Pipeline Overview
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Enterprise pipeline — open opportunities owned by Gillian Roth, Stephen Hult, and Jess McDaid. Cross-referenced from Salesforce, Glyphic, and #enterprise.
Enterprise Open Opps
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Gillian · Stephen · Jess
Late Stage (Verbal+)
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Verbal · Consensus · Negotiation
Closing Now
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Awaiting Signature / Negotiation
Active Accounts
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Unique accounts w/ open pipeline
FY2026 Enterprise Goal
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/
20
enterprise
accounts
accounts
Feb 1, 2026 → Jan 31, 2027 · — FY26 ARR
0% to goal
20 remaining
Existing customers
FY26 new closes
Days elapsed
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Days remaining
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Pace needed
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On track?
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Closed enterprise accounts
📈 Deal Progression — Week over Week
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Advances
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Regressions
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Total Moves
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vs Last Week
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🔥 Enterprise Pipeline — Gillian · Stephen · Jess
| Account | Opportunity | Stage | ARR | Close | AE | Top Accounts |
|---|---|---|---|---|---|---|
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🎯 ICP Quick Reference
$500M+ revenueRequired
SFCC / Custom / Non-Shopify dominantStrong signal
7-figure monthly performance marketingRequired
DTC-majority revenue modelKey qualifier
AI initiative signalsMultiplier
Best verticals: Beauty · Fashion · Supplements · CPG · Home Goods
📊 Pipeline by Stage
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📢 Latest #enterprise Signals
Tapestry — Legal redlines. Q1 close target. Steve: "101 are tagged, all have AI initiatives, $500M+ rev. Why can't we hit go?"
New Era — Signed! First enterprise close of the quarter. Kickoff in motion.
Proactiv — Budget approved. Final commercial terms. Push to signature.
Top 100 List — Rishabh: "Goal = conversation with all 100 by end of March." Saunder building outreach plan. List in SFDC.
Messaging reminder — Stop leading with "ads and microsites." Leads to narrow, incorrect view of the platform.
Vision Selling Framework
Straight from the enterprise deck and the Notion pitch doc. FERMÀT is a generative commerce platform — not a landing page builder, not a post-click tool, not an ads product. Lead with the data fragmentation problem, then the unified behavioral layer.
Core Positioning Statement
"FERMÀT is the generative commerce platform that unifies data across every touchpoint, continuously gathers behavioral insights, and optimizes experiences from discovery to customer acquisition."
One data layer. Full context. Enable marketing and product to solve customer experience problems at unprecedented speed across every touchpoint — without engineering dependency.
⚡ Elevator Pitches — Memorize These
15-second (Economic Buyers: CMO, VP Digital, VP Ecomm)
"FERMÀT is the generative commerce platform that unifies data across every touchpoint, continuously gathers behavioral insights, and optimizes experiences from discovery to customer acquisition. Brands like GNC and Backcountry use us to drive AI-powered optimization at scale, without engineering dependency."
"FERMÀT is the generative commerce platform that unifies data across every touchpoint, continuously gathers behavioral insights, and optimizes experiences from discovery to customer acquisition. Brands like GNC and Backcountry use us to drive AI-powered optimization at scale, without engineering dependency."
Use for: cold outreach, LinkedIn, quick intros, email subject lines
30-second (Problem-forward — cold/early conversations)
"Your marketing data is fragmented across touchpoints: paid media, email, AI search, product pages, checkout. Each channel operates independently, behavioral insights don't flow between them, and optimization happens manually in silos. FERMÀT is the generative commerce platform that solves this. We unify data across every touchpoint, continuously gather behavioral insights, and optimize experiences from discovery to customer acquisition. Brands like Backcountry see 36% conversion lifts because FERMÀT optimizes across the entire journey — not just individual channels."
"Your marketing data is fragmented across touchpoints: paid media, email, AI search, product pages, checkout. Each channel operates independently, behavioral insights don't flow between them, and optimization happens manually in silos. FERMÀT is the generative commerce platform that solves this. We unify data across every touchpoint, continuously gather behavioral insights, and optimize experiences from discovery to customer acquisition. Brands like Backcountry see 36% conversion lifts because FERMÀT optimizes across the entire journey — not just individual channels."
Use for: cold/early conversations
30-second (Vision-forward — warmer conversations)
"Every touchpoint generates behavioral insights about what customers want: search behavior, ad engagement, email clicks, on-site actions. But those insights stay trapped in silos. FERMÀT changes this. We unify data across every touchpoint and optimize experiences from discovery to customer acquisition. That's why brands like Backcountry and GNC choose FERMÀT as the platform that powers intelligent, cross-channel optimization."
"Every touchpoint generates behavioral insights about what customers want: search behavior, ad engagement, email clicks, on-site actions. But those insights stay trapped in silos. FERMÀT changes this. We unify data across every touchpoint and optimize experiences from discovery to customer acquisition. That's why brands like Backcountry and GNC choose FERMÀT as the platform that powers intelligent, cross-channel optimization."
Use for: first calls, conference intros, referral warm-ups
Shift 01
LLM-Based Search & Discovery
58% of shoppers now prefer AI tools over traditional search engines. Brands need to be visible in ChatGPT, Perplexity, Google AI — not just Google Search. FERMÀT makes your brand citeable across AI models.
Shift 02
Responsive, Adaptive Digital Experiences
78% of consumers now expect personalized digital experiences. Static product pages and one-size-fits-all funnels are losing conversion at every stage. FERMÀT generates dynamic, personalized experiences across every entry point.
Shift 03
Internal Operational Efficiency + AI Superpowers
72% of AI-adopting retailers report measurable cost reductions. Marketing teams are bottlenecked by engineering. FERMÀT removes that dependency — marketing launches, tests, and optimizes without dev tickets.
🏗️ What FERMÀT Actually Does — Three Capabilities
🔍
Shoppable Content for AI Discovery
Reduce discovery costs by making your brand visible across AI models like ChatGPT. Your content gets cited, your products get recommended, your brand wins in LLM search before the shopper ever visits your site.
⚡
Responsive Experiences Embedded On-Site
Automatically turn fragmented product content and catalog traffic into structured, reusable experiences. AI merchandising, dynamic PDPs, personalized layouts — all without engineering lift.
🎯
Personalized Experiences from Any Entry Point
Design, launch, and iterate on digital experiences across channels and shopper contexts — influencer, email, AI search, merchandising — without engineering dependency. One platform, infinite agentic experiences.
The Platform Advantage — vs The Fragmented Stack
One data layer, full context.
❌ The Fragmented Stack (What They Have Today)
Landing & Product Pages → Replo · Instapage · Unbounce
AI Search → Profound · Scrunch · Evertune
Merchandising → Bloomreach · Algolia · Constructor
Behavior Data → Heap · Medallia · Amplitude
Each tool is a silo. Data doesn't flow. Insights don't compound. Every optimization requires manual work across every channel.
