DomainValuation.site

The New Generation of Domain Valuation

Including Blockchain Domain Valution

Plan for The ANALYTICS.1 Dashboard

What the dashboard should be

The dashboard should be positioned as the control plane for an analytics namespace — not just “site analytics.”

The winning framing is:

ANALYTICS.1 = the Web3-native analytics endpoint
Web2 twin (e.g., analytics.website / analytics1.site) = onboarding + HTTPS access
The dashboard is where operators, partners, and subdomain tenants monitor performance, campaigns, and revenue across your ecosystem.

Use of the dashboard

This should be a multi-tenant analytics console that supports:

The WEB-3 network
Track each TLD site / landing page / partner page as a “tenant,” including:

traffic and conversion funnels
partner campaign performance
lead submissions / signups
lease inquiries / purchases
affiliate/referrer attribution

On-chain + off-chain in one view (dual stack)
Combine:

Web events (page views, CTA clicks, form submits)
Campaign metadata (UTM, referrer, partner)
On-chain signals (mints, leases, payments, wallet connects) if applicable

A “generic endpoint” model
What this offers:

tenant.analytics.1 as a namespace concept (even if it’s routed today)
api.analytics.1 for ingest/query endpoints (Web2-hosted but branded as the analytics root)
a “verified analytics” directory later (optional)

As well as providing Analytics for the Web-3 Network and deriving an income from this, the operator of Analytics1.Site and Analytics.1 will also be able to independently operate the sites and derive income externally.

Phased build

Phase 1 (MVP, 1–2 weeks):

Dashboard UI
Event tracking snippet (1 JS file)
Ingest endpoint (POST events)
Basic reports: KPIs, time series, top pages, top referrers, campaign performance, conversions

Phase 2 (Real product, 2–6 weeks):

Multi-tenant RBAC (admin / partner / viewer)
Alerts (spikes, drops, bot traffic)
Export + API keys per tenant
Consent + privacy settings (GDPR-friendly)

Phase 3 (Web3-native differentiator):

Wallet-based access (Sign-In With Ethereum)
On-chain indexing integration (The Graph / RPC indexing)
Proof/attestation of campaign metrics if you want an auditable layer

Architecture (simple and scalable)

Frontend: React + Tailwind + Recharts (fast to ship, good visuals)
Backend API: Node/Express (ingest + query)
Storage: start with SQLite/Postgres; scale to ClickHouse later
Event model: tenant_id, event, url, referrer, utm_*, wallet, timestamp

Production-ready starter code (Frontend + Backend)

Below is a working starter that can be can run in minutes:

A modern analytics dashboard UI (multi-tenant selector, date range, KPIs, charts, table)
A simple backend with:
- POST /api/events (ingest)
- GET /api/metrics (dashboard query)
- (Real sources can be wired later - (PostHog, Plausible, GA4 export, ClickHouse, Subgraphs, etc.).

1) Backend (Node + Express) — `server.js`

// server.js
// Minimal analytics ingest + metrics API (in-memory store for MVP).
// Replace the in-memory array with SQLite/Postgres/ClickHouse as you scale.

import express from "express";
import cors from "cors";

const app = express();
app.use(cors());
app.use(express.json({ limit: "1mb" }));

/**
 * Event schema (MVP):
 * {
 *   tenantId: "analytics.1" | "scotland.web-3" | ...
 *   type: "pageview" | "click" | "signup" | "purchase" | ...
 *   url: "/pricing"
 *   referrer: "https://example.com"
 *   utm: { source, medium, campaign, content, term }
 *   wallet: "0x..." (optional)
 *   ts: number (ms epoch)
 * }
 */

const events = [];

