BrainTech, LLC: Sales Analysis and Statistical Modeling Services

January 16, 2007: BrainTech, LLC is looking for an independent movie theater or theater chain that is willing to share (and make public) their daily ticket sales figures in exchange for services.

BrainTech, LLC is looking for an independent movie theater or theater chain that is willing to share (and make public) their daily ticket sales figures for a single location (or city) during the first half of '06. In return, we are offering a free (public) analysis of how weather, general market trend, and holidays might have influenced ticket sales during the first half of '06. In addition, we are offering 3 (private) future trend analyses of recent sales figures, upon request, at any time during 2007, along with (private) analysis for potential trend change. Our purpose in extending this offer is to collect an additional sample data set and test our modeling algorithms in a scenario where poor weather may occasionally lead to increased ticket sales. If you are interested in this offer (valued at approximately $300; or would like to propose an alternative arrangement), please contact us at your earliest convenience. Thank you. [Hide details]

Better manage inventory by accurately estimating future sales

Identify changes in market trends as they occur

More thoroughly understand customer preference*

* By combining sales figures with environmental and psychological factors that may have influenced customer behavior on each date-of-sale, the statistical models we build can offer deep insight into the behavioral patterns and preferences of customers.

How we achieve our goals:

We use appropriate statistical analyses to help companies make informed business decisions.

We work with individuals to help provide an intuitive understanding of what factors may influence sales.

We use clear language and informative examples to help convey important (but possibly complex) findings.

We clearly explain what factors are associated with increased or decreased sales, and discuss the relative strength of each factor that may influence sales.

When complex interactions are discovered, we use clear explanations and real-world, market-relevant examples to explain what the interaction means in terms of sales.

We provide references and tutorials throughout the web site (and we will continue to add more) for individuals interested in learning more about statistics and predictive modeling.

We are valued by our clients for:

Using multiple sources of data (such as weather data) to achieve a thorough understanding of what influences company sales.

Providing online access to sales forecasts, reports, graphs, charts, and other tools that can be used to compare estimated and actual sales figures.

Our predictive modeling and daily report service.

Properly using statistical techniques to extract information from data, and then conveying this information in a way that is immediately useful and simple to understand.

Offering free online tools for companies or individuals who want to analyze and interpret their own sales data.

sales in relationship to high temperature

In the graph to the right, there is a possible relationship between high daily temperatures (in red) and sales (blue). What proportion of variability in sales might be due to warmer weather, and what proportion might be due to a time-related (or seasonal) trend?

In the graph to the right, daily wind gust speeds are indicated in red. Is there a relationship between wind gust speed and sales? Does the relationship between wind speed and sales change over time? These are a few of the questions you can try your hand at answering using our online tools, available free of charge.

Example of comparing estimated sales to actual sales

Post-hoc comparison of actual versus estimated sales, used to assess accuracy of a predictive model.

BrainTech, LLC: Using Statistics to build Models of Customer Behavior

Use Multiple Regression to develop models that forecast future sales

We use weather forecasts and time-series and seasonal trends for data analysis

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