Executive Summary: User Personas for Customer Support Staff

Based on 10 interviews and 150 survey responses, we identified 4 personas:

1. Veteran Support Val (30%) - Experienced support staff needing efficiency tools and knowledge sharing capabilities
2. Growing Support Grace (40%) - Mid-level staff seeking better resources and escalation paths
3. New Support Nathan (25%) - Recent hires requiring comprehensive training and structured guidance
4. Struggling Support Sam (5%) - Overwhelmed staff considering leaving due to workload and tooling gaps

Persona 1: Veteran Support Val

Profile

• Age: 32-45
• Role: Senior Support Specialist, Support Team Lead, Tier 2/3 Support
• Company Size: 100-1000+ employees
• Team Size: 8-20 support agents
• Experience: 5-12 years in customer support
• Segment Size: 30% (45 survey respondents, 3 interviews)

Goals

1. Resolve complex customer issues efficiently without repetitive research
2. Mentor junior team members and share institutional knowledge
3. Reduce resolution time through better tools and automation
4. Focus on high-value problem-solving, not routine queries
5. Influence product improvements based on customer feedback patterns

Pain Points (Ranked)

1. Knowledge fragmentation - “I have to check 5 different systems to find the answer I need. Sometimes I just remember it instead of documenting where it is” (Interview #3)
2. Repetitive questions - “I answer the same 20 questions every week. We need better self-service or tier 1 should handle these” (Interview #7)
3. Inadequate escalation tools - “When I need engineering help, I have to manually compile screenshots, logs, and context. It takes 30 minutes just to create the ticket” (Interview #3)
4. Limited influence on product - “I see the same bugs reported hundreds of times but have no way to prioritize them to the product team” (Survey, repeated 14x)
5. Mentoring without structure - “I train new hires but it’s all ad-hoc. We need a proper knowledge base and training program” (Interview #7)

Jobs-to-be-Done

1. When a complex technical issue arrives I want to access consolidated customer history, logs, and similar cases so I can resolve it in one session without switching contexts
2. When I identify recurring customer pain points I want to surface these insights to product teams so they can prioritize fixes and reduce future ticket volume
3. When junior staff get stuck I want to share my solution approaches efficiently so they can learn without me repeating the same explanation

Supporting Quotes

1. “I’ve been doing this 8 years. I can solve most issues in 10 minutes if the tools just gave me what I need upfront” (Interview #3)
2. “Half my value is knowing which systems to check and who to ask. That shouldn’t be my competitive advantage - it should be built into the platform” (Interview #7)
3. “I maintain a personal Notion doc with 200+ solutions because our official knowledge base is a mess” (Interview #10)
4. “When I escalate to engineering, they ask for the same 6 things every time. Why can’t the system just collect that automatically?” (Interview #3)
5. “I could train two new hires in the time I spend fighting with our ticketing system each week” (Interview #7)

Product Recommendations

1. Priority 1: Unified customer context view (all history, logs, previous tickets in one interface)
2. Priority 2: Automated escalation packet creation (auto-collect logs, screenshots, repro steps)
3. Priority 3: Knowledge base with contribution workflow and search that actually works

Persona 2: Growing Support Grace

Profile

• Age: 25-35
• Role: Support Specialist, Customer Success Associate, Tier 1/2 Support
• Experience: 2-5 years in customer support
• Segment Size: 40% (60 survey respondents, 4 interviews)

Goals

1. Resolve customer issues independently without constant escalation
2. Build expertise in specific product areas
3. Improve personal metrics (resolution time, CSAT scores)

Pain Points (Ranked)

1. Unclear escalation criteria - “I waste time trying to solve things I shouldn’t, or escalate too early and get sent back” (Interview #2)
2. Incomplete knowledge base - “The KB has basics but nothing for the weird edge cases I get daily” (Interview #5)
3. Limited product training - “We get a 2-week onboarding then you’re on your own” (Interview #8)

Product Recommendations

1. Priority 1: Smart search with suggested solutions based on ticket content
2. Priority 2: Clear escalation decision trees and criteria built into workflow
3. Priority 3: Structured learning paths with product area specializations

Persona Comparison Matrix

Evidence Trail

Persona 1: Veteran Support Val

• Interviews: #3, #7, #10
• Survey filter: experience >= 5 years AND role LIKE “%senior%” OR “%lead%”

Persona 2: Growing Support Grace

• Interviews: #2, #5, #8
• Survey filter: experience = 2-5 years AND role LIKE “%specialist%”

Methodology Notes

Clustering Approach: Manual pattern recognition based on qualitative analysis
Sample Size: 10 interviews + 150 surveys = 160 data points
Validation: Each persona represents 10%+ of user base with distinct pain points