Understanding your customer and competitive analysis landscape requires asking the right questions to uncover why customers consider competitor alternatives and what drives their decisions. This guide shares the best questions for competitive analysis using customer perception surveys. When you know the switching triggers behind customer choices, it becomes much easier to improve your positioning, messaging, and product roadmap.
Why traditional surveys miss competitive insights
Traditional surveys often fall short because static multiple-choice questions can’t explore the “why” behind competitor preferences. When you just ask customers to check boxes, you miss the nuanced context—like friction points in your onboarding or subtle product gaps—that determine why they consider or choose competitors.
The richest competitive intelligence comes from understanding not only who else your customers consider, but also what is contextually pushing or pulling them toward those choices. Relying solely on collecting competitor names skips the essential layer: the unique, personal stories and motivators behind switching and selection.
Recent research shows that conversational AI-powered surveys lift response rates up to 30% higher than traditional methods, tapping into deeper and more actionable feedback [1].
Traditional Survey | Conversational AI Survey |
|---|---|
“Which other solutions have you used?” | “Which other solutions have you considered, and what made you look elsewhere?” |
“They use Competitor X.” | “They use Competitor X because our onboarding takes 3 weeks, while theirs takes 2 days.” |
The difference lies in conversational depth. With tools like automatic AI follow-up questions, you don’t stop at the surface—you keep asking “why” until the story’s clear.
Essential questions to uncover competitor alternatives
The right questions kickstart meaningful competitive analysis and reveal what alternatives customers truly weigh. Here’s how I approach it, along with specific probes and configuration advice:
Direct competitor discovery:
“Which other products or solutions did you consider before choosing us (or when deciding to leave)?”
This question maps the competitive landscape from the customer’s view—not your assumptions. You’ll often uncover up-and-coming direct or indirect rivals.Please tell me more about each alternative you seriously considered. What stood out about them?
Comparative experience prompt:
“Can you describe any recent experiences you’ve had with competing products?”
This uncovers raw, recent touchpoints. It surfaces differentiators or hidden strengths/weaknesses.Could you share a specific aspect of their experience you found better or worse than ours?
Feature comparison questions:
“Are there any features/attributes you wish we had, based on what you’ve seen elsewhere?”Which missing features or capabilities made you think about switching, even briefly?
Category mindset check:
“When you think about solutions in our category, what brands or products come to mind first?”What makes those options stand out to you? Is it something they do differently or better?
By setting your AI follow-up configuration to 2–3 levels deep on competitor-related questions, you'll surface not just who customers compare you to—but how their expectations are set. That means richer positioning insights for your team, and a more engaging experience for your customers. Conversational follow-ups, done right, make people far more willing to open up and be candid with their feedback. According to recent surveys, this method can increase customer satisfaction by 25% and reduce complaints by 30% [2].
Questions to identify value drivers and decision criteria
The most valuable competitive insights come from understanding why customers choose—or stick with—a solution. Here are my favorite questions to reveal priority decision drivers:
“What mattered most to you when considering different solutions?”
If you had to rank your top three factors (e.g., price, support, integrations), what would they be?
“What made you confident in your choice?”
Was there a specific moment or feature that convinced you you’d made the right (or wrong) choice?
“When thinking about alternatives, were there any trade-offs you had to make?”
Which trade-off was hardest for you? How did you decide what mattered more?
“What would make you more likely to recommend—or try—a competitor?”
Are there improvements or changes you’d need to see from us in order to stay?
When configuring follow-up tone for decision criteria, I keep it empathetic—especially if probing around price versus value (“I’d love to better understand how you balance cost versus what you get.”). Empathy makes it easier for people to share trade-offs and rationalizations honestly. Follow-ups transform static questions into a real conversation: it’s not a one-way form, it’s a conversational survey, and it’s exactly how AI survey generators like Specific help you create custom competitive analysis surveys that feel like smart interviews, not interrogation.
