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What Strategies Can Help Us Improve Response Times During Peak Seasons?
Our company faces significant challenges in managing customer support during peak seasons, where the volume of inquiries can spike dramatically. These periods of increased demand often strain our support teams, leading to longer response times and potentially reduced customer satisfaction. We need a solution that can help us maintain, or even improve, our response times during these busy periods without compromising the quality of support we provide. Our goal is to optimize our support operations to handle these peaks efficiently and ensure a seamless customer experience.
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1 Solution
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Recommended Steps to Improve Response Times During Peak Seasons
To effectively manage support volume and improve response times during peak seasons, consider the following steps:
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Implement AI for Routine Inquiries: Use AI to handle common, low-complexity inquiries that make up a significant portion of support volume. This will free up your support team to focus on more complex issues.
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Scale AI Deployment Gradually: Start by training the AI on existing help center content and gradually roll it out to larger audiences to ensure accuracy and effectiveness.
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Monitor and Optimize AI Performance: Continuously monitor the performance of your AI solution, making adjustments as needed to improve accuracy and customer satisfaction.
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Align AI with Seasonality: Prepare your AI to handle seasonal spikes by training it on relevant content and adjusting its deployment based on anticipated support volume.
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Use Data to Refine Support Strategies: Leverage data from AI interactions to identify trends and areas where additional support or content might be needed.
Case Study: How Fundrise Improved Response Times During Peak Seasons with Intercom
Fundrise, a leading online investment platform, faced similar challenges in managing customer support during peak periods, especially around tax season when inquiries would surge. Here’s how they successfully addressed these challenges using Intercom’s AI-powered platform, Fin.
1. Implementing AI to Handle Routine Inquiries
Challenge: Fundrise experienced significant spikes in support volume during peak seasons, particularly related to tax document inquiries. Their Investor Relations team was overwhelmed with routine questions that could be automated.
Solution: Fundrise implemented Intercom’s AI agent, Fin, to handle these routine, low-complexity inquiries. Fin was trained on existing help center content, investor updates, and marketing materials, allowing it to provide accurate responses to common questions. This automation significantly reduced the burden on human agents, enabling them to focus on more complex customer needs.
2. Scaling AI Deployment Gradually
Challenge: Ensuring that AI could effectively handle a large volume of inquiries without compromising the quality of responses.
Solution: Fundrise conducted a proof of concept, gradually rolling out Fin to larger audiences. By monitoring success metrics throughout the rollout, they ensured that the AI was providing accurate and helpful responses before expanding its use. This cautious approach allowed them to build confidence in the system’s effectiveness and improve customer experience.
3. Monitoring and Optimizing AI Performance
Challenge: Maintaining a high standard of accuracy in AI-generated responses, especially during peak demand periods.
Solution: After launching Fin, Fundrise’s Product and Investor Relations teams worked together to increase the accuracy of Fin’s responses from 80% to over 95%. This continuous improvement, achieved without the need for technical resources, ensured that the AI consistently delivered high-quality support.
4. Aligning AI with Seasonal Peaks
Challenge: Handling the sharp increase in support inquiries during the tax season without extending response times.
Solution: Fin was specifically prepared to manage the seasonal spike in inquiries, handling nearly 50% of the total support volume during this period. By proactively training the AI on relevant content, Fundrise was able to maintain rapid response times, even as demand surged.
5. Leveraging Data to Refine Support Strategies
Challenge: Understanding the impact of AI on support processes and identifying areas for further improvement.
Solution: Fundrise used data from Fin’s interactions to refine their support strategies, identifying common issues and opportunities to improve their help content. This data-driven approach allowed them to continuously enhance the customer experience, even during the busiest times.
Conclusion
Fundrise’s successful implementation of Intercom’s Fin AI agent demonstrates how AI can significantly improve response times during peak seasons. By automating routine inquiries, gradually scaling AI deployment, continuously optimizing performance, and aligning AI with seasonal demand, Fundrise was able to reduce support volume by 50% and maintain high-quality customer service. For companies facing similar challenges, these strategies offer a proven roadmap to enhancing customer support efficiency during periods of high demand.
https://www.intercom.com/customers/fundrise/
intercom.com
Investing in success: How Fundrise resolves 50% of its support volume with Intercom’s Fin
We spoke with Luke Ruth, Chief Product Officer at online investment platform Fundrise, about the challenges of supporting a growing customer base without the right technology, and striking the right balance between personal, human support and AI-powered efficiency.
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