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Performance Max spend fluctuation troubleshooter
Performance Max spend fluctuation troubleshooter
Client: Google
Project date: 2023
Industry: Technology
Services provided: Content strategy and curation, project management, video production, automation implementation, program creation, education
Project overview
Enhance external Performance Max troubleshooter content, making them more accessible and personalized to adequately address customer pain points with spending fluctuation directly in scaled support. Improving the troubleshooting content experience and tailoring content to specific user issues, my goal was ti enable self-resolution and reduce reliance on one-to-one agent support.
Project objectives
- Increase accessibility: Make content more discoverable, allowing for users seeking help to easily navigate Performance Max issues.
- Personalize content: Tailor content to specific customer pain points, providing more relevant and actionable solutions
- Scale & expand: Build upon the success of previous troubleshooting strategies to expand content utilization into other high-priority customer journey areas.
- Drive content creation: Develop new troubleshooting content to address a wider range of high-priority issues and further improve self-resolution rates.
- Partner with product troubleshooting team: Collaborate with key stakeholders to implement and optimize the enhanced troubleshooters, leveraging their expertise and insights to improve the content.
By achieving these objectives, we can empower users to resolve their Performance Max issues independently, reduce agent contact rates, and improve customer satisfaction.
Challenge
Performance Max campaign performance issues, particularly spend fluctuations, are a major pain point for users, leading to increased churn and a significant volume of support cases. As Performance Max product adoption usage increases, the need for effective troubleshooting resources becomes more critical.
This situation presents a challenge in providing adequate support to users facing spend fluctuation issues, hindering their ability to self-resolve and impacting their overall product experience.
Key points
• High support demand: Performance issues drive user agent support need.
• Exponential product growth: Adoption is expected to grow significantly, further increasing support needs.
• Underutilized troubleshooters: Existing resources are not effectively reaching users.
• Content gaps: Some articles lack comprehensive troubleshooting guidance.
Addressing these challenges is crucial to ensure a positive user experience, improve self-resolution rates, and support the continued product growth.
Task
Enhance external troubleshooter content by leveraging the expertise of internal Google Ads case agents. This involved:
- Gathering insights: Collaborating with support agents to identify common pain points and troubleshooting strategies related to Performance Max spend fluctuations.
- Creating new content: Developing clear, actionable, and external-facing content.
- Implementing improvements: Updating existing troubleshooters, or creating new ones, to incorporate changes.
The goal was to empower users to effectively diagnose and resolve issues independently, ultimately improving their confidence and reducing reliance on one-to-one agent support.
Action
My plan was to improve the article structure, discoverability, and personalization, while leveraging internal knowledge, I aimed to empower users to self-resolve issues more efficiently.
Specific actions included:
- Enhanced article structure: Transformed troubleshooting articles into interactive decision trees, improving user navigation and guiding them to relevant solutions based on their specific issues.
- Improved content discoverability & SEO practices: Optimized article titles, descriptions, and metadata to enhance their visibility in search results, within and outside the Google Ads help center.
- Targeted user journeys: Personalize the troubleshooting experience, tailoring content and recommendations based on user context and behavior.
- Leveraged agent knowledge: Tapped into internal knowledge bases to ensure the accuracy and comprehensiveness of content.
Results
The enhancements to the external Performance Max troubleshooters, and program practices, yielded positive outcomes:
- Increased self-resolution: A significant decrease of approximately 17.2% in PMax performance cases indicates that users were more successful in resolving their issues independently, reducing the need for agent assistance.
- Improved efficiency: A reduction of approximately 10% in case handling time suggests that agents were able to address remaining cases more quickly and efficiently, potentially due to improved user understanding and self-service capabilities.
