Project execution
With more data than you almost can imagine, we began together laying the foundation for a centralised and completely owned by Stureplansgruppen, data strategy on how to collect (internal and external), move and store and eventually explore & transform this data, and eventually label/aggregate and finally move towards learn and optimize.
Thanks to Stureplansgruppen State of the Art Data Stack, Holistic digital approach and strategy, AI and close collaboration between SPG and Nimble, we’ve managed to continuously improve and iterate a way of working that is in constant change and adapts to the even more so ever changing market and world – leading to powerful results, and especially laying the foundation for years to come.
We work across the following business areas:
- 2x – Overall brands within Stureplansgruppen
- 18x – Restaurants (Example: Ekstedt, Hillenberg, Asian Post Office, L’Avventura)
- 11x – Bars (Example: Röda Huset, Lucy’s Flower Shop, Tyge & Sessil)
- 4x – Nightlife (Example: Berns Night Club)
- 5x – Events
- 3x – Hotels & Resorts (Bank Hotel, Berns Hotel, Skepparholmen)
Marketing Analytics
Understanding the impact of marketing campaign efforts on customer acquisition and engagement. This is defined with reporting as customer journey analysis, marketing mix, ROI, cost of acquisition, and more insights.
Business Value Proposition
- Centralize all brands on the same data analytics infrastructure
- Increase in personalization and revenue
- Best in class media spend efficiency and organic growth
- Total control of how to acquire customers paid and organically
Use case
- Nimble Recency, Frequency and Monetary Value data model (nRFM), example: John visits SPG restaurants once a week, enjoys Spesso and L’Avventura. With the model John gets communication that turns him into a customer who on average visits SPG restaurants 2 times a week instead, and also discovers a new favorite venue.
Operational Analytics
Understanding the current demand and supply to adjust communication, marketing and offers to increase revenue on low demand periods and capture excess demand on peak periods.
Business Value Proposition
- Dynamic data and insights driven activation to ensure occupancy KPI:s of hotels and also restaurant bookings on times and dates that are less likely to be full
- Data driven restaurant recommendations (e.g) to hotel guests
Use case
- Capture potential customers when one place is fully booked, redistribution of demand
- Increase bookings and revenue on less sexy dates and times
