This Machine Learning -/Python/SAScourse is designed for professionals who want to explore data incepting from cleaned data set to Statistical Analysis and through Predictive modeling and finally Data Optimization and recommend most optimized solution. R, Python and SAS are important tool for advancement in machine learning spaces and numerical analysis.It is equipped with a unique feature that helps in processing,modeling and visualizing data.It is easy to learnand it takes only a few lines to write a complete code.



Customer Analytics

  • CUSTOMER SEGMENTATION
  • Call center Analytics
  • Churn Modellin
  • Customer Loyalty Analytics


  • CUSTOMER SEGMENTATION
    • Segment the customers to improve marketing investments and deliver enhanced customer experience.

    • Each customer has unique needs that is reflected in their behavior and the way they are influenced in their purchase drive.

    • Grow as your customers grow! Big data gives you the advantage of enlarging share of wallet, establishing new business models, tapping on future markets and more.

    • Get to know your customer like never before! Customize and design your marketing plan and campaigns for desirable results on your ad spends.

    • Feed on the pool of data available to you to examine and monitor the adrift customers feed back for enhanced customer reactivation.




  • CALL CENTER ANALYTICS
    • Any company with a service demand, establishes and manages a call center in order to service their customers. Call centers are powerful points of contacts for customers. Customers contact call centers when they face issues. So, a typical call center tends to be a high-pressure domain.Needless to say there are several concerns that these call centers face such as lack of motivation, high employee churn, stability in call output and reaching the Key Result Areas. But, the call center managers do not have look too far to solve these concerns. The solutions may lie in the data that the call centers have. Unfortunately, very few call centers use them, and even fewer use them productively.Brainswig helps in analyzing the call center data and provide insights to empower managers to develop right strategies and initiatives to increase the efficiency of the team while improving customer satisfaction. The call center data can be wealthy sources of input for product development and enhancement. Brainswig uses NLP and NTLK techniques to text and voice mine call center data and provide insights to the products and operations teams.At Brainswig, we not only develop insights based on past data, but also use multi variate regression techniques to enhance predictive models. Using these insights the call center clients have:Gained speed in diagnosing and executing automatic issue resolutions and thereby eliminating human error possibilities.

    • Upgraded operational metrics and reduced Average Handle Time.Upgraded customer experience and satisfaction at call centers.Improved employee satisfaction leading to reduced employee churn. CHURN MODELLING



  • CHURN MODELLING
    • Every company faces with trouble of customer churn – some more than the others. What can the companies do reduce the churn?
    • The first step is to recognize the high-risk customers that are most likely to churn. But it’s easier said than done! Identifying which customer, from the tens of thousands of your customers, will churn, when there is no one on one interaction, is very hard. That’s where the advanced analytics helps.At Brainswig, we use a range of advanced analytics techniques such as logistic regression, CHAID and other alike decision tree methods to score the risk propensity of each consumer. In addition, we also provide guidance on which consumers to focus and with what messaging.These advanced analytics techniques, not only, recognize high risk customers, but also the key drivers that you can address to prevent churn.Once the initial model is developed, then we use Machine Learning techniques to constantly improve the efficacy of the model. We know your biggest challenge – Churn Prevention! We believe in the golden rule that ‘Retaining a customer is more profitable than acquiring a new one’

    • Integrate and analyze significant data to forecast and prevent customer attrition.Strategized and targeted marketing spends, which are the result of an intelligent analytics, increase customer loyalty and retention.With the advantages of accurate forecasting, provide your customers a hassle-free experience.



  • CUSTOMER LOYALTY ANALYTICS
    • Every company would like to invest their marketing dollars to keep their most profitable customers. You can see this across all the industries and most importantly in the hospitality industry where the frequent fliers of an airlines or frequent stayers of a hotel get pampered.The research and data prove that it’s valuable for these companies to go that extra step to pamper their best customers in order to retain them. Not only this extra care shields customer retention, but also customer expansion – where these customers increasingly spend all their dollars in that specific category with that company thereby increasing the share of wallet.In order to run a successful loyalty program, you need to consider many aspects such as customer purchase value, frequency of purchase, customer preferences, demographics, growth potential andcustomer churn probability. Many a times, companies reduce them to a concession program. These concessions that are given without much thinking neither build loyalty nor help company’s profitability.At Brainswig, we start with your business objectives and an understanding of your core customers. Then we will help you segment your customers based on your business goals. In addition to that, we develop customer churn model that feeds into the calculation of customer lifetime value (CLTV). The CLTV of each customer is then used to identify the investment levels either at individual customers level or at segment level.
    • Data analytics, when integrated into loyalty programs, pricing strategy and marketing analysis outcome in optimum profitable growth and increased market shareUtilize analytics to analyze and assess the impact of sales and marketing programs, campaigns and promotions on the customers and the resulting ROIs.