UNDERSTAND THE PRODUCTS

Product decisions from evidence, not instinct

Slice the Recurring Revenue Intelligence model along the product axis and every product, down to its sub-components, delivery platform and content type, carries its own revenue, usage, cost and ROI. Which products are earning their keep stops being a debate.

Product questions recurring revenue intelligence can answer

Which products generate the most revenue and the highest ROI, and which merely draw interest?
Where is usage declining in a way that signals churn risk, and on which products?
Which products are driving mid-cycle and renewal expansion, and what usage levels precede the upgrade?
How are new products penetrating existing customers vs new logos?
Which products are generating the most interest, and in which industries, regions and company sizes?
Where should product investment go next, judged by component-level demand and ROI?

What the product perspective enables

PRODUCT ARCHITECTURE & TAXONOMY

The product foundation for decision-making

We enable product architecture and taxonomy as the product foundation for decision-making by the CPO and the product organisation:

Attribute cost, ARR and revenue to the lowest grain of the product, not just the bundle, so every KPI can be traced back to a specific component
See which product components actually drive ARR, cross-sell, renewal expansion and new business, so investment follows evidence, not instinct
Standardise bundling and unbundling around industry-vertical patterns instead of a bespoke structure for every deal
Ground new product and GTM decisions in component-level demand and margin, not the historical roadmap
PRODUCT PORTFOLIO · TOP GRAIN
Pricing DataResearch & AnalysisIndustry BenchmarkingRisk & Advisory Services
DELIVERY COMPONENTS · DEMAND ACROSS THE BASE
Illustrative index
API
84
Web application
71
Desktop application
52
Excel add-on
38
Mobile apps (Android/iOS)
24
Cost, ARR and revenue attributed at this grain, so every KPI traces to a component

Product intelligence separates revenue from interest

WHAT THIS ENABLESVIEW MORE
ARR, cost and ROI on one governed basis
Interest-to-conversion attribution per product
Performance by content type and platform
WHAT THIS ENABLES · IN DETAIL

Product intelligence separates revenue from interest

Marketing sees which products draw attention; finance sees which generate revenue; nobody sees both on one basis. The product cut shows which products are generating the most revenue and the highest ROI, which are drawing interest and attributing lead and customer conversions, and where those two lists disagree, which is where product strategy actually lives.

Product ARR, revenue, cost and ROI on one governed basis
Interest-to-conversion attribution: which products pull prospects into the funnel
Performance by content type and delivery platform, showing where format, not product, is the problem

Usage as a leading indicator shows expansion and churn before they happen

WHAT THIS ENABLESVIEW MORE
Usage thresholds that drive expansion
Churn-risk patterns per product and cohort
Down-sell exposure made visible early
WHAT THIS ENABLES · IN DETAIL

Usage as a leading indicator shows expansion and churn before they happen

Usage per product per customer is the earliest honest signal in a recurring revenue business. Rising adoption depth identifies which product usage levels drive renewal expansions; declining usage in a pattern that historically precedes churn flags the account months before the renewal conversation.

Which products drive mid-cycle and renewal expansion, and at what usage thresholds
Usage-decline patterns that signal churn risk, per product and cohort
Down-sell exposure: accounts paying for breadth they demonstrably do not use

New product development steered by component demand

WHAT THIS ENABLESVIEW MORE
Launch tracking on the portfolio basis
Existing-base vs new-customer penetration
Investment planning with product-level ROI
WHAT THIS ENABLES · IN DETAIL

New product development steered by component demand

Because interest, usage and revenue exist at component level, new product decisions start from observed demand: which components are over-used relative to their packaging, which combinations are co-consumed, and which cohorts show interest with no matching product to buy.

New-product performance tracked from launch on the same basis as the established portfolio
How new products penetrate existing customers vs new customers, two different growth stories
Investment planning with product-level ROI: where the next pound of product spend earns most

Commercial assessment at decision speed

WHAT THIS ENABLESVIEW MORE
Product assessment time reduced 60%
Cross-sell evaluation 40% faster
Feeds bundling, pricing and sunset decisions
WHAT THIS ENABLES · IN DETAIL

Commercial assessment at decision speed

Assessing the commercial performance of a product line (revenue, cost, usage and cohort fit) previously meant weeks of manual extraction. On the Recurring Revenue Intelligence model it is a cut, reducing assessment time by 60% and making bundling, pricing and sunset decisions routine rather than annual.

