Hi! 👋

If you’ve ever stared at a pile of customer feedback and thought, “Cool, but what am I supposed to do with all of this?”, welcome to this week’s issue!

So today we’re unpacking something every marketer, CX leader, and product storyteller wrestles with: How do you turn scattered feedback into messaging people actually feel?

A quick thank-you to this week’s sponsor: an AI-powered feedback analytics platform that helps teams turn raw customer comments into structured insight. You’ll see how that fits into the story in just a second.

Let’s dive in. 👇

1. Messaging Starts With What Customers Actually Say, Not What We Hope They Say

Brands often build messaging by starting with what they want to talk about: features, roadmap highlights, big shiny value propositions.

But customers speak in real-life language:

“I just want it to work.”

“This saved me three hours.”

“I didn’t realize how stressed I was until this fixed it.”

“That step made zero sense.”

The gap between brand-speak and customer speak? That’s where messaging fails.

Your job is never to invent a story. It’s to excavate the one already alive in your customers’ words.

The trick is recognizing patterns: the repeated phrases, emotional beats, unexpected use cases, and “aha moments” that show up across feedback. That’s where AI feedback analytics platforms shine: they surface the themes humans would miss or spend hours manually sorting.

If your narrative doesn’t sound like your customers, it won’t resonate with your market. Period.

2. Look for Emotion Before You Look for Data Points

Most teams skim customer feedback like they’re scanning for errors in a spreadsheet: “positive, negative, bug report, feature request”

But messaging isn’t built from sentiment scores. It’s built from emotion.

Use the sentiment scores as signals. But dive deeper and look for:

• The frustration behind the complaint

• The joy behind the success story

• The insecurity hidden in a question

• The relief behind a solved pain point

• The surprise when something “just works”

Emotional patterns are your narrative anchors. They tell you not just what customers want, but why they want it. And that’s the difference between messaging that feels flat and messaging that hits nerve endings.

When customers say, “This saves me time,” take note. When multiple customers independently say, “This made my day easier,” that’s your message.

3. Let Insights Shape the Story, Not the Other Way Around

Here’s one of the most common mistakes: teams gather feedback, then retro-fit it into a narrative they’ve already decided on.

That’s backwards.

True customer-led messaging requires letting insights lead, even if they reshape what you thought your product was “about”.

Start with three simple questions:

• What keeps surfacing?: These are your core messages. They’re not optional.

• What surprised you?: These are your differentiation points. They signal unexpected value.

• What’s missing from your current story?: This is the messaging gap, the stuff customers care about that you never talk about.

If you want messaging that resonates, you have to be brave enough to let the narrative evolve with the data. AI tools help teams identify these shifts early instead of waiting months to notice the pattern.

4. Turn Raw Insight Into Clear, Human Messaging

Once you’ve collected themes, now the fun begins: translation.

Great messaging is just customer truth, articulated with clarity and intention.

A simple framework to turn feedback into a real narrative:

Customer Phrase > Insight > Positioning > Message

Example:

“It took me five minutes instead of an hour.”

• THey value speed and efficiency.

• Our advantage is fast time-to-value.

• You can word it as: “Get results in minutes, not hours.”

Another example:

“Your onboarding felt like a personal guide.”

• They value feeling supported.

• Our advantage is intuitive guidance.

• You can word it as: “Onboarding that actually feels like someone’s got your back.”

Your goal isn’t to paraphrase feedback, it’s to articulate the emotion behind it in a way that connects instantly.

That’s what turns a jumble of quotes into a cohesive story.

5. Close the Loop by Testing Messaging With the People Who Inspired It

Most teams stop too early. They gather feedback, extract insights, rewrite the messaging, and then send it into the world without showing it to the very people who supplied the input.

Huge missed opportunity.

Great messaging is co-created.

Here’s how to test the story with customers:

• Feed your new messaging through your feedback analytics tool to spot how closely it mirrors themes.

• Share drafts with your customer champions and community groups.

• Ask: “Does this sound like you? Did we capture the real value?”

• Watch for emotional alignment, not word choice.

• Iterate before you publish.

Customers feel ownership over the messages they help shape, which makes adoption stronger, loyalty deeper, and your story far more believable.

What This Means for You

Here’s your playbook to turn feedback into a story your market actually cares about:

1. Start with customer language, not product language. Comb through feedback. Look for the phrasing customers repeat.That’s what you need to focus on.

