At Decision City, we utilise creative and customised methods that tailor our work to the client’s environment to the maximum.
We use a mix of analytical methods to resolve problems based on issues identified, following effective understanding of issues affecting client’s performance. These methods include:
- Cluster analysis – used in market research
- Factor analysis – used in quantitative studies to evaluate dependent and independent issues.
- Decision Tree analysis – used in examining probabilities of events (losses or profits) occurring
- Machine or Autonomous Learning – using software algorithms to facilitate findings
- Regression analysis – used in evaluating a dependent issue against one or more independent issues
- Multivariate analysis – used in evaluating one or more statistical outcomes
- Correlation analysis – used in visualising the relationships between issues
- Segmentation analysis – used in evaluating and grouping customer behaviours
- Sentiment analysis – used in identifying and categorising opinions expressed in written texts
- Simulation analysis – used in evaluating change
- Time Series analysis – used in evaluating demand against time in demographic studies
At Decision City, a mix of methods are utilised in problem analysis and solution modelling, using the following five analytics structure:
- Descriptive analysis
- Diagnostic analysis
- Predictive analysis
- Prescriptive analysis
- Adaptive and autonomous analysis.
We invite you to discover value with us!