// Helpers
const clamp = (n, min, max) => Math.max(min, Math.min(max, n));
const parseMs = (v, fallback) => {
  const n = Number(v);
  return Number.isFinite(n) ? n : fallback;
};
const dayKey = (ms) => {
  const d = new Date(ms);
  const yyyy = d.getUTCFullYear();
  const mm = String(d.getUTCMonth() + 1).padStart(2, "0");
  const dd = String(d.getUTCDate()).padStart(2, "0");
  return `${yyyy}-${mm}-${dd}`;
};

app.post("/api/events", (req, res) => {
  const body = req.body || {};
  const now = Date.now();

  const tenantId = String(body.tenantId || "analytics.1").slice(0, 80);
  const type = String(body.type || "pageview").slice(0, 40);
  const url = String(body.url || "/").slice(0, 300);
  const referrer = String(body.referrer || "").slice(0, 300);
  const utm = body.utm && typeof body.utm === "object" ? body.utm : {};
  const wallet = body.wallet ? String(body.wallet).slice(0, 120) : null;
  const ts = clamp(parseMs(body.ts, now), now - 1000 * 60 * 60 * 24 * 365, now + 1000 * 60);

  events.push({
    tenantId,
    type,
    url,
    referrer,
    utm: {
      source: String(utm.source || ""),
      medium: String(utm.medium || ""),
      campaign: String(utm.campaign || ""),
      content: String(utm.content || ""),
      term: String(utm.term || ""),
    },
    wallet,
    ts,
  });

  // Keep memory bounded for MVP
  if (events.length > 200000) events.splice(0, events.length - 200000);

  res.json({ ok: true });
});

// Compute metrics for a tenant and date range.
app.get("/api/metrics", (req, res) => {
  const now = Date.now();
  const tenantId = String(req.query.tenantId || "analytics.1");
  const from = parseMs(req.query.from, now - 1000 * 60 * 60 * 24 * 30);
  const to = parseMs(req.query.to, now);

  const filtered = events.filter(
    (e) => e.tenantId === tenantId && e.ts >= from && e.ts <= to
  );

  // KPIs
  const pageviews = filtered.filter((e) => e.type === "pageview").length;
  const clicks = filtered.filter((e) => e.type === "click").length;
  const signups = filtered.filter((e) => e.type === "signup").length;
  const purchases = filtered.filter((e) => e.type === "purchase").length;

  const conversionRate = pageviews > 0 ? (signups / pageviews) : 0;

  // Time series (daily)
  const byDay = new Map();
  for (const e of filtered) {
    const k = dayKey(e.ts);
    if (!byDay.has(k)) byDay.set(k, { day: k, pageviews: 0, signups: 0, purchases: 0 });
    const row = byDay.get(k);
    if (e.type === "pageview") row.pageviews += 1;
    if (e.type === "signup") row.signups += 1;
    if (e.type === "purchase") row.purchases += 1;
  }
  const series = Array.from(byDay.values()).sort((a, b) => a.day.localeCompare(b.day));

  // Top pages
  const pageCounts = new Map();
  for (const e of filtered) {
    if (e.type !== "pageview") continue;
    pageCounts.set(e.url, (pageCounts.get(e.url) || 0) + 1);
  }
  const topPages = Array.from(pageCounts.entries())
    .sort((a, b) => b[1] - a[1])
    .slice(0, 10)
    .map(([url, count]) => ({ url, count }));

  // Top referrers
  const refCounts = new Map();
  for (const e of filtered) {
    if (e.type !== "pageview") continue;
    const key = e.referrer || "(direct)";
    refCounts.set(key, (refCounts.get(key) || 0) + 1);
  }
  const topReferrers = Array.from(refCounts.entries())
    .sort((a, b) => b[1] - a[1])
    .slice(0, 10)
    .map(([referrer, count]) => ({ referrer, count }));

  // Campaign performance
  const campCounts = new Map();
  for (const e of filtered) {
    const c = (e.utm?.campaign || "").trim() || "(none)";
    campCounts.set(c, (campCounts.get(c) || 0) + 1);
  }
  const campaigns = Array.from(campCounts.entries())
    .sort((a, b) => b[1] - a[1])
    .slice(0, 10)
    .map(([campaign, events]) => ({ campaign, events }));

  res.json({
    ok: true,
    tenantId,
    range: { from, to },
    kpis: { pageviews, clicks, signups, purchases, conversionRate },
    series,
    topPages,
    topReferrers,
    campaigns,
  });
});

const port = process.env.PORT || 8787;
app.listen(port, () => console.log(`API running on http://localhost:${port}`));

Run backend

2) Frontend (React + Tailwind + Recharts) — `App.jsx`

This is a complete dashboard UI. It expects the backend above on http://localhost:8787.

