The StrateSci advantage comes from combining real business decision making experience with state of the art advanced analytics and deep consumer insight. StrateSci was developed to provide quality research to decision makers. StrateSci is not a one-size-fits-all shop. We ensure that your business questions drive our research methods, designs, and analytic choices.
StrateSci's team provides a combination background in behavioral science and quantitative methodology which allows us to delve into the minds of consumers.
StrateSci has the answers for business challenges. We apply advanced analytical techniques to your data and transform it into knowledge to be used in your decision making. Below is just a sample of the strategies and techniques in which we have extensive experience.
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Choice Modeling describes the choices of consumers among a finite set of substitutes for a given product. These choices are then related to the attributes of the person making the decisions: how their choices are affected based on income and age as well as other factors.
The prediction of the value a business receives from a relationship with a consumer. Life Time Value helps businesses acquire a lot of customers, maximizing the value of your products or services. This analysis method also allows your business to discover which customers are more valuable, a specific age or income group perhaps; giving you the ability to market more directly.
Next Logical Product identifies the product which is most likely to be purchased by a consumer based on purchasing history.
Segmentation divides the market into parts which are definable. This allows your business to market towards a targeted group of people, without trying to tackle the whole market at once.
Shows the probable relationships, if any, between seemingly random variables. Bayesian Networks are useful for modeling reality and adaptability to your situation.
A more visual approach of Bayesian Networks, machine learning, and statistics. Graphical Modeling depicts the dependence structure of random variables.
Machine Learning is a method of research that relies solely on computer knowledge. Computers learn through patterns in order to analyze your data. We believe in a more hands-on approach. A computer cannot interpret your data into easy-to-use analysis like the team at StrateSci.
Data Mining, which is similar to machine learning, describes the method of searching for patterns and similarities within a dataset. Discovering these patterns can allow your business to make reasonable predictions about your clientele and aid in the decision making process.
This technique is used to analyze data that comes from more than one variable. This type of analysis allows businesses to model reality in which decisions, products, or events involve more than one variable.
This technique identifies the positioning of brans that consumers have or prefer. This analysis is graphed on an X and Y axis, usually by a range of most preferred to least preferred. This allows businesses to identify their own brand perception in the eyes of consumers based on different variables.
Price elasticity, also referred to as price elasticity of demand, is a measure of how much consumer demand for a product changes in response to changes in price. If the quantity that consumers order changes a lot in response to a change in price, then the price elasticity is very high.
Unique to StrateSci, we can provide you with an Excel Simulator based on the data and analysis from your project. These simulators can give probable real-life reactions to any future changes that you decide to make.
A multi-dimensional approach to understanding the shifting variables that affect your business and identifying best prospects for growth.