✅ FERMÀT — Generative Commerce Infrastructure
Tactics
Layout
Merchandising
Content
Consumer Behavior
One agentic platform. 30+ data sources. 20+ metrics. Behavioral insights from every touchpoint inform every other touchpoint — continuously, in real-time, without dev work.
🎙️ 60-90 Second Discovery Pitch (Marketing Leaders)
"Let me describe the data and optimization problem every brand faces. You're running paid media, email campaigns, AI search optimization, product page testing — but each touchpoint operates independently. Your data lives in silos. Behavioral insights from one channel don't inform another. Optimization happens manually, channel by channel, with weeks of delay.
FERMÀT is the generative commerce platform that changes this. We unify data across every touchpoint — paid media performance, search behavior, email engagement, product page interactions, conversion signals — and continuously gather behavioral insights to optimize experiences from discovery to customer acquisition.
Our AI continuously gathers behavioral insights from every touchpoint. It learns what messaging resonates in paid ads and applies those insights to email. It sees what search intent drives conversions and optimizes product pages accordingly. It identifies high-intent customers in one channel and personalizes their experience in the next. It's constantly testing, learning, and optimizing across your entire journey from discovery to acquisition without dev work.
The result? BISSELL sees 17% conversion lifts. Backcountry drives 36% higher conversion. Everything operates safely in a sandbox separate from your core infrastructure."
FERMÀT is the generative commerce platform that changes this. We unify data across every touchpoint — paid media performance, search behavior, email engagement, product page interactions, conversion signals — and continuously gather behavioral insights to optimize experiences from discovery to customer acquisition.
Our AI continuously gathers behavioral insights from every touchpoint. It learns what messaging resonates in paid ads and applies those insights to email. It sees what search intent drives conversions and optimizes product pages accordingly. It identifies high-intent customers in one channel and personalizes their experience in the next. It's constantly testing, learning, and optimizing across your entire journey from discovery to acquisition without dev work.
The result? BISSELL sees 17% conversion lifts. Backcountry drives 36% higher conversion. Everything operates safely in a sandbox separate from your core infrastructure."
Close with: "What do you know about customers in one channel that you wish you could use to optimize their experience in another?"
🚫 Messaging Rules — What to Say vs. What NOT to Say
❌ Never Say
"We're an experimentation and personalization platform"
"We're infrastructure and data layer" or "We enable AI to optimize"
"We help marketing teams move faster without engineering"
"We have three products: AI search, dynamic PDPs, and funnels"
"We sit in the space between" or "We optimize channels"
⚠️ "We're a post-click or landing page tool" — this leads to a narrow, incorrect view
✅ Always Say
"FERMÀT is the generative commerce platform that unifies data across every touchpoint and optimizes from discovery to customer acquisition"
"We continuously gather behavioral insights and optimize experiences"
"One platform, infinite agentic experiences — 30+ data sources, 20+ metrics"
"A continuous flywheel that gets smarter with every interaction"
🔁 Discovery Transition Lines (Move from Pitch → Qualification)
"What do you know about customers in one channel that you wish you could use to optimize their experience in another?"
"Where do you see the biggest gaps between channels in your customer journey right now?"
"If your paid media team and your ecommerce team could share what they're learning in real-time, what would change?"
"Walk me through a customer journey — where are you learning something valuable in one place that never makes it to the next touchpoint?"
📐 90-Day POC Framework — De-Risk Before Scaling
Days 1–30 · Foundation
Set Up + Audit
Set up integration · Add pixel to main site · Audit top 20 pages · Identify 3-5 quick wins · Set success metrics
Days 31–60 · Build + Launch
Ship + Test
2-3 agentic experiences live · A/B test against control · Daily optimization · Weekly reviews and alignment
Days 61–90 · Scale + Decide
Prove + Commit
Scale winning experiences · Build 12-month roadmap · Present business case to leadership · Decision point on annual contract
📈 Key Proof Points — Memorize These
| Brand | Use Case | Result | Quote |
|---|---|---|---|
| Backcountry | Google Shopping conversion · 200K+ products optimized | +36% conversion · Days not months | "Growth doesn't come from plug-and-play tools; it comes from innovation partners willing to build alongside you." — Kevin Lenau, President |
| GNC | AI Search visibility · OpenAI top referrer | +200% week-over-week LLM citations | "We began seeing our AI-optimized content cited across AI models, like ChatGPT, within the first week." — Amanda Carvell, Sr. Dir. Ecommerce |
| BISSELL | Funnel personalization · SFCC · No engineering lift | +54% CVR · +93% Revenue/Session · +135% subscription opt-in | "FERMÀT gives us the speed and flexibility to create consistency between real-time media touchpoints and landing experiences." — Kevin Marsh, Dir. Ecommerce |
| Glossier | New product drop personalization | +55% more funnels · +65% ROAS · -25% CPA | "FERMÀT helps us align creative and full-funnel experiences, bridging our brand vision with performance." — Madeline Kutner, Dir. Performance Marketing |
Buyer Personas
Five psychographic archetypes based on real deal data — Kevin Lenau (Backcountry), Mike + Harsh (Vuori), Bissell, Scotts, American Eagle, Away. Identify the persona in the first 10 minutes of call 1, then adjust your talk track accordingly.
🏆 The Champion Model — Learning from Vuori's Harsh
✅ Real Champion Behavior (Harsh at Vuori)
Saw conference talk → initiated relationship over time
Explicitly said "Mike is the person you want to be speaking to"
Facilitated EB intro without trying to buy alone
Stayed engaged but enabled EB to have strategic conversation
❌ Fake Champion Signs
Tries to evaluate solution without EB involvement
Can't or won't facilitate EB access by call 2
Wants to be educated for months before involving decision-maker
Ghosts when you ask for EB engagement
The Test: If a "champion" can't get you to the EB by Call 2, they're not a champion.
📊 Persona Priority Matrix
| Persona | % of Deals | Close Rate | Cycle Time | Priority | Time Allocation |
|---|---|---|---|---|---|
| Ian (Innovator) | 15% | HIGH | Fast (60–90 days) | TIER 1 ✅ | 60% of your time |
| Olivia (Operator) | 30% | MEDIUM | Medium (90–120 days) | TIER 1 ✅ | 60% of your time |
| Paulo (Pragmatist) | 20% | HIGH | Fast (60–90 days) | TIER 1 ✅ | 60% of your time |
| Sam (Strategist) | 25% | MEDIUM | Slow (120–180 days) | TIER 2 ⚠️ | 30% of your time |
| Rita (Risk-Manager) | 10% | LOW | Very Slow (180+ days) | TIER 3 ❌ | Disqualify early |
Tier 1 · Innovator
Ian the Innovator
VP/Director Digital Commerce · Head of Growth · Chief Digital Officer · Example: Kevin Lenau (Backcountry)
Psychographic
Experimental mindset
Sees FERMÀT as competitive advantage
Partnership orientation
Often has budget authority
Identify in First 10 Min
Asks "how does this work under the hood?"
