Catalyst for a sustainable world
ABOUT US
Analytics for SME
Data analytics produces transparency and clarity for numerous improvements, including better service level performance, better order fulfilment, improved supplier management, maximised customer value, lower costs and better product management. They are more likely to outperform competitors in key performance metrics including sales, sales growth, profit and return on investment.
Knowing and tracking your business at any time and place, gives you the fuel for not only faster but, effective decision making transforms your business and gives it the competitive advantage it needs to grow in the demand-driven economy today.
Solution
REDUCE TIME
* Build, mentor and deploy in house data science capability with transformational data science projects
REDUCE RISK
* Reskill/Upskill organizational training and development modules
REDUCE COST WITH EFFECTIVE RESULTS
* Cost effectively build, mentor and deploy in house data science capability through projects
WHY CHOOSE US
Ecommerce Analytics
Recency, frequency, monetary value (RFM) Analytics
promotions, the more frequently the customer buys, the more engaged and satisfied they are, their spend differentiates heavy spenders from low-value purchasers. Knowing your customers’ RFM score will help you focus on acquiring and retaining good customers.
Customer Relationship Management (CRM) Analytics
Digital Marketing Analytics
Frequently Asked Questions
Data Science is a field which contains various tools and algorithms for gaining useful insights from raw data. It involves various methods for data modelling and other data related tasks such as data cleansing, preprocessing, analysis, etc. Big Data implies the enormous amount of data which can be structured, unstructured and semi-structured generated through various channels and organisations. The tasks of Data Analytics involve providing operational insights into complex business situations. This also predicts the upcoming opportunities which the organisation can exploit.
Statistics plays a powerful role in Data Science. It is one of the most important disciplines to provide tools and methods to find structure in and to give deeper insight into data. It serves a great impact on data acquisition, exploration, analysis, validation, etc.
Data cleansing is a process in which you go through all of the data within a database and either remove or update information that is incomplete, incorrect, improperly formatted, duplicated, or irrelevant. It usually involves cleaning up data compiled in one area. For individuals, data cleansing is important because it ensures Data cleansing usually involves cleaning up data compiled in one area. In the case of an organisation, data cleansing is important because it improves your data quality and in doing so, increases overall productivity.
- Descriptive
- Diagnostic
- Predictive
- Prescriptive
Descriptive : What’s happening in my business?
. Comperhensive, accurate and live data
. Effective visualisation
Diagnostic : Why is it happening ?
. Ability to drill down to the root-cause
. Ability to isolate all confounding information
Predictive : What’s likely to happen?
. Business strategies have remained fairly consistent over time
. Historical patterns being used to predict specific outcomes using algorithms
. Decisions are automated using algorithms and technology
Prescriptive : What do I need to do ?
. Recommended actions and strategies based on champion / challenger testing strategy outcomes
. Applying advanced analytical techniques to make specific recommendations
