Overview
You work with CPG brand teams (think Kellogg's, Unilever, Coca-Cola) to help them use Bedrock's analytics platform to understand their retail performance. Half your job is teaching people how to use the software, the other half is being a data analyst/consultant who helps them figure out what their numbers actually mean. You're measured on retention, expansion, and how much clients actually use the platform.
Role Snapshot
| Aspect | Details |
|---|---|
| Role Type | Customer Success Manager / Technical Consultant Hybrid |
| Sales Motion | Expansion-focused (upsell/cross-sell), some new logo onboarding |
| Deal Complexity | Consultative - requires understanding client's category strategy |
| Sales Cycle | N/A for renewals, 1-3 months for expansion deals |
| Deal Size | Likely $50K-250K annual contracts (typical CPG analytics deals) |
| Quota (est.) | Probably measured on net revenue retention (110-120% target) and product adoption metrics |
Company Context
Stage: Early-stage (43 employees suggests Seed to Series A)
Size: 43 employees
Growth: Actively hiring for account management, which means they're shifting from land to expand mode
Market Position: Niche player in CPG analytics - competing against Nielsen, IRI, and internal BI teams. Their angle is AI-powered insights and faster data visualization.
GTM Reality
Pipeline Sources:
- 100% existing customers for this role - you're not hunting new logos
- Expansion comes from: adding new categories, more users, premium features, or deeper integrations
- Leads come from usage data (who's logging in, what features they use) and quarterly business reviews
SDR/AE Structure: You're post-sale, but likely partner with AEs on expansion deals that need procurement/legal
SE Support: You ARE the technical expert - no separate solutions engineer
Competitive Landscape
Main Competitors: Nielsen IQ, Circana (formerly IRI), internal BI teams using Tableau/Power BI, legacy CPG analytics tools
How They Differentiate: AI-powered storytelling (auto-generates insights), faster cloud infrastructure, purpose-built for CPG vs generic BI tools
Common Objections: "We already have Nielsen," "Our BI team can build this," "Too expensive for what it is," "Data integration is too complex"
Win Themes: Speed to insight, easy to use vs building custom dashboards, AI finds patterns humans miss, GPU-accelerated performance
What You'll Actually Do
Time Breakdown
Client Calls/Training (40%) | Data Analysis (30%) | Internal Coordination (20%) | Renewal/Upsell (10%)
Key Activities
- Onboarding new clients: You spend 2-4 weeks teaching them how to use Bedrock, connecting their data sources (often messy retailer feeds), and showing them how to build dashboards. Lots of screenshare sessions.
- Quarterly business reviews: You prep analysis showing what insights they've uncovered, present usage stats, and pitch expansion opportunities. These are high-stakes - renewals depend on proving value.
- Ad-hoc analysis requests: Clients email asking "why did sales drop 15% at Kroger in Q3?" You dig into their data using Bedrock and help them figure it out. This is detective work with retail POS data.
- Training sessions: You run webinars teaching category managers how to use specific features. Same presentation multiple times to different client teams.
- Renewal conversations: 60-90 days before contract end, you're building the business case for why they should renew and expand. This means pulling usage data, calculating ROI, and dealing with procurement.
The Honest Reality
What's Hard
- Client data is always a mess: Retailer feeds are inconsistent, clients don't know what data they have, and you spend tons of time just getting clean data into the platform before you can show value
- Adoption is a grind: You can onboard someone, but if they don't log in regularly, you're fighting for retention. Chasing people to actually use the tool you sold them is tedious.
- You need to know CPG category management: If you don't understand promotional lift, distribution gaps, or retailer scorecards, you can't help clients. There's domain knowledge required beyond just the software.
- Stakeholder turnover: Your champion gets promoted or leaves, and suddenly you're re-selling the platform to their replacement who didn't choose it
- Expansion deals move slowly: Getting budget for new categories or users means business cases, approvals, and procurement cycles
What Success Looks Like
- 95%+ gross retention (clients actually renew)
- 120%+ net retention (existing clients expand their contracts)
- Clients log in 3+ times per week and build their own dashboards without always needing your help
- You expand 3-5 accounts per quarter into new product categories or user seats
Who You're Selling To
Primary Buyers:
- Category Managers / Category Directors at CPG brands (mid-level, own a product category like "Breakfast Cereals" or "Laundry Detergent")
- Sales Analytics leaders (director-level, own the retailer relationship data)
- Revenue Growth Management teams (strategic pricing and promotion planning)
What They Care About:
- Speed: Can they get insights in hours instead of weeks waiting for their BI team?
- Simplicity: Can their team use this without being data scientists?
- ROI: Does this help them grow sales, optimize trade spend, or win at retail?
- Integration: Does it work with their existing data sources (Nielsen, retailer portals, SAP)?
Requirements
- 2-4 years in CPG category management, sales analytics, or insights consulting (you need to speak their language)
- Experience with data analysis - SQL helpful, but mainly Excel/BI tool proficiency
- Comfortable presenting to director/VP-level stakeholders in business reviews
- Account management or CSM experience - you've managed renewals and upsells before
- Technical enough to learn the Bedrock platform deeply and troubleshoot client issues
- Willingness to become a subject matter expert in CPG retail analytics (trade promotion, distribution, velocity metrics)