Project Summary
Fieldstream helped an Italian sportsbet operator to evaluate its investments in team sponsorships - namely, a big team and several smaller teams. As there was an upcoming decision to be made regarding a new investment in the bigger team, Fieldstream was tasked with gaining insights into their Marketing ROI and the impact of their sponsorships. The results: an 8% uplift in Marketing ROI and an organization aligned on the overall marketing budget strategy.
Project Details
“With Fieldstream, we are not able to make informed budget decisions when needed and better direct our efforts to increase retention, in line with our company strategy."
— Marketing Manager, Swedish iGaming Brand
Background
A Swedish iGaming brand had previously done MMM as part of a project with an external agency. Now, they wanted to implement a more advanced solution with regular data updates for frequent decision-making. They were also interested in seeing if Fieldstream's platform could be useful for helping with retention.
Challenges
- Old legacy MMM model – did not provide up-to-date insights.
- Struggled with low retention – even if NDC numbers looked fine.
- Wanted increased ROI for total deposits.
Why it Mattered
- The company wanted more frequent budget decisions based on the latest data.
- Needed actionable insights on how to activate specific customer cohorts.
- Partly due to retention problems, the Marketing ROI was not at a satisfactory level.
Fieldstream's Objectives
- Improve retention.
- Have up-to-date decision-making material for budgeting.
- Improve Marketing ROI.
Fieldstream Solution
1. Data Quality Audit & Pipeline
- Set up connectors to media platforms and data warehouse.
- Set up a robust pipeline with monthly data refresh.
2. Custom MMM Build
- Core hierarchical Bayesian model, weekly granularity, channel-specific ad-stock and saturation curves.
- Specific focus on different customer cohorts to enable retention analysis.
3. Fieldstream Dashboard
- Monthly auto-refresh; executive-ready ROI reports.
- Optimizer and scenario planning tool for the team's ongoing work.
- Possibility to estimate effect on different customer cohorts in budget planning.
5. Review of LTV Model
- Reviewed the existing LTV model and suggested improvements to make sure that ROI calculations were accurate.
Key Findings
1. Having a tailored marketing strategy helped retention
- Evidence: There was a clear optimization potential for the identified customer cohort.
- Action: Create a marketing plan for increased retention.
2. DOOH was underutilized
- Evidence: There was strong ROI and low saturation at its current spend level.
- Action: Increase DOOH in combination with social.
3. Several affiliate sources led to high churn of customers
- Evidence: Identified affiliates had much lower customer LTV than average.
- Action: Cut out the non-performing affiliates.
Results
- We saw a 11% retention improvement for the analyzed customer cohort.
- 10% uplift in overall Marketing ROI.
- The team now has a tool to make sound operational decisions.
