We work with our clients to establish the aims and determine a clear strategy and data-driven approach. This helps to provide direction and control. The decisions taken are based on experience and backed up by analyses and models.
How can I develop my organisation? To what extent can I use the data I already have to develop new business models? What sort of data governance structure do I need to do so? What scenarios are achievable? What work and expenditure would be needed? What are my results and performance indicators? What levers do I have to work with and how are they related to each other? How can I achieve acceptance within the organisation? What results can I expect? And finally, what will be the outcome?
Having a business strategy based on making optimal use of data science requires you to deploy people, tooling, data process and systems correctly. What determines customer satisfaction and how much does it contribute to profitability? What would be the optimal customer journey? Where should I focus my acquisition and what is a sensible budget for it? How can I achieve optimal contact and interaction with my target group? Which channels are most effective? How can I manage my risks and what are they? What tooling and competencies do I need? Is it better for me to do this myself or outsource it?
There are many analyses that offer insights into operational issues. How effective is a campaign; which customers appear to be leaving us; as an insurance provider, how can I reduce my claims liability; how can I identify the right segment of customers for acquisition? Do I have the right data and customer view to do so?
Do you want to know more about this subject? Please contact Kees Groenewoud using the details below