Proposes creative use cases unprompted
References competitors as "not innovative enough"
Wants to be "first to market"
Call 1 Talk Track
"We're building the experimentation engine for commerce. You'd be helping shape what's possible." Ask: "What would you build if you had unlimited dev resources?" Show platform flexibility, not just use cases. Introduce to Shreyas (CTO) for call 2.
Warning Signs
Says "I need to run this by my VP" on call 1
Risk-averse about trying new approaches
Deal Structure
Co-create pilot · Beta access · Design partner framing
Tier 1 · Operator
Olivia the Operator
Director/Manager E-commerce · Director Performance Marketing · Manager Growth Marketing · Examples: Bissell, Scotts
Psychographic
Resource-constrained, frustrated
Stuck behind dev/IT bottlenecks
"Just let me do my job" mentality
Focused on velocity and execution
Identify in First 10 Min
"We can't get dev time" / "8 weeks to launch anything"
Has specific upcoming campaigns that are blocked
Frustrated tone about current tools/process
Call 1 Talk Track
Mirror their pain: "So you're spending $2M/month on campaigns but can't optimize the on-site experience because of dev constraints?" Quantify the bottleneck. Show velocity: "ARMRA went from 8-week cycles to launching in 2 days." Ask: "What's the first campaign you'd want to launch if you could go live next week?"
Warning Signs
No specific blocked campaign/initiative
Academic/theoretical about the problem
Wants 60-day eval before committing
Tier 1 · Pragmatist
Paulo the Pragmatist
Director/VP Performance Marketing · Head of Paid Media · VP Growth · Director Customer Acquisition · Examples: BlueMercury
Psychographic
"Show me the numbers and get out of my way"
Data-driven, metric-obsessed
Willing to move fast if ROI is clear
Impatient with vision/strategy talk
Identify in First 10 Min
Leads with metrics: "Our current CVR is X"
Asks "What lift have you seen with similar brands?"
Wants to talk pilot immediately
Call 1 Talk Track
Open with metrics: "Brands at your scale see 20–40% CVR improvement." Quantify their opportunity: "You're spending $3M/month. A 20% lift is $600K/month." Skip the vision — show the path to results. Fast pilot framing: "We can prove this in 60 days with 2–3 experiences."
Warning Signs
Can't articulate current metrics (CVR/ROAS baseline)
Wants to "explore" rather than "test"
Tier 2 · Strategist
Sam the Strategist
VP/SVP E-commerce · CMO · Chief Digital Officer · VP Customer Experience · Examples: Mike at Vuori, American Eagle, Away CEO
Psychographic
Thinks in multi-year transformation arcs
Focused on organizational impact
Needs executive alignment
Prefers discussion over demo ("We can just talk")
Identify in First 10 Min
References board-level priorities or CEO mandates
Asks risk/longevity questions (funding, SLAs, renewal rates)
"What questions am I not asking that I should be asking?"
Strategic framing: "How does this fit our broader roadmap?"
Call 1 Talk Track (Vuori-style)
Match their preference for discussion: "We can just have a conversation." Answer risk questions directly: funding, renewal rates, SLAs. Frame as strategic evaluation. Ask: "What does success look like in 2–3 years? Who else cares about this internally?"
Deploy Rishabh for VP+ Sams
Deploy founder strategically on Call 2/3
Frame POC using Backcountry/Vuori pattern
Warning Signs
No other executives engaged by call 2
Solo decision-maker without stakeholder alignment
Vuori Deep Dive (Mike's Sam Pattern): New in role, drinking from firehose, re-prioritizing entire stack. Core objective: "Reduce reliance on paid." Thinking in 2–3 year arcs. Asked: "How long are you planning on being around?" / "What happens after POC — do you just leave them with the tool?" POC agreed using Backcountry stepwise rollout pattern. Harsh (champion) was the model — facilitated EB access without trying to evaluate alone.
Tier 3 · Risk-Manager
Rita the Risk-Manager
Often a committee · Director/Manager with limited authority · Large enterprise ($15B+) mid-level contacts · Procurement/IT stakeholders involved early
Psychographic
Focused on de-risking the decision
Consensus-driven, committee-based
6–12 month evaluation cycles
RFP/formal process mentality
Identify on Call 1
Mentions "evaluation process" or "RFP" immediately
Multiple procurement/legal/IT on the call
Security/compliance questions before product questions
Disqualification Language
"It sounds like your organization's evaluation process is comprehensive, which makes sense at your scale. Based on our experience with similar enterprises, this typically requires 6–12 months with C-suite sponsorship. We're optimized for faster-moving opportunities right now. Let's reconnect in [Q3] when you have executive bandwidth for this."
Disqualify Immediately If
No EB access path by end of call 1
Timeline is 6+ months
Multiple vendors in parallel evaluation
No clear decision-maker on committee
Objection Handler
Field-tested responses sourced from Glyphic transcripts and #enterprise Slack. Always listen for which persona is objecting — the same objection needs a different response for Ian vs. Sam vs. Paulo.
🏗️ Build vs. Buy
"We can build this ourselves with our engineering team."
The challenge isn't whether you can build it — it's whether building and maintaining this infrastructure is the highest-leverage use of your engineers. Backcountry built their own. Then they replaced it with FERMÀT. FERMÀT lets engineering focus on your core product while your marketing team operates world-class AI-native experiences independently — with a platform that compounds intelligence with every interaction.
📍 Ask: "What would your team actually build if they had the time? And how long would it take to match what FERMÀT already does today?"
"We already use [Replo / Unbounce / Instapage / Adobe / Bloomreach] for this."
Those tools solve one piece of the puzzle — a single channel, a single page type, a single optimization loop. FERMÀT is the unified layer that sits across all of those touchpoints and lets behavioral insights from one inform all the others. We're not replacing your stack — we're giving it a brain. What do you know about your customers in paid search that your product page team never gets to use?
📍 Use the fragmented stack slide: "Here's what you have today vs. one data layer with full context."
💰 Budget & Timing
"We don't have budget right now / timing isn't right."
Understood. Let me ask — what channels are you spending on today, and what's your current optimization cycle time? The cost of fragmented optimization isn't visible on a budget line, but it shows up in conversion rates and customer acquisition costs. FERMÀT's 90-day POC is designed exactly for this: prove the lift first, build the business case, then expand. Backcountry and BISSELL both started this way.
📍 Offer the POC as the path. Frame it as: "Start with foundation, prove the lift in 90 days, present the business case to leadership."
