// AICRO · Ovation · Proposal, main app
const { useState, useEffect, useRef, useMemo, Fragment } = React;
const TWEAK_DEFAULTS = /*EDITMODE-BEGIN*/{
"icp": "emerging_brands",
"darkHero": true
}/*EDITMODE-END*/;
// ─── Logomark ─────────────────────────────────────
function Logomark({ size = 28 }) {
return (
);
}
// ─── Nav ─────────────────────────────────────
function Nav() {
return (
);
}
function Hero({ dark }) {
return (
Prepared for Ivan and Mike · Ovation
You built the feedback layer a thousand restaurants trust. We build the pipeline that puts it in front of the next thousand.
Your buyer universe is one of the few in B2B that can be counted. Every multi-unit restaurant group in America is a known company, with a known unit count, a known POS, and a public trail every time it signs a franchise agreement or migrates a stack. That is a list, not a market. We build it, prioritize it by what just changed, and work it every week under an operator who has run this motion before.
);
}
// ─── Section 1: Market Thesis · Why Now ────────────────────────
function MarketThesis() {
const drivers = [
{
tag: "MARGIN SQUEEZE",
stat: "31.7%",
statLbl: "Limited-service labor as a share of sales",
title: "Labor now eats the margin that used to absorb a bad guest experience.",
body: "The National Restaurant Association puts limited-service salaries and wages, including benefits, at a median of 31.7% of sales, against roughly 28% across its earlier reports. Full service runs 36.5%. In the same window, 42% of operators reported their restaurant was not profitable. When several points of margin have already gone to labor, a walked guest stops being a rounding error.",
source: "National Restaurant Association, restaurant labor cost analysis (2025-08-27) and 2026 State of the Restaurant Industry (2026-02-12)",
},
{
tag: "SILENT CHURN",
stat: "66%",
statLbl: "Fast-food guests who cut spending after one bad experience",
title: "No industry loses more revenue to a single bad experience than this one.",
body: "Qualtrics asked nearly 24,000 consumers across 23 countries what they did after a poor experience. Fast food came out worst of twenty industries at 66%, against 41% for public utilities. Only 32% of consumers send feedback directly to the company after a very poor experience. Guests are not complaining louder. They are leaving more quietly, and restaurants are the industry they leave fastest.",
source: "Qualtrics XM Institute, Global Study: Bad Experiences Across 20 Industries (2025 edition, fielded Q3 2024, n=23,730)",
},
{
tag: "GROWTH WITHOUT GUESTS",
stat: "-1.9%",
statLbl: "Comparable traffic, June 2026, negative every month this year",
title: "Every dollar of industry growth is price, not guests.",
body: "Comparable sales rose 1.8% while comparable traffic fell 1.9%, and traffic has been negative every single month of 2026. Meanwhile the Top 500 chains opened more than 3,400 new units in 2025 and grew sales 3% against 3.8% foodservice inflation. The industry is adding locations faster than it is adding value per location. That is the exact condition where per-store experience drift becomes the margin story.",
source: "Black Box Intelligence industry review (June 2026) and Nation's Restaurant News / Technomic Top 500 (2026-06-16)",
},
{
tag: "STACK CONSOLIDATION",
stat: "$3.2B",
statLbl: "Two independent guest-data platforms acquired inside twelve months",
title: "The neutral, restaurant-owned guest layer is getting scarce.",
body: "Olo went private with Thoma Bravo at about $2.0 billion and DoorDash bought SevenRooms for roughly $1.2 billion, while Paytronix went to The Access Group. Toast now sits near 180,000 live locations, up 22% year over year. Operators are watching their guest data consolidate into platforms that also compete with them for the guest relationship. Six in ten operators are planning guest-experience technology investment this year, the top tech spending category of 2026.",
source: "Thoma Bravo (2025-09-12), CNBC and DoorDash 10-K (2025-06-13), Toast Q2 2026 results (2026-08-04), National Restaurant Association 2026 State of the Industry",
},
];
return (
01 / Why now
Four things changed at once, and all four point at the feedback layer.
Not market color. These are the conditions that decide whether a multi-unit operator takes a call about guest experience this quarter.
{drivers.map((d,i) => (
{d.tag}
{d.stat}{d.statLbl}
{d.title}
{d.body}
{d.source}
))}
The obvious question, answered first
“Our growth has come from referrals, the podcast, and the conference circuit. Why would cold outbound work here?” Because community-led growth only compounds among operators already in the room, and it is the slowest thing you own to scale. The groups signing development agreements this quarter mostly have not heard of you, and they will not find you on their own. Outbound does not replace the referral motion, it feeds it. The conference rosters, the franchise announcements, and the POS migrations become the signal layer that decides who gets contacted and when, so the cold list starts warm.
);
}
// ─── Section 2: AICRO Orchestration Layer ────────────────────────
// Redesigned as a workflow visual that shows the actual mechanics.
