Advanced analytics focus on the forecasting, simulation and optimization of future events to produce insights that traditional business intelligence approaches, such as query and reporting, are unlikely to discover. Using complex and intricate methodologies – such as text analytics, data mining, machine learning, pattern matching, forecasting, visualization, semantic analysis, network and cluster analysis, multivariate statistics, graph analysis, simulation, complex event processing, and neural networks – advanced analytics seek to provide predictions and recommendations to business questions. They can be applied in a variety of settings, including market research, Voice of the Customer (VoC) programs, Voice of the Employee (VoE) programs (VoE), and any other setting that needs deeper insight into big data.
There are two types of advanced analytics: predictive and prescriptive. Predictive analytics use data collected in the past, such as user preferences, demographics, purchase history and consumer sentiments, to forecast the future. Amazon is a great example of this. By examining what and when consumers buy on their website, their algorithms can suggest items that the customer may be interested in purchasing. In a customer experience (CX) setting, this technology would allow prediction of what customers want, even if they don’t directly state it.
Prescriptive analytics takes predictive analytics one step further by giving recommendations on what should be done, even on questions that were not posed. This is done by running simulations and optimizations to discern possible procedures, their results, and then suggesting the best course of action. An example of this is used in Google’s self-driving cars. By running models about possible routes, and the probability of pedestrians walking out onto cross walks, Google’s car can get to the destination in the fastest way and stay alert for potential pedestrian hazards. In this same way, prescriptive analytics can help a business. By consistently testing scenarios and outcomes, a company can keep apprised of obstacles and can chart a course safely to their desired CX or other business destination.
According to Gartner, advanced analytics is a top business priority. Yet, only four percent of companies are able to combine the right people, tools, data and organizational focus to take advantage of advanced analytics. In order to implement advanced analytics, it is essential to create an environment in which it will thrive. This can be done by:
- Creating a solid data infrastructure for advanced analytics – With ever-increasing streams of data, it is necessary to have data-processing capacity.
- Choosing the right advanced analytics techniques – A proper analytics platform needs to be flexible to keep up with the changing business landscape.
- Letting the business process be your guide – There is no one right way to apply advanced analytics; business leaders need to use it in the way that best suits company needs.
- Exploring industry-specific lessons – By exploring how different industries utilize advanced analytics, leaders may find new applications for advanced analytics abilities.
- Organizing for advanced analytics to accelerate success – Help the company understand and implement advanced analytics through better communication and application.
At MaritzCX, we believe in taking action with confidence as customer experiences unfold. Leaders should be able to take the information provided by survey respondents and apply that knowledge to the entire customer base using dormant stockpiles of organic customer data. What was once a limited view of respondents will evolve into a clear picture of which customers to engage and what you can do to win their loyalty—and their business. Some of the key benefits to our approach include:
- Increase the value of your customer data
- Apply insights to your entire customer base – at the individual level
- Supercharge your closed loop program
- Boost customer retention
- Improve actionable opportunities well beyond the respondent population
- Proactively recover at-risk customers
- Capitalize on opportunities to sell new products and services