Zigment

Conversation Graph

The data layer that understands clicks and conversations.

Clicks, chats, mood and intent—stored in one query‑ready timeline.

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Illustration of a conversation graph shows how Zigment unifies qualitative signals, such as Hesitant, Eager, and Happy from conversations with quantitative data on a single graph. Combining touchpoints such as web, socials etc, then chooses next actions such as email demo request, demo booked, onboarding form, and customer support handoff using agentic AI as core

Clicks are out. Conversations are in.

70 % of B2C engagement now happens outside the clickstream. Legacy tools can't hear it—Zigment can.

Structured to Unstructured

Human-like agents that qualify, nurture and sell—on any channel, 24x7

Siloed Marketing Data

Drag-and-drop journeys that react to any CRM update, ad click or uploaded list

LLMs are here

Every click, message, intent and decision in a single timeline—query with prompt

Why It Matters

Digital journeys have outgrown clickstream tables.

Pain todayBusiness impactHow Conversation Graph fixes it
Chat logs isolated from CRMSlow response, generic nurtureYesOne timeline that stitches clicks, chats, email, voice
No sentiment or intent fieldsCan't prioritise hot or at-risk leadsYesNLP layer tags every utterance with intent, mood, entities
Manual revenue attributionWeeks to prove ROIYesGraph links ad click → conversation → purchase in seconds
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The Platform

Every message, mood and click in a single timeline—unlocking AI-ready insights no CDP or CRM can match

Platform screenshot

Key Capabilities

Source Attribution

Resolve lead source attribution for every prospect or customer.

Intent Signals

Capture & store qualitative signals like mood or intent on the event timeline.

Realtime Triggers

Drive dynamic workflows based on click, mood or intent.

Query Unstructured Data

Show users who are 'High Intent' but found it 'too expensive'.

Stack Integration

Connect any software in the funnel. CRM, CDP, chatbot or automation.

Open Lakehouse Export

Push to Snowflake, ClickHouse, BigQuery.

Integrations

Conversation Graph adds an Agentic AI layer across the existing stack

Explore Integrations
  • Braze
  • Clevertap
  • Moengage
  • Snowflake
  • HubSpot
  • Salesforce
  • Freshdesk
  • Zoho
  • Google Drive
  • Instagram
  • Facebook
  • WhatsApp
  • Microsoft
  • AWS
  • Gmail

Unstructured to Structured

Real-time Conversation Processing

U

Any discounts for students?

A

Absolutely—use code STUDENT10 at checkout.

{
  "actor_id": 102947,
  "utterance": "Any discounts for students?",
  "intent": "discount_inquiry",
  "sentiment": "curious",
  "confidence": 0.92
}

This node is instantly searchable and can trigger a nurture path for similar requests.

High-Value Use Cases

Use Zigment for every use case - conversion, onboarding, retention or support.

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Micro-segment Nurturing

Query: "Users expressing 'concern about price' in last 7 days." → personalised discount workflow.

Agent Escalation

Trigger human hand-off when intent = high-value lead & sentiment = frustrated.

Revenue Attribution

Join ad_click_id → conversation path → purchase event; include mood shifts as weighting factors.

Feedback Mining

Vector search for utterances similar to "too expensive".

Comparison to Legacy Tables

FeatureCRMCDPConversation Graph
Click & purchase eventsYesYesYes
Raw chat & voice turnsNotes onlyNoYes
Sentiment & intent fieldsNoNoYes
Vector similarity searchNoNoYes
Real-time orchestration triggersLimitedWebhook hacksNative

Turn every conversation into a revenue-driving journey

From a quick DM to a week-long nurture thread, Zigment drives every conversation forward on autopilot.

  1. Meet customers across every channel and anytime

  2. Extract qualitative signals - mood, urgency, intent

  3. Instantly Orchestrate the next best step in the journey

  4. Conversation Graph records every signal, context and event

From Clicks to Conversations, From Structured to Sentient

Clicks, views and CRM fields don't tell you why a prospect buys—or why they ghost you. Legacy CDPs cannot store or query fuzzy constructs like "mildly frustrated." Zigment can.

  1. 1. Real intent lives in words, not clicks.

    Message replies and support-chat rants carry the urgency a pageview or add-to-cart never shows.

  2. 2. Branch by Intent or Mood.

    We parse mood, objections, and buying signals in real time, then trigger the perfect next step—no tagging, no SQL.

  3. 3. Every touchpoint, one timeline.

    Our Conversation Graph™ keeps structured events and free-text sentiment side-by-side, giving growth teams a single source of truth + feeling.

Ready for a data layer that actually speaks human?