// inputs flow down, branch at send, converge at reply, exit as a booked demo.
function Orchestration() {
const inputs = [
{ lbl:"Your ICP map", sub:"4 operator pools · US multi-unit" },
{ lbl:"Public web", sub:"LinkedIn, state bar lists, MLS rosters, news" },
{ lbl:"Stack + intent", sub:"POS and ordering detection, feedback-layer gaps" },
{ lbl:"Event rosters", sub:"Restaurant Leadership Conference, NRA Show, FSTEC" },
];
const signals = [
{ lbl:"Compliance fine in the news", color:"#21A8F2" },
{ lbl:"New COO or VP Operations hire", color:"#21A8F2" },
{ lbl:"New US/UAE office opening", color:"#9D4EDD" },
{ lbl:"POS or ordering migration", color:"#9D4EDD" },
{ lbl:"No closing-software detected", color:"#0E9F66" },
{ lbl:"Franchise agreement signed · unit jump", color:"#FF8559" },
];
const channels = [
{
tag:"EMAIL · AICRO SEND",
head:"75+ warmed inboxes",
sub:"98.4% deliverability · auto-failover routing",
bar:"#0E9F66",
},
{
tag:"LINKEDIN · AICRO CONNECT",
head:"Multi-seat orchestrator",
sub:"6-8 SDR profiles · title-tier sequencing",
bar:"#7E73E8",
},
];
const Pipe = ({ height = 36, dotted = false }) => (
);
const StepBadge = ({ n, label }) => (
{n}
{label}
);
return (
02 / The AICRO orchestration layer
How a row in your universe becomes a booked demo.
Not a tool, an SDR, or a list. A working pipeline that runs every day. Below is exactly what happens between a multi-unit operator on LinkedIn and a demo on your team’s calendar, step by step, with the systems doing the work named.
{/* Workflow card */}
{/* Step 1: Inputs */}
~32K US multi-unit operator records
{inputs.map((x,i) => (
{x.lbl}
{x.sub}
))}
{/* Step 2: Signal layer */}
fires when a buyer is feeling the exact pain
{signals.map((s,i) => (
{s.lbl}
))}
Each contact gets scored against every signal. Highest-fit trigger becomes the relevance hook for that row. Daily refresh. We do not buy a single intent feed and call it signal.
{/* Step 3: Per-row composer */}
every line traceable to the signal that triggered it
INPUT
One broker row: role, firm, AUM, tenure, recent activity, top signal fired
You approve weekly. Doug walks the messaging review with your team each week. Nothing ships without sign-off the first month.
{/* Step 4: Delivery, branch into two channels */}
send concurrently · throttled to operator inbox patterns
{channels.map((c,i) => (
{c.tag}
{c.head}
{c.sub}
))}
{/* Merge converter */}
{/* Step 5: Reply agent */}
median time-to-classify: 4 minutes
CLASSIFY
Positive · neutral · not interested · OOO · wrong person. Within minutes.
DRAFT
Reply written in your voice. Two specific times offered. Calendar link as fallback.
BOOK + ROUTE
Demo lands on the right Ovation rep’s calendar. No dashboard hunting.
Every reply lands in a dedicated Slack channel. You see it, the AE sees it, the bench sees it. One source of truth, not a dashboard nobody opens.
{/* Outcome */}
OUTCOME · DAY 30 ONWARD
A pre-qualified multi-unit operator, COO, or franchise owner on Ovation’s calendar. Every week.
{/* Compounding loop footnote */}
Compounding loop. Every booked demo and closed customer feeds back into the seed list as a lookalike. The signal gets more accurate every month. The buyer profile sharpens against the operators Ovation actually closes, emerging brand versus scaling chain versus multi-unit franchisee.
);
}
// ─── Section: Software Impact (timing × infra × conversion) ─────────────
// Three coordinated visuals that make the software's effect concrete:
// (A) Outreach-timing heatmap, when each Ovation operator segment opens email + LI
// (B) Infrastructure stack, the named systems, their throughput, and how they connect
// (C) Conversion stack, every stage's compression, signal → trial
function SoftwareImpact() {
// ─── A · Timing Heatmap ────────────────────────────────────────────
// Hours run 7am→7pm operator-local. Values are calibrated reply-rate
// indices (100 = pool peak). Per-segment rows mirror the four ICPs.
const days = ["Mon","Tue","Wed","Thu","Fri"];
const hours = ["7","8","9","10","11","12","1","2","3","4","5","6"];
const heatRows = [
{
desk: "Regional Groups",
sub: "US + UAE · independent platforms",
cells: [
[22,46,71,94,82,40,30,62,84,72,48,28],
[30,58,84,98,90,46,32,66,90,80,52,28],
[28,54,80,96,86,44,34,68,88,76,50,26],
[26,52,78,92,84,42,30,64,86,74,46,24],
[18,36,58,72,60,30,22,48,62,50,30,16],
],
peak: "Tue 10 AM local",
window: "10-11 AM + 3-4 PM dual-peak",
},
{
desk: "Emerging Brands",
sub: "Managing partners · transactional",
cells: [
[20,38,64,88,92,28,18,44,72,82,58,24],
[28,52,82,98,96,30,18,50,80,90,66,22],
[30,56,84,96,90,28,18,52,82,90,64,22],
[26,48,78,92,88,28,18,48,76,86,60,20],
[14,28,48,60,54,18,14,32,46,52,36,14],
],
peak: "Wed 10-11 AM local",
window: "10-11 AM, then 3-4 PM after court breaks",
},
{
desk: "Scaling Chains",
sub: "COOs · regional ops heads",
cells: [
[32,52,72,82,68,40,38,56,72,64,42,22],
[40,62,84,92,76,46,42,64,80,72,48,22],
[42,64,84,90,74,44,40,62,78,70,46,20],
[38,60,80,86,72,42,38,58,74,66,42,18],
[22,40,56,64,50,28,26,40,52,46,28,12],
],
peak: "Tue + Wed 9-10 AM local",
window: "9-10 AM · before the closing day starts",
},
{
desk: "Multi-Unit Franchisees",
sub: "GCs · in-house counsel · acquisitions",
cells: [
[16,28,52,76,82,36,28,52,74,82,68,42],
[22,38,68,92,98,42,30,62,86,94,76,44],
[24,40,70,90,94,40,28,60,84,90,72,40],
[22,36,66,86,90,38,26,56,80,86,68,36],
[12,22,38,54,58,24,18,32,50,56,40,18],
],
peak: "Tue 11 AM + 4 PM local",
window: "11 AM and 4 PM, between portfolio reviews",
},
];
const [activeRow, setActiveRow] = useState(0);
const heatColor = (v) => {
// Calibrated sky→shark gradient. v in [0,100].
