Akshun Dogra × Eye-Able | hire.akshundogra.com/eyeable

Build the engine. Scale the pipeline—
turning compliance-driven inbound into scalable outbound.

Eye-Able scaled fast on inbound demand driven by European accessibility laws (BFSG & EAA across Germany, Netherlands, France, Spain, Poland). As buyer urgency and compliance maturity vary account by account across international markets, AEs need warm intent signals rather than cold lists. I build the GTM engineering stack that identifies where sales effort creates the most pipeline — a system I've already built twice.

✉ businessakshun@gmail.com

Every website needs accessibility—outbound needs signals.

BFSG & European Accessibility Act (EAA) compliance created an immediate inbound wave for Eye-Able, but scaling international TOFU across European markets (Germany, Netherlands, France, Spain, Poland, Portugal) requires a repeatable outbound engine. With prospects spanning every industry from e-commerce to public sector, buyer urgency and technical readiness vary wildly. I build intent-signal pipelines, automated disqualification crawlers, and native HubSpot lead scoring so your sales team gets 80%+ warm, pre-qualified accounts — so reps can focus on selling the product.

Part marketer,
part engineer.

I don't fit neatly in one box — and that's the point. I design systems that connect data to revenue across paid, organic, and automation channels.

⚡

Account-Signal Mapping

Instead of burning expensive enrichment credits on cold accounts, I build custom Python crawlers that inspect target accounts' HTML source code and privacy policies for existing accessibility vendor tags (AccessiBe, UserWay, EqualWeb, Recite Me, AudioEye). Accounts are categorized into tailored outreach tracks based on compliance maturity.

Inspired by the RB2B → Clay → Lemlist pipeline built at Ingestro & Theo.

Python Scraper

Clay

HubSpot

Lemlist

Signal Prioritization & TOFU Pipeline

🎯

ICP List

European

→

🐍

Python

Crawler

→

🔍

Policy Scan

Tool Tag?

→

🧱

Clay

Enrich

NO TOOL

🔥 BFSG Risk Sequence

POLICY ONLY

💬 Compliance Maturity

HAS WIDGET

⚔ Competitor-Displacement

−80% Evidence: DOM tags · privacy policy · statements

Most relevant for Eye-Able

📈

CRM-Native Lead Scoring

Start with the high-value form data Eye-Able already owns—domain, company size, role, request type—then add enrichment only where it improves the decision, keeping GTM tooling spend efficient.

At Theo — built native lead scoring directly in CRM, cutting paid credit costs to zero for initial rollout.

HubSpot

Clay

Calendly

Form Data

Native Scoring & Signal Waterfall

🏢

Company Fit

Domain & Size scoring

👤

Role Persona

Stated activity & title

Signal Trigger

Score

No accessibility tool tag

+25

BFSG-liable vertical

+20

Leadership change <90d

+15

Has competitor tool

DISPLACE

80+

Tier 1 · AE Now

50–79

Tier 2 · Sequence

<50

Tier 3 · Nurture

Inputs Form data · firmographics · intent · maturity

💻

Signal Routing & Workflow Automation

Building robust webhooks, n8n automation pipelines, and custom Python scrapers. When a demo is booked, Calendly/HubSpot triggers an n8n workflow that enriches the account and sends the assigned AE a concise Slack brief before the meeting — while ambiguous signals remain in a human-review queue.

At Ingestro & Theo — built automated Slack HITL briefing pipelines for instant rep notification.

n8n

Slack

Python

APIs & Webhooks

Demo-prep automation stack

n8n Orchestrator

Demo Booked

↓ enriches & generates payload

Enrich + Meeting Brief Generator Slack HITL

↓ routes to

AE Slack Alert

HubSpot Update

Demo Booked AE prepared before the meeting

🤖

AI-Assisted GTM Operations

At Theo, I engineered a custom AI agent pattern (Python + Claude Code + n8n) that automatically crawls target accounts, parses tech signals, and executes TOFU workflows. AI helps classify public signals, draft research briefs, and maintain the feedback loop—while routing rules and human review prevent confident-looking mistakes from reaching sales.

At Theo — 5 AI agents live, saving €32.7k in ad spend & manual ops.

Claude Code

Python

n8n

AI Scrapers

Autonomous Agent Cycle

🔍

Site Scraping

Source code & policy check

🧠

Intent Analysis

LLM signal parsing

⚡

CRM Enrichment

HubSpot auto-sync

📊

Daily Pipeline Digest

SQL velocity & intent report

Continuous loop: detect → score → enrich → report

€32.7k Ad spend & ops saved at Theo

What I'd do in the
first 90 days

I reduced manual SDR effort by 80% by building an intent-signal pipeline connecting RB2B, Apollo, Make, Clay, and Lemlist—and built personalised ABM landing pages at scale using Make, Clay, and Webflow. For Eye-Able, that means automating account disqualification and signal scoring across European markets without scaling headcount. My technical background in systems and data means I can work directly with your internal product and ops infrastructure, not around it.

Audit & upgrade existing lead-to-call workflow — Sit directly with your Sales Ops team to audit how lead data currently flows through HubSpot. Identify manual research bottlenecks and streamline existing lists before expanding scoring logic. Success test: reliable fields, clear ownership, and an agreed baseline for AE research time.

