LLMs have become a starting point for nearly everything — work, play, consumerism, health, and more.
But one thing gets overlooked: how they finish answering prompts. They don’t — and that matters.
They operate in a “no, you hang up first” mentality. The prompts we enter don’t just end. LLMs “nudge” us to continue the conversation, offering to take the next step.
“Would you like me to create that travel itinerary for you?” “Would you like me to compare the Nike and New Balance running shoes and tell you which is best for a marathon?”
These nudges make it easy to keep going. Most of the time, I enter “sure” or “sounds good. Thank you,” and move to the next step to see what it provides.
These nudges drive consumer behavior. Where LLMs take us matters.
If you’re a premium brand and the LLM suggests a price comparison, you may not like it, but you need to understand it so you can react.
We analyzed how different LLMs use these nudges across prompts and platforms to understand the patterns shaping user behavior — and what they signal for brands trying to stay in control of the journey.
What LLM nudges actually look like across platforms
Budget and deals dominate
LLMs provide different types of follow-up suggestions. Overall, 45% of mentions are budget- and deal-related. While not evenly distributed, budgets and deals are treated as the default of what consumers want to see.
Perplexity and ChatGPT are over 60% budgets and deals. Meta is the only one that doesn’t make that assumption at the same level.
Comparisons drive the next step
The second biggest recommendation type is product comparisons. LLMs offer to compare various products, including financial services products, health treatments, and retail products. All industries see suggestions for comparisons.
Specs play a minor role
Another key point: much of the current thinking urges you to provide LLMs with detailed technical specs. But those make up a small share of these suggestions. That doesn’t mean content lacks ranking value — it does — but it’s not how LLMs usually extend conversations with users.
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How each platform uses nudges differently
We also analyzed the dominant nudge style across platforms. Each LLM uses a distinct tone when continuing the conversation. How these systems guide users forward reflects the personalities they present.
| Platform | Dominant nudge style | Key characteristic |
| ChatGPT | “If you want…” | Heavy commerce focus: Primarily nudges toward deals and product comparisons. |
| Microsoft Copilot | “If you tell me…” | Interactive/clarifying: Frequently asks for more user data to refine its recommendation. |
| Google Gemini | “Would you like me…” | Polite and permission-based: Exclusively uses this formal invitation to continue helping. |
| Perplexity | “I can help…” / “If you’d like…” | Service-oriented: Uses more varied phrasing to offer utility and assistance. |
| Meta AI | “Let me know…” | Casual and passive: Primarily nudges toward product comparisons and specs with a less aggressive, “standing by” tone. |
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What actions to take based on AI nudges
These nudges are designed to keep the conversation going and push users to explore further. They drive consumer behavior and shape the customer journey.
Over time, we’ll be able to better optimize for them as more data becomes available. For now, insights are limited to individual responses, with no way to connect conversations.
The actions to take fall into three buckets, mostly tied to the content you create across onsite and offsite channels:
- Capitalize on the “support” gap
- Proactive nudges for troubleshooting and support are significantly lower than commerce-driven themes.
- Own the post-purchase “how-to” and technical support space to build long-term authority where AI is currently less aggressive.
- Prioritize the “comparison” hook
- LLMs consistently nudge users toward comparative analysis.
- Double down on “Product A vs. Product B” guides to capture the AI’s primary next step.
- Maximize the “budget and deals” opportunity
- Pricing and discounts are the No. 1 driver of AI nudges (48% of all triggers).
- Maintain structured, real-time deal data to ensure your site is the preferred destination for AI commerce referrals.
The LLM landscape will keep evolving quickly as these platforms become the primary interface for consumer research and decision-making. Your priority now is to understand how LLMs talk about your brand and how those conversational nudges affect users.
By analyzing these automated suggestions across platforms like Gemini, ChatGPT, and Perplexity, organizations can see how consumers are being directed — whether toward budget-friendly alternatives, product comparisons, or technical specifications.
Recognizing these patterns lets you move from passive observation to action, keeping your value proposition clear even when an LLM reframes the conversation around price or competitors.
Tracking this shift is key to maintaining brand authority as AI-driven interactions shape the customer journey.
Contributing authors are invited to create content for Search Engine Land and are chosen for their expertise and contribution to the search community. Our contributors work under the oversight of the editorial staff and contributions are checked for quality and relevance to our readers. Search Engine Land is owned by Semrush. Contributor was not asked to make any direct or indirect mentions of Semrush. The opinions they express are their own.
