ANALYTICS

Marketing Analytics

Social Media Analytics

Credit Risk Analytics

Work Force Management Analytics

Actuarial Analytics

Financial Analytics

How can we help...

Analytics is a source of competitive advantage. We map client analytics initiative to quantifiable business outcomes with data driven approach.

  • Identify Potential Customers

  • Optimise products/services pricing

  • Design products/services with customers insights

  • Maximise sales with minimal inventory risk

  • Optimise marketing or advertising strategy

  • Identify locations for setting up business units

  • Get accurate financial insights 

OPTIMISATION

Problem Statement: How do we do things better? What is the best decision for a complex problem?

Optimization supports innovation. It takes your resources and needs into consideration and helps you find the best possible way to accomplish your goals.

Example: Given business priorities, resource constraints and available technology, determine the best way to optimize your IT platform to satisfy the needs of every user.

2

PREDICTIVE MODELLING

Problem Statement: What will happen next? How will it affect my business? You have 1 million customers and want undertake a marketing campaign, who is likely to respond? How do you determine who will leave your organization most likely? Predictive modelling provides the answers. Example: Hotels & casinos can predict which customers will be more interested in particular vacation packages.

3

FORECASTING

Problem Statement: What if these trends continue? How much is needed? When will it be needed?

Forecasting is the most relevant analytical applications in the market right now. It applies everywhere. Forecasting demand helps supply just enough inventory, so you don’t run out of it or have too much of it left.  

Example: Retailers can predict how demand for individual products will vary from store to store.

4

STATISTICAL ANALYSIS

Problem Statement: Why is this happening? What opportunities am I missing?

We do complex analytics, such as frequency models and regression analysis. We can begin to look at why things are happening using the stored data and then answer questions based on the data.

Example: Banks can discover why an increasing number of customers are refinancing their homes.

5

ALERTS

Problem Statement: When should I react? What actions are needed now? With alerts, you can learn when you have a problem and be notified when something similar happens again in the future. Alerts can appear via        e-mail, RSS feeds or as red dials on a scorecard/dashboard.

Example: Sales executives receive alerts when sales targets are falling behind.

6

QUERY DRILLDOWN

Problem Statement: Where exactly is the problem? How do I find the answer?

Query drilldown allows for a little bit of discovery. OLAP lets you manipulate the data yourself to find out how many, what and where? Example:  Sort and explore data about different types of cell phone users and their calling behaviour.

7

AD-HOC REPORTS

Problem Statement: How many? How often? Where?

Ad-hoc reports let you ask questions and help you build a number of custom reports to find answers.

Example: Custom reports that show the number of hospital patients for every diagnosis code for each day of the week.

8

STANDARD REPORTS

Problem Statement: What happened? When did it happen?

Reports are generated on a regular basis and answer question: “What happened?” in a business area. They are useful to  an extent, but not for making long-term strategic decisions.

Example:  Monthly or quarterly financial reports.