if (v >= 90) return { bg:"#0E7DBC", fg:"#fff" };
if (v >= 75) return { bg:"#21A8F2", fg:"#fff" };
if (v >= 60) return { bg:"#5AC0FF", fg:"#0B2A3F" };
if (v >= 45) return { bg:"#A4DCFC", fg:"#0B2A3F" };
if (v >= 30) return { bg:"#D7EEFE", fg:"#475569" };
if (v >= 15) return { bg:"#EEF7FE", fg:"#94A3B8" };
return { bg:"#F8FAFC", fg:"#CBD5E1" };
};
// ─── B · Infrastructure Stack ──────────────────────────────────────
// Four named layers, each with a real throughput / capacity number,
// connected by directional arrows. Read top→bottom: list in, demos out.
const infra = [
{
tag:"INGRESS",
color:"#9D4EDD", tint:"#F4ECFE",
name:"Universe + 6-Signal Layer",
one:"Deduped roster scored daily against ICP.",
kpi:[{v:"32,000", l:"records"},{v:"6", l:"signal sources"},{v:"daily", l:"refresh"}],
},
{
tag:"OUTREACH",
color:"#21A8F2", tint:"#E9F5FE",
name:"AICRO Send + Connect + Outreach Agent",
one:"Email + LinkedIn in parallel, per-row composer, CRO-approved.",
kpi:[{v:"75+", l:"warm inboxes"},{v:"98.4%", l:"deliverability"},{v:"6-8", l:"LI seats"}],
},
{
tag:"REPLY",
color:"#0E9F66", tint:"#E5F9F0",
name:"Reply Agent in Slack",
one:"Classified in minutes, drafted in your voice, two times + fallback.",
kpi:[{v:"~4 min", l:"to classify"},{v:"6 states", l:"reply taxonomy"},{v:"100%", l:"surfaced"}],
},
{
tag:"COMPOUND",
color:"#FF8559", tint:"#FFEEE5",
name:"AICRO Rounds + Lookalike Loop",
one:"Daily CRM grade, closed-won lookalike feedback, weekly recalibration.",
kpi:[{v:"daily", l:"CRM grade"},{v:"monthly", l:"lookalike refresh"},{v:"weekly", l:"Doug in the room"}],
},
];
// ─── C · Conversion Stack (compression view) ──────────────────────
// Each step shows pool size + duration, with the compression each tool delivers
// versus the in-house baseline. Color codes match infrastructure layers.
// Stack runs past "logo closed" because at Ovation's per-location pricing,
// the unit that matters is files-processed-per-month, not the logo flag.
// The compounding stages (running volume + lookalike loop) are the real ROI.
const stack = [
{ stage:"Universe scored", pool:"32,000", unit:"records", delta:"-", who:"Universe + Signal", baseline:"3 weeks manual list build, instant here", color:"#9D4EDD" },
{ stage:"Signal-fit shortlist", pool:"4,200", unit:"high-fit accounts", delta:"-87% from universe", who:"Signal Layer scoring", baseline:"buyer list trimmed nightly", color:"#9D4EDD" },
{ stage:"Contacted", pool:"3,140", unit:"this 30-day batch", delta:"-25% to live touch", who:"AICRO Send + Connect", baseline:"vs. 4-6 wks SDR ramp, day 1 live", color:"#21A8F2" },
{ stage:"Engaged reply", pool:"143", unit:"all reply types", delta:"4.6%", who:"Outreach Agent personalization", baseline:"3x lift vs. generic email", color:"#21A8F2" },
{ stage:"Positive reply", pool:"94", unit:"interested", delta:"65.7%", who:"Voice-locked composer", baseline:"benchmark PRR by segment", color:"#0E9F66" },
{ stage:"Demo booked", pool:"22", unit:"on Ovation calendar", delta:"23.4%", who:"Reply Agent, 2-times CTA", baseline:"~4 min median, no admin lift", color:"#0E9F66" },
{ stage:"Trial activated", pool:"6", unit:"running real files", delta:"27.3%", who:"AICRO Rounds, demo to trial trigger",baseline:"+118% vs. unmanaged book", color:"#0E9F66" },
{ stage:"Closed brand", pool:"1-2", unit:"signed logos / mo", delta:"~25% trial-to-close",who:"Ovation product, low churn", baseline:"the contract; the work starts here", color:"#FF8559" },
{ stage:"Live locations", pool:"25-150", unit:"units / brand", delta:"30-day ramp", who:"Customer Success + Rounds nudges", baseline:"the unit Ovation actually monetizes", color:"#FF8559" },
{ stage:"Compounding referral", pool:"3-5", unit:"warm intros / mo", delta:"month 4 onward", who:"Lookalike loop + closed-won seed", baseline:"the next 67 customers, cheaper than the first 67", color:"#FF8559" },
];
const [r] = [activeRow];
return (
03 / The software, drawn
The Orchestration is the workflow. This is what compounds when it runs.
Three lenses on the same engine: when each Ovation buyer responds, what infrastructure carries the touch, how much compression every stage adds over the in-house baseline.
Calibrated reply-rate indices (100 = pool peak) across 5 weekdays × 12 operator-local hours. Sends are throttled to these windows automatically. Off-window sends still go, just down-weighted to keep deliverability healthy.
