Our client wanted to leverage their information rich environment and external data sources to transparently manage customer marketing based on relative profitability. Velrada designed machine learning algorithms alongside SQL (SSAS) based models to model customer churn and the profitability of customers, channels and products. This model was then surfaced through and made available through an API to be consumed by Dynamics 365. Our client is now able to focus on profitable customers, reduce churn and create tailored marketing campaigns based on the models.
It was critical to create a clear, comprehensive strategy for leveraging data across the organisation to give the client confidence in moving from to execution and in our ability to deliver value quickly.
The critical importance of leveraging data and insight to achieve profitable product and portfolio management was key to our client’s growth strategy. It was also recognised that there was a between capability and aspirations and a between capability and aspirations and this gap needed to be closed quickly in order to deliver on the strategic objectives. Velrada gave a sharp capability uplift and the internal confidence to endorse the data strategy and roadmap proposed by Velrada which outlined a comprehensive, long term vision for unlocking the value in our client’s data from a people process, systems and business perspective.
The strategy provided the momentum and confidence to move quickly on key proof of value solution work, in the context of a clearly articulated data platform, tools and governance approach. Velrada understood the scale of the challenge from operational, technical and cultural perspectives recognised the need to move quickly and focus on an initial proof of value around a high impact challenge – customer profitability and segmentation. BBA are now able to focus on profitable customers, reduce churn and create tailored marketing campaigns based on the models, allowing a more customer focussed experience and further growth.
Velrada has driven the momentum for our client’s data team to implement a full Microsoft data, BI and AI ecosystem inside the Microsoft reference architecture. For the specific proof of value work around profitability modelling, Velrada designed machine learning algorithms alongside SQL (SSAS) based models to model not only customer churn but the profitability of customers, channels and products. This model was then surfaced through and made available through an API to be consumed by Dynamics 365.