"We're going through procurement / a platform migration right now."
FERMÀT is additive to almost any platform decision — not a replacement for your core commerce stack. We operate in a sandbox, separate from your core infrastructure. Your ecommerce backend stays protected. This means we can run a scoped POC concurrently with a platform migration without interfering. Some of our best customers (BISSELL on SFCC) started exactly this way.
📍 Offer a scoped POC that doesn't require full procurement commitment while they move through the broader process.
⚔️ Competitive
"We're also looking at Replo / Shogun."
Replo and Shogun are great Shopify page builders for SMB and mid-market brands. If you're on SFCC, Magento, or a custom platform, they simply don't have the native depth FERMÀT does. Beyond that, they're single-channel, single-function tools — they don't unify behavioral data across touchpoints or provide cross-channel intelligence. Ask yourself: does Replo know what your email traffic tells you about product intent? FERMÀT does.
📍 Kill shot: "What platform are you on? If SFCC or custom — Replo isn't built for this."
"We're investing in Profound / AI search tools."
Profound and FERMÀT are actually complementary — Profound optimizes how your brand shows up in AI discovery (Perplexity, ChatGPT). FERMÀT makes your brand's content shoppable and citeable within those same AI models, while also optimizing the on-site and cross-channel experience after discovery. They're different layers of the same AI commerce stack. GNC uses FERMÀT to dominate AI search citations — 200%+ week-over-week growth in LLM citations.
📍 Position as the AI search + on-site layer, not versus Profound.
🔧 Technical
"We're worried about our core site being impacted / page speed."
FERMÀT operates entirely in a sandboxed environment separate from your core commerce platform. Your ecommerce backend is protected. You maintain full visibility into what we're gathering and how we're optimizing. Rollback is instant. And our generated experiences are built with performance in mind — BISSELL runs FERMÀT on top of SFCC with no core site impact. This is a risk mitigation strategy, not a risk creator.
📍 Reference BISSELL on SFCC as the enterprise proof point for safe, zero-engineering-lift deployment.
"We need to handle data privacy / security / DPA."
We're enterprise-ready on security: SOC2 compliant, SSO support, robust access controls, and we'll execute a DPA alongside your MSA. For companies with heightened privacy sensitivity (like Gen Digital), we have a dedicated security questionnaire process and can engage your InfoSec team directly. This is a standard part of our enterprise onboarding process, not an edge case.
📍 For Gen Digital specifically: have DPA ready to send, engage InfoSec early.
Enterprise TAM List
189 accounts from RevOps Google Sheet · SFDC data pulled by Account ID · Owners TBD — updating later this week. Click any row to expand signals, AI strategy, C-level changes, and SFDC pipeline.
Total Accounts
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Late Stage (Verbal+)
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Pipeline ARR
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Active Pipeline
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Accounts with open opps
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Call Insights
Sourced from Glyphic call transcripts, #presales-call-notes, and #sales-coaching. Glyphic VISION/MIXED/FEATURES scores reflect whether calls were led with vision or features.
🧠 Recurring Themes Across Calls
Top Pain Points
Engineering bottleneck on experience creation
Data siloed by channel — no cross-channel intelligence
Slow time-to-launch for new experiences
Not visible in AI search / LLM results
Static product pages losing conversion
Common Objections
Platform compatibility (Magento/SFCC)
Budget timing / procurement
Already evaluating Replo/Shogun
Security / DPA requirements
Internal build vs. buy debate
Deal Accelerators
Champion who facilitates EB access (Harsh model)
Cross-channel data pain is quantified
Reference customer on same platform
90-day POC offered with clear metrics
Vision-led call (🟢 Glyphic VISION score)
David's BridalPre-Sales🟢 VISIONGlyphic · Feb 2026
Pain / Constraint
Running on Magento with $10M+ annual ad spend. On-site experiences are static and not optimized per channel or context. Engineering backlog prevents rapid experience launches. Cross-channel behavioral data is siloed — paid signals never reach product pages.
MEDDPICC Snapshot
Pain: ConfirmedChampion: VP EcommPlatform: MagentoSpend: $10M+/yr
FERMÀT Fit
Strong ICP — Magento, massive spend, clear pain around cross-channel optimization and speed. Champion engaged and internally sold on vision. FERMÀT's Magento integration story is the differentiator here vs. Replo/Shogun.
Risks / Next Step
Need exec sponsorMust demo Magento integrationProcurement complexity
TubeSciencePre-Sales🟢 VISION#presales-call-notes
Pain / Context
Agency producing high-volume video creative. On-site experiences don't adapt to the creative context — behavioral insights from video engagement never reach the on-site experience. Cross-channel intelligence gap is directly costing clients ROAS.
FERMÀT Angle
FERMÀT unifies behavioral signals from video creative engagement with on-site experience optimization. Agency resell / white-label opportunity alongside direct deal. Explore FERMÀT as a client-facing value-add in their performance stack.
TapestryLegal Redlines🟢 VISION#enterprise + #presales-call-notes
Deal Summary
Multi-brand luxury group (Coach, Kate Spade, Stuart Weitzman). Vision-led sales process completed. Champion confirmed. Economic buyer engaged. Q1 2026 close target. All-hands urgency on legal.
Action Required
🔴 HIGHEST PRIORITY. Do not let slip to Q2. Assign legal resource. Get to redlines resolution this week. This is the largest deal in current pipeline.
TonalPre-Sales🟢 VISION#sales-coaching · Glyphic
Coaching Summary
Strong vision-led call. AE established constraint early — high CAC on hardware acquisition campaigns, on-site experience not reflecting the software+hardware value bundle. Drew compelling future state. Champion engaged throughout.
Signals + Next Step
High CAC hardware categorySoftware/hardware bundle storyChampion: VP Growth
Demo with performance marketing team. Pilot on top-spending hardware acquisition experiences.
Demo with performance marketing team. Pilot on top-spending hardware acquisition experiences.
Power DigitalPre-Sales🟡 MIXED#sales-coaching · Glyphic
Coaching Summary
Started with vision elements but drifted into product features without establishing constraint clearly. Agency context — need to reframe entirely around client ROI and agency margin, not internal platform evaluation.
Recovery Plan
Reframe to agency revenue modelLead with client ROAS impactExplore resell / margin opportunity
Reset conversation: How does FERMÀT improve client results → strengthen agency retention and upsell?
Reset conversation: How does FERMÀT improve client results → strengthen agency retention and upsell?
EcomExpertsPre-Sales🔴 FEATURES#sales-coaching · Glyphic
Coaching Summary
Feature-led conversation from the start. Demo shown too early before establishing pain or vision. Conversation became a checklist evaluation — comparing features vs. competitors — instead of a vision sale.
