A customer experience measurement approach is today the key factor on which retail organizations rely in order to gain precious insights, minimize the risk and improve profitability.
In a world where fast-change and short-term thinking dominates, what is the best way to anticipate trends and consumer buying patterns? How to manage optimal inventory levels and all related operations?
Predictive analytics provide retail firms with data that contain answers to industry specific questions and uncover new business opportunities, forecasting store traffic and foreseeing customers behaviour.
The following 4 steps are imperative to master Predictive Analytics and thereby drive business growth.
Basic data: Time series of quantity to forecast
Hierarchy or grouping for generating harmonized forecasts, internal (prices, product attributes, etc.)
and external variables (marketing actions, promotions, etc…), calendar effects (holidays, etc.)
Forecasting strategy: Model mix with exception and anomalous data management.
Tools: Evaluation of the most suitable technologies for forecasting and predictive purposes
First stage: slowly-changing or static attribute.
Understand the socio-demographic composition
Second stage: dynamic attributes.
Classify the behaviours by further segment, setting the final cluster with the prevailing and the full spectrum of behaviour for each class (segment) defined on the basis of quasi-static and static attributes. The targeting will therefore be sensitive to socio-demographic, behavioural and cultural variables.
In an ever evolving marketplace, enterprises have to extract critical knowledge from the high volume of data collected on a daily basis. Thanks to a deep understanding of Predictive Analytics, SDG consultants give retail firms the right tools and confidence to lead and make better decisions by using global insights.
Contact us, take the most out of your analytics and plan your next steps.