Analytics is all pervasive. Whether it is IT, BFSI, Manufacturing, Supply Chain, or the Automotive industry, the analytical albatross has spread its wings in every industry and every function within that industry. Functions like Marketing, Sales, and HR, etc. in all organizations are using analytics to their advantage to solve their problems, fill loopholes, alleviate pain points and ensure the success of their businesses. More and more organizations are reaching out to consulting firms to use analytics to solve their problems. Here are the top 6 applications of analytics by consulting companies to resolve their clients’ problems:
- Linking mental health and wellness for a health payer serving U.S. government employees – A business unit of a health payer serves U.S. government employees and their dependents through participation in the national contract with the U.S. Office of Personnel Management. The client was seeking to develop an analytics strategy to initially meet clinical needs but also to lay a foundation for expansion. Gartner determined analytic goals and formulated the required target state, including required governance and infrastructure. Read the complete solution here.
- Use automation to scale up services and manage growing demand – A consulting company’s approach of delivering bespoke consulting engagements on an individual customer basis involved heavy manual data processing, limiting its reach to service and engage all players in the market. Fractal Analytics build a scalable solution out of its standard services by bringing data, consulting, domain expertise, and visualization altogether. Read how for details.
- Enabled a leading casino operator to build reinvestment plans by accurately predicting customer’s next trip spend – Mu-Sigma’s client, one of the largest gaming companies in the world, invested ~$2 BN each year in marketing efforts, based on customers’ perceived worth. The client’s major objective was to reinvest the marketing spend for a better customer experience. Mu-Sigma built logistic regression models and redefined customer segmentation to solve their problem. Here is how.
- Understand and predict key drivers of customer satisfaction – One of the world’s largest tech companies was looking to better understand the key drivers of its customer and partner experience program. It wanted to understand what drove satisfaction for each customer segment, and to be able to predict a satisfaction-score if it invests into a specific driver. Fractal Analysis enabled the client to gain a globally live analysis that was capable of generating new viewpoints into trackers and satisfaction metrics. Read the several key considerations that went into designing this solution.
- Optimized marketing strategy using Bayesian Regression analytics – A leading CPG manufacturer recently changed its messaging strategy from attribute-oriented to customer experience-oriented and thus wanted to compare the impact of its old messaging to its new messaging on brand volume sales at the retailer level. Fractal Analysis used a Hierarchical Bayesian Regression technique and a Bayesian Belief Network to build marketing mix models to measure campaign performance at the total US level by evaluating the impact of each campaign in generating incremental sales. Read the full details here.
- Improved the alert mechanism to flag off fraud transactions by building a surveillance workbench – Mu Sigma regularized the analyst investigation process as well as optimized the alert generating engine. The alert mechanism and report generation module together formed the AML surveillance workbench which was then used as the major single-screen review framework for the entire transaction monitoring process. Read more.
Sources: Mu-Sigma, Fractal Analytics, Gartner.0