Required Actions
Do NOT advance without resetMap constraint before any further demo
Send vision-first email sequence. Schedule constraint discovery call. AE coaching session before re-engagement.
Send vision-first email sequence. Schedule constraint discovery call. AE coaching session before re-engagement.
Competitive Intelligence
Full battle cards, positioning, objection handling, and landscape context. Core framing: FERMÀT is generative commerce infrastructure — not a page builder, not a personalization engine, not an A/B testing tool. We unify behavioral data across every channel and generate AI-native experiences from it. No single competitor does all three.
Category Positioning — Lead With This
FERMÀT is the generative commerce platform. The category we own: behavioral data unification → AI-native experience generation → cross-channel conversion optimization.
Every competitor solves one layer. Replo/Shogun build pages. Dynamic Yield personalizes on-site. Optimizely runs experiments. Spangle/Jurni generate AI storefronts and funnels for SMBs. Profound optimizes AI search visibility. FERMÀT is the only platform that connects all entry points (search, social, email, influencer, merch) to a single behavioral data layer and uses that data to generate and optimize experiences autonomously — without engineering lift. That's the structural moat.
🗺 Competitive Landscape — Where They Play
Page Builders
Replo · Shogun
Shopify-only landing pages. SMB/MM. No data layer, no AI, no SFCC.
Personalization / Testing
Dynamic Yield · Optimizely
On-site A/B and recommendations. 3–9 month impl. Rule-based, not agentic.
Agentic Commerce / AI Funnels
Spangle · Jurni
AI-generated storefronts and funnels. Shopify-only. SMB/MM. No enterprise data layer or SFCC support.
AI Search Visibility
Profound · Goodie AI
Brand citation in ChatGPT/Perplexity. Complementary, not competitive.
Engagement / CDP
Bloomreach · Insider · Nosto
Cross-channel engagement, email/push, product recs. Different buyer.
Generative Commerce
FERMÀT
Behavioral data unification + AI-native experience generation. All entry points. No engineering lift.
Capability Comparison Matrix
| Capability | FERMÀT | Replo | Shogun | Dynamic Yield | Optimizely | Spangle | Jurni | Profound | Bloomreach |
|---|---|---|---|---|---|---|---|---|---|
| Unified cross-channel behavioral data layer | ✅ Core | ❌ | ❌ | ⚠️ On-site only | ⚠️ On-site only | ❌ | ❌ | ❌ | ⚠️ Partial |
| SFCC / Magento / Custom platform depth | ✅ Native | ❌ Shopify only | ❌ Shopify/BigC | ⚠️ API-based | ⚠️ API-based | ❌ Shopify only | ❌ Shopify only | ❌ | ⚠️ Partial |
| AI search / LLM citation optimization | ✅ Core (GNC 200%+) | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ✅ Core | ❌ |
| Personalized experiences — any entry point | ✅ Search/Email/Social/Influencer | ❌ | ❌ | ⚠️ On-site | ⚠️ On-site | ⚠️ ProductGPT only | ❌ | ❌ | ⚠️ Email/push |
| Zero / low engineering lift to go live | ✅ Days | ✅ Self-serve | ✅ Self-serve | ❌ 3–6 months | ❌ 3–9 months | ✅ Self-serve | ✅ Self-serve | ⚠️ Moderate | ❌ 2–6 months |
| Agentic AI — autonomous optimization | ✅ Core | ❌ | ❌ | ⚠️ Rule-based | ⚠️ Add-on | ⚠️ Seller Agent beta | ⚠️ Prompt-to-funnel | ❌ | ⚠️ Basic |
| Enterprise security / SOC2 / SSO | ✅ | ⚠️ | ⚠️ | ✅ | ✅ | ❌ Early-stage | ❌ Early-stage | ⚠️ | ✅ |
| 30+ behavioral data source integrations | ✅ | ❌ | ❌ | ⚠️ Own data | ⚠️ Own data | ⚠️ 30+ signals claimed | ❌ | ❌ | ⚠️ Limited |
| Influencer / creator commerce flows | ✅ Core | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
| Additive to existing stack (no rip-and-replace) | ✅ | ✅ | ✅ | ⚠️ | ⚠️ | ✅ | ✅ | ✅ | ⚠️ |
Battle Cards
⚔️ vs. Replo
Most common SMB alternative
Who They Are
YC-backed (W21), ~$10M raised. No-code landing page and section builder built exclusively for Shopify. Self-serve, growth-team focused. Strong Shopify App Store presence. ~$99–$299/mo pricing.
Their Strengths
Fast, beautiful page creation with zero dev. Large component library. Deep Shopify + Klaviyo integrations. Loved by performance marketing teams for quick LP iteration. Active community and responsive support.
Critical Weaknesses
100% Shopify-only — hard stop for SFCC/Magento/custom. No behavioral data layer. No AI optimization. No cross-channel personalization. Pages are static once built. No enterprise contracts or SLAs. Cannot handle influencer or multi-channel entry flows.
Handling "We're looking at Replo"
If SFCC/Magento: "Replo is Shopify-native — it won't work on your stack. This isn't a feature comparison, it's a platform incompatibility."
If Shopify: "Replo builds pages. FERMÀT builds intelligence. After Replo creates a page, someone still has to manually decide what to test, what to change, who to show it to. FERMÀT automates that entire loop using your behavioral data."
On price: "Replo is $299/mo. We operate at a different scale — our customers see $500K–$2M+ in incremental annual revenue. What's a 15% lift in conversion worth to you annually?"
On multi-channel: "Replo only handles your website pages. What happens when your influencer traffic hits a generic PDP? FERMÀT handles every entry point — influencer, paid search, email, social — with a personalized experience."
First question: "What platform are you on?"
They build pages. We build intelligence.
Typical win: prospect outgrows Shopify, migrates to SFCC, or needs data-driven optimization
⚔️ vs. Shogun
Incumbent at some MM accounts
Who They Are
~$100M raised (Series C, 2021). Visual page builder + frontend-as-a-service for Shopify and BigCommerce. Has "Shogun Frontend" for headless/Hydrogen builds. More mature than Replo, larger installed base, but growth has stalled.
Their Strengths
Shopify + BigCommerce support (broader than Replo). "Shogun Frontend" headless storefront option. Built-in A/B testing feature. Larger enterprise contracts possible. More brand name recognition than Replo at mid-market.
Critical Weaknesses
Shopify/BigCommerce-only — no SFCC/Magento. Shogun Frontend requires heavy dev investment to build and maintain. A/B testing is basic with no AI. No behavioral data layer or cross-channel optimization. Reported support and product quality issues at scale. Growth stagnated post-2021 funding.
Handling "We already use Shogun"
On displacement: "Shogun manages your pages. FERMÀT generates new experiences from behavioral data and optimizes them autonomously. Different jobs. You can run FERMÀT alongside Shogun on your highest-value traffic flows first — no rip-and-replace required."
