justify their efforts by conducting a ROI on their different departments. The research determined the ROI to the state for each dollar innovated.
We in-person interviewed and phone surveyed department managers, created surveys, and used economic data to perform our ROI analyses. We presented the organization with an Executive Summary, analysis of employer and employee non-responses, satisfaction, service, and summary and recommendations.
Credibility in Marketing Material: A Juice Company Investigates the Health Correlates of Their Product
A juice company was seeking marketing material, purporting that their juice was related to the reduction in stress and tension, an increase in sexual desire, mood, general health, and energy level. (Makes you want to buy a case!)
We conducted an in-depth examination of the placebo controlled double-blind dosage study research design, analyzed the correlates between the amount of juice consumed with age and gender, and used bonferroni correction on the alpha levels to account for the numerous correlations. In fact, there were numerous statistically significant relationships, and the company used this information in their marketing material with integrity and credibility.