Customer Success Associate

Overview

You're the CS team (or one of very few CS people) at PassBy, making sure retail customers who bought the platform actually use it and renew. You'll onboard new accounts, run training calls, answer questions about the AI insights, and flag risks when customers stop logging in. At 23 people, this role is part customer support, part account management, part product feedback loop.

Role Snapshot

Company Context

Stage: Early (23 employees, likely Seed/Series A)

Size: 23 employees

Growth: Adding SDR + CS simultaneously suggests they have a base of customers and need both pipeline and retention

Market Position: Niche retail analytics provider—customers likely testing this as a new tool, not replacing entrenched systems

GTM Reality

Customer Base: Probably 15-40 active customers at this stage (estimate based on team size). Mix of growing retail brands testing PassBy to inform expansion decisions and optimize existing locations.

CS Structure: You're either the first CS hire or joining one other person. No formal playbooks yet—you'll be building processes as you go.

Upsell Motion: Likely land-and-expand: customers start with a pilot or limited scope, then expand to more locations or add-on features if they see value.

Competitive Landscape

Retention Challenges: Customers might churn because they don't see ROI fast enough, find the data hard to act on, or decide to build similar analytics in-house. You're competing against "do nothing" and "our BI team can handle this."

Your Job in This: Show customers quick wins, make the platform easy to understand, and position PassBy as the faster/better option vs building internally.

What You'll Actually Do

Time Breakdown

Onboarding (30%) | Customer Check-ins (35%) | Reactive Support (25%) | Internal (10%)

Key Activities

• Onboarding New Customers: When a deal closes, you're running kickoff calls, walking through the platform, helping customers connect their data (if needed), and setting up initial dashboards. You're teaching retail operators—often not data people—how to interpret AI-generated insights.
• Proactive Health Checks: Weekly/biweekly calls with accounts to review their usage, ask what insights they've acted on, and uncover issues before they become churn risks. You'll notice patterns like "they haven't logged in in 3 weeks" and need to re-engage them.
• Answering Questions: Customers will ask, "Why is this metric showing X?" or "How do I filter by geography?" or "Can I export this data?" You're the first line of response, escalating to product/engineering when it's actually broken.
• Flagging Risks and Upsells: You'll spot when a customer is at risk (low usage, complaining about value) and when they're ready to expand (asking about more locations, requesting features, showing high engagement). You report both up to the CRO or whoever owns revenue.

The Honest Reality

What's Hard

• Customers Don't Always Use the Product: Retail operators are busy. They'll buy PassBy with good intentions, then never log in. You're constantly nudging people to engage, which feels like pulling teeth.
• Vague Product-Market Fit: At this stage, PassBy is still figuring out exactly which use cases stick. Some customers will love it, others won't know what to do with the data. You're stuck in the middle managing expectations.
• Reactive Fire Drills: No matter how proactive you try to be, customers will hit you with urgent requests right before renewals or escalate issues that should've been caught earlier.
• You're Building the Playbook: There's no CS handbook. You'll figure out onboarding, cadences, and success metrics as you go. If you need structure and clear processes, this will frustrate you.

What Success Looks Like

• 95%+ net revenue retention (most customers renew, minimal downgrades)
• Customers actively using the platform weekly and citing specific business decisions they made with PassBy data
• Spotting upsell opportunities early and handing them off to sales to close
• Building a repeatable onboarding process that gets customers to value faster

Who You're Working With

Your Customers:

• Operations managers at retail chains trying to figure out which locations underperform and why
• Real estate/expansion teams deciding where to open the next 5 stores
• Marketing leaders trying to understand customer demographics and foot traffic patterns

What They Care About:

• "Is this data helping me make better decisions, or is it just interesting to look at?"
• "Can I trust these insights enough to act on them?"
• "Is this worth the cost, or should I cancel and use the budget elsewhere?"

Requirements

• Comfortable on Zoom calls all day explaining software to non-technical retail operators
• Ability to learn a data/analytics product quickly and translate technical outputs into business language
• Proactive—you need to spot problems before customers complain, not just react
• Organized enough to manage 15-30 accounts without dropping balls
• Patience for repetitive questions and slow adoption curves
• London-based (onsite role)