Audaption

Data layer · extends “Market” in the approach

Know your best customer before you chase the next one.

An ideal customer profile is only useful if it is built from evidence and it can score the whole market. We build it from the customers who buy, stay and expand, then score every account against it so every team knows where effort goes first.

Where the value leaks

Three ways it goes missing.

  1. 01

    A profile written from opinion

    Most are a workshop output: a paragraph of adjectives. Nobody can count against it, so it changes nothing about where effort goes.

  2. 02

    Every account treated alike

    Without tiers, a small account and a strategic one get the same follow-up, and the best accounts wait in the same queue as the rest.

  3. 03

    Winners lost in an average

    Blended win rates and deal sizes hide that a small slice of the base produces most of the revenue.

The leak, shown

A profile built from the customers who stay, set against the whole base, and what it does once it scores the market.

Ideal customer profile · built from the customers who stay

Illustrative$120M B2B manufacturer

Trait

Best customersAll accounts

Lift

Industrial distribution

64%
18%

3.6×

250–2,000 employees

71%
33%

2.2×

Multi-site operations

58%
14%

4.1×

Runs ERP and e-procurement

49%
12%

4.1×

New commercial leader this year

31%
9%

3.4×

A

412 accounts6% of the base

Work these first
Win rate 41%Avg deal $186K
46% of revenue
B

1,930 accounts28% of the base

Nurture to A
Win rate 27%Avg deal $74K
41% of revenue
C

4,560 accounts66% of the base

Low touch
Win rate 9%Avg deal $21K
13% of revenue

0% of accounts carry 0% of revenue. That is where effort goes first.

How we ensure the value

A baseline, a standing control, and proof.

The same three moves on every engagement, so a gain is a number against a starting point, held by a rule with an owner, and reported whether or not it flatters us.

  1. 1

    Baseline

    We start from closed-won and retained customers, not from the pipeline, and fix today's win rate, deal size and retention by tier, so progress has something to be measured against.

  2. 2

    Standing control

    Fit scores are recalculated on a schedule against new outcomes, and any change to a tier definition is logged and reviewed with sales and marketing.

  3. 3

    Proof

    Each tier's win rate, deal size and revenue share are reported against the baseline. If a tier stops separating winners from the rest, we say so and redraw it.

What you get

What we hand over.

  • An ideal customer profile written from your own customers
  • Fit scoring across your whole market, inside your CRM
  • Tier definitions and the plays that follow from each
  • A short guide so new hires and agencies use one definition
  • A reporting view of win rate and revenue by tier

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