Product commercial performance assessment time reduced 60%
Cross-sell strategy per account evaluated 40% faster, without manual data extraction
Feeds directly into bundling and unbundling decisions; see the bundling deep dive

Multi-year deals and the value stack

WHAT THIS ENABLESVIEW MORE
MYD penetration % of ARR, monthly
Contracted vs delivered CAGR per deal
Value-stack migration by content type
WHAT THIS ENABLES · IN DETAIL

Multi-year deals and the value stack

Two product-level views answer the questions boards ask about pricing power. MYD tracking: penetration as a share of total ARR, CAGR per contracted deal and renewal-chain CAGR, proves whether multi-year agreements are genuinely building forward revenue visibility at sustainable growth rates, and which segments are converting to multi-year versus reverting to annual. ARR by content type over time shows whether customers are moving up the product value stack or concentrating in the commodity base tier, informing new product development and pricing strategy ahead of the next renewal cycle, not after it.

MYD penetration % of total ARR, monthly, with current vs prior-year comparison
Contracted CAGR per deal and aggregated across the multi-year book, delivered vs promised
Value-stack migration by content type and delivery platform (web, desktop, mobile, API)
Enterprise-access model ROI: GRR, NRR and revenue commitment measured before and after conversion from per-licence selling
BUNDLE · AS SOLD
Market Intelligence Premium
$120k ARR · one line in the CRM
COMPONENT · $64k
Pricing Data
Usage 92% · earns the renewal
COMPONENT · $38k
Research & Analysis
Usage 41% · expansion lever
COMPONENT · $18k
Industry Benchmarking
Usage 6% · down-sell exposure
One bundle, decomposed

The renewal signal lives below the bundle line

01

Allocate the revenue

Bundle ARR is split to components on a consistent, IFRS 15-aligned basis, so each part has real economics: revenue, cost, margin, ROI.

02

Read usage as the renewal signal

Heavy use earns the renewal; unused breadth is down-sell exposure to repair before the customer discovers it at renewal.

03

Repackage from evidence

Co-used components argue for the bundle; components that never get opened argue for a cheaper tier and a stronger attach motion, decided with data rather than instinct.

What a product cell carries

A product is not one line in a price book. The product perspective decomposes every offering into a hierarchy of measurable parts, then attaches the full measure set to each level.

STRUCTURE

Product › sub-components › delivery platform › content type. A "premium intelligence" package resolves to specific datasets, report series, delivery channels and formats, each individually addressable.

MEASURES

Interest (engagement before purchase), sales, ARR and revenue, usage after purchase, cost to serve and ROI, plus active customers per product, price upgrade / downgrade and licence-upsell movements, cross-sell ARR, and CSAT / NPS per product. The full arc from attention to margin, at every level of the hierarchy.

JOINED TO EVERYTHING

Because product cells share customer and journey keys with every other measure, "usage of product X" is immediately "usage of product X, by cohort, at renewal" with no re-derivation.

PRODUCT BUNDLING

A bundle is a view, not a product

A bundle booked as one line blends the economics of its components: usage and revenue can never be joined, and every repackaging cycle rewrites history. The model allocates bundle revenue to components consistently, aligned with the IFRS 15 treatment of performance obligations, so the bundle becomes a packaging decision rather than a reporting problem.

HONEST ECONOMICS

Each component carries its own revenue, cost, usage and ROI, so you can see which components actually earn the renewal and which are dead weight.

BUNDLES FROM EVIDENCE

New packages are constructed from observed co-purchase and co-usage within cohorts, with eligible accounts counted across the base, rather than from portfolio intuition.

THE WATERFALL SURVIVES

Because every change is evaluated at component level, a bundle swap decomposes into its real movements (expansion, cross-sell, down-sell) and GRR / NRR stay honest through repackaging.

Commercial assessment of bundled products reduced 60%, so bundling, pricing and sunset decisions become routine analysis

Which of your products earn their keep?

A discovery session assesses how far your product hierarchy and usage data can already support the product cut.

Book a discovery session