Data Science

At KatalystM, our approach to Data Science is simple, but structured and made robust through decades of experience. The approach rests on three ‘pillars’ of thought:

– A ‘data strategy’ must be put in place to connect business objectives, actions and results
– Achievable Goals and KPIs need to be defined
– There must be alignment between the continuing Business and its available data

We have seen many cases where organisations have embarked on marketing projects that miss one of the above pillars. Invariably, the outcome is the same: Solutions that do not meet expectations, either for marketing and/or the business overall.

To avoid these common pitfalls and ensure that everyone works towards the same goals, KatalystM has a documented approach for the collection and management of all its clients’ data. Organisations today need these processes to help manage and understand the firehose of information that comes with the diversity and volume of data available. With our methodologies and analytical models, we help all our clients make sense of the madness, and focus on the things that matter.

What you can expect from our process:

1) Agree on the Data strategy: This is an iterative, consultative process where we understand your current availability of data, gaps and objectives. A roadmap is charted to fill the gaps and determine steps required to meet goals.

2) Develop and deploy: Calibrate, clean and monitor the data flows to get you going. These steps are integral and critical through the first 12-18 months because this is the key period for optimisation.

3) Optimize: Understand the story that the data tells us, analyze implications and use the insights to drive decisions or make adjustments.