On Shogun's A/B testing: "How many experiments is your team running per month on Shogun? 3? 5? FERMÀT runs hundreds of micro-optimizations simultaneously across every entry point — automatically."
On Shogun Frontend: "Shogun Frontend is a dev-heavy investment. Our integration is additive — we don't replace your frontend, we layer intelligent experience generation on top."
Position as additive — start on highest-value flows alongside Shogun
Target: accounts using Shogun for basic pages who need AI-driven optimization + multi-channel coverage
⚔️ vs. Dynamic Yield
Most common enterprise incumbent
Who They Are
Acquired by Mastercard in 2022 (~$300M). Enterprise personalization, A/B testing, and product recommendations. Originally founded 2011. Strong retail brand — McDonald's, IKEA, Sephora, Urban Outfitters. Post-acquisition, now positioned inside Mastercard's commerce data infrastructure.
Their Strengths
Deep on-site personalization engine. Strong recommendation algorithms. Mastercard transaction data layer is a genuine differentiator. Omnichannel triggers (email/push/web). Solid SOC2, SSO, enterprise SLAs. Established brand trust at enterprise procurement level.
Critical Weaknesses
3–6 month implementation + dedicated implementation team. Rule-based optimization — not agentic. No AI search/LLM coverage. Mastercard acquisition → slower product velocity, financial-services company culture. Expensive: $100K–$500K+/yr. On-site only — no influencer/off-site entry points.
Handling "We use / are evaluating Dynamic Yield"
On timeline: "DY is a 3–6 month implementation with significant ongoing engineering dependency. We're live in days and run independently of your tech team after onboarding."
On capability gap: "DY optimizes the site you already have. FERMÀT generates net-new experiences from behavioral data you're not capturing yet — influencer flows, paid search LPs, email entry points. These are different surfaces DY doesn't touch."
On the acquisition: "Since the Mastercard acquisition, DY's roadmap has slowed considerably. They're operating inside a financial services company now — not a product-led commerce platform. Their AI investment has stalled."
On coexistence: "Many of our customers run DY for on-site and FERMÀT for off-site entry points. We're additive — we handle the surfaces DY doesn't reach."
Kill shot: "DY optimizes the site you have. FERMÀT generates experiences from data you're not capturing yet."
Play: FERMÀT for off-site entry points + influencer flows, DY stays for on-site personalization
⚔️ vs. Optimizely
Common enterprise objection / incumbent
Who They Are
The largest experimentation platform. Multiple acquisitions (Episerver → Optimizely rebrand 2021). Broad suite: web A/B testing, feature flagging, CMS, personalization, commerce. Serves enterprise across retail, media, financial services. ~$300M ARR. Heavy enterprise sales motion.
Their Strengths
Gold standard for A/B testing and feature flagging. Strong enterprise relationships — often already embedded. Broad suite under one contract. Statistical rigor in experiment analysis. Developer-grade feature flag tooling. Well-understood by enterprise procurement.
Critical Weaknesses
3–9 month implementation. Optimization requires a dedicated CRO team — not agentic. Product bloat from acquisitions = slow velocity. Commerce-specific features weak vs. DY. Very expensive: $150K–$1M+/yr. No AI search coverage. Suite modules don't share a unified data layer.
Handling "We use Optimizely for experimentation"
On manual vs. agentic: "How many experiments is your CRO team running per month? 5? 10? FERMÀT runs hundreds of micro-optimizations simultaneously across every entry point — without your team designing each one."
On incumbency: "Optimizely is an experimentation platform — it runs the tests your team designs. FERMÀT is an autonomous optimization engine — it designs, runs, and iterates without your team. These are complementary, not redundant."
On suite fragmentation: "Optimizely's CMS, personalization, and experimentation modules don't share a data layer — they're acquired products stitched together. FERMÀT is purpose-built with a single behavioral data layer from the ground up."
On off-site coverage: "Optimizely is on-site only. What's converting your influencer traffic? Your paid search traffic? Your email clicks? None of those are surfaces Optimizely touches."
Kill shot: "Optimizely runs the experiments your team designs. FERMÀT runs experiments your team would never have time to design."
Play: sell FERMÀT for off-site surfaces, keep Optimizely for on-site A/B infrastructure
⚔️ vs. Builder.io
Occasional overlap in visual page creation
Who They Are
~$50M raised. Headless CMS and visual development platform targeting dev teams on Next.js, Qwik, and other modern frameworks. Unique angle: visual editor that outputs production-ready code. Broad framework support. "Builder AI" adds AI-assisted content generation.
Their Strengths
Genuinely platform-agnostic — not Shopify-locked. Strong visual editor with real code output. Good for marketing teams at headless/composable brands. SOC2 certified. Growing enterprise base at brands running custom/headless commerce.
Critical Weaknesses
Requires dev resources for setup and ongoing maintenance. No behavioral data layer. No autonomous optimization. Content management, not conversion intelligence. "Builder AI" is generative content creation, not agentic commerce optimization. Primarily a publishing/CMS tool.
Handling "We use Builder.io"
Complementary framing: "Builder manages your content and visual layer. FERMÀT handles behavioral intelligence and experience optimization. Builder is your CMS. FERMÀT is your conversion intelligence layer running on top of it. These are different jobs — we're additive."
Position as complementary — Builder for content management, FERMÀT for conversion intelligence
Different primary buyer: dev teams (Builder) vs. growth/marketing teams (FERMÀT)
🤝 vs. Profound — Complementary
Partner, not competitor
What Profound Does
AI search optimization platform — helps brands get cited and recommended in ChatGPT, Perplexity, Google AI Overviews, and other LLM-powered surfaces. Tracks brand citation share, analyzes LLM prompt patterns, and recommends content changes to improve AI search visibility. Early-stage, high traction.
The Complementary Stack
Profound = get discovered in AI search (top-of-funnel visibility)
FERMÀT = make that AI-referred traffic land on shoppable, citation-structured, conversion-optimized experiences (mid + bottom funnel)
GNC proof: 200%+ WoW citation growth in LLM results using FERMÀT's AI-native content architecture.
FERMÀT = make that AI-referred traffic land on shoppable, citation-structured, conversion-optimized experiences (mid + bottom funnel)
GNC proof: 200%+ WoW citation growth in LLM results using FERMÀT's AI-native content architecture.
Frame as the AI commerce stack: Profound gets you found → FERMÀT converts the traffic
GNC: 200%+ WoW LLM citation growth
Prospect using Profound = strong AI-forward signal → ideal FERMÀT buyer
⚔️ vs. Build In-House
Most dangerous objection at enterprise
The Objection
"We have the engineering team to build this." Usually comes from CTOs or technical buyers at large brands with strong internal platforms. Sometimes triggered by recent bad vendor experience or internal platform pride. Often used as a stall tactic with no real conviction.