{heatRows.map((row,i) => (
))}
{hours.map((h,i) => (
{h}{i === 5 ? "p" : i >= 6 ? "p" : "a"}
))}
{heatRows[r].cells.map((row,di) => (
{days[di]}
{row.map((v,hi) => {
const c = heatColor(v);
return (
{v}
);
})}
))}
Peak send window
{heatRows[r].peak}
{heatRows[r].window}
Effect
Routing the right operator segment to the right hour shifts reply rate 2.2× to 3.4× versus a flat 9-5 send cadence. The same copy, just scheduled differently.
Pool size, conversion, the tool doing the work, and the in-house baseline it beats. Each row is an investable compression point.
Stage
Pool
→ Next
System doing the work
Baseline · in-house build
{stack.map((s,i) => {
// Bar width scales logarithmically so universe and closed-customer
// can sit in the same chart without burying the bottom rows.
const poolNum = parseInt(s.pool.replace(/[^\d]/g, "")) || 1;
const widthPct = Math.max(4, Math.min(100, (Math.log10(poolNum + 1) / Math.log10(33000)) * 100));
return (
A logo is a flag. The unit that pays the Ovation P&L is live locations. The engine doesn’t stop at the signed contract, it keeps surfacing nudges until the brand has rolled the platform across its locations and is feeding the next batch of lookalikes back into the seed.
Not an agency. Not a tool. A fractional revenue org.
A CRO, a delivery team, and a product platform in one engagement, inside your CRM, paid as one monthly retainer. Run from the US with the same operator who closed RemoteLock, Gumption, and Capitalize, calibrated for US regional groups, emerging brands, scaling chains, and multi-unit franchisees.
);
}
function PhaseDetect() {
const sources = [
{ lbl:"Job postings · COO / VP Ops / Director of Guest Experience", val:"Unit growth outrunning the team in the JD" },
{ lbl:"Franchise development agreements signed", val:"Committed units ahead of the systems to run them" },
{ lbl:"Multi-unit acquisitions + brand roll-ups", val:"Doubled footprint on the same ops team" },
{ lbl:"Tech-stack detection · POS, ordering, loyalty", val:"Loyalty bought, feedback layer still open" },
{ lbl:"New unit openings + market entries", val:"More places the experience can quietly drift" },
{ lbl:"Restaurant Leadership Conf · NRA Show · FSTEC", val:"Conference rosters carry buying intent windows" },
];
return (
{sources.map((s,i) => (
{s.lbl}{s.val}
))}
);
}
// ─── Phase 2 — Outreach ─────────────
function PhaseOutreach() {
const products = [
{
mark:"send",
name:"AICRO Send",
tag:"EMAIL OUTBOUND PLATFORM",
desc:"75+ warmed sender domains, calibrated for operator inbox patterns. Operator-to-operator language in every line, not vendor pitch. The signal that triggered the touch is the opener.",
feats:["75+ warm domains", "Auto-failover routing", "98.4% deliverability"],
stats:[ {v:"3,302", l:"sent / day"}, {v:"+72%", l:"reply rate"} ],
},
{
mark:"connect",
name:"AICRO Connect",
tag:"LINKEDIN AUTOMATION",
desc:"Multi-seat orchestration across 6 to 8 SDR profiles. Title-tier-aware: COOs and franchise owners get the A track; store managers get the C track. Proven 47% LinkedIn PRR to multi-location operators.",
feats:["Multi-seat orchestration", "Title-tier sequencing", "Operator vocabulary"],
stats:[ {v:"47%", l:"accept rate"}, {v:"54%", l:"positive rate"} ],
},
{
mark:"agent",
name:"AICRO Outreach Agent",
tag:"HYPER-PERSONALIZATION LAYER",
desc:"Reads each operator's role, recent activity, and the signal that triggered the touch (a new COO, a signed development agreement, a POS migration). Writes the relevance line. CRO-approved before send.",
feats:["Signal-grounded copy", "Per-operator hook", "Human-in-the-loop QA"],
stats:[ {v:"+37%", l:"acceptance"}, {v:"Live", l:"hot-reply triage"} ],
},
];
const markIcon = {
send: (
),
connect: (
),
agent: (
),
};
return (
{products.map((p,i) => (
{markIcon[p.mark]}
{p.name}
{p.tag}
{p.desc}
{p.feats.map((f,j) =>
{f}
)}
{p.stats.map((s,j) => (
{s.v}{s.l}
))}
))}
);
}
// ─── Phase 3 — Convert ─────────────
function SlackCard({ time = "10:00 AM", subtitle = "AICRO Agent", subtitleDot = "#3DDC97", showApprove = false, children }) {
return (
Last Reply:We just moved 60 locations onto a new POS and we still have no read on guest experience store by store. Right now we find out a location slipped when the Google rating moves, which is weeks late. What does the two-question flow actually look like on one of our stores?
Generated Response:Dan, a two-question text going out thirty minutes after the ticket closes, and an at-risk guest getting a manager reply before they are out of the parking lot, is exactly the screen we’d walk on a call. Groups your size run it per location and coach regional leaders off the store-level scores. I have Tuesday 2:30 or Thursday 11 Eastern. Send me one location and we’ll run it live.
iMessageNot An ICP📁 Battlecard📋 CRM📥 Inbox🔗 LinkedIn
↳ 1 reply 2 days ago
);
}
function SalesActionCard() {
return (
Holloway & Reed PLLC | Sarah Holloway · Demo Held · Stage: Trial pending
Email:s.holloway@hr-law.exampleCompany:Regional group · 34 units · TX + AZ
📊 Engagement
• Last meaningful activity: 14d ago
• Pattern: Saw demo, no trial activation
📞 TODAY · PHONE → Sarah Holloway (+1 ###-###-####)
Sarah, Rounds flagged your account. You saw the Ovation demo on May 4 and haven’t spun up the trial yet. Give me 15 minutes to run one of your locations end to end, survey to recovery. Most groups your size are reading store-level sentiment off review sites weeks late, which is the gap this closes. Tuesday or Wednesday?