// App.jsx
import React, { useEffect, useMemo, useState } from "react";
import {
  LineChart, Line, XAxis, YAxis, Tooltip, ResponsiveContainer, CartesianGrid,
  BarChart, Bar, Legend
} from "recharts";

// Simple helpers
const fmtInt = (n) => new Intl.NumberFormat().format(n ?? 0);
const fmtPct = (n) => `${((n ?? 0) * 100).toFixed(1)}%`;
const daysAgoMs = (d) => Date.now() - d * 24 * 60 * 60 * 1000;

function Card({ title, value, subtitle }) {
  return (
    <div className="rounded-2xl border bg-white p-4 shadow-sm">
      <div className="text-sm text-gray-500">1testAnalytics2025</div>
      <div className="mt-1 text-2xl font-semibold text-gray-900">{value}</div>
      {subtitle ? <div className="mt-1 text-xs text-gray-500">{subtitle}</div> : null}
    </div>
  );
}

function Table({ title, columns, rows, rowKey }) {
  return (
    <div className="rounded-2xl border bg-white p-4 shadow-sm">
      <div className="mb-3 text-sm font-semibold text-gray-900">1testAnalytics2025</div>
      <div className="overflow-auto">
        <table className="min-w-full text-sm">
          <thead className="text-left text-gray-500">
            <tr>
              {columns.map((c) => (
                <th key={c.key} className="border-b px-2 py-2 font-medium">
                  {c.label}
                </th>
              ))}
            </tr>
          </thead>
          <tbody className="text-gray-800">
            {rows.map((r) => (
              <tr key={rowKey(r)} className="hover:bg-gray-50">
                {columns.map((c) => (
                  <td key={c.key} className="border-b px-2 py-2">
                    {c.render ? c.render(r) : r[c.key]}
                  </td>
                ))}
              </tr>
            ))}
            {rows.length === 0 ? (
              <tr>
                <td className="px-2 py-6 text-gray-500" colSpan={columns.length}>
                  No data in this range.
                </td>
              </tr>
            ) : null}
          </tbody>
        </table>
      </div>
    </div>
  );
}

export default function App() {
  const [tenantId, setTenantId] = useState("analytics.1");
  const [from, setFrom] = useState(daysAgoMs(30));
  const [to, setTo] = useState(Date.now());
  const [loading, setLoading] = useState(false);
  const [data, setData] = useState(null);
  const [error, setError] = useState("");

  const apiBase = "http://localhost:8787";

  const tenants = useMemo(
    () => [
      "analytics.1",
      "web-3.scotland",
      "web-3.gbr",
      "avgas.1",
      "lettings.1",
      "zipcode.1",
    ],
    []
  );

  async function load() {
    setLoading(true);
    setError("");
    try {
      const url = new URL(`${apiBase}/api/metrics`);
      url.searchParams.set("tenantId", tenantId);
      url.searchParams.set("from", String(from));
      url.searchParams.set("to", String(to));
      const res = await fetch(url.toString());
      const json = await res.json();
      if (!json.ok) throw new Error("API error");
      setData(json);
    } catch (e) {
      setError(e?.message || "Failed to load");
    } finally {
      setLoading(false);
    }
  }

  useEffect(() => {
    load();
    // eslint-disable-next-line react-hooks/exhaustive-deps
  }, [tenantId]);

