This case study is part of my Google Data Analytics Professional Certificate journey. It applies the first step of the data analysis process — Ask — to a real-world-inspired business challenge.
Scenario: ShopSmart, a fictional online retail company, has noticed that a large percentage of its customers only make a single purchase and do not return. This impacts long-term revenue and increases marketing costs, since acquiring new customers is more expensive than retaining existing ones.
Challenge: to understand why customers are not returning and to frame clear questions that will guide future data analysis.
Identifying stakeholders helps clarify what information is needed for analysis. It ensures the final results meet the goals of everyone involved.
- Executive team — They are concerned with overall revenue and profitability of the business.
- Marketing team — They want to design effective campaigns and advertisements to increase customer retention.
- Operations team — They are responsible for delivery speed and reliability, which may influence customer satisfaction.
- Customer support team — They are the customer-facing team and deal with complaints, service quality issues etc.
- Customers — Prime focus of the analysis. They seek good value products, fast delivery, and a smooth shopping experience. Solving their problems will fix the issues faced by the rest of the stakeholders.
The SMART Framework enables us to ASK the right questions necessary to solve the problem statement or business challenge. These questions are:-
- S - Specific: Identify which factors (delivery, support, loyalty program, etc.) most influence repeat purchases.
- M - Measurable: Increase the percentage of customers making a repeat purchase within 90 days.
- A - Action-Oriented: Provide marketing and operations with insights to improve retention strategies.
- R - Relevant: Retaining customers directly increases revenue and reduces acquisition costs.
- T - Time-Bound: Achieve a 10% increase in repeat purchase rate within the next 12 months.
Now, using the answers gathered from answering the SMART questions, let us frame an appropriate question.
Framed Question:
“How can ShopSmart increase its repeat purchase rate within 90 days by at least 10% over the next 12 months, and which customer segments should we target to achieve this?”
We have used all the SMART questions to frame this question.
To answer this question, the following data would be useful:
- Transaction history (purchase frequency, order dates, amounts).
- Customer demographics (age, location, etc.).
- Delivery performance (average delivery times, delays).
- Support interactions (complaints, ticket counts).
- Loyalty program membership data.
This data will be collected, cleaned, and validated in the Prepare stage.
- Executives: Share a concise one-page summary highlighting the challenge, objective, and key question.
- Marketing & Operations: Hold a kickoff meeting to align on goals and confirm the data required.
- Analytics team: Provide a more detailed project brief (including this case study) to guide the next steps.
This case study demonstrates the importance of the ASK step in analytics. Clearly defining the business challenge, aligning stakeholders, and setting a SMART objective lays the foundation for effective data analysis.