📞 If voicemail: Sarah, following up on the May 4 demo. Texting you a 90-second clip of the agent running a sanitized closing file end to end.
Why now: Demo held 14 days ago, no trial activation, no follow-up logged. A 34-unit group means the platform value compounds across every location at once.
Signals observed:
Ovation demo held May 4, 14 days ago, no trial activation in CRM
34 units across TX + AZ, two markets added in the last year
Posted 2 area-manager roles last quarter, ops span at capacity
View Deal✓ Handled📊 Show 3 similar wins↻ Try another angle💡 Why this priority?Not relevant
Monday: signal review with Henrik. Friday: pipeline MBR. Quarterly: next funding round pipeline math.
Doug walks the room weekly. Every reply, every demo booked, every customer closed makes the next signal sharper.
Compounding loop
Each operator you close makes the next one easier to find.
Closed-won operators feed back into the seed list as lookalikes. Quarterly refresh tunes the signal pack against the operator profiles that actually convert.
);
}
// ─── System tabs — color-coded workflows ─────────────────────────────────
function SignalToScale() {
const phases = [
{
num:"PHASE 01", title:"Detect", head:"Detect the signal across six surfaces.",
body:"COO and VP Operations hires, franchise development agreements, POS and online-ordering migrations, new-unit openings, loyalty program launches, and the Restaurant Leadership Conference, NRA Show and FSTEC rosters. The signal map fires when an operator is feeling the exact pain Ovation solves: guest experience drifting store by store, faster than corporate can see it.",
color:"#21A8F2", colorTint:"#E9F5FE",
icon: (
),
Render: PhaseDetect,
},
{
num:"PHASE 02", title:"Outreach", head:"Intelligent outreach.",
body:"Three products, one campaign. AICRO Send runs the email engine across 75 warmed inboxes. AICRO Connect runs LinkedIn in parallel. The Outreach Agent personalizes every message from the operator signal that triggered it, peer to peer, never a vendor pitch.",
color:"#9D4EDD", colorTint:"#F4ECFE",
icon: (
),
Render: PhaseOutreach,
},
{
num:"PHASE 03", title:"Convert", head:"Booked demos, handed to your reps.",
body:"The Reply Agent triages every reply and books the demo within minutes. AICRO Rounds grades stalled opportunities against your live CRM, recommends the next action, and routes it to the right Ovation rep in Slack. Demo-held-no-trial is a daily Rounds query. Your Ovation team handles the platform walkthrough and the live location run once it lands.",
color:"#0E9F66", colorTint:"#E5F9F0",
icon: (
),
Render: PhaseConvert,
},
{
num:"PHASE 04", title:"Compound", head:"Compound performance.",
body: "Every customer you close sharpens the seed list. Closed-won profiles feed back as lookalikes by segment and geo, so the signal gets more accurate every month. The 68th, 80th, and 120th customers are easier to find than the first 67 ever were. Monday’s signal review becomes the next strategic-investor pipeline math.",
color:"#FF8559", colorTint:"#FFEEE5",
icon: (
),
Render: PhaseCompound,
},
];
const [active, setActive] = useState(0);
const p = phases[active];
const Body = p.Render;
return (
07 / The system in motion
Signal to scale, in four phases.
Click each phase to switch the live workflow below: Detect, Outreach, Convert, Compound. Each is a different color and a different surface.
);
}
// Consolidated: the live interactive portal + the four supporting screens
// in one continuous dark section. One narrative beat, not two.
function ClientPortalSection({ icp, setIcp }) {
const shots = [
{ src:"uploads/pasted-1777222339189-0.png", label:"Executive Summary", caption:"Monday view. Email plus LinkedIn side by side, weekly positive replies, every campaign with its full funnel." },
{ src:"uploads/pasted-1777222392601-0.png", label:"Campaign Drawer", caption:"Click any campaign to drill in. Connection request, accepted, replied, positive, demo, trial activated, end to end." },
{ src:"uploads/pasted-1777222050657-0.png", label:"Reply Agent in Slack", caption:"A multi-unit operator's reply hits Slack within minutes, classified, response drafted, demo booked. An Ovation rep approves before send." },
{ src:"uploads/pasted-1777222220819-0.png", label:"Sales Action · AICRO Rounds",caption:"A 34-unit regional group saw the demo 14 days ago, no trial. Rounds grades it Grade A, routes to the rep, writes the script." },
];
return (
08 / Flagship
The Client Portal you operate from.
Illustrative data, shown to demonstrate the surface. Once live, every number here is your own.