It’s worth emphasizing: AI-powered conversational surveys see completion rates of 70–90%, compared to the 10–30% usually achieved with traditional static forms [3]. That’s a massive upgrade in both the quality and quantity of insights you’ll collect.
Uncovering switching triggers and retention opportunities
Switching triggers—the reasons customers leave or look elsewhere—are gold for both retention and product development. I always ask questions that target both push and pull forces:
“Tell me about a time you considered switching solutions. What prompted you to look at other options?”
Was there a problem or frustration that made you start looking? Please share details.
“What did you hope to gain from a competitor that you weren’t getting with us?”
Were there promises, features, or guarantees that felt stronger elsewhere?
“Have you ever switched back or decided not to switch after all? Why?”
Did anything about the process (or competitor) make you stick with us?
“What would make it easier (or harder) for you to transition from one solution to another?”
What are the biggest switching costs or migration concerns you have? Who or what would need to change?
With these questions, I configure the AI to gently but persistently follow up—asking for specifics, but always respecting boundaries if a customer seems frustrated or concerned. A single rich insight about migration pain, for example, can directly inform how you build out onboarding or integration projects to reduce churn risk. Insights about push and pull help not just with retention, but with sharpening your competitive story.
One study found that AI interventions here can help companies reduce service costs by 15% and resolve customer issues 40% faster—proof that understanding these triggers pays off immediately [4].
Configuring AI follow-ups for competitive intelligence
Configuring AI-driven surveys for competitive analysis is all about balancing curiosity and tact. Here’s how I set the tone and depth for maximum insight without crossing the line:
Tone: Professional and genuinely curious, but never aggressive. I always instruct the AI to “dig gently.”
Follow-up depth: I set it to probe two times on important competitor and switching questions, with a third follow-up only if the prior answers are vague (“Is there anything else that comes to mind?”).
Agent instructions:
For competitor-related questions, always ask about both what attracted the customer to alternatives, and what barriers kept them from switching. Avoid making assumptions—invite stories.
Leading questions: Avoid yes/no prompts. Instead, use “Tell me more about…” or “Can you elaborate on…” whenever responses are brief.
Boundaries: I set a rule: Don’t ask about pricing specifics unless the customer brings it up first, to avoid putting anyone on the spot.
After your first wave of responses, you can easily use the AI survey editor to adjust follow-up rules, update tone, and refine which scenarios trigger deeper probes. You might want different depth for “new customer research” versus “churned customer analysis”—the platform lets you tailor this per survey with no hassle.
Analyzing competitive insights with AI
Once you’ve gathered responses, Specific’s AI-powered analysis gives you a huge head start in spotting patterns and themes. It’s almost like having a research analyst in your pocket:
AI automatically searches for repeated competitor names, feature mentions, and switching narratives. I often run chat-based analyses to dig into why certain competitors or pain points surface more in one segment than another.
“Show me the top three reasons our customers mention Competitor X in switching stories, and compare to results from growth-stage customers.”
You can filter responses by customer type, plan, or experience to spot emerging competitive risks or opportunities in specific segments.
I recommend kicking off multiple analysis threads for different angles—like price sensitivity, onboarding experience, or support quality—especially when sharing insights back to product or sales teams.
When you use features like conversational response analysis, you get instant, shareable summaries—making it simple to loop in product and GTM teams with actionable competitive themes. AI tools like these achieve up to 95% accuracy in sentiment analysis, letting you trust the direction you’re seeing in your data [4].
Turn competitive insights into strategic advantage
Understanding your competitive landscape from the customer’s perception is non-negotiable if you want to build and position winning solutions. These conversational approaches surface the real reasons behind choices—giving you the power to make better product, marketing, and retention decisions. Ready to see what you’ve been missing? The unique value of conversational AI surveys is how much richer and more honest customer insights become. Create your own survey and see your market position through your customers’ eyes.