2. Map the emotional patterns hiding inside comments. This is where resonance lives. In the feelings, not the features.

3. Identify the themes that keep bubbling up. Make these the pillars of your narrative. Don’t fight the data.

4. Translate insight into messaging using a simple chain: What they said > what it means > what you stand for > what you say.

5. Validate the story with the people who inspired it. This is where your narrative gets sharper, more human, and more honest.

The goal isn’t to guess what will resonate. It’s to listen your way into a message your customers already believe.

Thank you for being here! And for caring enough about your customers to turn their voices into your greatest storytelling asset.

That’s the work that separates brands people buy once, from brands people follow forever.

See you next week!

Talk soon,

Marian 💚

Hi! 👋

I took a quick pause because the past few weeks were a blur of travel, conferences, and nonstop work events. If you’ve got any work-travel hacks, please share. I’m still recovering!

The good news? All that time on the road sparked new ideas about growth loops and customer advocacy. This week, we’re diving into how those same success signals can drive your next wave of expansion.

We often talk about “word of mouth” as if it’s luck. But in reality, referral momentum starts with something far more intentional: customer readiness.

When your users hit success milestones, they adopt key features, achieve measurable outcomes, and start telling others, that’s not just nice feedback. It’s a growth signal waiting to be activated.

So in this edition, we’re unpacking how customer usage patterns and success signals can help you identify who’s ready to refer, expand, or upsell, and how to turn that insight into a repeatable referral engine. Here’s how:

1. What a “Customer-Led” Referral Engine Really Means

A customer-led referral engine doesn’t start with incentives or discounts, it starts with success.

Your best advocates aren’t just happy; they’re achieving tangible results. Their internal story, “this product helped me do x faster, easier, better”, is the emotional currency that powers referrals.

When you recognize and nurture those success moments, referrals become a natural extension of the customer journey rather than an afterthought in marketing.

The formula is simple but powerful:

Success > Recognition > Advocacy > Growth

2. Detecting Referral Readiness Through Usage and Behavior

Referral readiness isn’t random. It’s visible in data, if you know where to look.

Here’s what often signals that a customer might be ready to advocate or expand:

• Feature Depth: They’ve adopted core features and some advanced ones, a sign they’re embedded in your workflow.

• Frequency & Consistency: They log in often, use multiple modules, and show stable engagement.

• Milestone Achievements: They’ve reached measurable wins (ROI, time saved, growth unlocked).

• Positive Feedback Loops: They leave positive NPS comments, share stories in support chats, or show up in community spaces.

• Peer Mentions: They tag you on social or recommend you in user groups, this is pure advocacy gold.

If you see these patterns, don’t just celebrate. Treat them as the trigger point for referral or expansion outreach.

3. Turning Signals into Strategy

Once you’ve identified those signals, your next move is to design systems that catch and act on them.

Here’s how:

• Map success milestones: Define what “value realized” looks like for your product (e.g., activated X features, achieved Y results).

• Create automatic alerts: Use success metrics or health scores to flag referral-ready accounts.

• Time your ask: Reach out when customers are basking in success, right after a key result or milestone.

• Make sharing effortless: Give them stories, assets, or programs that make referring easy and authentic.

• Reward advocacy, not transactions: Recognition (case studies, shoutouts, access) often fuels better advocacy than cash.

By systematizing this, referrals stop being opportunistic and start being operational.

4. Example: How Usage Data Can Power Referrals

Imagine this:

A SaaS platform notices a cluster of customers using its automation feature daily and completing 5x more workflows than the average user. Their NPS? 9+.

Instead of waiting for those users to maybe refer others, the team flags them as “advocacy-ready,” invites them to a customer spotlight webinar, and launches a referral offer tied to that recognition.

Result: The campaign feels like a celebration of success, not a sales push, and participation skyrockets.

5. Why This Approach Fuels Sustainable Growth

When your referral strategy starts with customer outcomes, you:

• Build advocacy rooted in authentic success, not incentives.

• Reduce churn by celebrating progress publicly.

• Align marketing, CX, and sales around shared metrics of value.

• Turn existing users into your most credible salesforce.

Because growth isn’t just about acquisition anymore, it’s about amplifying the voices of those already winning with you.

What This Means for You

Here’s a framework to get started:

1. Define your customer success milestones (activation > habit > outcome).

2. Instrument your data to detect when those milestones are hit.

3. Build a “referral-ready” segment, users with high usage, satisfaction, and ROI.

4. Trigger contextual outreach: highlight wins, invite stories, or offer shareable moments.

5. Track referrals as a product signal, not just a marketing metric.

6. Iterate by analyzing which success signals correlate most strongly with referral activity.

Your goal isn’t to manufacture advocacy. It’s to reveal it, by listening for success as closely as you listen for pain.