  // Quick local event simulator so you can see the dashboard populate
  async function simulateTraffic() {
    const pages = ["/", "/pricing", "/partners", "/docs", "/contact"];
    const refs = ["(direct)", "https://x.com", "https://google.com", "https://reddit.com", "https://example.com"];
    const campaigns = ["(none)", "winter-launch", "partner-a", "affiliate-42"];

    const now = Date.now();
    const n = 250 + Math.floor(Math.random() * 400);

    for (let i = 0; i < n; i++) {
      const ts = now - Math.floor(Math.random() * 1000 * 60 * 60 * 24 * 21);
      const roll = Math.random();
      let type = "pageview";
      if (roll > 0.82) type = "click";
      if (roll > 0.92) type = "signup";
      if (roll > 0.985) type = "purchase";

      const payload = {
        tenantId,
        type,
        url: pages[Math.floor(Math.random() * pages.length)],
        referrer: refs[Math.floor(Math.random() * refs.length)] === "(direct)" ? "" : refs[Math.floor(Math.random() * refs.length)],
        utm: { campaign: campaigns[Math.floor(Math.random() * campaigns.length)] },
        ts,
      };

      await fetch(`${apiBase}/api/events`, {
        method: "POST",
        headers: { "Content-Type": "application/json" },
        body: JSON.stringify(payload),
      });
    }

    await load();
  }

  const k = data?.kpis || {};
  const series = data?.series || [];

  return (
    <div className="min-h-screen bg-gray-50">
      <header className="border-b bg-white">
        <div className="mx-auto flex max-w-6xl items-center justify-between px-4 py-4">
          <div>
            <div className="text-lg font-semibold text-gray-900">ANALYTICS.1 Dashboard</div>
            <div className="text-xs text-gray-500">Multi-tenant analytics control plane (MVP)</div>
          </div>

          <div className="flex items-center gap-2">
            <select
              className="rounded-xl border px-3 py-2 text-sm"
              value={tenantId}
              onChange={(e) => setTenantId(e.target.value)}
            >
              {tenants.map((t) => (
                <option key={t} value={t}>{t}</option>
              ))}
            </select>

            <button
              className="rounded-xl border px-3 py-2 text-sm hover:bg-gray-50"
              onClick={load}
              disabled={loading}
            >
              {loading ? "Loading…" : "Refresh"}
            </button>

            <button
              className="rounded-xl bg-gray-900 px-3 py-2 text-sm text-white hover:opacity-90"
              onClick={simulateTraffic}
              disabled={loading}
              title="Generates sample events so you can see the charts update."
            >
              Simulate traffic
            </button>
          </div>
        </div>
      </header>

      <main className="mx-auto max-w-6xl px-4 py-6">
        {/* Date controls */}
        <div className="mb-6 flex flex-wrap items-center gap-2">
          <div className="text-sm text-gray-600">Date range:</div>
          <button
            className="rounded-xl border px-3 py-2 text-sm hover:bg-gray-50"
            onClick={() => {
              setFrom(daysAgoMs(7));
              setTo(Date.now());
            }}
          >
            Last 7 days
          </button>
          <button
            className="rounded-xl border px-3 py-2 text-sm hover:bg-gray-50"
            onClick={() => {
              setFrom(daysAgoMs(30));
              setTo(Date.now());
            }}
          >
            Last 30 days
          </button>
          <button
            className="rounded-xl border px-3 py-2 text-sm hover:bg-gray-50"
            onClick={() => {
              setFrom(daysAgoMs(90));
              setTo(Date.now());
            }}
          >
            Last 90 days
          </button>
          <button
            className="rounded-xl bg-white border px-3 py-2 text-sm hover:bg-gray-50"
            onClick={load}
          >
            Apply
          </button>

          {error ? <div className="ml-2 text-sm text-red-600">{error}</div> : null}
        </div>

        {/* KPIs */}
        <div className="grid grid-cols-1 gap-4 sm:grid-cols-2 lg:grid-cols-4">
          <Card title="Pageviews" value={fmtInt(k.pageviews)} subtitle={tenantId} />
          <Card title="Clicks" value={fmtInt(k.clicks)} subtitle="CTA + interactions" />
          <Card title="Signups" value={fmtInt(k.signups)} subtitle="Form / onboarding" />
          <Card title="Signup rate" value={fmtPct(k.conversionRate)} subtitle="Signups / pageviews" />
        </div>