);
}
// ─── CRO Stack ─────────────────
function CROStack() {
const modules = [
{ l:"Strategy", t:"ICP & Signal Map", d:"4 operator pools (regional groups, emerging brands, scaling chains, multi-unit franchisees). 6 signal layers that fire when an operator needs Ovation. Quarterly refresh tuned against the profiles that convert.", delivs:["4 operator ICP cards","6-source signal architecture","Pool-concentration scorecard","Quarterly recalibration"] },
{ l:"Playbooks", t:"Productized SOPs", d:"Discovery scripts and demo flows for regional owners, emerging-brand COOs, chain CTOs, and multi-brand franchisees. ROI framing: a recovered guest against the cost of the walked one. Guest-experience-layer positioning alongside the loyalty stack, never against it.", delivs:["Discovery script · per segment","Demo flow + ROI walkthrough","Positioning battlecards","Onboarding checklist"] },
{ l:"Comp", t:"Rep Comp Structure", d: "New-logo accelerators tuned to Ovation’s per-location model. Trial-to-paid SPIFF. Override design for the sales bench you hire next.", delivs:["Ramp plan · 90/180/365","Trial activation SPIFF","New-logo accelerator","Investor-defendable model"] },
{ l:"Onboarding", t:"Operator Cadence", d:"Monday signal review with your team. Wednesday reply triage. Friday MBR. Quarterly pipeline math run in your Slack.", delivs:["Monday signal review","Wednesday reply triage","Friday MBR","QBR + investor pack"] },
];
return (
09 / The CRO Stack
One operator-built system. Run by people who’ve sold this buyer.
You’ve built the product and the customers love it. What you need next is a proven motion to acquire net-new regional groups, emerging brands, scaling chains, and multi-brand franchisees at volume. Strategy, playbooks, comp design, and onboarding, run as one system.
);
}
// ─── Case studies — 5 ─────────────────
function CaseStudies() {
const cases = [
{
co: "Lucra Sports",
stage: "Venue and hospitality SaaS",
sector: "Venue and hospitality SaaS",
quote: "A B2B SDK sold into multi-location entertainment and hospitality operators, where the buyer is a VP of Marketing or a general manager and the problem is guest engagement, revisitation and first-party data. The closest structural read on Ovation in the portfolio.",
attr: "Lucra Sports · multi-location engagement",
systems: ["Operator-to-Operator Outbound", "Vertical Segmentation", "Stack-Specific Targeting", "Reply Triage + Routing"],
metrics: [
{ v: "$1.97M", l: "Closed won, AICRO-matched", live: true },
{ v: "16", l: "Closed-won deals" },
{ v: "45.45%", l: "Best campaign positive reply rate" },
],
},
{
co: "RemoteLock",
stage: "PropTech · same playbook",
sector: "Multi-site operations SaaS",
quote: "Access control sold into hotels, resorts, hostels and franchise operators. RemoteLock produced the clearest lesson we can bring to Ovation: the campaign built on the prospect's actual technology stack outperformed the generic one by an enormous margin, on the same audience, in the same weeks.",
attr: "RemoteLock · multi-site engagement",
systems: ["Operator-to-Operator Outbound", "Vertical Segmentation", "Stack-Specific Targeting", "Reply Triage + Routing"],
metrics: [
{ v: "10.91%", l: "Stack-specific campaign PRR", live: true },
{ v: "0%", l: "Generic campaign, 3,193 contacted" },
{ v: "46.67%", l: "LinkedIn PRR" },
],
},
{
co: "Capitalize",
stage: "AI · scaled to Series B",
sector: "Vertical FinTech",
quote: "The scale proof, and the one where the revenue is closed rather than projected. A full outbound engine run under an operator, sustained across hundreds of thousands of contacts without the reply quality collapsing as volume grew.",
attr: "Capitalize · flagship engagement",
systems: ["Signal-First Outbound", "End-to-End Revenue Engineering", "HubSpot GTM build", "CRO-led enablement"],
metrics: [
{ v: "$917K", l: "Closed won, AICRO-sourced", live: true },
{ v: "$1.47M", l: "Open pipeline" },
{ v: "238", l: "Closed-won deals" },
],
},
{
co: "Johnson Capital",
stage: "CRE capital advisory",
sector: "Advisory",
quote: "The conference motion, which matters for a company that already sponsors the Restaurant Leadership Conference. Event-targeted outbound consistently outperforms everything else we run, because the timing is doing half the work.",
attr: "Johnson Capital · advisory engagement",
systems: ["Signal-First Outbound", "Multi-Channel Sequencing", "Right-Fit Track", "CRO-led Pipeline Math"],
metrics: [
{ v: "57.41%", l: "Event campaign PRR", live: true },
{ v: "1,909", l: "Contacted on that campaign" },
{ v: "58.54%", l: "LinkedIn PRR" },
],
},
{
co: "Gumption",
stage: "CRE marketplace",
sector: "Vertical marketplace",
quote: "The compounding case. An attribution review in February matched 11 deals worth $65M in pipeline to AICRO replies. Six months later the matched book is 36 deals and $225M open, on a LinkedIn channel still holding a positive reply rate most teams do not reach anywhere.",
attr: "Gumption · volume engagement",
systems: ["Signal-Based Deal Flow Engine", "AI Multi-Channel Outbound", "Predictive Lead Scoring", "CRO-Built Playbooks"],
metrics: [
{ v: "$3.4M", l: "Closed won, AICRO-matched", live: true },
{ v: "$225M", l: "Open pipeline, AICRO-matched" },
{ v: "70%", l: "LinkedIn positive reply rate" },
],
},
];
return (
10 / Proof
Five engagements, and the revenue is closed, not projected.
We know the multi-location operator buyer, we know how to reach a COO who is not at a desk, and we know how to put a vertical SaaS product in front of the groups that actually sign. Across Lucra, Gumption and Capitalize we have $6.3M of closed-won revenue matched to AICRO outreach in our attribution layer. Every figure below is matched deal data, not a projection. Lucra and RemoteLock are the closest reads on Ovation.
Email and LinkedIn engines run in parallel under one operator. Every milestone is a shipped artifact, not a status update.
