Project overview
- Organisation
- Burda Luxury
- Role
- Senior BI & Data Analyst, first tenure
- Period
- Jul 2021 - Aug 2022
Customer Behaviour Forecasting & Audience Intelligence
Customer-behaviour forecasting, campaign and audience analytics covering frequency, recency, LTV and performance measurement; forecasting improved targeted-advertising precision by approximately 25%, and analytics contributed to approximately 20% and 15% improvements in campaign effectiveness and customer engagement.
~25%improvement in targeted-advertising precision
Context
A media business selling audiences to advertisers needs to predict how customers and audiences will behave, not just report how they behaved.
My Role
In my first tenure at Burda Luxury I managed 3 analysts delivering customer, audience and campaign analytics across commercial and digital stakeholders, and built the forecasting used for targeting.
Measurement
- Frequency and recency
- LTV
- CPC, CTR and ROAS
- Campaign and audience performance
Business Impact
- Forecasting improved targeted-advertising precision by approximately 25%.
- Analytics contributed to an approximately 20% improvement in campaign effectiveness.
- Analytics contributed to an approximately 15% improvement in customer engagement.
Technology
- Forecasting
- BI and reporting
- SQL
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