Go to market engineer

Engineer the AI powered GTM system of your dreams.

GTM Efficiency is the name of the game. 

With outbound becoming less effective and customer acquisition cost (CAC) on the rise we need a new and better way to acquire customers and deliver impact. The future of GTM is AI + human. 

Decrease customer acquisition cost (CAC)
Increase sales velocity
Get a better view of your go to market, pipeline, customers and prospects

We build AI powered systems that help you scale your go to market.

From outbound motions, inbound routing and deep company research to fully automated AI agents. We're building it. 

Highly targeted micro-campaigns
Figure out message-market-fit
Set up fully automated motions
Email infrastructure

How we work

1. Situation
Asses current go to market & tech stack.
2. Constraint
Look for the point of constraint.
3. Articulate hypothesis
Hypothesise on possible solutions
4. Launch
Build & launch solutions.
5. Evaluate & iterate
Evaluate results against the hypothesis.

How we work

1. Situation

Get a full scan of your current go to market system (bowtie), tech stack and data. 

Full go to market scan
Tech stack scan (crm, email infra, outbound/ inbound tools...)
Create a data dashboard to see what's happening

2. Constraint

After assessing all the data we look for the point of constraint or bottleneck that, if addressed, will unlock the most significant improvement in output.

Find the point of constraint in your go to market

3. Articulate hypothesis

Now that we know what we need to solve (the point of constraint), it's time to come up with possible solutions. 

Usually the solution will be on one of 3 metrics:
- Time (doing something faster)
- Volume (doing more - adding more leads for example)
- Conversion (doing something better)

Come up with possible solutions
Look at ways to do it faster, better or add volume

4. Launch

The time has come to actually build and launch now. 

Build out the new systems and/ or processes based on our previous findings

5. Evaluate & iterate

The work isn't done when we launch, it's done when we get the the output or result we where looking for. 

From here we'll enter a closed loop where we'll keep improving our go to market system using the previous 3 steps:

1. Find constraint
2. Articulate hypothesis
3. Launch
4. Evaluate & iterate
Repeat

Evaluate our hypothesis
If unsuccessful, build & test new hypothesis
If successful, solve the new point of constraint

Our services

Workflow build

Do you know exactly what you want to build and just want to get it done? 

This is the one.

AI powered motions that work on auto-pilot
Data scraping and enrichment
Email infrastructure
Work with us

Fractional

If you're looking for a real partnership, where we'll take a look at your current go to market system, tool stack and start solving from the point of constraint, this is the one.

Full go to market & tech stack scan
Ideal customer profile (ICP) and ideal customer situation (ICS) analysis
AI powered motions that work on auto-pilot
Email infrastructure and warm-up
Work with us

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