Huge thanks for being here, and for waiting patiently while I caught my breath the past few weeks. We’re back on track and more inspired than ever to explore how customer insight drives smarter, more human growth.

Keep listening deeply, building boldly, and turning signals into strategy.

Talk soon,

Marian 💚

Hi! 👋

This week’s been a little hectic as we gear up for some upcoming events at work, including the second edition of our BFCM webinars. Prepping for it got me thinking about how much listening matters this time of year.

BFCM is almost here, and it’s a critical moment for every business. The noise gets louder, from customers, campaigns, and competitors, and the challenge becomes knowing which signals truly deserve your attention.

So in this edition, we’re diving into a question that’s essential for both CX and product strategy: How do you distinguish between loud customer complaints and critical pains that actually impact retention or expansion? Because not every gripe is strategic feedback. Some are noise, and some are the insights that shape your next big move.

Let’s dive in.

1. Why Loud Complaints Capture Attention (Even When They Don’t Matter)

We all have that one customer whose voice echoes across Slack channels. Their emails are fiery, their support tickets rapid-fire, and their social posts vocal. Naturally, teams rush to respond.

This is normal and we see it everywhere. The people who are the loudest normally get the most attention.

It’s very tempting to treat every raised hand as an urgent inquiry. But here’s the danger with that type of approach: These loud signals can crowd out quieter but more systemic issues.

• Loud complaints often come from highly engaged users (power users, vocal criticas) who already care deeply.

• Sometimes they relate to edge cases, individual workflows, or preferences that affect fewer people.

• They demand fast fixes, because they’re visible, but not always strategic.

If your roadmap is shaped by the squeakiest wheels, you risk chasing reactive fixes instead of solving the underlying problems that undermine growth.

So before you sprint into “fix mode”, ask: Is this high volume or high impact?

2. What Makes a Pain “Critical” (for Retention or Expansion)

A critical pain is one that meaningfully affects your customers’ ability to succeed, stay, or grow with your product. It’s not just frustrating, it’s costly. Critical pains are issues that occur across multiple users or segments, block key actions like onboarding or upgrading, and show measurable impact on metrics such as churn or feature adoption.

The key distinction is simple: loudness is emotional; impact is behavioral. A single complaint shouted loudly might sting, but if the majority of your users aren’t affected, it’s not a strategic fire. Conversely, a quiet pain, like onboarding step that silently causes 30% of users to drop off, is a hidden growth killer.

When you assess feedback, look beyond the decibels. Measure how often the pain appears, how deeply it affects engagement or revenue, and whether it signals a broader behavioral trend. The most critical pains often whisper before they roar.

3. Listening Loops as Signal Filters

This is where the “listening loops” concept we talked about last time becomes a superpower. (Yes, I brought it back. It’s that important.)

When feedback flows in, you want to surface what’s meaningful, not just loud.

Here’s how:

1. Aggregate and Cluster Feedback: Use AI or manual analysis to bucket comments, complaints, and suggestions by theme. This helps you see patterns and avoid burying voices in noise.

2. Annotate with Signal Strength: Label clusters with indicators like “affects activation,” “churn risk,” “feature ask,” “edge cas,” etc. Tagging gives teams clear guidance beyond sentiment.

3. Cross-Reference with Behavior Data: Be curious and ask questions. Do users who complain show measurable drop-off? Are their cohorts representative? Use data to validate.

4. Rank Problems vs. Requests: Distinguish between problems (frustrations preventing action) and requests (nice-to-haves) can help you identify what needs prioritizing. You need to prioritize problems first.

5. Close the Loop, Strategically: Announce what you fixed, but also what you chose not to fix, stating why. This transparency helps customers feel heard without derailing strategy.

By layering these steps, your listening turns into smart curation, and the loud voices help light the path, not hijack it.

4. Real-World (Hypothetical) Example: Onboarding Frustrations

Imagine this scenario:

• A small but vocal group of users complains about a confusing setup wizard.

• Separately, your data shows that 20% of users drop out before even reaching “first success.”

• You cluster feedback and see recurring mentions like “step three is unclear,” “fields too many,” “didn’t know where to start.”

• You annotate that this aligns with your activation funnel drop-off.

• You prioritize reducing friction in the wizard over one-off feature requests or cosmetic tweaks.

