When analyzing exit interview survey responses, you need to understand both why employees are leaving and where they're going. Pinpointing push factors—internal frictions—and pull factors—external attractions—gives HR teams the power to focus on what to fix or improve. By letting AI ask smart follow-up questions in real time, you automatically dig deeper into these real reasons for departing employees.
Core questions that uncover push factors
Push factors are the pain points within the organization that drive people to look elsewhere. Getting to the core of these issues means asking questions that surface everyday frustrations and mismatched expectations—things that leadership can actually address.
What aspects of your role didn't match your expectations?
This explores any disconnects between what was promised and the reality. Maybe responsibilities changed, growth was slower than expected, or support was lacking.Which company policies or processes hindered your work?
This uncovers bottlenecks, outdated tools, or inefficient workflows that add needless friction or make people feel undervalued.What would need to change for you to consider staying?
This is your chance to surface actionable feedback—what employees think would have made a real difference. Given that 77% of employees who quit could have been retained by organizational change[1], these insights are gold for HR.
With conversational exit interview surveys, AI follow-ups can instantly ask for specific examples or clarify vague statements. This digging is where the real context emerges, and Specific’s AI follow-up logic works just like a sharp human interviewer—probing, clarifying, and surfacing untold stories.
Give me an example of a company policy you found particularly frustrating.
Can you describe a specific situation where a process hindered your productivity?
What did you hope would happen that didn’t?
This approach helps break through generic feedback to discover patterns worth fixing—whether that’s micromanagement, slow decision-making, or misaligned leadership priorities. And because approximately 3.2 to 3.4 million employees voluntarily leave their jobs each month[1], knowing these push factors rapidly can translate to big cost savings and retention gains.
Questions that reveal pull factors
While push factors tell you what employees are running from, pull factors highlight what’s luring them to something new. These are external attractions—better offers, perks, or cultural alignments—that help you benchmark your organization against the competition.
What excited you most about your next opportunity?
This uncovers compelling draws—maybe it’s the prospect of a new challenge, leadership style, or organizational mission.Which benefits or perks influenced your decision?
If your competitor offers remote work, unique stipends, or accelerated promotion paths, you need to know.How does your new role better align with your career goals?
Spotting gaps between your employees’ aspirations and what you offer helps improve development paths, support, and clarity for future hires.
Each question supports HR in surfacing your competitive disadvantages. Pull factors are harder to control, but recognizing them lets you refine your employer value proposition. With GPT-based AI, you can compare responses at scale and spot the recurring attractions elsewhere. If new jobs consistently offer remote-first work or stronger upskilling, you’ll know what’s truly pulling talent away.
Factor Type | Description | Example Question |
|---|---|---|
Push Factors | Internal issues driving employees away (e.g., poor management, lack of growth, low pay) | What would need to change for you to consider staying? |
Pull Factors | External attractions that draw employees to competitors (e.g., higher salaries, flexible work, career advancement) | What excited you most about your next opportunity? |
Analyze the most common reasons departing employees are attracted to competitors, and summarize any recurring perks, benefits, or cultures they mention.
Only 5.5% of organizations report being “very effective” in acting upon information from exit interviews[2], but by distinguishing push from pull with conversational surveys, you break that bad cycle—helping HR teams prioritize where to invest and evolve. And considering 74% of HR leaders cite poor compensation as the top reason for leaving[1], these insights no longer sit in a spreadsheet—they drive action.
Turning exit feedback into action with AI analysis
Once you’ve gathered honest, detailed feedback, what’s next? This is where AI survey analysis—especially using GPT-based tools like Specific—automatically groups responses into actionable, prioritized themes. No one wants to slog through pages of free-text responses. Instead, analysis bots can instantly surface patterns: maybe a particular manager, policy, or compensation issue is handily the top driver of attrition across departments.
When you chat with AI about responses, you can ask for breakdowns by location, job level, or any filter you care about. This on-demand querying removes guesswork for HR teams and brings transparency to the exit interview process. For example, you can:
Spot widespread management or culture themes
Quantify how much compensation facts into departures (especially when turnover costs 20%-200% of annual salary per employee[3])
Uncover hidden gaps in career development or support for specific teams
Summarize the common management challenges mentioned by engineering and marketing teams.
Show trends in compensation-related departures over the last six months.
What career development gaps are cited most frequently by employees under 30?
AI summaries let leaders see which issues actually matter and where to act first. And with conversational surveys, the process never feels like a rigid form—employees stay candid, offering richer stories for the AI to analyze. Organizations adopting AI-powered exit analytics see a 42% reduction in preventable turnover[4], showing how powerful analysis at scale can be.
If you want more guidance on setting up surveys for this, see how to generate your own survey using AI or review how to easily modify survey questions for different teams and use cases.
Making exit interviews work for your organization
Timing matters: run exit interview surveys 1–2 weeks before an employee’s last day, when feedback is fresh but emotions have settled.
Anonymous responses usually yield the most honest feedback, especially on sensitive topics—linked responses can work for smaller teams or leadership exits. Running your exit interviews on a conversational survey page helps guarantee anonymity and boosts participation. In fact, AI-driven exit surveys see far higher response rates than traditional ones[4], breaking through the usual 30–35% ceiling toward much richer datasets.
Keep initial questions brief and straightforward to avoid overwhelming respondents
Let AI power your deeper follow-ups—it can probe nuances without feeling robotic or invasive
Share how you will use the feedback (“We’ll focus on fixing recurrent management issues and updating benefits”)
It’s easy to customize your surveys for each department, job level, or exit scenario—giving every departing employee the chance to share actionable feedback in a format that feels like a conversation, not an interrogation.
If you’re ready to transform your organization with AI-powered feedback, create your own survey and discover the real reasons people leave (and stay).