Data analytics refers to qualitative and quantitative techniques used to study behavioral data and patterns with a view to improving decision making. Techniques vary according to organizational requirements.

Data Analytics process involves 90 % Data Preparation and 10 % Data Interpretation.

Data Analytics is used to answer business questions like:

Which customers are going to churn?

Which customers will default?

Predicting success of a marketing campaign?

Predicting loyalty

Predicting part failure

Generating insights from Customer – speak on Twitter

Companies collect and analyze data associated with customers, competitors, market campaigns, economic indicators etc. Data is categorized, derived, and analyzed to study various kinds of trends and patterns.

Data can be both structured and unstructured. In the structured environment – data maybe available – to the extent it is captured in systems or forms. In the unstructured form- data maybe available as brand reviews, opinion blogs, community interests etc. It may be harder to tag these statements to a demographic, age or gender. Sentiment Analysis, association analysis is some of the types of analysis done with Social Data.

Quantitative techniques involve – supervised and unsupervised learning techniques. Other techniques involve understanding linguistic pattern analysis. Machine learning can be iteratively deployed to get better and better. This is important because as models are exposed to new data, they can independently adapt.

Ixsight supports Data Analytics by providing insights on both “Who” and “Where”” of the customer. Ixsight provides Data Analytics expertise starting from Data Preparation to Model Building in enabling organisations to answer questions with respect to churn, renewal, redemption, default rate etc. In addition, Location Analytics provides insights – which combine the who and where of the customer.