GOALS

• Identify and acquire high-quality customers at a lower cost per acquisition (CPA) by optimizing paid advertising campaigns based on data-driven insights.
• Improve website conversion rates and average order value (AOV) by understanding customer behavior and personalizing the online shopping experience.
• Build a data-driven growth team by implementing robust reporting and analytics processes, empowering team members to make informed decisions.

Frustrations

• Dealing with siloed data across different marketing platforms, making it challenging to gain a unified view of campaign performance.
• Difficulty in attributing conversions to specific touchpoints, leading to uncertainty about which marketing efforts are truly effective.
• Limited visibility into the impact of creative assets on campaign performance, hindering efforts to optimize creatives for better results.

GOALS

• Develop and implement a multi-touch attribution model that accurately reflects the customer journey and provides actionable insights for optimizing marketing spend.
• Create compelling data visualizations and dashboards that effectively communicate marketing performance to stakeholders at all levels of the organization.
• Contribute to a culture of data-driven decision-making within the marketing team and across the wider company by advocating for data literacy and providing actionable insights.

Frustrations

• Working with limited historical data or unreliable data sources, making it challenging to build accurate and robust attribution models.
• Overcoming resistance to change from traditional marketers who may be hesitant to embrace data-driven approaches.
• Balancing the need for complex statistical analysis with the need to communicate findings in a clear and concise manner that is accessible to non-technical audiences.