contexture · live
visit· session views· total views· time on site· avg views/visit· days since last·
sample

behavioral profile

visitor type
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first page of session
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avg time on site
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engagement
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query yourself · CX.io()

CX.io(
//==> run a query to see your own context

the concept

The context layer, made visible.

A calculated, first-party context layer that sits beneath the data and personalization categories, computed once and portable everywhere. The idea this whole project is named for.

context·relevance·engagement

The borrowed-context problem

Every tool in the marketing stack calculates context, and every tool calculates it differently. "Engaged visitor" means one thing in your testing tool, another in analytics, a third in the CDP. The math gets rebuilt by hand in each platform, every engagement. And the result is captive: it lives inside the vendor that computed it, so switching tools leaves your context behind.

You end up renting your own behavioral data back from the platforms that happen to hold it. The context layer is the answer to that: calculate context once, on your side, in storage you own, and feed it to every tool consistently.

What a context layer is, and is not

It is not a tag management system. A TMS delivers tags; it does not build a persistent behavioral profile or calculate context. It is not a CDP. A CDP needs identity and stitches known records; the context layer works on the anonymous, unidentified traffic that never logs in, the majority of every site. It is not a testing or personalization tool. Those act on context; they do not own a portable, first-party definition of it.

A context layer is the thin, owned tier underneath all of them: persistent, anonymous, first-party, vendor-neutral. It is a first-party, headless CDP that fills the gaps, onsite, in the middle of the funnel.

Context, relevance, engagement

Context is what you know about a visitor's behavior. Relevance is the decision that context enables. Engagement is the result when relevance lands. The model runs in that order, and each beat depends on owning the one before it. Borrowed context breaks the chain at the first link.

Why now

Third-party cookies are collapsing, and with them the borrowed-identity model that personalization quietly depended on. First-party, anonymous, consent-gated context is what remains, and it is what this layer is built to own. The shift is not a threat to the approach; it is the reason for it.

The ownership and portability thesis

If you own the context, you can move it. Switch your testing tool and the engagement score comes with you. Add a new channel and it inherits the same affinities. The context layer makes your behavioral data an asset you carry, not a feature you rent.

source: the field manual, adapted to web reading.

principles

What you already believe, if you've felt the problem.

  1. 01

    Own your context

    Most of the data deciding what a visitor sees isn't yours. Reclaim that layer.

  2. 02

    Compute once, syndicate everywhere

    One definition of "engaged," calculated on your side, fed to every tool.

  3. 03

    Context should outlive the tool

    If switching vendors loses your behavioral data, you never owned it.

  4. 04

    Fill the gap the vendors leave

    CRMs and CDPs need identity, and third-party cookies are going away. The anonymous majority of your traffic falls through both. First-party context catches it.

  5. 05

    Let context choose the subtext

    Who they are and what they keep returning to tells you which message is relevant, and relevance is what earns engagement. Context, then relevance, then engagement.

    "Context is the customer's side of the conversation. Subtext is the marketer's side."

  6. 06

    Small enough to run first

    6 KB gzipped, zero dependencies, frozen on purpose. Code that runs before everything else has no business being heavy or shifting under you.

the journey

From borrowed to owned

borrowed context

Every tool computes its own definition. The same visitor is three different people.

rebuilt by hand

The same math gets reimplemented in every platform, every engagement, and stays stranded there.

owned and portable

One definition, calculated on your side, in first-party storage, syndicated everywhere.

the stack

Five layers, one instrument

Integrated Orchestration syndicate to any tool you own
Calculated Context scores · affinities · recency
Persistent Profile anonymous first-party identity
Abstracted JSAPI one io() surface over everything
Embedded Data dataLayer · params · meta · cookies

profile

  • whotraits
  • whatbehaviors
  • howaffinities

segment

  • whymotives
  • wheremilestones
  • whenthresholds

collect at the base · calculate in the middle · syndicate from the top