In this case, even though not everyone wrote in, the combination of feedback and behavior signals this is a critical pain, one worth solving fast. The loud voices were useful as early warnings; the data confirmed it.

5. Why This Approach Builds Loyalty and Growth

When you stop chasing noise and start solving pains that impact real behavior, something powerful happens.

• Customers feel seen, you’re not just patching superficial complaints, you’re removing barriers they care about.

• Teams focus on outcomes, not just output, features that really move the needle.

• You prevent decision fatigue and roadmap drift caused by loud-but-irrelevant demands.

• Your product improves in ways that reduce churn, boost expansion, and increase advocacy.

Remember: Loudness doesn’t equal importance. Metrics, behavior, scale. Those are your true compass.

What This Means for You

If you want to get started, here’s a step-by-step you can adapt:

1. Collect feedback broadly: Support tickets, reviews, NPS free text, social, customer interviews.

2. Cluster & theme consistently: Use AI or tagging workflows to group related complaints.

3. Tag signal/pain metrics: Use your own schema: frequency, severity, behavioral impact, revenue risk.

4. Validate with quantitative data: Look at funnel drop-offs, cohort retention, usage metrics, churn logs.

5. Score and rank: Use weighted scoring (e.g., pain x impact x count) to rank problems.

6. Hold debates (with empathy): Some loud voices may push for non-strategic things. Use debate with your team to calibrate priorities.

7. Build transparently: When you resolve pain points, share changelogs, customer stories, and the “why”. Closing loops strengthens loyalty.

8. Monitor before/after: Did the fix improve funnel metrics, lower support volume, or raise satisfaction? If not, iterate.

9. Refine over time: Listening is continuous. Repeat clustering, tagging, prioritizing every cycle.

Your mission is to separate signal from noise. Loud complaints, surface-level dislikes, or personal preferences should never distract you from tackling the pains that actually drive churn, derail growth, or block expansion. Use structured listening, combined with metric validation, to build a product that doesn’t just respond, it resonates.

Until next time, may your ears stay open and your roadmap stay disciplined.

Talk soon,

Marian 💚

Hi! 👋

Today, we’re exploring a topic that I’m very interested in: psychology. More specifically, the psychology of listening and the reason why customers become fiercely loyal to brands that truly hear them.

In my case, there are some brands that just keep me coming back day after day. I’m sure we’ve all been there before too.

Because loyalty isn’t bought, it’s built one listened-to customer at a time.

1. Listening Is the Shortcut to Trust

If you’ve ever been in a conversation where someone was clearly just waiting to speak, you know how frustrating it feels to not be truly heard.

Now imagine that happening between your brand and your customers, on repeat.

When customers share feedback and nothing changes, it creates distance. But when they see their words reflected in your roadmap, your copy, or your features, it builds instant credibility.

There’s a fascinating bit of psychology here: when people feel heard, their brains release oxytocin, the same chemical tied to trust and bonding. Listening literally creates a biological sense of connection.

For customers, that means:

• They’re moving forgiving when things go wrong.

• They’re more engaged with your updates.

• And they’re more likely to advocate for your brand.

Takeaway: Listening isn’t just good CX, it’s neuroscience in action.

2. The Hidden Power of “Listening Loops”

Here’s the thing: most companies collect feedback, but few close the loop.

You can ask for opinions all day long, but if customers never see evidence that you acted on it, they’ll stop sharing.

AI makes this scalable. It can synthesize thousands of comments or tickets, identify common themes (“confusing billing”, “love the mobile app”, “want integrations”), and help teams prioritize what matters most.

Then it’s on you to close the loop:

• Update your changelog to show what’s been fixed.

• Send an email saying, “You asked, we listened.”

• Or simply reply to a user with, “We heard your feedback, and here’s what we’re doing about it.”

Those small touches tell customers, your voice shapes what we build.

And that’s when listening transforms research into relationship.

Takeaway: Listening builds loyalty only when it’s visible. Let customers see their fingerprints on your product.

3. The Psychology Behind “Feeling Heard”

Let’s zoom out for a second.

Why does being heard feel so good?

Psychologists call it validation, the sense that your feelings and experiences are acknowledged. When people feel validated, their defenses drop, and their engagement rises.

In business terms: validation creates loyalty.

Here’s what that looks like in practice:

• When a customer says, “I’m frustrated that setup took too long,” and you respond with, “Thanks for letting us know, we’re simplifying onboarding next month,” they feel understood, not dismissed.

