← Nuvello
Proof

If we can't measure it,
we didn't do it.

Most revenue consulting ends with a deck and an assertion. We end with a metric that has a baseline, a definition, a reading history, and a delta you can take to your board.

The chain

Section 01
01

Baseline

Before we change anything, we write down what the number is today and how it is calculated. Both halves matter: a metric with no stated definition cannot be improved, only re-described. The baseline is agreed with you in writing and it does not get quietly revised later.

02

Delta tracking

Every engagement carries a small set of metrics that we read on a fixed cadence — not a dashboard of everything, a short list of what this intervention is supposed to move. The delta is measured against the baseline definition, and a flat quarter is reported as a flat quarter.

03

Attribution integrity

We separate what the work caused from what the market did. Where a lift is confounded by seasonality, a pricing change or a large one-off deal, we say so on the record. We would rather report a smaller honest delta than a larger one you cannot defend to your board.

04

Publication

Results are published into your portal with the definition, the baseline, the reading history and the provenance of every value attached. Nothing reaches a published delta without being reviewed and accepted first — there is no bulk accept, anywhere.

Engagements, read end to end

Section 02

The engagements below are illustrative composites drawn from the shape of RevOps work delivered through the ZINFI partner network. Figures show how we baseline, read and publish a delta — they are not attributed to a named client, and we publish nothing under a client's name without their written sign-off.

Partner management

B2B infrastructure software

Mid-market · ~420 employees
Partner program stand-up · attribution model build
5 months · 1 partner ops specialist, 1 fractional RevOps lead
Illustrative composite

The leak

Partners were influencing deals nobody could count, so the programme was funded on anecdote and cut first in every budget review.

The seam

Between the partner portal and the CRM: registrations were logged in one system, opportunities in the other, and nothing joined them.

What the operators did

  • Wrote one attribution rule — sourced, influenced, or neither — and got it signed before the quarter opened.
  • Rebuilt deal registration so a registration creates the CRM record rather than shadowing it.
  • Tiered partners on pipeline actually produced, not on logo size.
  • Put a fortnightly partner pipeline read in front of the same two people every time.

Partner-sourced pipeline

Opportunities whose first qualified touch is an approved partner registration, counted at creation.

Baseline

Not measurable

After

22% of new pipeline

Delta

First defensible reading

Registration compliance

Partner-involved opportunities carrying an approved registration at stage 2.

Baseline

31%

After

88%

Delta

+57 pts

Active-partner ratio

Partners producing at least one registered opportunity in a rolling 90 days.

Baseline

9%

After

27%

Delta

+18 pts

What we did not claim

A pricing change landed in month four and lifted deal size across all channels. We reported the partner delta on volume rather than value for that quarter and said why.

What stayed behind

The attribution rule, the registration flow and the fortnightly read stayed with the partner team. No Nuvello operator is in the cadence today.

Read the full case study →
Sales management

Managed services

Mid-market · ~700 employees
Forecast methodology standardisation · CRM rescue
4 months · 1 fractional RevOps lead, 1 RevOps generalist
Illustrative composite

The leak

Three regions forecast three different ways, so the roll-up was a negotiation and the board stopped believing the commit number.

The seam

Between stage definitions and the forecast category — a stage meant a different thing in each region and nothing enforced exit criteria.

What the operators did

  • Collapsed three stage models into one with written exit criteria per stage.
  • Separated the forecast category from the stage so commit is a judgement, not a side-effect.
  • Killed 14 of 19 dashboards and rebuilt the two the leadership team actually reads.
  • Instituted a weekly deal inspection with the same four questions every week.

Forecast accuracy

Absolute variance between week-three commit and closed-won at quarter end, same read point each cycle.

Baseline

±34%

After

±11%

Delta

−23 pts of variance

Stage-2 data completeness

Opportunities at stage 2+ carrying all six required fields.

Baseline

52%

After

94%

Delta

+42 pts

Cycle time, core segment

Median qualified-to-closed, segment-held so a mix shift can't flatter the number.

Baseline

94 days

After

81 days

Delta

−13 days

What we did not claim

Two enterprise deals closed early in the final quarter. We reported cycle time with and without them; the delta above is the figure excluding both.

What stayed behind

The stage model, the inspection agenda and the two dashboards are owned by the regional sales operations leads.

Read the full case study →
Customer management

Vertical SaaS

Enterprise · ~2,400 employees
Retention signal build · onboarding-to-adoption redesign
9 months · 1 engagement lead, 2 operators, 1 analyst
Illustrative composite

The leak

Churn was discovered at renewal. Health scoring existed but nothing in it predicted anything, so nobody used it.

The seam

Between onboarding completion and the first renewal read — nine months where no one owned the account signal.

What the operators did

  • Rebuilt the health score on four behaviours that actually preceded past churn, and retired the rest.
  • Moved the first renewal conversation to day 90 with a defined trigger set.
  • Split expansion from contraction in reporting so a strong upsell quarter can't hide churn.
  • Gave onboarding a completion definition tied to product behaviour, not a checklist.

Net revenue retention

Expansion less contraction and churn on the same cohort basis, reported separately.

Baseline

97%

After

108%

Delta

+11 pts

Churn warning lead time

Median days between first triggered risk signal and the renewal decision date.

Baseline

11 days

After

96 days

Delta

+85 days

Onboarding-to-value

Median days from contract start to the defined first-value product behaviour.

Baseline

76 days

After

41 days

Delta

−35 days

What we did not claim

One large account renewed on a multi-year term inside the window. NRR is reported both with and without it internally; the figure above includes it and is flagged as such on the record.

What stayed behind

The signal set, the day-90 trigger and the split reporting run inside the customer team's own weekly cadence.

Read the full case study →

The metrics we stand behind

Section 03

These five carry most engagements. Which of them your engagement is judged on is agreed at the start, in writing, before anyone touches a system.

Forecast accuracy

Committed versus closed, read at the same point in every cycle, against one stage definition.

Pipeline coverage

Qualified pipeline against target, with the qualification rule written down rather than assumed.

Partner-sourced revenue

Revenue attributable to partner motion under an attribution rule agreed before the quarter starts.

Net revenue retention

Expansion less contraction and churn, separated so a good expansion quarter cannot hide churn.

Cycle time

Time from qualified to closed, tracked by segment so a mix shift is not mistaken for a process win.

What operators hear at the end

Section 04

Composite voices, written by us to show the kind of feedback this method produces. They are not attributed to a named person or company — we publish a client's words only with their written sign-off.

“The first month was uncomfortable because they wouldn't let us restate the baseline. That's also why the number meant something by the end.”
Chief revenue officer, mid-market softwareForecast methodology standardisationComposite
“We'd argued about partner contribution for two years. It took a written attribution rule and one quarter of clean data to end the argument.”
Director of partnerships, infrastructure vendorPartner attribution model buildComposite
“What stayed after they left is the part I'd pay for again — the cadence still runs and it isn't ours-because-they-set-it-up, it's ours.”
Chief operating officer, vertical SaaSRetention signal buildComposite

What you see in the portal

Section 05

Your engagement runs in a shared workspace. There is no separate internal view of your own numbers — you and your operators read the same metrics, the same cadence and the same open actions.

Every value carries its provenance on the record: entered by a person, produced by a connector, or proposed by an agent and accepted by a named reviewer. You can always answer where a number came from.

When the engagement ends, the definitions, the baselines and the cadence stay with you. That is the difference between a result and a dependency.

See the engagement types →

Bring us the number you don't trust. We'll start by agreeing what it means.

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