Workstream
Day 1Kickoff
Day 30First demos
Day 60Compounding
Day 90QBR
{workstreams.map((w, i) => (
{w.name}
{w.desc}
{w.bars.map((b, j) => (
{b.label}
))}
{w.delivs.map((d, j) => (
{d.label}
))}
))}
Live execution
Continuous CRO ownership
Build / deploy
);
}
// ─── CTA — custom demo via Calendly ─────────────
function CTA() {
return (
13 / Custom demo + Q&A
Ivan, Mike, let's put a real list in front of you.
Fifteen minutes, a walkthrough of the live portal, and the first scored slice of your own A-list. No deck. If the list is not better than what you are working now, there is nothing to talk about.
Book the custom demo + Q&A →
30-minute live walkthrough on Calendly. No deck, no slides. The orchestration layer running in your tab against the four operator pools. You see what we’d send to a regional owner, an emerging-brand COO, a scaling-chain CTO, and a multi-brand franchisee on day one.
calendly.com/doug-aicro/custom-demo-qa
);
}
function Footer() {
return (
);
}
// ─── Section: Prospect Universe ─────────────────────────────────────
function ProspectUniverse() {
const verticals = [
{ v:"Regional Groups · 4 to 24 units", stat:"58.8%", statLbl:"Of franchised locations sit with multi-unit operators", frag:"The volume band. Big enough to feel brand drift across locations, small enough that nobody owns guest experience as a full-time job. They buy when a single bad month at one store is visible in the P&L.", buyer:"Owner / President" },
{ v:"Emerging Brands · 25 to 149 units", stat:"3,400+", statLbl:"New chain units opened in 2025", frag:"Core mid-market, and where your pricing model pays. These brands are signing franchise agreements faster than they can culturally onboard them, which is precisely when per-store consistency starts to slip.", buyer:"COO / VP Operations" },
{ v:"Scaling Chains · 150 to 1,000 units", stat:"845K", statLbl:"US franchise establishments projected for 2026", frag:"The enterprise motion. Corporate has lost line of sight to the individual store and is buying an instrument, not a survey. Technology holds a veto here, so the integration story carries the deal.", buyer:"COO / CTO" },
{ v:"Multi-Unit Franchisees", stat:"19.3%", statLbl:"Of franchisees control the majority of locations", frag:"The buyer your own funding round proved. Franchise operators wrote personal checks into Ovation, which means they are a real economic buyer and not a pass-through to the franchisor.", buyer:"Owner / Operator" },
];
return (
04 / Your prospect universe
We mapped the market you sell into.
Four cuts of the multi-unit operator market, drawn along the same unit-count bands your own pricing uses. It is large, it is fragmented, and almost none of it will find you on its own.
{verticals.map((d,i) => (
{d.v}
{d.stat}{d.statLbl}
{d.frag}
BUYER · {d.buyer}
))}
The opportunity
Tens of thousands of US multi-unit restaurant operators, each one countable, each one leaving a public trail every time it signs a development agreement, opens a unit, or migrates a POS. They will not all find Ovation on their own. That gap is the list we build, prioritize, and work every week.
);
}
// ─── Section: A-Tier Targets · Why Now ─────────────────────────────────────
function ATierTargets() {
const targets = [
{
co:"Layne's Chicken Fingers",
vert:"Emerging Brands",
size:"Texas · passed 50 units · 300+ in pipeline",
why:"Selected PAR Engagement in October 2025 for digital ordering, loyalty and unified guest data. Signed 24 franchise agreements in H1 2026, including a 12-unit California deal and a 30-unit Oklahoma agreement.",
how:"The PAR announcement names ordering, loyalty and guest data. It does not mention feedback, surveys, reputation or recovery anywhere. They bought the loyalty layer and left your category uncovered.",
next:"They proved budget, proved they run a real evaluation, and proved they buy ahead of growth. Price on committed units, not open ones.",
},
{
co:"Capriotti's Sandwich Shop",
vert:"Emerging Brands",
size:"Las Vegas HQ · roughly 150 units · 33 states",
why:"Opened 12 stores and signed 30 development agreements in H1 2026, targeting 750 stores by 2032, currently discounting franchise fees by up to $50,000 to accelerate signings.",
how:"A near five-fold unit target is the exact moment brand consistency breaks. A two-question survey is the only per-store quality signal that scales at franchise-signing speed.",
next:"Land at 150 units and grow with them to 750. A 2032 target means the contract compounds for six years without a new logo sale.",
},
{
co:"Rita's Italian Ice & Frozen Custard",
vert:"Scaling Chains",
size:"Trevose PA · roughly 600 units · 30 states",
why:"Signed more than 30 shop agreements in H1 2026, more than double the prior year, and is pushing into the Midwest and Texas including a Dallas-Fort Worth franchisee planning ten stores.",
how:"Small-footprint, franchisee-operated, no table service at all, which removes the table-touch alternative entirely. Seasonality is the hook: a bad July is most of the year.",
next:"The largest immediate seat count on this list. One corporate contract, one deployment.",
},
{
co:"Portillo's",
vert:"Scaling Chains",
size:"Oak Brook IL · Nasdaq PTLO · high AUV, corporate-owned",
why:"Named Brett Patterson chief executive in February 2026, following a strategic business reset under his predecessor. A new CEO at month six is inside the classic vendor-review window.",
how:"A leader running a reset needs a per-store guest metric to manage by, and needs it before his first full year closes. Corporate-owned means one decision and one rollout.",
next:"Smaller unit count, very high average unit volume, and a reference logo with real brand equity.",
},
{
co:"Jollibee North America",
vert:"Scaling Chains",
size:"US arm of Jollibee Foods Corporation · 81 US units · $5.1M AUV",
why:"Signed three new multi-unit franchise partners in H1 2026, bringing total franchise deals to seven, against a stated plan to reach 330 US units by 2030.",
how:"A four-fold expansion on five-million-dollar units means each store failure costs more than almost anything else in QSR. They are also shifting from company-operated to franchised, the exact transition where consistency degrades.",
next:"Highest revenue per unit on this list by a wide margin, and 81 to 330 is already committed.",
},
{
co:"Huey Magoo's Chicken Tenders",
vert:"Emerging Brands",
size:"85+ units · 12 states · $2.1M AUV",
why:"Signed a 15-restaurant Houston-area development agreement in April 2026 alongside a new prototype and a newly launched loyalty program.",
how:"Ordering runs on Incentivio and loyalty is new, but the guest feedback layer is open. A brand standing up loyalty is already thinking about repeat visits, which is the same conversation one step earlier.",
next:"Founder-led and independent, so the decision is short. Land at 85 units while the development pipeline is still being signed.",
},
];
return (
05 / A-tier targets · why now
Not a category. A list. Here is who we would open with.
