LagrangeAI-what is it and how does it work?
Updated: Oct 31, 2019
Recommender system to achieve your goals on overall star-rating and quality incentives finding the least resistive path on domains, based on the analysis of historical data, growth trends, acquisitions, and social media trends.
We have talked about recommender systems in some of our videos before. The example we always described is about cocktails and how similar a cocktail can be to another. Also, these systems are used in applications we use every day like Amazon, Netflix. When the algorithm recommends a movie, all this information comes from historical data of your account and on how similar are the recommendations to your previous selections.
In this sense, the algorithm saves you precious time in order to find something you may like right away.
Our algorithm works under the same principle. In this case, instead of your taste on movies or books, the algorithm sifts historical data on your previous results, for MLTC star ratings or quality incentives for example, in order to predict your next ratings or where are you going to be placed among your competitors. The variables or information that goes into the algorithm are growth trends, quality results from previous years, social media or news about the insurance market and acquisitions.
Just as your Netflix account, the process is customized to your needs. When you decide to begin to work with us, we will have a preliminary meeting where you can tell us what are your goals for the month, semester or even year with respect to quality, growth and star rating.
Using this information, we begin the customization of our algorithm.
At this point, we have two different offers:
1) You can tell us your goals in time and we will tell you the predictions on where those goals are going to take you for final results, ratings and quality incentives.
2) We can tell you which is the less resistive path to improve results, quality incentives, and ratings.
We will have preliminary results that we will give to you and your team in order to begin the identification of opportunity areas and the actions that can be taken.
After the second meeting, we will readjust the algorithm if necessary to make the projections. With these projections, you will know where are you going to be by the end of the month, semester or next measurements periods among your competitors.
During the time of our commitment, we will give you the results and relevant information that will help you to make well-informed decisions based on statistical data. We know you always thrive to be the best and our compromise is to help you by giving you a broader view and how to reach the growth, incentive, and ratings your company wants.
We provide extensive analysis and conclusions of your latest results, why you did not reach your goals and how they can be met.
Statistical projections on quality incentives and ratings.
Insights and conclusions on opportunity areas: where to improve and
actionable solutions to get the results you deserve.
If you want to know more, subscribe to our webinar about what can we do for you!
For more details about calculations visit our YouTube channel