Navgating AI in Technical Support: Insights from Rachel at Iterable

We dove into a range of topics, including:

• Rachel's unique career path from software engineering to sales and finally to technical support
• The structure of Iterable's support tiers, including their Premier support offering
• How they're implementing AI in customer service, from chatbots to ticket management
• Their STAR (Skills Through Alternative Routes) philosophy for hiring
• Strategies for maintaining top-notch support quality as companies grow
• Balancing the demands of work and life in a high-pressure support environment

Rachel also shared some valuable advice for support leaders thinking about adopting AI and her methods for staying on top of the rapidly changing customer service landscape. This conversation offers a wealth of insights into modern customer support practices, AI integration, and leadership in the tech industry.

Rachel's journey and the structure of support at Iterable

1. Rachel's career path took her from software engineering to retail sales, then to software sales, before she found her sweet spot in technical support - a perfect mix of talking to people and solving complex problems.
2. Iterable offers three levels of support: standard, plus, and premier. Premier support gives customers a dedicated, senior agent as their main point of contact, enabling deep partnerships and tackling complex use cases.
3. The support team is split into tier one agents, premier agents, and tier two agents. Premier agents mainly work with premier customers, building long-term relationships.

How Iterable is using AI in customer support‍

1. They're using AI in several areas of customer support, including a chatbot for standard customers, ticket data analysis for reporting, and AI-assisted tools for agents.
2. Their chatbot, powered by Ada, uses generative AI to answer questions for customers who don't have access to live chat support.
3. On the management side, AI helps analyze ticket data, including sentiment scores and impact scores.d. For agents, AI tools help summarize tickets and expand bullet points into full sentences, boosting efficiency.

Challenges and considerations in AI implementation

1. Ensuring data accuracy and privacy is a top priority, especially given how complex Iterable's platform is.
2. They run extensive testing periods to make sure AI-generated information is spot-on before rolling it out.
3. They measure AI impact through metrics like the chatbot's deflection rate, which shows how often it can answer customers' questions without needing a live agent.
4. They're cautious about AI implementation, focusing on enhancing efficiency rather than replacing human agents, especially in premier support where personal relationships are key.

Advice for support leaders considering AI implementation:

1. Understand what AI will actually do for your business and make sure it aligns with what your customers need and your company values.
2. Identify specific goals and requirements before adopting AI tools to ensure they fit your unique situation.
3. Consider the nuances of your team and support structure when implementing AI - one-size-fits-all solutions often fall short.d. Get your support agents involved in training AI models to ensure accuracy and relevance to your specific customer queries.

Team management and professional development in a distributed support environment

1. Iterable organizes regional in-person meetups and company-wide annual gatherings to help team bonding and create learning opportunities.
2. Daily communication is mostly asynchronous, using Slack channels for question-answering and knowledge sharing among agents.
3. They hold virtual "study halls" via Zoom to mimic office-like interactions and give agents a chance for quick sanity checks.
4. The company puts a strong emphasis on diverse hiring practices, including rethinking job descriptions to be more inclusive of candidates from various backgrounds, following the STAR philosophy.

To wrap it up, Rachel shared some fantastic insights into how Iterable handles customer support, highlighting their tiered support structure and the importance of building strong relationships in Premier support. She stressed the value of diverse hiring practices, including the STAR philosophy, to find talented candidates from non-traditional backgrounds. Rachel also dove into Iterable's approach to implementing AI in customer support, emphasizing the need to align AI tools with business goals and thoroughly test before deployment. On top of that, she offered advice on maintaining work-life balance and keeping support teams connected and learning continuously in a distributed work environment.

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Watch the full Podcast here

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