Social Media Customer Support Experience Survey
Measures how well your brand's support holds up on social channels — response speed, resolution, agent tone — for customers who reached out via Twitter/X, Facebook, Instagram, or DM. An AI follow-up reconstructs the actual conversation thread to surface what closed loops fast and what left customers hanging.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
Which social platform did you use to contact us?
- Twitter/X
- TikTok
- Other
What was the main reason you reached out?
- Billing or payment issue
- Technical problem or bug
- Order or shipping status
- Complaint about product/service
- General question
- Other
How satisfied were you with how quickly we first responded to your message?
Overall, how would you rate how your issue was resolved?
How easy or difficult was it to get your issue resolved through social media support?
Thinking about the person or team who helped you, how much do you agree with each statement?
- They understood my issue quickly
- They were friendly and professional
- They kept me updated on progress
- They followed up to confirm the issue was fixed
Was your issue fully resolved?
- Yes, fully resolved
- Partially resolved
- No, not resolved
- Still ongoing
Reconstruct exactly what happened in this respondent's social media support conversation: what they asked for, how the agent responded, and whether it required switching to another channel (phone, email, in-app chat) to get resolved. If the issue was not fully resolved or still ongoing, probe specifically what broke down — slow replies, being passed between agents, wrong information, or no follow-up — and what would have fixed it in that moment.
Based on this support experience, how likely are you to recommend our company to a friend or colleague?
Would you contact us through social media again for future issues?
- Yes, definitely
- Maybe, depends on the issue
- No, I'd use a different channel
What is your age range?
- Under 18
- 18-24
- 25-34
- 35-44
- 45-54
- 55-64
- 65+
- Prefer not to say
That's everything — thank you for the honest feedback! Your responses go directly to the team that manages our social support channels to help us respond faster and resolve issues in fewer steps.
What’s included
AI follow-ups
Adaptive probes on open-ended answers that pull out detail a static form would miss.
Attention checks
Built-in safeguards against rushed answers and low-quality respondents.
AI-drafted copy
Wording, ordering, and branching written by the AI — tuned to your research goal.
Auto report
Themes, quotes, and a plain-English summary write themselves once responses come in.
How it compares
We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.
Why this template
- Includes an AI follow-up interview that reconstructs the actual social media conversation thread, surfacing exactly what closed loops fast and what left customers hanging
- Covers the full journey — platform used, reason for contact, response-speed satisfaction, resolution rating, and a matrix on agent conduct — rather than a single generic satisfaction score
- Automated per-response quality scoring and auto-generated reports turn open-ended feedback into actionable insight without manual read-through
- Transparent prompts mean you can see exactly what the AI asked and why, unlike static form builders
Jotform
Social Support Survey Form TemplateA ready-to-field static form template specifically framed around social media support experiences, which is a direct topical match. It relies on fixed multiple-choice and rating questions rather than any dynamic follow-up, so nuance in a customer's story has to be captured through predefined fields. Customization is drag-and-drop, which is convenient for quick edits but doesn't adapt in real time to what a respondent says.
What it does well
- Purpose-built for social media support feedback, so questions are contextually relevant out of the box
- Drag-and-drop form builder allows fast customization of fields and branding
- Part of a large established template library, suggesting broad testing across use cases
Where it falls short
- Static question set with no adaptive AI follow-up to reconstruct what actually happened in a conversation
- No automated quality scoring of open-ended responses — analysis is manual
- No voice interview option for respondents who prefer speaking over typing
SurveyMonkey
Social Support Survey TemplateA directly comparable template addressing social media support satisfaction, backed by SurveyMonkey's mature survey infrastructure and analytics dashboards. Like most template-based tools, it is built on fixed question logic (skip logic at best), not conversational follow-up. Reporting is strong for aggregate stats but doesn't reconstruct individual support threads.
What it does well
- Established survey platform with reliable distribution and response-collection tools
- Built-in analytics and benchmarking features for aggregate trend reporting
- Large template library suggests the survey has been refined against common use patterns
Where it falls short
- No adaptive AI interview to probe deeper into a specific respondent's unresolved issue
- No mechanism to reconstruct the actual back-and-forth conversation a customer had with support
- No published methodology on how questions were validated or scored
QuestionPro
Customer Support Service Evaluation Survey TemplateThis is a general customer support evaluation template rather than one specifically built around social media channels (Twitter/X, Facebook, Instagram, DMs), so it's a broader but still relevant comparison. It offers standard satisfaction and resolution questions typical of CX survey tools. As a static template, it would need manual editing to address social-specific nuances like platform choice or public vs. private thread handling.
What it does well
- Covers general support-quality dimensions like resolution and agent performance
- Backed by QuestionPro's enterprise survey and reporting tooling
- Template library offers broad customization options for different support contexts
Where it falls short
- Not tailored to social media-specific contact channels or conversation reconstruction
- No adaptive AI follow-up to dig into why a specific issue went unresolved
- No automated per-response quality scoring; analysis relies on standard cross-tab reporting
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.