One Size Does Not Fit All

One Size Does Not Fit All

Differentiating with Preprocessing, Machine Learning Algorithms, and “What-If” Scenarios –

Everyone is unique.

We fill our free time a number of different ways. We spend a night out at our favorite restaurant, enjoying different types of cuisine. We buy clothes from certain stores because they are more suited for our shape and our style. While we are bound to share some characteristics with others, we are still one of a kind. Thus, we tailor many of our decisions to our individual features and interests to build a lifestyle that is unique.

Similar to individuals, companies, and their data, are unique. At Othot we work with businesses in different industries and from various locations. They all have different quantities of data, comprised of different variables, and are looking to tackle a variety of problems. While there may be overarching factors and pain points that are shared across businesses – similar to people – each business is unique, and thus their solutions should be as well.

pumpkin

This is why Othot developed a cloud based platform that makes it easy for customers to generate predictive and prescriptive insights that are specific to their business.

We have implemented a number of preprocessing and machine learning algorithms, which utilize various parameters, in order to build high performing models for all of our customers. The preprocessing steps and the parameters of the model are driven by the characteristics of each dataset, and thus will vary across customers. Together these components allow us to optimize the model performance for every customer, and every model built.

The predictive models are built using a customers’ historical data, learning trends that are specific to their business. Thus, when predictions are made for current prospects, their probabilities reflect these trends. Furthermore, “what if” scenarios – which allow our customers to identify the potential outcomes of taking specific actions – are also driven by the insights learned from the model. These “what if” scenarios are made up of variables and values that are relevant to each individual customer, such as administering certain types of marketing material or offering specific amounts of financial aid. This allows customers to best allocate their resources in order to reach their own targets.

All of these components work together in the platform to produce the most accurate and actionable insights for each customer – all of which is straightforward to use, easy to understand, and generated real time. That’s the power of Othot analytics.

By | 2017-02-26T07:07:20+00:00 October 28, 2016|Business, Industry, and Markets, Predictive Analytics|