Foundit!

The Four Forces of Product Discovery

Stop fixing four problems. You’ve only ever had one.

Every multi-category retailer is quietly losing money to customers who can’t find the right product fast enough, then leave before they ever show up in a conversion report.

Product discovery is governed by four forces. They only pay out when they work together.

  • B&Q
  • CPC
  • Fenwick
  • John Lewis & Partners
  • Ironmongery Direct
  • M&S
  • Michael Kors
  • Net-a-Porter
  • Neiman Marcus
  • Brico Depot
  • B&Q
  • CPC
  • Fenwick
  • John Lewis & Partners
  • Ironmongery Direct
  • M&S
  • Michael Kors
  • Net-a-Porter
  • Neiman Marcus
  • Brico Depot

Why this exists

We don’t sell features. 
We sell a force multiplier.

Four forces govern product discovery. None works in isolation. Apply all four, in order, and each force amplifies the next in a loop we call the Intent Flywheel.

The center is the outcome: products found, journeys completed and therefore more revenue, typically a 4–6% uplift once all four forces are pulling together. But the center isn’t the point. The compounding is.

Warren Cowan

“Competitors treating search, merchandising, SEO, and enrichment as separate problems are pushing four flat tyres. Our clients are spinning a flywheel.”

Warren CowanCEO & Founder, FoundIt!

The Intent Flywheel

Four forces. One compounding system.

Every interaction sharpens the next one, so the system gets more useful rather than more complicated.

The Four Forces

Four forces, applied in order

  1. 1

    Understanding Layer

    What does the customer actually want?

    Intent

    You can sell to a customer whose intent you don’t understand. It is just harder, slower and smaller. Intent is the first force because everything else is built on top of it.

    FoundIt!’s knowledge graph captures the relationships between what customers type, what they mean, what they want next and what they eventually buy. Every interaction sharpens the signal.

    Force 1 in action

    Demand Made Visible

    Listening surfaced searches for “midaxi” and “sequin dress” before the catalog had pages to meet them.

    Marks and Spencer

    Force 1 in action

    +3.7%

    Revenue uplift on inspirational, mission-led PLPs, annualised to a six-figure outcome on a single component

    John Lewis

  2. 2

    Customer decision tree layer

    How do customers actually make decsions

    Structure

    Understanding intent is not enough. Structure turns it into an operational framework: an organized, attributable map of how customers actually make decisions in your categories.

    Not flat tags. Relationships. The hierarchies of attributes customers care about, plus the semantic layer that connects them.

    Force 2 in action

    40,000+ Products, One Logic

    A customer decision tree let products live wherever the job took them, reflecting how tradespeople actually think.

    Ironmongery Direct

    Force 2 in action

    7-Figure

    Annualised revenue impact from a Fashion & Beauty PLP A/B test, enough to roll visual navigation out site-wide.

    John Lewis

  3. 3

    Findability layer

    Can every product be found by every relevant intent

    Product Data

    Most catalogs are built for internal teams. Customers shop by outcome, occasion, constraint and mood. FoundIt! enriches existing product data at scale so every product is findable by every intent.

    Force 3 in action

    Granddads Like Whiskey

    Intent data revealed what “gifts for granddad” shoppers wanted, enriching hundreds of long-tail pages at scale.

    Marks and Spencer

    Force 3 in action

    The Long Tail, Found

    A specialist part once found only by exact SKU became reachable through dozens of intent paths.

    Ironmongery Direct

  4. 4

    Distribution layer

    Is intelligence deployed everywhere customers look?

    Channels + platforms

    Customers research everywhere. Channels are where the accumulated intelligence gets deployed, internally across owned surfaces and externally across search, answer engines, feeds and marketplaces.

    Every channel is also a sensor. Each interaction feeds a new signal back into Force 1. That is what makes this a flywheel rather than a pipeline.

    Force 4 in action

    +8.6%

    Organic PLP traffic, validated through SearchPilot’s A/B methodology, with an estimated eight-figure annualized revenue impact.

    John Lewis

    Force 4 in action

    PDP as a Landing Page

    Intent-led discovery near the top of product pages cut bounce significantly and re-routed intent.

    Marks and Spencer

The framework at a glance

The whole system, on one page.

#ForceLayerThe question it answersCore FoundIt! capability
1

Intent

Understanding

What does the customer actually want?

Knowledge graph, intent signals, behavioral data

2

Structure

Customer decision tree

How do customers actually make decisions in this category?

Taxonomy, attribute hierarchies, semantic relationships

3

Product data

Findability

Can every product be found by every relevant intent?

Product enrichment, structured data, PDPs

4

Channels + platforms

Distribution

Is our intelligence deployed everywhere customers look?

SEO, AEO, customer journeys, navigation, syndication and feeds

Self Diagnostic

Where are you on the flywheel?

The flywheel cannot compound if any one force is weak. Find the weakest force first, then fix it.

ForceBeginnerEmergingWorkingCompounding

Intent

Decisions made on gut feel, anecdote or last week’s report.

Basic analytics in place, but siloed across tools.

Intent signals captured and structured across the journey.

Knowledge graph actively improves with every interaction.

Structure

Tags come from suppliers; no map of how customers actually decide.

Partial taxonomies in a few categories; relationships are patchy.

Decision trees mapped across key categories, with attributes and semantics.

Structure evolves automatically as intent signals change.

Product data

Catalog used as supplied; attributes missing everywhere.

Manual enrichment on hero SKUs only.

Structured, enriched data across the full catalog.

Product data auto-improves based on intent signals.

Channels + platforms

On-site only; SEO treated as a separate workstream.

SEO and feeds are running, but inconsistent and uncoordinated.

Intent-led experience across search, SEO, AEO and feeds.

Every channel contributes signals back into the flywheel.

Four questions to ask your team

Find the drag on the system.

  • Intent

    How confident are we that we understand what customers actually want, not what we assume?

  • Structure

    Have we turned that understanding into a map of how customers make decisions?

  • Product data

    Is every product findable by every relevant intent, or only by the keywords we anticipated?

  • Channels + platform

    Does our intelligence show up everywhere customers do, or only selectively?

Without all four, the multiplier never kicks in, and the compounding never starts.

Getting all four moving, in sequence, is the work - and it’s where the Intent Flywheel starts to spin.

Find your weakest Force

Find out which force is holding your flywheel back.

We’ll show you where each force sits on the maturity curve, where compounding is blocked and what it would take to get the flywheel turning.