All capabilities

Understand your audience

Interests that change over time

Follow how one person's interests move, and tell a settled taste apart from a single unusual session.

What it does

The mechanism

  1. 01

    Fragmented behavioural signals are turned into one current picture of what a person is interested in now, rather than an average of everything they have ever done.

  2. 02

    Long-term preference and short-term intent are held separately, so an unusual evening does not rewrite a profile - and a genuine change is still picked up quickly.

What it gets you

Three things you can point at

01

A profile that stays current

Interactions fold into the profile within seconds of arriving, so the next request already reflects the last one.

02

Intent apart from taste

Session-level intent steers the current visit; established preference survives it. Neither is allowed to drown out the other.

03

Why did this change?

A timeline of the events that moved an interest, a profile or a recommendation, so a shift can be explained rather than guessed at.

Find the model that wins on your data. Ship it without a rewrite.

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