        {/* Charts */}
        <div className="mt-6 grid grid-cols-1 gap-4 lg:grid-cols-2">
          <div className="rounded-2xl border bg-white p-4 shadow-sm">
            <div className="mb-3 text-sm font-semibold text-gray-900">Traffic over time</div>
            <div className="h-72">
              <ResponsiveContainer width="100%" height="100%">
                <LineChart data={series}>
                  <CartesianGrid strokeDasharray="3 3" />
                  <XAxis dataKey="day" tick={{ fontSize: 12 }} />
                  <YAxis tick={{ fontSize: 12 }} />
                  <Tooltip />
                  <Legend />
                  <Line type="monotone" dataKey="pageviews" strokeWidth={2} dot={false} />
                  <Line type="monotone" dataKey="signups" strokeWidth={2} dot={false} />
                  <Line type="monotone" dataKey="purchases" strokeWidth={2} dot={false} />
                </LineChart>
              </ResponsiveContainer>
            </div>
          </div>

          <div className="rounded-2xl border bg-white p-4 shadow-sm">
            <div className="mb-3 text-sm font-semibold text-gray-900">Daily signups</div>
            <div className="h-72">
              <ResponsiveContainer width="100%" height="100%">
                <BarChart data={series}>
                  <CartesianGrid strokeDasharray="3 3" />
                  <XAxis dataKey="day" tick={{ fontSize: 12 }} />
                  <YAxis tick={{ fontSize: 12 }} />
                  <Tooltip />
                  <Bar dataKey="signups" />
                </BarChart>
              </ResponsiveContainer>
            </div>
          </div>
        </div>

        {/* Tables */}
        <div className="mt-6 grid grid-cols-1 gap-4 lg:grid-cols-2">
          <Table
            title="Top pages"
            columns={[
              { key: "url", label: "URL" },
              { key: "count", label: "Pageviews", render: (r) => fmtInt(r.count) },
            ]}
            rows={data?.topPages || []}
            rowKey={(r) => r.url}
          />

          <Table
            title="Top referrers"
            columns={[
              { key: "referrer", label: "Referrer" },
              { key: "count", label: "Pageviews", render: (r) => fmtInt(r.count) },
            ]}
            rows={data?.topReferrers || []}
            rowKey={(r) => r.referrer}
          />
        </div>

        <div className="mt-6">
          <Table
            title="Campaigns (by events)"
            columns={[
              { key: "campaign", label: "Campaign" },
              { key: "events", label: "Events", render: (r) => fmtInt(r.events) },
            ]}
            rows={data?.campaigns || []}
            rowKey={(r) => r.campaign}
          />
        </div>

        <footer className="mt-10 text-xs text-gray-500">
          Tip: Once deployed, keep the dashboard on your Web2 twin for HTTPS trust, and treat ANALYTICS.1 as the namespace and API brand.
        </footer>
      </main>
    </div>
  );
}

Create the frontend project

Use Vite + React + Tailwind + Recharts:

Add Tailwind

Update tailwind.config.js:

Update src/index.css:

Replace src/App.jsx with the code above.

How to deploy the Dashboard under ANALYTICS.1)

Recommended deployment pattern (dual-stack):

Host dashboard at your Web2 twin: https://analytics.website/dashboard (or similar)
Brand the product as ANALYTICS.1 Dashboard
Provide gateway access links like: https://hns.to/analytics.1 that redirect users to the Web2 dashboard

Who it serves best:

Web-3 Network admin: oversees all WEB-3 Network tenants
Partners: view their own tenant dashboards
Future buyers: immediately see the “namespace-as-a-network” story

What to build next to increase value quickly:

Add tenant onboarding + API keys
Add role-based access (admin/partner/viewer)
Add conversion funnels and a simple alert system
Add on-chain event ingestion (wallet connect, mints, lease payments)

Next.js + Postgres + ClickHouse (later) is the best balance of speed to ship, enterprise credibility, and scaling headroom.

