How might Sendoso improve its address confirmation system to reduce failed deliveries and save costs?

Introduction

Improving Sendoso's address confirmation system to reduce failed deliveries and save costs is a critical challenge that impacts both operational efficiency and customer satisfaction. As we dive into this problem, we'll explore user behavior, pain points, and innovative solutions to enhance the address confirmation process. I'll structure my approach using a comprehensive framework that covers user segmentation, pain point analysis, solution generation, and measurement strategies.

Step 1

Clarifying Questions

• Looking at Sendoso's position in the gifting platform market, I'm curious about the scale of the problem. Could you share what percentage of deliveries are currently failing due to address issues, and how this compares to industry standards?

Why it matters: This helps quantify the problem and set appropriate goals for improvement. Expected answer: Around 5-7% of deliveries fail, which is slightly higher than the industry average of 3-4%. Impact on approach: If significantly higher than industry standards, we'd focus on fundamental system overhauls; if close, we'd look at incremental improvements.

• Considering the diverse user base of Sendoso, I'm wondering about the primary use cases where address confirmation is most critical. Can you elaborate on the most common scenarios where users are inputting addresses, and which of these are causing the most issues?

Why it matters: Identifies key areas to focus our improvement efforts. Expected answer: Bulk uploads for large campaigns and one-off gifts for high-value clients are the most common scenarios, with bulk uploads causing more issues. Impact on approach: Would tailor solutions to address specific use case pain points, potentially prioritizing bulk upload improvements.

• Given Sendoso's integration with various CRM and marketing automation tools, I'm curious about the data flow. How is address data typically sourced and synced across these integrations, and where in this process do you see the most errors occurring?

Why it matters: Helps identify if the problem is internal to Sendoso or stems from integration issues. Expected answer: Data is primarily pulled from CRM systems, with most errors occurring during the initial import or sync process. Impact on approach: Would focus on improving data validation at integration points and enhancing sync processes.

• Considering the potential cost savings, I'm interested in understanding the current verification processes. What methods does Sendoso currently employ for address verification, and at what stages of the user journey are these checks performed?

Why it matters: Identifies existing processes that can be improved or gaps that need to be filled. Expected answer: Basic regex checks during input, with a third-party API verification before shipping. Impact on approach: Would look to enhance real-time verification and potentially introduce machine learning for pattern recognition in address data.