Sales & marketing

kontact

Sales as a system, not as a filing cabinet

kontact is the largest system in my workshop. It reflects how selling actually works: not as a collection of contacts, but as the question of who decides on the other side, who has a say, and what the next sensible move is. Playbooks walk the team through those steps, and when you switch from an existing CRM, your data comes along.

Status
Läuft
Who it's for
Sales teams who'd rather sell than document
The gain
The next move is in there — not just the last one

Why CRMs fail

A CRM rarely fails for lack of fields. It fails because it documents work instead of structuring it — and salespeople don't enjoy writing reports for a system that gives nothing back. What's left is a well-kept database with no effect, while the most important part of the business lives on in people's heads and inboxes.

kontact turns the direction around: who are the people behind a deal? Who decides, who reviews, who blocks? Out of that picture come playbooks that suggest the team's next step instead of merely recording the last one.

What the team gets out of it

Open it in the morning and you don't see a list of open tasks but an order of play: these three conversations matter most today, and here's why. New colleagues get up to speed faster, because the approach lives in the system rather than in one person's experience.

For leadership that means the state of the pipeline can simply be read, without anyone preparing it first.

AI you can hold to account

In most products the AI instructions are buried somewhere in the program, and afterwards nobody can say why a suggestion looked the way it did. In kontact they sit visibly in one place, separated per customer, and every single run is logged: which instruction, which model, which result. All of it can be changed while the system is running.

That sounds like bureaucracy and is the opposite: if AI helps decide in sales, you must be able to say at any time what it did, when and why. Otherwise it isn't a tool, it's a risk.

What it does day to day

  • Shows who really decides on the customer side — not just who replied
  • Suggests the next step instead of logging the last one
  • Playbooks make what works repeatable instead of person-dependent
  • Switching from an existing CRM without losing data
  • Every AI suggestion is traceable and, if challenged, defensible

What sticks

AI in a product needs the same discipline as money in a company: a receipt, a log, clear ownership. Magic is not an architecture.