An introduction to "Clusters"
Clusters are a key feature of NEXT that let you group highlights together that relate to the same theme or objective. Essentially, they let you "cluster" highlights into something new.
Product team leverage clusters to organize and validate big-picture ideas and topics they are working on, such as strategic themes, top findings and insights, hypotheses, product deliverables such as User Stories or PRDs, or UX deliverables, such as Personas or User Journeys.
In a way, clusters serve as a "reverse AI chat". In the chat, you prompt the AI to find something unknown or create something new based on highlights. Clusters, on the other hand, can offer a place for:
Something you (think you already) know – in this case, you don't need to start from highlights
Artifacts/deliverables that you've created (either manually or via the AI chat)
Elements of a Cluster
A clusters contains the following ingredients:
A title
A description
Labels
Files
And most importantly; Highlights
Once a cluster is created, NEXT AI will automatically use the cluster's title and description to find (more) supporting evidence for that cluster in the form of highlights. This basically puts product discovery on autopilot: simply upload recordings of customer interactions and NEXT will connect the dots.
Use cases for Clusters
Store artifacts or UX/Product deliverables
Nurture big-ticket items with evidence
How to get started with Clusters
Getting started with Clusters is easy once you've added your first recordings. Here are the high-level steps you need to get going:
Create or open a teamspace
If you haven't already, upload your first recording
Navigate to Library > Clusters
Click on Add cluster
Add a title and description to the clusters
If you already have highlights in your teamspace, wait a few moments for highlight suggestions to appear
Add or reject highlight suggestions to nurture your cluster with evidence
Note: Clusters can be created and enriched with highlights in many ways. Take a look at the article "How to create Clusters" and "How to enrich clusters with evidence" for a more detailed explanation.