From Fragmented Systems to Scalable Insights
Objective
Map out key data initiatives and timelines to deliver value from analytics.
Obstacle
An omni-channel customer journey with multiple touchpoints blocking one source of truth.
Outcome
Developed a comprehensive data roadmap for scaling subscription analytics and marketing insights.
Background
Carista is a leading provider of after-market car services, offering features such as diagnostics, maintenance tracking, and personalisation tools for car owners. With ambitions to grow their active subscribers to 75,000 by 2026, Carista sought to centralise and enhance their data capabilities to optimise customer insights and subscription strategies and turned to 173tech for pragmatic advice. Our first step was a half-day strategy session with their senior leaders and ours to map out the customer journey and suitable touchpoints.
Strategy Review
Data Fragmentation and Limited Visibility: Disconnected data sources, such as backend databases, Amazon sales, and marketing platforms, created significant challenges in understanding user behaviour and business performance. The lack of integration between these systems resulted in fragmented insights, making it difficult to track customer interactions across different touchpoints. Additionally, existing reports were inflexible and failed to connect pre-app marketing funnel behavior with in-app activities, limiting visibility into the entire customer journey.
High Costs and Lack of Actionable Insights: The reliance on BigQuery for direct raw data queries led to unexpected cost spikes, making data analysis expensive and inefficient. Furthermore, the absence of advanced analytics hindered the ability to identify churn signals or predict high-value customers. Without robust retention and churn insights, optimising customer engagement strategies and maximising lifetime value became increasingly difficult.
Solution
Strategic Business Alignment: Collaborated closely with the founding team to define strategic business goals and identify key data use cases that could drive growth. This process involved conducting in-depth interviews with key stakeholders to map the entire customer journey, ensuring a clear understanding of critical touchpoints that impact user engagement and retention. By aligning data strategies with business objectives, the foundation was set for more data-driven decision-making.
Scaleable Data Infrastructure: To support scalable growth, a thorough audit of the existing infrastructure and data processes was conducted, identifying key data silos that hindered efficiency. Key performance indicators (KPIs) were defined in alignment with the customer journey to measure and optimise growth effectively. Finally, a comprehensive data roadmap was developed, designed to deliver immediate value, encourage company-wide data adoption, and iteratively scale analytics capabilities for long-term success.
The Proof Is In The Numbers...
Half
2
$57k
Implementation
Iterative Approach: To drive quick wins and maximise return on investment, the initial focus was on integrating high-value data sources such as backend databases and Amazon sales. This provided immediate insights into key business metrics. As part of a phased approach, additional data sources like CRM and Shopify analytics were gradually incorporated to enhance customer journey visibility. A unified data pipeline was then established, seamlessly integrating backend databases, Amazon sales, and marketing platforms to ensure smooth data flow and accessibility.
Strengthening Data Capabilities: Investing in internal data talent became a priority, with dedicated specialists hired and trained to maintain and expand the analytics infrastructure. We assisted in putting together the job spec and onboarding this new hire. We are unusual as an agency in that we actually encourage our clients that long-term they should inhouse their analytics requirement, although we are always here to help.
