Akshun Dogra × Flowers-Software | Senior Marketing Manager / Growth & AI Automation Lead application

Which invoice-approval signals
reveal buying intent?
Let's turn them into qualified pipeline.

As Senior Marketing Manager / Growth & AI Automation Lead, I will integrate custom APIs across Webflow and HubSpot to establish an automated lead generation machine for Flowers-Software. I previously delivered 36x+ peak ROAS while managing \$50K+ AUD monthly ad budgets, and I would apply that tracking discipline to Organisationsmanagement acquisition without forecasting identical results.

✉ businessakshun@gmail.com

Balancing AI-Agent Lead Generation and Consent-Safe Attribution for Flowers-Software

Building an automated, AI-agent-powered lead generation machine for Flowers-Software while balancing Webflow, GA4, and HubSpot script integration creates friction between aggressive channel expansion and consent-safe attribution. For the Growth & AI Automation Lead, unverified tracking risks skewed CAC metrics and inefficient ad spend when promoting Rechnungsfreigaben and Vertragsverwaltung automation to the German Mittelstand. I will validate this tension by auditing script triggers, mapping custom API endpoints to CRM properties, and testing consent management rules before scaling paid acquisition budgets.

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, automation, and full-funnel GTM intelligence.

📈

Performance Marketing

End-to-end paid media across Google, Meta, and LinkedIn. 36x+ ROAS, $50K+ monthly budgets managed. Demand creation and capture in one unified funnel.

At Ingestro & Theo — cut CPC 20%, raised CTR 30%, and recovered €32.7k in suppressed conversion value & ad waste.

Google Ads

Meta Ads

LinkedIn Ads

A/B Testing

Full-funnel architecture

Demand Creation LinkedIn · Meta

↓

Demand Capture Google Search

↓

Retargeting Display · Social

36x+ Peak ROAS achieved

⚡

Measurement & Experiment Operations

I turn ambiguous growth questions into reproducible measurement, clear experiment design, and documented decisions with human review where it matters.

The point is not more automation. It is a traceable path from evidence to a decision a growth team can defend.

Evidence

Measurement

Experiment

Review

Evidence-to-decision loop

🌐

Evidence

Public signals

→

🔗

Measure

Baseline

→

🧪

Test

Experiment

→

🧱

Review

Decision

LEARN

Keep testing

REVIEW

Check evidence

STOP

Document why

Evidence before scale

Most relevant for Flowers-Software

🎯

GTM Signal Intelligence

Full-pipeline value capture — from raw public signals to scored, routed accounts. I built an autonomous research agent that turns funding, hiring, ad-presence, and tech-stack signals into a live fit score before a single outbound message goes out.

At Ingestro & Theo — built signal-scoring engine evaluating funding stage, hiring velocity, and channel gaps to prioritize account outreach.

Signal Scoring

Fit Tiering

Evidence Routing

Autonomous Research

Signal-to-pipeline engine

🌐

Scraper

6 Modules

→

💼

Signals

Jobs & Stack

→

🎯

Score Engine

0–100 Score

→

⚡

ABM Page

Auto-Publish

HIGH (80+)

⚡ Auto-Publish & AE Route

MID (55-79)

💬 SDR Approval Review

LOW (<55)

⏳ Nurture / Hold

100% Signal-traceable, zero guesswork

🔍

SEO & GEO

Technical SEO, schema markup, and LLM/GEO visibility strategy. 400% organic growth. Early practitioner of Generative Engine Optimisation.

At Ingestro & Theo — AI-sourced traffic scaled 1% → 20% of sessions, contributing 10% of total pipeline.

SEMrush

GA4

Schema

GEO

Python

LLM visibility strategy

📐

Dynamic Schema

Per-page structured data, LLM-readable

🔎

Prompt Tracking

Peec AI + Search Console gaps

💬

Community Signals

Reddit + LinkedIn citations

⭐

Authority Profiles

G2 + Crunchbase optimised

400% Organic traffic growth

💻

Technical Marketing

Webflow builds, GTM, conversion tracking, and ABM page generation at scale. I build and measure without needing a dev team.

At Ingestro & Theo — built personalized ABM pages & 5 governed GTM AI agents (Python + Claude + n8n + HubSpot).

Webflow

GTM

HTML/CSS

Tracking & measurement stack

Webflow

HTML/CSS/JS

↓ events fire

Google Tag Manager Central hub

↓ distributes to

GA4

FB Pixel

Google Ads

0 Dev team needed

What I'd do in the
first 90 days

With 6+ years across growth, paid media, SQL, GA4, GTM, HubSpot, Webflow, and custom APIs, I bring direct experience managing \$50K+ AUD/month Google and Facebook ad budgets while achieving 50% faster ROI measurement through cohort tracking and multi-channel attribution. My background in orchestrating marketing automation and SQL-backed tracking frameworks enables me to build Flowers-Software's B2B pipeline infrastructure with reliable data integrity.

01Days 1–30

Diagnose Consent Management and Telemetry Triggers — I will audit observed script execution states across Webflow, GA4, and Usercentrics on Flowers-Software landing pages to evaluate existing consent management triggers. This diagnostic yields a consent-safe telemetry audit that clarifies how landing pages for Organisationsmanagement and Prozessautomatisierung capture user intent. Based on these signals, I will decide whether script execution sequences require reconfiguration before launching new paid campaigns.