Deploy the disqualification crawler & native scoring — Build and run the negative-signal accessibility tool crawler across target European verticals. Build native account & role scoring directly in HubSpot using captured inputs (domain, company size, role) — zero extra tool spend required until proven necessary. Success test: AEs accept the scored accounts and false positives stay low enough to trust the queue.

Launch signal-triggered outbound & demo-prep workflows — Two connected workflows: qualified outbound accounts enter a concise, signal-led sequence; when a prospect books a demo, an automation enriches the record and sends the assigned AE a Slack meeting brief before the call.
Day 1 — Email: relevant accessibility observation + tailored angle
Day 3 — LinkedIn: connection note referencing the same context
Day 6 — Email: offer a free WCAG audit/report offer
Day 10 — Email: practical follow-up or case-study angle
Day 14 — Break-up note Success test: meetings per AE hour outperform the current cold-list baseline before scaling volume.

💡 ROI Business Case · Pilot Benchmark

Pilot target: 80 sales-ready accounts per month, measured against meeting rate, AE acceptance rate, and research time saved per qualified account. If AEs currently convert 8% of cold outbound vs. 30% of warm, pre-qualified accounts, the native scoring model pays for itself in week one.

I already did some
homework.

I looked at Eye-Able across martech disclosures, conversion flows, and site infrastructure—and found four clear opportunities worth acting on quickly.

⬡ Observations · Eye-Able Fit Score: 85/100 (HIGH_FIT)

ACCOUNT FIT SCORE

85/100 HIGH_FIT

📈

GTM System-of-Record Check — Public disclosures show active tools for both HubSpot AND ActiveCampaign. Before adding new automation, I would clarify which platform owns lifecycle stage, attribution, and outbound-trigger logic.
⚡

High-Intent Data Already Exists — Demo-booking and WCAG-test flows collect company domain, size, role, and request context — enough to begin a CRM-native qualification pilot without buying another data tool first.
⚠️

Compliance Urgency Needs Qualification — The BFSG has made accessibility a live commercial issue for many consumer-facing digital services. The opportunity is identifying where legal relevance, digital maturity, and accessibility gaps overlap — not treating every account as equally urgent.
✓

Conversion Path to Build On — The free WCAG test already creates a high-intent entry point. The next opportunity is connecting its report, firmographic inputs, and follow-up ownership into one measurable route to sales.
📹

Loom Walkthrough — I can share a 2-minute Loom walkthrough of the Theo AI agent & n8n pipeline on request — just ask.

ℹ

Data transparency: Observations are based on publicly available data (Screaming Frog, page source analysis, privacy disclosures) and may not reflect internal metrics.

Marketing, engineering,
and a lot of borders crossed.

My name, Akshun, means "undestructable" in Sanskrit. That's not a personal brand line — it genuinely shapes how I move. I don't quit on campaigns, goals, or challenges like learning German from scratch after landing in a new country.

I started freelancing in digital marketing at 19 in India — working with Punjabi music artists, Australian businesses, and tech clients before I'd ever left the country. That early pressure to figure things out without a team or a budget is where the technical + creative hybrid came from.

I moved to Nürnberg in 2022 for an M.Sc. at FAU, added an Erasmus semester in Madrid, hit German C1, and picked up enough Spanish to embarrass myself. Outside the dashboards, I run a YouTube channel documenting the unfiltered reality of being an Indian expat in Germany — no filters, real stories.

What I keep coming back to: the best marketing sits at the intersection of creativity, data, and technical execution. Most teams have one or two. I try to bring all three.

🇮🇳

India — Where it started

Started freelancing at 19. Music artists, Australian businesses, tech clients. Taught myself SEO, PPC, and web dev out of necessity.

2016 – 2022

🇩🇪

Germany — The big leap

M.Sc. at FAU Erlangen-Nürnberg. German to C1. Joined an AI startup, built full growth stack from scratch.

2022 – Present

🇪🇸

Spain — The bonus chapter

Erasmus at UPM Madrid. Picked up Spanish, confirmed food in Madrid is genuinely incredible.

Sep 2024 – Jan 2025

▶

On YouTube

The unfiltered reality of moving from India to Germany — visa stress, language barriers, real stories.

youtube.com/@akshundogra →

hover to meet the person behind the marketer →

The man behind all of this.

Akshun Dogra · Technical Growth Marketer

Build the engine. Scale the pipeline—
turning compliance-driven inbound into scalable outbound.

Every website needs accessibility—outbound needs signals.

Part marketer,
part engineer.

What I'd do in the
first 90 days

I already did some
homework.

Marketing, engineering,
and a lot of borders crossed.

Did we just build
something worth pursuing?

This page was built
specifically for Eye-Able.

Glad you stopped by,
Eye-Able.

Build the engine. Scale the pipeline— turning compliance-driven inbound into scalable outbound.

Every website needs accessibility—outbound needs signals.

Part marketer,part engineer.

What I'd do in thefirst 90 days

I already did somehomework.

Marketing, engineering,and a lot of borders crossed.

Did we just buildsomething worth pursuing?

This page was builtspecifically for Eye-Able.

Glad you stopped by,Eye-Able.

Build the engine. Scale the pipeline—
turning compliance-driven inbound into scalable outbound.

Part marketer,
part engineer.

What I'd do in the
first 90 days

I already did some
homework.

Marketing, engineering,
and a lot of borders crossed.

Did we just build
something worth pursuing?

This page was built
specifically for Eye-Able.

Glad you stopped by,
Eye-Able.