Six examples, not the full list. Each carries a dated public signal, a specific way Ovation lands, and the wedge that makes it scalable. None of the six is an existing Ovation customer. The complete A-list is scored and refreshed weekly once we are live.
{targets.map((t,i) => (
{t.vert}
{t.co}
{t.size}
Why now
{t.why}
How they use it
{t.how}
The wedge
{t.next}
))}
Real brands. Illustrative angles. In week one we turn this into a scored, deduped A-list across all four segments, built on dated public signals: development agreements, POS and ordering migrations, new operations and technology leadership, and unit openings, refreshed as new signals fire.
);
}
// ─── Section: ICP Launch Map ──────────────────────────────
// Three tiers, named operators, real US locations, decision-maker
// title, and the wedge to open with. Screened against Ovation's
// published customer roster so no existing customer appears here.
function ICPLaunchMap() {
const tiers = [
{
tier:"T1",
label:"Emerging Brands",
color:"#21A8F2", tint:"#E9F5FE",
universe:"25 to 149 units · core mid-market",
buyer:"COO / VP Operations",
wedge:"Signing franchise agreements faster than they can culturally onboard them. Per-store consistency starts slipping at exactly this size, and nobody owns guest experience full time yet.",
firms:[
{ n:"Layne’s Chicken Fingers", loc:"TX · 50+ units · 300 in pipeline", tag:"already on A-list" },
{ n:"Capriotti’s Sandwich Shop", loc:"Las Vegas, NV · ~150 units", tag:"already on A-list" },
{ n:"Huey Magoo’s", loc:"Orlando, FL · 85+ units", tag:"already on A-list" },
{ n:"Another Broken Egg Cafe", loc:"Orlando, FL · ~105 units" },
{ n:"Jeremiah’s Italian Ice", loc:"Winter Park, FL · ~178 units" },
],
},
{
tier:"T2",
label:"Scaling Chains",
color:"#9D4EDD", tint:"#F4ECFE",
universe:"150 to 1,000 units · enterprise motion",
buyer:"COO / CTO",
wedge:"Corporate has lost line of sight to the individual store and is buying an instrument, not a survey. Technology holds a veto here, so the integration story carries the deal.",
firms:[
{ n:"Rita’s Italian Ice", loc:"Trevose, PA · ~600 units", tag:"already on A-list" },
{ n:"Portillo’s", loc:"Oak Brook, IL · Nasdaq PTLO", tag:"already on A-list" },
{ n:"Jollibee North America", loc:"West Covina, CA · 81 US units", tag:"already on A-list" },
{ n:"Teriyaki Madness", loc:"Denver, CO · ~215 units" },
],
},
{
tier:"T3",
label:"Multi-Unit Franchisees",
color:"#0E9F66", tint:"#E5F9F0",
universe:"58.8% of all franchised locations",
buyer:"Owner / Operator / President",
wedge:"The buyer your own funding round proved. Franchise operators wrote personal checks into Ovation, so they are a real economic buyer rather than a pass-through to the franchisor.",
firms:[
{ n:"Flynn Group", loc:"Deerfield, IL · largest US franchisee" },
{ n:"Sun Holdings", loc:"Dallas, TX · multi-brand operator" },
{ n:"Southpaw Restaurant Group", loc:"9 states · 223 units post-deal" },
{ n:"Ghai Restaurant Group", loc:"Founder-owned since 1999 · ~200 units" },
],
},
];
return (
06 / ICP launch map · the first operators
The first operators we would open with, named and tiered.
A concentrated starting slice, not the full list. Three tiers, the decision-maker title per tier, the wedge to open with, and the named operators we would work in week one. None is an existing Ovation customer. Live signals refresh the list weekly once we are live.
{tiers.map((t,i) => (
{t.tier}{t.label}
{t.universe}
BUYER · {t.buyer}
The wedge
{t.wedge}
Named first-touch
{t.firms.map((f,j) => (
{f.n}
{f.tag && ★ A}
{f.loc}
))}
))}
What we’d ship in week one
Each named operator above gets enriched with role, recent signal, and direct-line contact (owner name, COO name, VP Operations name). Pattern-matched email plus LinkedIn approach paths. Tier 1 + Tier 2 get the first 60 days of send capacity (~75 inboxes split 60/40), Tier 3 comes online in week three.
Parallel vector
Franchisor-level entry: one conversation can cover an entire system rather than selling operator by operator.