02Days 31–45

Instrument SQL Dashboards and AI Stack Integration — Following the excerpt to orchestrate the Marketing AI Stack, I will map custom APIs connecting automated lead capture scripts to HubSpot CRM properties. This technical configuration delivers SQL-backed dashboards to analyze marketing CAC, conversion rates, and campaign ROI. Based on these metrics, I will decide which lead enrichment fields must be established to validate high-intent MQL-to-SQL qualification.

03Days 46–75

Test AI Lead Generation and Channel Experiments — To execute the mission of building an automated, AI-agent-powered lead generation machine, I will run structured campaign experiments across Google Ads and Meta Ads while testing LinkedIn B2B targeting hypotheses. This testing initiative generates a multi-channel acquisition benchmark evaluating lead conversion for Rechnungsfreigaben and Vertragsverwaltung automation messaging. Based on cost-per-qualified-lead outcomes, I will decide how to reallocate channel budgets to maximize high-intent B2B pipeline.

04Days 76–90

Operationalise Cross-Functional Growth Workflows — I will integrate marketing AI tools and automated workflows across design, engineering, analytics, and marketing functions to eliminate repetitive marketing operations at Flowers-Software. This cross-functional operationalisation establishes a standardized campaign rollout framework for German Mittelstand process automation. Based on workflow velocity and conversion data, I will decide which automated AI workflows to scale permanently across the acquisition pipeline.

💡 Day-90 decision gate

Scale AI-agent lead generation workflows when custom API integrations between Webflow and HubSpot deliver verified MQL-to-SQL qualification data without attribution gaps across SQL dashboards. Iterate campaign targeting and ad creative if Google Ads or Meta Ads yield engagement but CAC exceeds validated efficiency benchmarks across German Mittelstand segments. Stop manual outreach workflows only when automated lead enrichment scripts and AI tools demonstrate verified data accuracy and clear ROI across all 4 collaborating functions.

I already did some
homework.

Hypothesis: This audit evaluates the public digital signals and strategic growth requirements for Flowers-Software to align marketing automation with pipeline goals. Our analysis synthesizes observed technical infrastructure and multi-channel acquisition patterns to guide the Senior Marketing Manager / Growth & AI Automation Lead.

⬡ Observations · Flowers-Software
Full analysis available on request Fit Score: 100/100 (HIGH_FIT)

ACCOUNT FIT SCORE

100/100 HIGH_FIT

📈

Consent-Safe Measurement Architecture — Public telemetry indicates observed script states for Google Analytics / GTM, HubSpot, and Usercentrics across 2 inspected public pages, while 2 valid JSON-LD blocks are present. How effectively does this stack capture attribution without compromising user privacy? The incoming lead should audit script execution triggers and consent management rules to form a consent-safe measurement hypothesis. This action enables clean performance tracking across lead capture touchpoints.
⚡

AI-Agent Workflow and CMS — Flowers-Software relies on Webflow as an observed CMS, GA4 for analytics, and observed HubSpot HTML references, while setting an objective to build an AI-agent-powered lead generation machine. Integrating custom AI workflows into existing Webflow forms and HubSpot CRM endpoints could present technical sync challenges. The growth lead must map API endpoints between automated scripts and CRM properties. This effort enables seamless MQL-to-SQL qualification and rapid lead enrichment.
🔍

Multi-Channel Paid Acquisition Balancing — Public advertising telemetry shows observed tags for Google Ads and Meta Ads, whereas LinkedIn Ads tags were not observed on crawled surfaces. Relying exclusively on search and social channels without verified LinkedIn tag presence might leave B2B decision-makers unreached. The growth manager should test structured campaign experiments across current channels while testing LinkedIn targeting hypotheses. This approach enables optimized CAC and improved campaign ROI tracking.
🎯

Mittelstand Workflow Positioning — Flowers-Software focuses on process automation for the German Mittelstand, automating invoice approvals and contract management across 4 collaborating functions including design, engineering, analytics, and marketing. Can automated messaging effectively translate complex workflow automation into clear customer propositions for traditional enterprises? The lead should align product value messaging across all 4 functions to refine positioning. This decision enables accelerated B2B pipeline velocity and consistent brand identity.
✓

Flowers-Software establishes a strong technical baseline with Webflow, GA4, and HubSpot to support automated B2B lead generation workflows.
i

I can share a Loom walkthrough with more detail — just ask.

ℹ

Data Transparency: These are outside-in hypotheses based on verified first-party and public evidence. “Not observed” is not the same as “does not exist”; internal data and stakeholder context would be the first validation step.

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

Which invoice-approval signals
reveal buying intent?
Let's turn them into qualified pipeline.

Balancing AI-Agent Lead Generation and Consent-Safe Attribution for Flowers-Software

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 Flowers-Software.

Glad you stopped by,
Flowers-Software.

Which invoice-approval signals reveal buying intent? Let's turn them into qualified pipeline.

Balancing AI-Agent Lead Generation and Consent-Safe Attribution for Flowers-Software

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 Flowers-Software.

Glad you stopped by,Flowers-Software.

Which invoice-approval signals
reveal buying intent?
Let's turn them into qualified pipeline.

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 Flowers-Software.

Glad you stopped by,
Flowers-Software.