Customer Service Representative

Overview

You're the main point of contact for customers after they buy Brox's digital twin platform. Your job is keeping them using it, helping them design good experiments, interpreting results, and finding new use cases to expand their contract. You're part CS manager, part technical consultant, part business advisor.

Role Snapshot

Company Context

Stage: Early-stage (likely Seed/Series A based on 19-person size)

Size: 19 employees total

Growth: Hiring multiple roles, likely scaling the customer base

Market Position: Category creator—customers are learning how to use digital twins for the first time. Heavy education and hand-holding required.

GTM Reality

Customer Profile: Early adopters at mid-to-large companies—insights teams, product teams, innovation groups. They're experimenting with digital twins, often as a replacement for traditional research methods.

Book of Business: Likely managing 8-15 accounts (small portfolio given early stage and need for high-touch support)

Support Model: You're the strategic layer. Day-to-day questions likely go to support/docs, but you're handling experiment design, results interpretation, expansion conversations, and renewals.

What You'll Actually Do

Time Breakdown

Customer Calls/Check-ins (40%) | Experiment Design & Support (30%) | Expansion/Upsell (20%) | Internal (10%)

Key Activities

• Onboarding new customers: Teaching them how to use the platform, set up their first twins, design initial experiments. This takes weeks—they're learning a new tool and a new way of thinking about research.
• Experiment consulting: Customer wants to test something—you help them frame the question, design the experiment for the twins, set parameters. Then interpret results and help them action insights.
• Troubleshooting confusion: "Why did the twin predict X when we thought Y?" Explaining model behavior, helping them understand limitations, managing expectations around accuracy.
• Usage expansion: Finding new use cases within their org. If marketing team is using twins, can you get product team interested? Can you expand from one twin panel to multiple?
• Renewal management: Tracking usage, health scores, ensuring they see ROI. Building business cases for why they should renew and expand.
• Feedback loop to product: You're hearing what's confusing, what features are missing, what customers wish the platform did. Feeding this back to the 19-person team.

The Honest Reality

What's Hard

• Teaching a new mental model: Customers are used to surveys and focus groups. Using digital twins to predict behavior is completely different. Lots of "why doesn't it work like our old tool?" conversations.
• Expectation management: Some customers think AI = magic. When predictions are wrong or uncertain, you're explaining why. Managing disappointment is part of the job.
• Proving ROI is ambiguous: How do you quantify the value of "we didn't launch a product that would've failed"? Building renewal business cases is tricky.
• You're spread thin: At 19 people, there's no huge CS team. You're handling everything from strategic planning to "how do I export this data?" questions.
• Customers get stuck: They run a few experiments, get results, then... don't know what to do next. Your job is keeping them engaged and finding new use cases before they churn.

What Success Looks Like

• 90%+ gross retention (customers renew)
• 120%+ net retention (existing customers expand usage/spend)
• Customers running experiments weekly/monthly (active usage = renewal likelihood)
• At least 2-3 case studies per year of customers getting big wins (cancelled launches, validated strategies, etc.)
• Expansion deals from initial team to other departments (marketing → product, etc.)

Who You're Working With

Your Day-to-Day Contacts:

• Insights/Research team members (hands-on users of the platform)
• Product managers (using twins to test concepts)
• Occasionally execs (for renewals, expansions, or strategic planning)

What They Need From You:

• Guidance on experiments: "Should I test A vs. B or ask an open-ended question?"
• Results interpretation: "What does this twin prediction actually mean for our strategy?"
• Reassurance: "Is this tool actually working? How do we know?"
• Expansion ideas: "What else could we use this for?"
• Proof for renewals: "Help me build the business case to my boss for why we should keep paying for this."

Requirements

• Technical enough to understand how digital twins / AI predictions work and explain them simply
• Consulting mindset—you're advising customers on how to use the tool strategically, not just doing support tickets
• Comfortable with ambiguity—this is a new product category, so there's no playbook
• Proactive about reaching out to customers (not waiting for them to come to you)
• Able to work East Coast hours (company requirement)
• Smart and "moderately interesting" (per founder's own words)