Account Executive

Overview

You're selling AI automation software to mid-market and enterprise CPG brands - the companies behind products you see at Target, Whole Foods, or CVS. Your main pitch: Glimpse automates deductions management and revenue recovery, putting real cash back in their bank account while eliminating manual work. You're talking to finance directors, controllers, and operations leaders who are drowning in Excel spreadsheets and chasing down retailer documentation.

Role Snapshot

Company Context

Stage: Series A (estimated based on 45 employees, 14x growth, hyper-growth hiring)

Size: ~45 employees, grew from ~30 to 45 recently

Growth: 14x revenue growth last year, signed largest customer ever in January 2024, hiring 15+ roles

Market Position: Category creator in AI for CPG back-office automation - relatively new space with strong product-market fit based on ROI proof points

GTM Reality

Pipeline Sources:

• 40% Inbound - brands who've heard about them through industry channels, some product-led awareness (tryglimpse.com suggests self-serve exploration)
• 40% Outbound - targeted prospecting into CPG brands that fit their ICP (brands selling through major retailers)
• 20% Referrals/Existing customers - word of mouth in CPG industry

SDR/AE Structure: Dedicated SDRs generating meetings, AEs run full cycle from demo to close

SE Support: Forward Deployed Engineers help with technical scoping and implementation during sales cycle for complex deals

Competitive Landscape

Main Competitors: Traditional deductions management software (legacy players), finance automation tools, internal CPG teams building in-house solutions, keeping status quo with manual Excel processes

How They Differentiate: AI agents that actually automate the work vs just organizing data - they retrieve documents, classify deductions, apply cash, manage disputes without human intervention

Common Objections: "We have someone doing this already", "Our ERP handles this", "How do we know your AI is accurate?", "Implementation seems risky", "We need to see proof it works with our specific retailers"

Win Themes: ROI is quantifiable and fast (cash recovery shows up in bank account), time savings are massive (eliminate 80%+ of manual work), accuracy of AI vs human error, scalability as brands grow retail partnerships

What You'll Actually Do

Time Breakdown

Prospecting (25%) | Active Deals (50%) | Internal (25%)

Key Activities

• Discovery calls: You're digging into their current deductions process - how many deductions per month, how much time they spend chasing documentation, what their recovery rate is, where money is leaking. You need to build a solid ROI model showing $X recovered + Y hours saved.
• Product demos: Walking through the Glimpse platform showing how it ingests retailer data, categorizes deductions, retrieves backup documentation automatically, and flags disputes. You're screen-sharing real examples and ideally pulling in their actual data to make it concrete.
• Multi-threading: CPG deals involve finance (who owns the budget and cares about cash recovery), operations (who does the daily grunt work), and sometimes IT/procurement. You're managing multiple stakeholders, different priorities, and long approval chains.
• Deal progression: Chasing next steps, scheduling follow-ups, handling procurement questionnaires, coordinating with FDEs for technical scoping, getting contracts through legal review. Lots of nudging people along.

The Honest Reality

What's Hard

• CPG brands move slower than you'd expect - finance teams are conservative, budgets get frozen, approvals require multiple sign-offs. Deals that should close in Q1 slip to Q2.
• You're often educating buyers on a new category - many haven't thought about "AI agents for back-office" before, so there's concept selling involved before you get to product features.
• The ROI is real but you need good data to prove it - if a prospect won't share their deductions volume or current recovery metrics, you can't build a compelling business case.
• Champion turnover can kill deals - if your finance director leaves mid-cycle, you're starting over with someone new who has different priorities.
• Implementation dependencies - deals require integration with their ERP/retailer portals, which can extend timelines if their IT team is slow.

What Success Looks Like

• Closing 1-2 mid-market deals ($30-50K) per month or 1 enterprise deal ($100K+) per quarter
• Building a pipeline of 3-4x your quarterly quota (realistic given cycle length)
• 40-50% win rate on qualified opportunities that reach demo stage
• Customers renewing and expanding after seeing actual ROI (strong retention signal helps with sales narrative)

Who You're Selling To

Primary Buyers:

• Finance Directors / Controllers at CPG brands ($50M-500M revenue)
• Operations leaders who manage retailer relationships and deductions
• CFOs at mid-market brands (economic buyer for larger deals)

What They Care About:

• Cash recovery: How much money can we get back that we're currently leaving on the table?
• Time savings: How many hours per week does this free up for my team?
• Accuracy: Can we trust the AI to handle this correctly? What's the error rate?
• Speed to value: How fast can we see results after implementation?
• Risk mitigation: What happens if it breaks? How do we audit the AI's work?

Requirements

• 2-4 years full-cycle sales experience, preferably selling B2B SaaS to finance or operations buyers
• Comfortable with consultative selling - you need to understand their business operations, not just pitch features
• Can build ROI models and business cases with real numbers (not just hand-waving)
• Hustle and self-direction - 45-person startup means fewer resources, more figuring it out yourself
• Okay with ambiguity and fast iteration - product is evolving, messaging is getting refined, processes are being built
• Genuinely curious about CPG/retail industry dynamics (or willing to learn fast) - you need to speak their language about retailers, trade spend, deductions, chargebacks