Writing Sponsored Questions That Convert: Perplexity Ad Creative Guide

Perplexity's ad format is a question. Not a headline. Not a description. A question.

This simple difference changes everything about creative strategy. The skills that make great Google ad copy—urgency, CTAs, keyword stuffing—don't transfer. Writing sponsored questions that users actually click requires different thinking.

Here's how to write Perplexity ad creative that works.

Understanding the Format

Perplexity shows sponsored questions alongside organic follow-up suggestions after delivering an AI answer. Users have just received information. They're deciding whether to go deeper.

Your sponsored question competes with organic questions for attention. It must:

• Feel like a natural next question
• Promise valuable information
• Match the research mindset
• Earn the click through curiosity, not pressure

The click leads to an AI-generated response incorporating your brand messaging. The question is the hook; the response is the payoff.

If the question feels like an ad, users skip it. If it feels like genuinely useful exploration, they click.

The Anatomy of a High-Performing Question

Effective sponsored questions share common characteristics:

Specificity

Vague questions get ignored. Specific questions signal valuable, targeted information.

The strong version promises specific, actionable information. Users know exactly what they'll learn.

User Benefit Focus

Frame questions around what users want to know, not what you want to say.

Users don't care about your market position. They care about solving their problems.

Natural Language

Questions should sound like something a curious person would actually ask.

Read your question aloud. If it sounds like marketing copy, rewrite it.

Implicit Value Promise

The question should imply the answer contains something worth knowing.

The second question implies a specific, useful insight. Users click to get that insight.

Question Frameworks That Work

Several question structures consistently perform well:

The "How" Framework

"How does [Brand] help with [specific problem]?"

• How does Notion organize engineering documentation across multiple teams?
• How does Calendly handle timezone scheduling for global sales teams?
• How does Figma enable real-time collaboration between designers and developers?

"How" questions promise process information. Users learn how to do something, with your product as the mechanism.

The Comparison Framework

"How does [Brand] compare to [alternative] for [use case]?"

• How does Slack compare to Microsoft Teams for startups under 100 employees?
• How does Shopify compare to WooCommerce for first-time e-commerce sellers?
• How does Linear compare to Jira for fast-moving product teams?

Comparison questions work because users are often evaluating options. You're answering a question they already have.

The Use Case Framework

"What's the best way to [accomplish goal] with [Brand]?"

• What's the best way to automate invoice processing with QuickBooks?
• What's the best way to build landing pages without coding using Webflow?
• What's the best way to track OKRs across departments with Lattice?

Use case questions connect your product to specific outcomes users want.

The Problem Framework

"How do [user type] solve [problem] with [Brand]?"

• How do e-commerce brands reduce cart abandonment with Klaviyo?
• How do SaaS companies track feature adoption with Amplitude?
• How do remote teams maintain culture with Donut?

Problem framing resonates because users often start with problems, not solutions.

The Results Framework

"What results do [user type] see from [Brand]?"

• What results do marketing teams see from using Semrush for SEO?
• What results do sales teams see from implementing Gong?
• What results do customer success teams see with Gainsight?

Results questions promise proof. Users click to see if outcomes match their goals.

Writing for the Response

Your sponsored question leads to an AI-generated response. The question sets expectations; the response must deliver.

Ensure content alignment. If your question promises specific information, ensure your response content delivers it. "How does [Brand] reduce onboarding time?" should lead to a response with actual onboarding time data.

Prepare substantive inputs. Perplexity generates responses using your provided content. The richer your inputs—case studies, statistics, specific features—the better the response.

Anticipate follow-ups. Users who click may ask additional questions. Consider what they'll want to know next and ensure your content addresses likely follow-ups.

Maintain consistency. The tone and specificity of your question should match the response. A specific question followed by vague marketing speak disappoints users.

Testing and Iteration

Question performance varies. Systematic testing improves results:

Test question frameworks. Run the same campaign with "How" versus "What" versus "Comparison" framings. Data reveals which resonates with your audience.

Test specificity levels. Compare broad questions ("How does Stripe work?") versus specific questions ("How does Stripe handle subscription billing for SaaS companies?"). Often more specific wins, but test to confirm.

Test user types. "How do enterprise teams..." versus "How do startups..." versus "How do marketing teams..." Different user framings attract different audiences.

Test benefit angles. "How does [Brand] save time..." versus "How does [Brand] reduce costs..." versus "How does [Brand] improve accuracy..." Different benefits resonate with different priorities.

Measure beyond clicks. Click-through rate matters, but downstream metrics matter more. Which questions drive users who eventually convert? Engagement quality varies.

Common Mistakes

The Obvious Sell

Users know this is an ad trying to sell them. No curiosity generated. No click earned.

The Keyword Stuff

This reads like SEO garbage, not a human question. Perplexity users are sophisticated; they'll skip obvious manipulation.

The Vague Promise

What will users actually learn? Nothing specific is promised. No reason to click.

The Superlative Trap

Superlative claims trigger skepticism. Users don't believe "best" claims from advertisers.

Category-Specific Approaches

Different categories require different question strategies:

B2B Software

Focus on specific use cases, team sizes, and integration contexts.

• "How does Snowflake handle data sharing between analytics and data science teams?"
• "What integrations matter most when connecting Marketo to your existing tech stack?"

E-commerce/DTC

Focus on outcomes, customer experience, and operational challenges.

• "How do DTC brands reduce return rates using Narvar's post-purchase experience?"
• "What's the actual impact of Affirm buy-now-pay-later on average order value?"

Financial Services

Focus on specific scenarios, trust signals, and comparison shopping.

• "How does Wealthfront's tax-loss harvesting work for portfolios under $100K?"
• "What's the difference between Betterment and Vanguard for retirement accounts?"

Professional Services

Focus on outcomes, process, and differentiation.

• "How do companies typically evaluate management consulting firms for digital transformation?"
• "What should legal teams look for when choosing an e-discovery platform?"

The Bottom Line

Perplexity ads are questions. Writing effective questions requires abandoning traditional ad copywriting instincts and embracing curiosity-driven, value-focused, user-centric framing.

The best sponsored questions don't feel like ads. They feel like exactly what a curious user would want to ask next. Master that, and Perplexity becomes a powerful channel.