Surveys can serve an important purpose. We should use them to fill holes in our understanding of the customer experience or build better models with the customer data we have. As surveys tell you what customers explicitly choose to share, you should not be using them to measure the experience. Surveys are also inherently reactive, surface level, and increasingly ignored by customers who are overwhelmed by feedback requests. This is fact. There’s a different way. Some CX leaders understand that the most critical insights come from sources customers don’t even realize they’re providing from the “exhaust” of every day life with your brand. Real-time digital behavior, social listening, conversational analytics, and predictive modeling deliver insights that surveys alone never will. Voice and sentiment analytics, for example, go beyond simply reading customer comments. They reveal how customers genuinely feel by analyzing tone, frustration, or intent embedded within interactions. Behavioral analytics, meanwhile, uncover friction points by tracking real customer actions across websites or apps, highlighting issues users might never explicitly complain about. Predictive analytics are also becoming essential for modern CX strategies. They anticipate customer needs, allowing businesses to proactively address potential churn, rather than merely reacting after the fact. The capability can also help you maximize revenue in the experiences you are delivering (a use case not discussed often enough). The most forward-looking CX teams today are blending traditional feedback with these deeper, proactive techniques, creating a comprehensive view of their customers. If you’re just beginning to move beyond a survey-only approach, prioritizing these more advanced methods will help ensure your insights are not only deeper but actionable in real time. Surveys aren’t dead (much to my chagrin), but relying solely on them means leaving crucial insights behind. While many enterprises have moved beyond surveys, the majority are still overly reliant on them. And when you get to mid-market or small businesses? The survey slapping gets exponentially worse. Now is the time to start looking beyond the questionnaire and your Likert scales. The email survey is slowly becoming digital dust. And the capabilities to get you there are readily available. How are you evolving your customer listening strategy beyond traditional surveys? #customerexperience #cxstrategy #customerinsights #surveys
Using Technology to Measure Customer Satisfaction
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🎯 "The best salespeople ask good questions." But what if AI could help you ask the PERFECT questions at scale? Tomorrow on the GTM AI Podcast, I have Lihong Hicken joining me, the CEO of TheySaid | World's 1st AI Survey shared a brilliant framework for using AI surveys to both book meetings AND deeply understand your customers: Here's her fascinating approach: 1. Start with the Money Question "I ask sales teams: What's the ONE question that tells you if this is a good lead or not?" Real example she shared: ❌ Don't ask: "Are you interested in outsource development?" ✅ Instead ask: "How satisfied are you with your current outsource development agency?" 2. Let AI Go Deeper The AI then: - Explores pain points - Uncovers specific challenges - Discusses potential solutions - Books meetings with qualified prospects 3. Train AI Like Your Best SDR "You don't want a general AI chatting with your customer. You want it to be YOUR employee." She programs the AI to: - Use company messaging - Focus on specific value props - Route enterprise vs. SMB leads differently - Book directly into the right rep's calendar 🎯 The brilliant part? While booking meetings, you're simultaneously gathering intelligence about: - Customer satisfaction - Common pain points - Buying triggers - Product gaps She is thinking outside the box and leverage her own AI survey tech to do things that could not have been done before, like: Pipeline Generation & Sales: - Using AI surveys as an outbound prospecting tool - Converting research requests into sales opportunities - Qualifying leads through AI-driven conversations Customer Intelligence: - Getting honest feedback through AI conversations vs. human interactions - Capturing customer sentiment at different journey stages Win/Loss Analysis: - Moving from annual to continuous feedback collection - Reducing analysis costs (from $20-50K to $150) Upsell Strategy: - Moving from "sitting duck" to proactive upsell approach - Identifying expansion opportunities through AI conversations Customer Experience: - Creating engaging survey experiences vs. traditional methods - Using AI for continuous customer pulse checks Product Development: - Using customer feedback for feature prioritization - Understanding pricing expectations Market Research: - Reducing research costs and timeline - Getting both quantitative and qualitative insights Operations Efficiency: - Automating feedback collection - Reducing need for large BDR teams So excited to show this to you all and I may or may not have an example survey for you to test the tech out on yourself! Drops tomorrow ;)
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For decades, we've been playing a risky game in contact centers—reviewing just 2-3% of interactions and hoping it tells the full story. But what if we could analyze EVERY customer conversation? AI-powered quality monitoring is transforming how the best contact centers operate: ✓ 100% interaction coverage across all channels ✓ Real-time insights instead of after-the-fact reviews ✓ Objective evaluation based on consistent criteria ✓ Personalized coaching tailored to each agent The results? Targeted interventions that actually work, predictive performance scoring that focuses on outcomes (not just scripts), and the ability to identify exactly what your top performers do differently. The shift from sample-based to comprehensive QA isn't just an upgrade—it's a complete transformation that turns quality from a compliance function into a strategic driver of customer experience. Are you still gambling with the 3% sample approach, or are you ready to see the complete picture? Share your thoughts below! . . . #ContactCenterExcellence #CustomerExperience #AIinnovation #QualityAssurance
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