Adobe Customer Journey Analytics Features

LLM insights

Transform your own branded conversational experiences into a measurable new channel with an intelligence layer that reveals and explains AI behavior within customer journeys. By making these emerging touchpoints transparent and actionable, Adobe empowers businesses to understand the impact of LLMs on customer engagement and act with confidence.

Conversation Insights

Add the tone, sentiment, and topics of conversational experiences, along with their contextual signals, to your full customer journey.

Group conversations by intent and topic, then see what customers are asking, how often, and whether it was resolved.
Catch topic and friction shifts before they hit conversion or support volume, then drop into individual conversations to see why.
Attribute conversation outcomes to revenue, tickets, and other downstream KPIs to prove what those conversations are worth to the business.

UI mockups showing a conversation reply with text messages and an insights summary table displaying intents and conversation scores.

Ad featuring a red puffer jacket with performance metrics showing 2K Chat GPT mentions and a 24% increase in LLM conversions.

Adobe Brand Visibility integration

Understand how brand discoverability in LLMs results in unique customer engagement with actionable insights that connect platform traffic, content demand, and engagement patterns to business outcomes such as form fills, purchases, or pipeline influence.

LLM app data

Use your existing Adobe Experience Platform Web SDK and Data Collection APIs to bring interaction data from your LLM‑embedded applications into Customer Journey Analytics. Connect LLM‑based engagement to customers and unify those behaviors with activity across web, mobile, and in‑store channels.

Diagram linking AI search enhancer, AI marketplace, and AI customer support to a line chart comparing increasing agentic traffic to declining traditional channel traffic across Q1–Q4.

Learn how to use LLM insights features.

Find what you need in Experience League, our vast collection of how-to content — including documentation, tutorials, and user guides.

Learn more

Questions? We have answers.

Customer Journey Analytics lets you tag and classify LLM and AI traﬃc with derived ﬁelds based on user agent, referrer, and query parameters, so AI-generated interactions are separated from human behavior and your existing KPIs stay accurate. From there you build segments and dashboards to trend AI traﬃc volume, journeys, and downstream conversions alongside your other channels, rather than tracking AI traﬃc in a separate tool.

Conversation and AI interaction data is ingested into Adobe Experience Platform, modeled with topics, sentiment, tone, and outcomes, then joined with your web, app, and oﬄine datasets in Customer Journey Analytics to build full cross-channel journeys. That join is what lets you attribute a downstream outcome, a purchase, a churn event, a support resolution, back to a speciﬁc AI conversation and measure its impact on your KPIs over time, rather than treating the conversation as a dead end.

Conversation Insights extracts tone, topics, keywords, and sentiment from chat or voice transcripts using NLP or LLM models, then combines those signals with journey data in Customer Journey Analytics for aggregate reporting and conversation replay, rather than leaving each transcript as an isolated record. Tracking sentiment alongside outcomes is what makes this useful for a decision: it lets you pinpoint the speciﬁc experiences or ﬂows frustrating customers, prioritize ﬁxes, and conﬁrm which changes actually improved satisfaction and conversion.

LLM insights, together with Adobe Brand Visibility, shows where your brand is mentioned or cited in AI answers, how often AI agents crawl your content, and which prompts or topics you are winning or losing. Once that visibility data is connected into Customer Journey Analytics, you can see which AI-sourced visits actually drive engagement and revenue, which is what turns an AI-visibility metric into a content and SEO investment decision rather than a vanity number.

You typically combine AI interaction and log data, chat transcripts, bot metadata, CDN or edge logs, and Brand Visibility agentic and referral traﬃc, with your existing digital and oﬄine datasets in Adobe Experience Platform, then connect them into Customer Journey Analytics for reporting. Optional integrations with Customer AI, Adobe Journey Optimizer, and native Brand Visibility data sharing enrich those journeys further with predictions and AI-visibility metrics, so you can start with the interaction data alone and add the rest as it becomes available.

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Explore the impact of LLMs on customer engagement.

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Measure and analyze LLM interactions with Adobe Customer Journey Analytics to further understand impact and best actions for customer engagement.

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2026-04-20

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