RightPlace Consulting is a firm with deep experience in data science and predictive analytics.  Our goal is to transform data into actionable insights that can be deployed in real-time, scalable systems.  We find that the best analytical outcomes are achieved when data science and business area expertise are paired through close collaborative consultant and client interactions.  Our team consists of Ph.D. level, industry professionals that have over 20 years of experience and education to help you use your data to make better business decisions.

In a world of rich and abundant data, analytics is finding diverse and expanding areas of application that drive significant business value.

Transportation and Fleet Management Analytics

At RightPlace Consulting, our analytical professionals can help your organization with the development, validation, and deployment of analytical solutions to drive improved transportation and fleet decisioning.  Some examples of areas that we can assist you with are:

  • Use in-house and industry data to predict customer demand and future fleet distribution
  • Use real-time fleet management analytics to improve routing, fleet allocation, more efficient utilization, and lower costs
  • Leverage optimization techniques to better solve complex planning and scheduling problems
  • Integrate and build analytical modules to work with existing tools, software, and data infrastructures

The above examples are just a small sampling of application areas in which data science and analytics can drive real and actionable business value.  We have the experience and expertise to solve your unique data science challenges.

Customer Analytics

Interactions with potential and existing customer is at the core of any business.  Ensuring that this is done in the best way possible is incredibly important to the long-term viability of the enterprise.  At RightPlace Consulting, we use data science and predictive analytics tools to learn important and actionable insights about your customers.  For example:

  • How should similar types of customers be grouped and segmented?
  • What are drivers of response rates, customer loyalty, and attrition and how can this be improved?
  • How can marketing campaigns be made more effective so that the right customer / prospect receives the right offer at the right time?

Pricing Analytics

An effective pricing strategy reflects a number of considerations such as market dynamics, competitive environment, product offering, and the target customer.  Our area of expertise is in creating data-driven price optimization frameworks to enable a more efficient and robust pricing platform.  Some key components of this are:

  • Price elasticity and sensitivity models are used to understand the impact of price on sales volumes and revenue
  • Advanced price testing methodologies can be used to simultaneously learn the impact of price changes across multiple factors such as product, geography, customer segment, etc.
  • Pricing optimization methods are used to optimize prices for different products, channels, and customers based upon market and competitive dynamics

Statistical Methods We Use

  • Experimental Design and Optimization
  • Generalized Linear Models
  • Logistic Regression
  • Machine Learning Models
  • Mixed Modeling
  • Multivariate Statistics
  • Predictive Modeling
  • Regression Trees
  • Survival Analysis
  • Text Mining
  • Time Series Analysis

Technologies We Are Fluent In

  • CART
  • JMP
  • Matlab
  • Minitab
  • R
  • SAS
  • SPSS
  • Stata
  • TreeNet
  • Hadoop
  • Splunk
  • Python
  • C++
  • SQL
  • VBA