Frontend + API

Next.js (App Router) + TypeScript
Tailwind for UI
Recharts (or Tremor) for charts
Host on Vercel (fast deploys, global CDN)

Auth / Tenancy

Clerk or Auth.js (NextAuth)
- Clerk is fastest if you want polished org/role management.
- Auth.js is great if you want “own it” and keep costs down.
Use “Organizations” / “Teams” for multi-tenant access

Primary data store

Postgres (Supabase or Neon)
- Supabase if you want admin UI, edge functions, and storage built-in.
- Neon if you want pure Postgres + excellent scaling.

Event ingestion

Start with: Next.js API route (or a tiny Node service) writing to Postgres
After you get traction: move event storage to ClickHouse for cheap, fast analytics queries.

Why this stack wins

You can ship a serious MVP in days.
Postgres is perfect for tenants/users/billing/config.
ClickHouse is the industry standard for high-volume analytics events (PostHog uses it).
This stack is easy to sell to partners/investors.

What lives where

Postgres: users, tenants, sites, API keys, feature flags, billing, alerts
ClickHouse: raw events + aggregated rollups

Alternative 1 (fastest MVP): Next.js + Supabase only

To launch very quickly and keep infra simple:

Next.js + Supabase (Postgres + Auth + Storage + Edge Functions)
Store events in Postgres first, roll up daily aggregates
When the dataset grows, add ClickHouse later

Pros

One vendor does most things
Very fast to implement multi-tenancy
Great dashboards/admin convenience

Cons

Postgres is not ideal for massive event volumes long-term (but fine early)

Alternative 2 (privacy-first + low overhead): Cloudflare stack - “web3-native vibes” + global edge + low cost:

Cloudflare Pages (frontend)
Cloudflare Workers (ingest API at the edge)
D1 (SQLite-ish) for config
R2 for raw event blobs
Optional: send events to ClickHouse later

Pros

Very cheap at scale for ingestion
Extremely fast globally
Great for “endpoint” positioning (analytics.1 feels like edge infra)

Cons

More engineering complexity than Next.js+Supabase
D1 isn’t as flexible as Postgres for complex analytics queries

Customization for the WEB-3 Network)

The Web-3 network will comprise many TLD sites, leasing, partner pages, payments, analytics). So it needs:

multi-tenant roles
partner dashboards
billing + metering
long-term scale

Appropriate stack

Next.js + TypeScript + Tailwind + Auth (Clerk/Auth.js) + Postgres (Supabase/Neon) + ClickHouse later

The shortest path:

Next.js + Supabase + Recharts
Add ClickHouse only when event volume demands it

Practical “starter architecture”

Week 1 MVP

Next.js dashboard (tenant selector, KPIs, charts, referrers, campaigns)
Event snippet → /api/collect
Postgres tables:
- tenants, sites, api_keys
- events (or daily_rollups)

Week 2

Organizations/roles
Alerts (traffic spike/drop)
Funnel tracking
Export CSV

Week 3+

ClickHouse event store
Real-time dashboards
On-chain event connectors (wallet connect, mints, lease payments)

ANALYTICS.1

Dual-Stack Analytics Operator Programme

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Executive Summary

The Web-3 Network is establishing ANALYTICS.1 as a category-defining analytics endpoint for the next generation of the Internet—one that serves both humans and autonomous agents across Web2 and Web3.

We are appointing a single independent operator to run the Analytics Dual-Stack Programme, comprising:

ANALYTICS.1 — the Web3-native analytics namespace (Handshake)
Analytics1.site / Analytics.website — the Web2 twin for HTTPS onboarding, dashboards, and APIs

The operator will run analytics infrastructure for the Web-3 Network and operate an independent analytics business under the ANALYTICS.1 brand.

This is not a licensing deal for a website.
It is an opportunity to operate infrastructure-grade analytics anchored to a premium, category-defining domain.

Strategic Context

The Web-3 Network

The Web-3 Network is an initiative designed to:

Transition users and businesses from Web2 to Web3 using familiar patterns,
Anchor new digital infrastructure to industry-defining domains,
Move deliberately toward autonomous coordination using agentic AI.

