LLM Insights is a capability within Sprinklr Insights that helps you understand how your brand appears across large language model (LLM)–driven platforms such as ChatGPT, Gemini, and Perplexity. As customers increasingly rely on AI‑generated responses instead of traditional search engines, brands often lose visibility into how they are discovered, represented, and compared. LLM Insights brings transparency to this AI discovery layer by analysing brand visibility, sentiment, citations, and competitive presence within LLM responses. It takes traditional Voice of Customer (VOC) insights into AI-driven experiences, helping you measure performance, identify gaps, and improve discoverability across emerging AI search channels.

With LLM Insights, you can answer key questions such as:

• How visible is my brand in LLM responses?

• What sentiment is associated with my brand?

• How does my brand compare with competitors?

• Which sources and citations influence AI answers about my brand?

• How can I perform a prompt‑level deep dive to analyse low‑performing prompts?

In addition to analysis, LLM Insights provides recommendations to help optimise your content and improve visibility by making it more accessible to AI crawlers.

Key Capabilities

Key capabilities include:

• Real‑world prompt generation: Prompts are created using signals from social data, trends, news, brand pillars, and customer care data, rather than simulated prompts.

• Unified reporting: AI visibility insights are available alongside listening data in a single reporting layer with drill‑down capabilities.

• In‑platform actionability: You can take action through Sprinklr workflows for publishing, engagement, listening, and care, without switching tools.

How does LLM Insights work?

LLM Insights follows a structured workflow designed to reflect real user behaviour and deliver actionable outcomes:

1. Context collection: Gathers relevant brand, competitor, and business context.

2. Prompt generation: Creates prompts that simulate real customer questions using social data, trends, news, brand pillars, LLM data, and customer care inputs.

3. LLM analysis: Evaluates prompts across supported LLM platforms to assess visibility, sentiment, citations, and representation.

4. Insights and recommendations: Delivers reports and AI‑driven recommendations to improve discoverability and strengthen brand presence in AI‑generated responses.

This end‑to‑end approach ensures you not only understand how your brand appears in LLM conversations but also know how to act on those insights.

Prerequisites

In order to access LLM Insights, you would need permissions to View, Create, and Manage LLM Insights permissions under Conversations.

Accessing LLM Insights

The following navigation steps are listed out below:

1. Navigate to Sprinklr Insights and then access the LLM Insights Persona App.

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   Alternatively, navigate to Sprinklr Insights, and go to LLM Insights under Insights.

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