The Reality
A unified behavioral data layer + 30+ source integrations + agentic experience generation + AI search optimization + SFCC/Magento native rendering is a multi-year engineering investment. FERMÀT has been building this infrastructure for years with a specialized ML/AI engineering team. Opportunity cost of eng focus is the real argument.
Counter-Arguments
The Backcountry proof point: "Backcountry built their own personalization system. Then they replaced it with FERMÀT and saw 36% conversion lift in days — not because their team was bad, but because maintaining and iterating on this infrastructure is a perpetual tax on engineering focus."
The scope argument: "What you'd build is a page builder. FERMÀT is: 30+ behavioral data integrations, agentic optimization loops, AI search structuring, influencer flow management, SFCC/Magento native rendering, and an ML layer that gets smarter with every shopper. The scope is larger than it appears."
The opportunity cost argument: "Every sprint your engineering team spends on commerce infrastructure is a sprint not spent on your core product. What's the value of redirecting 3–5 engineers back to your roadmap for 18 months?"
The time-to-value argument: "You could start building today and be live in 18 months. We can have you live on your highest-traffic entry points in 2 weeks and generating incremental revenue immediately."
Backcountry replaced their own system → 36% lift in days
Frame as opportunity cost of eng focus, not capability question
Never say "you can't build it" — say "the scope is larger than you think, and our ROI is faster"
⚔️ vs. Spangle AI
Closest direct competitor — agentic commerce
Who They Are
$15M Series A (Jan 2026, ~$100M valuation). Founded by Maju Kuruvilla (former Bolt CEO) and ex-Amazon execs. Backed by Madrona Ventures, NewRoad Capital Partners. Proprietary "ProductGPT" large product model + "Seller Agent" for real-time agentic optimization. Customers include REVOLVE, Steve Madden, Alexander Wang, Anne Klein, WHP Global. Shopify + Meta + Google Ads native integrations.
Their Strengths
Strong agentic framing and "generative storefront" positioning — closest to FERMÀT's language. Real-time context-based personalization (no cookies, no PII). ProductGPT is a genuine moat claim — brand-specific intelligence that compounds over time. No-code implementation. Fashion/luxury ICP well-matched to REVOLVE/Steve Madden pedigree. $15M to build brand and hire — now a real competitor on the positioning battlefield.
Critical Weaknesses
Shopify-native — same hard stop as Replo/Shogun for SFCC/Magento prospects. No SFCC/Magento/custom platform support confirmed. No influencer/creator commerce flow management. No AI search / LLM citation optimization layer. No unified cross-channel behavioral data layer (30+ sources). Just raised — limited proven enterprise track record vs. FERMÀT's existing customer base. Narrower ICP (fashion/apparel-forward).
Handling "We're looking at Spangle"
On platform: "Spangle is Shopify-native — if you're on SFCC, Magento, or a custom platform, it's a non-starter. What platform are you on?"
On data depth: "Spangle optimizes the shopping journey using session context and campaign signals. FERMÀT unifies 30+ behavioral data sources — paid search, email, social, influencer, on-site — into a single layer that trains across every touchpoint. That's a different depth of intelligence."
On track record: "Spangle just emerged from stealth with a Series A in January 2026. FERMÀT has proven enterprise deployments with Backcountry, GNC, New Era Cap, Bissell — and a track record of conversion lift you can reference by name."
On AI search: "Spangle doesn't have an AI search / LLM optimization layer. GNC achieved 200%+ WoW citation growth in ChatGPT and Perplexity through FERMÀT. If AI search is part of your strategy, Spangle doesn't cover it."
On influencer: "What happens when your influencer traffic lands on a generic PDP? Spangle handles ad landing pages. FERMÀT manages the full influencer commerce flow — dedicated shoppable experiences personalized per creator, per campaign, per audience."
First question: "What platform are you on?" — SFCC/Magento/custom = immediate win
FERMÀT: 30+ data sources, AI search, influencer flows, proven enterprise track record
Watch list: Spangle moving upmarket post-Series A — will likely pursue SFCC/Magento over time
Customers: REVOLVE, Steve Madden, Alexander Wang, WHP Global (fashion-forward ICP)
⚔️ vs. Jurni (getjurni.ai)
AI funnel builder — overlaps on LP/funnel creation
Who They Are
Early-stage AI funnel builder positioned as "The AI Funnel Engine for Commerce Growth." Targets DTC/ecommerce brands, particularly agencies and growth teams. Shopify + Klaviyo + Meta Ads native integrations. AI builds entire funnels from a text prompt — no dev, no design. Case study: Doubletiz jewelry, 2.6× CVR and 45% more engagement. Agency-focused distribution (fast funnel variation creation for clients).
Their Strengths
Extremely fast funnel creation — prompt to live in minutes. Campaign-context awareness: detects traffic source and adapts headline, copy, CTA automatically. Built-in testing and conversion logic with single-command updates. Good agency fit — rapid client LP variation at scale. AI CDP syncs ads, email, SMS, on-site behavior for smarter targeting. Low friction entry for SMB/DTC with no dev resources.
Critical Weaknesses
SMB/agency focus — not enterprise-grade. No SFCC/Magento/custom support. No unified 30+ source behavioral data layer. No influencer commerce flows. No AI search / LLM optimization. Funnel creation tool, not agentic optimization engine — still requires human direction per campaign. No proven enterprise brand reference customers. Early-stage, limited product depth vs. FERMÀT's years of infrastructure build.
Handling "We're looking at Jurni"
Displacement framing: "Jurni builds funnels fast from prompts — it's a creation tool. FERMÀT builds intelligence that autonomously optimizes experiences over time without your team directing each campaign. Different jobs."
On platform: "If you're on SFCC or Magento, Jurni doesn't support your stack. FERMÀT is native on both."
On enterprise fit: "Jurni is built for agencies and SMB DTC brands. FERMÀT's enterprise security, SLAs, SOC2, SSO, and integration depth is purpose-built for brands at your scale."
On optimization depth: "Jurni helps you create more funnel variants quickly. FERMÀT autonomously decides which variant wins, who sees it, and why — using 30+ behavioral data sources without your team running each experiment."
Jurni = fast LP creation. FERMÀT = autonomous intelligence layer. Different categories.