As users increasingly bypass search engines, analytics becomes the control plane—not merely a reporting tool.

Why ANALYTICS.1 Matters

ANALYTICS.1 is positioned as:

a generic analytics endpoint (e.g. tenant.analytics.1),
a neutral measurement layer across industries,
a future interface not only for dashboards, but for machine-to-machine analytics consumption.

Unlike conventional analytics brands:

the domain itself communicates category authority,
the namespace can outlive any specific UI or tool,
it aligns naturally with autonomous agents and APIs.

Role of the Analytics Dual-Stack Operator

The appointed operator will:

1. Operate Network Analytics

Provide analytics dashboards for Web-3 Network TLDs, partners, and lessees
Track traffic, funnels, campaigns, conversions, and revenue signals
Support multi-tenant access with role-based permissions
Integrate on-chain and off-chain signals where applicable

2. Operate the ANALYTICS.1 Platform Independently

Offer analytics services to external Web2/Web3 clients
Develop premium features, APIs, and AI-driven analytics agents
Monetize dashboards, reporting, attribution, and insights
Evolve ANALYTICS.1 into a standalone analytics brand

3. Maintain Neutrality and Trust

Operate independently of Web-3 Network commercial decisions
Act as a neutral measurement authority
Preserve credibility for partners, operators, and future investors

Technical Scope (Operator-Led)

The operator has architectural freedom, but is expected to deliver:

Web2 dashboard (React / Next.js or equivalent)
Ingestion APIs (event tracking, campaign attribution)
Multi-tenant analytics model
Secure auth & role management
Scalable storage (Postgres initially; ClickHouse or equivalent later)
AI-ready analytics surface (alerts, summaries, agent hooks)

The Web-3 Network does not prescribe tooling—only outcomes.

Commercial Opportunity

Built-In Demand

From day one, the operator gains:

live traffic from multiple TLDs,
real commercial funnels,
a growing ecosystem of tenants and partners.

This removes the cold-start problem faced by most analytics startups.

Independent Upside

Outside the network, the operator can:

sell analytics services globally,
license dashboards or APIs,
build agentic analytics products,
establish ANALYTICS.1 as a long-term brand asset.

Governance & Relationship Model

The operator is independent, not a subsidiary.
The Web-3 Network retains stewardship of the ANALYTICS.1 namespace.
Commercial alignment is achieved via revenue share and service commitments.
Either party may terminate under defined conditions (see terms).

Ideal Operator Profile

Analytics, data, or infrastructure-first mindset
Comfortable operating multi-tenant systems
Product-led and commercially aware
Interested in long-term infrastructure plays, not short-term projects

Why This Is Rare

It is unusual to combine:

a category-defining domain,
guaranteed ecosystem demand,
independence to build a standalone business,
and early positioning for agentic AI analytics.

ANALYTICS.1 is designed to become infrastructure, not software.

. Commercial Terms (Proposed)

Term Length

Initial term: 3 years
Renewal: automatic by mutual agreement

Revenue Share (Network-Derived Revenue)

Applies to revenue generated from Web-3 Network tenants and partners:

70% Operator
30% Web-3 Network

This reflects:

operator responsibility for build, hosting, compliance, and support,
Web-3 Network contribution of domain, distribution, and ecosystem.

Independent Revenue

100% retained by the Operator
Applies to all non-network clients, products, and services

Minimum Operator Obligations

The operator must:

Maintain uptime ≥ 99.5% (rolling 30 days)
Provide dashboards and reporting for all core network TLDs
Support onboarding for new network tenants
Maintain GDPR-compliant data handling
Provide quarterly performance summaries to the Web-3 Network

Network Obligations

The Web-3 Network will:

Designate ANALYTICS.1 as the official analytics endpoint
Promote analytics usage across its ecosystem
Avoid operating a competing analytics platform
Provide reasonable notice of major network changes

Exit / Termination

Either party may terminate if:

material breach remains uncured after notice,
prolonged service failure occurs,
insolvency or abandonment is evident.

On termination:

operator retains independent analytics business,
network retains domain stewardship and data continuity rights.