MarQuant Analytics provides solutions to help companies in identifying, capturing, measuring and analyzing their data, the results of which can increase revenues, profits, customer lifetime value and market share, for example.
Solutions We Provide:
- Database Development & Validation
We determine if appropriate data is captured and measured.
We inventory our clients' databases and review the data
fields for accuracy and necessity.
- Primary Research
We interview selected current customers, former customers and prospective customers to help determine list selection, creative, promotions, packaging, etc. Primary research includes in person interviews, telephone questionnaires, on-line surveys and focus groups.
- Customer Demographics Analysis
We profile the customers and calculate price elasticity, to help increase revenues and determine price sensitivity
- Predictive Analytics
We analyze historical data to determine trigger events that help our
clients market more effectively. For example, we
analyzed public data to determine which customers were more
likely to purchase the client's product. When our client
contacted the top prospective customers, they were able to
immediately close the sales, which immensely improved
- Marketing Resource Analysis
We analyze statistically all the marketing activities and other factors that may affect sales to determine which marketing is providing the best lift.
For example, one client found that direct mail was more
effective than mass marketing enabling them to shift their
budget into direct.
- Customer Lifetime Value Analysis
We determine the value of customers segmented by a number of variables including profile, geography, etc.
- Computer Models
We build customized computer models to graphically display and evaluate data.
Econometrics, the use of statistical analysis to determine which mix of factors best explains a result, is both a science and an art. After gathering the client’s data and certain external data, such as economic factors, we build a database for time-series (longitudinal) and/or cross-sectional analysis.
The results of the econometric analysis can be loaded into
an optimization program to determine the ideal marketing
budget and how much should be spent on the various marketing
activities as well as the amount on products, on customer
segment or by region..
We use statistical models, such as linear, log, poisson, integer, non-linear, log log, etc., to analyze the data. Each of these models analyzes the data differently. In addition, each model has lag of one, two, etc. periods. Our goal is
to identify the model that best fits predicted outcomes with historical actuals.
In identifying the model with the best fit, we test dozens of various models with lags. The results of each model have several factors that reflect the fit, probability, etc. In addition, we test other factors such as collinearity. The results indicate the lift of various marketing activities and the influence of non-marketing activities.