Most likely seen at agency accounts and SMB DTC — not typical enterprise target
If prospect is comparing: they may not yet understand the enterprise value prop — qualify harder
📊 Win / Loss Patterns
We Win When…
Prospect is on SFCC / Magento / custom platform — Replo/Shogun auto-eliminated
Multi-channel entry point problem — influencer + paid + email landing on generic PDPs
Prospect burned by DY/Optimizely implementation timelines or cost
AI strategy is a board-level priority — FERMÀT is the concrete action vs. vague roadmap
Large eng team that resents maintaining commerce infrastructure
Strong growth/marketing champion with exec sponsorship
We Lose When…
No exec sponsor — deal lives only in a CRO manager's backlog
Budget freeze / vendor consolidation — caught in a platform contraction
"Build in-house" used as a stall — no urgency to decide
DY already embedded — IT/security won't approve another vendor
Procurement drags past quarter-end — POC results can't create urgency
🌐 Know These Names
Bloomreach
CDP + email/SMS + product discovery + search. $1.7B valuation. "Loomi AI" personalization layer. Overlap in on-site personalization — but Bloomreach is a heavier platform and doesn't cover off-site entry points or agentic optimization. If it comes up: focus on time-to-value and off-site surfaces they don't reach.
Monetate / Kibo
Enterprise personalization + A/B testing. Kibo acquired Monetate + Certona. Product has stagnated post-acquisition. Position same as DY — implementation-heavy, rule-based, no AI. Not commonly seen head-to-head.
Intellimize
AI-powered website personalization — closer to FERMÀT's positioning but on-site only, B2B SaaS focus, no off-site entry points or cross-channel data unification. Counter: "Intellimize personalizes the website. FERMÀT personalizes every entry point into the website."
Nosto
Product recommendations + personalization + search + UGC. Strong in fashion/apparel (Shopify + Magento). Mid-market focus. Limited AI, no agentic optimization, no off-site coverage. Not a common direct competitor — different ICP.
Insider
Cross-channel engagement platform — email, push, web personalization, SMS. $1.2B+ valuation. Strong in EU/APAC markets. Primarily retention/engagement vs. FERMÀT's acquisition/conversion focus. Minimal direct overlap.
Discovery & Qualification
🔍 Platform & Stack Questions
Always ask first:
"What commerce platform are you running — Shopify, SFCC, Magento, something custom?" (SFCC/Magento = immediate Replo/Shogun killshot; custom = same)
Entry points:
"Where does your paid traffic land today — PDPs, generic LPs, or something personalized per campaign?" and "How much revenue runs through influencer channels? Where does that traffic land?"
Current stack:
"What do you have in place today for on-site personalization or A/B testing?" (DY/Optimizely = position additive for off-site; nothing = full greenfield)
Data layer:
"Do you have a CDP or unified data layer today? If yes — which one, and does it connect to your commerce platform in real time?" (Segment/mParticle/Klaviyo = good signals, we integrate)
Engineering dependency:
"How long does it typically take to get a new LP or PDP variant live today?" and "Is your eng team a bottleneck for marketing experiments?"
🎯 Qualification & Champion Questions
Business impact:
"What's your total annual digital commerce revenue? What would a 10–15% conversion rate lift mean in dollar terms?" (Qualify ROI quickly — sub-$50M digital = small deal)
AI strategy:
"Is AI a board-level or exec priority this year? What does your roadmap look like for AI in commerce specifically?" (Strong AI mandate = urgency to buy concrete capability)
Champion:
"Who owns conversion rate and growth experimentation on your team? And who owns the commerce technology decisions — is that the same person or separate?" (Need both marketing champion + IT/tech sign-off path)
Urgency:
"What's driving this evaluation right now — is there a specific event, season, or business objective that makes timing important?"
Disqualify early:
"Do you have budget allocated for commerce tech this year, or would this need to go through a new approval process?" (No budget + no champion = park it)
⚡ Quick Objection Cheat Sheet
| Objection | Source | One-Line Counter | Full Reframe |
|---|---|---|---|
| "We already have Dynamic Yield / Optimizely" | Enterprise incumbent | "DY/Optimizely is on-site only. FERMÀT handles every entry point they don't touch." | Sell additive — off-site surfaces (influencer, paid search, email) first. Prove incremental revenue. |
| "We're looking at Replo" | SMB / MM Shopify | "What platform are you on? If SFCC/Magento — Replo won't work. If Shopify — Replo builds pages, we build intelligence." | Platform question auto-closes it for non-Shopify. For Shopify, focus on data layer and optimization loop. |
| "We'll build it in-house" | CTO / tech buyer | "What you'd build in 18 months, we can deploy in 2 weeks. What's the opportunity cost of 3–5 engineers for that time?" | Backcountry proof point. Scope the real build (30+ integrations, ML layer, SFCC rendering). Use Backcountry. |
| "Your pricing is too high" | Procurement / CFO | "What's 10% lift on [their GMV] worth annually? Our contract is typically less than one month of incremental revenue at target conversion." | Anchor to revenue impact, not feature set. Most customers break even within 60–90 days of go-live. |
| "We don't have bandwidth right now" | Any | "Our typical integration is 2–3 days of engineer time. What we need from you is a URL, your data sources, and 30 minutes with your growth team." | Reduce perceived implementation lift. Offer to scope it specifically against their stack. |
| "We want to wait until Q[X]" | Procurement delay | "What specifically changes in Q[X]? If it's budget — we can structure the contract to start then. If it's bandwidth — we can run a no-code POC today while you evaluate." | Surface the real blocker. Offer a low-lift POC to maintain momentum without full commitment. |
| "AI is on our roadmap but not a priority yet" | Any | "GNC and New Era Cap said the same thing 12 months ago. Both are now pointing to FERMÀT as their AI commerce strategy." | Customers move fast once AI becomes a priority. Create urgency with competitor risk — ask if their competitors are moving. |
| "We need IT / security review first" | Enterprise | "We have SOC 2 Type II, SSO, data processing agreements, and standard MSA templates ready. What's the fastest path to get our security package to your team?" | Don't let security review become a stall. Proactively send security docs. Offer IT-to-IT call. |
💰 Commercial Positioning vs. Competitors
Competitor Pricing Context
Dynamic Yield
$100K–$500K+/yr + impl services
Optimizely (full suite)
$150K–$1M+/yr
Bloomreach
$80K–$300K+/yr
Shogun (enterprise)
$12K–$60K/yr
Replo
$1.2K–$3.6K/yr (self-serve)
Build in-house
$500K–$2M+ all-in (eng cost)
How to Talk About Our Price
Never defend price — anchor to revenue
"Our typical enterprise customer breaks even within 60–90 days of go-live. What's 10% conversion lift on your digital channel worth annually?"
vs. DY/Optimizely: total cost of ownership
"DY at $200K/yr + 6 months of implementation services + a dedicated CRO team = $400K–$600K year one, before you've seen a result. We can be live in 2 weeks."
vs. Replo: scale argument
"Replo is $3K/yr. We're not in the same category — our customers see $500K–$2M in incremental annual revenue. It's not a price comparison, it's a capability comparison."
Procurement framing
Position as growth investment, not cost. "This contract sits on the revenue side of the P&L, not the cost side. The ROI model makes it self-funding within a quarter."