Fractional Growth & Commercial Analytics Lead

Your Mission

Give Krotos one reliable commercial truth, explain why the numbers move, and identify where we should focus to grow recurring revenue.

This is not primarily a dashboard or reporting role.

We want someone who can answer questions such as:

• Why did MRR increase or decrease?
• What is actually driving churn?
• Which acquisition channels create customers who activate and retain?
• Which product behaviours predict long-term retention?
• Where is the biggest constraint in our growth funnel?
• Is an experiment actually working?
• What should we stop, scale or investigate next?

You will work directly with the CEO and leadership team and will be expected to challenge our assumptions when the evidence does not support them.

The Kind of Problems You'll Solve

You might discover that three systems report different MRR numbers.

We expect you to investigate the underlying data, determine why they disagree and establish which number the company should trust.

You might find that a paid acquisition channel looks efficient at signup but produces customers with poor activation or retention.

We expect you to identify that before we scale it.

You might find that users who perform a particular action during their first week retain significantly better.

We expect you to quantify the opportunity and recommend what Product or Growth should do about it.

The output we value is:

Insight → recommendation → action

not simply analysis.

Your First 45 Days

1. Establish One Commercial Truth

Audit our key commercial data sources, including:

• ChartMogul
• Chargebee
• BigQuery / our data warehouse
• Mixpanel
• website analytics
• advertising platforms
• Xero
• enterprise sales data

Define the authoritative source and metric definition for each key company number.

Resolve important discrepancies or clearly explain why they exist.

2. Build a Simple Commercial Scoreboard

Create a trusted view of the growth journey:

Acquisition → Activation → Retention → Revenue

Covering the handful of metrics leadership actually needs to run the company.

The goal is not another large dashboard.

The goal is that leadership can quickly understand:

Are we growing? Why? What is stopping us growing faster?

3. Identify the Biggest Opportunities

Identify and prioritise the 3–5 most important commercial opportunities or problems you find.

For each one tell us:

• What is happening?
• Why do you believe it is happening?
• What is the commercial impact?
• How confident are you?
• What should we do next?

Ongoing Responsibilities

You will:

• analyse acquisition, activation, retention, expansion and revenue
• connect product behaviour to commercial outcomes
• analyse cohorts and customer segments
• evaluate channel performance based on customer quality, not vanity metrics
• help Product and Growth design measurable experiments
• validate whether experiments actually worked
• identify instrumentation and tracking gaps
• work with Engineering when data pipelines need fixing
• translate complex analysis into simple commercial recommendations

You are not a reporting service.

We expect you to proactively identify things leadership has missed.

Technical Expectations

Strong SQL is mandatory.

You should be comfortable independently querying and validating raw data rather than relying entirely on dashboards.

You do not need to be a data engineer, but you must be technically strong enough to investigate inconsistencies yourself and clearly specify what Engineering needs to fix.

Experience with tools such as BigQuery, Mixpanel, ChartMogul, Chargebee and similar platforms is highly desirable.

Who We're Looking For

The ideal person has likely worked as a:

• Senior Growth Analyst
• Growth Analytics Lead
• Commercial Analytics Lead
• Head of Analytics in a smaller company

Ideally within:

• SaaS
• subscription businesses
• product-led growth
• consumer / prosumer software
• digital products

We particularly value experience in businesses where the analytics team was expected to answer:

"Why aren't we growing faster?"

rather than simply fulfil reporting requests.

You should be excellent at:

• commercial and SaaS metrics
• SQL
• funnel analysis
• cohort and retention analysis
• experimentation
• segmentation
• analytical reasoning
• communicating complex findings simply
• distinguishing correlation from causation
• prioritising what matters

What We Don't Want

This role is probably not right for you if your main strength is:

• building dashboards
• producing weekly reports
• completing analytics tickets
• data engineering
• presenting large amounts of data without a recommendation

We care far more about finding the important insight than analysing everything.

How You'll Be Measured

Outcome 1: One Commercial Truth

Within 45 days, leadership agrees on definitions and authoritative sources for the company's core commercial metrics.

Outcome 2: Insight, Not Reporting

Each week leadership receives a concise view of:

What changed → Why → What matters → What we should do

Outcome 3: Material Growth Opportunities

Within 90 days, identify at least three evidence-backed opportunities that could materially improve acquisition, activation, retention, expansion or revenue.

Outcome 4: Measurable Experimentation

Major Product and Growth experiments have clear:

• hypotheses
• baselines
• success metrics
• measurement
• decision criteria

Job Details

Location: Remote Europe, ideally UK / Greece

Job Type: Freelance agreement: 2 days per week initially, reducing to approximately 1 day per week once the core analytics system is established.

Reports to: CEO