• When you feature customer quotes in a product update or case study, you’re saying, “Your opinion matters here.”

• When you use customer language in your marketing, they feel like you get them.

AI can help you uncover those emotional cues at scale, detecting frustration, joy, confusion, or excitement across massive datasets. But the magic happens when humans use that data to respond with empathy.

Takeaway: Being heard isn’t about agreement. It’s about acknowledgement. That’s what builds emotional loyalty.

4. How AI Helps You Listen Better with Feedback and Feeling

Listening isn’t just reading feedback, it’s interpreting the emotion behind it.

That’s where modern AI feedback tools shine. They help teams pick up on tone, sentiment, and recurring emotional drivers across thousands of customer interactions.

Here’s what’s possible:

• Sentiment analysis: Spot patterns of joy or frustration instantly.

• Emotion mapping: Understand which features spark delight or disappointment.

• Urgency detection: Identify emotionally charged comments that may signal churn risk.

• Thematic clustering: Group similar emotional responses together to uncover deep behavioral insights.

For example, if AI analysis shows that “confusion” keeps surfacing around your pricing page, it’s not just a usability issue, it’s an emotional friction point.

Fixing it isn’t just good UX. It’s good psychology.

Takeaway: AI helps you listen not just to what customers say, but to how they feel, and that’s where true loyalty begins.

5. Listening as a Growth Strategy

When you consistently listen to your customers, three powerful things happen:

1. They tell you what to build next. You stop guessing and start aligning your roadmap to real demand,

2. They sell for you. Customers who feel heard become advocates, not just users.

3. They stay longer. Emotional loyalty beats convenience every time.

Here’s a secret most growth teams overlook: the act of listening is itself a marketing strategy.

When customers see that you ask questions, follow up, and act transparently, they perceive your brand as more trustworthy and more human.

And in an age of AI and automation, humanity is the ultimate differentiator.

Takeaway: Listening isn’t a soft skill, it’s a scalable growth engine.

6. The Human Side of Listening

AI can help you capture and categorize every voice. But it’s still your team’s job to interpret with heart.

Because customers can tell when you’re “analyzing” them versus actually listening.

The future of customer experience isn’t about removing the human, it’s about amplifying empathy through better data.

AI can surface the signals, but it takes people to turn those signals into stories, decisions, and lasting connections.

Takeaway: Technology gives you reach. Empathy gives you resonance.

What This Means for You

Here’s how to start building loyalty through listening:

1. Map your listening points: Where are you hearing from customers now? Make a list: Support tickets, reviews, social, or calls.

2. Use AI to find emotion, not just keywords: Look for frustration, excitement, confusion, and joy across interactions.

3. Identify emotional patterns by segment: Which types of customers feel most seen? Which don’t? That’s where loyalty gaps form.

4. Act visibly on feedback: Communicate changes, share updates, and make customers part of the story.

5. Train your team to respond with empathy: The fastest way to make a customer feel valued? Let them know you’ve really heard them.

At the end of the day, customers don’t stay because of your features, they stay because of how you make them feel.

And nothing makes someone feel more connected than being truly listened to.

So if you want to earn loyalty that lasts, start with the simplest (and most underrated) growth strategy of all: listening well.

Because loyalty isn’t built through automation. It’s built through attention.

That’s a wrap for this week!

What would you like to read about next edition?

Talk soon,

Marian 💚

Hi! 👋

I’ve been in content marketing long enough to see the trends come and go, the SEO keyword-stuffing era, the “blog every day” craze, the rush to video, and now the AI boom.

And here’s what I’ve learned after working with brands of all shapes and sizes: the tactics may change, but the challenge stays the same. Everyone’s fighting for attention, and only a fraction of content actually connects.

Fast forward to 2025, and that challenge has only intensified. Content marketing has never been noisier. AI is flooding feeds with generic posts. AI images and videos are everywhere. Algorithms are shifting daily. Teams feel pressure to churn out “more content” just to keep up.

But here’s the truth I’ve seen play out again and again: content volume alone doesn’t drive growth. Content that deeply resonates with your customers does.

But here’s the truth: Content volume alone doesn’t drive growth. Content that deeply resonates with your customers does.

And where does that kind of content come from? Your customers.

The smartest companies in 2025 are no longer brainstorming in a vacuum. They’re transforming everyday customer interactions into a high-performing content engine using AI to listen, extract insights, and create assets that truly serve their audience.

Here’s how you can do the same:

1. Content Strategy is Shifting from Guesswork to Listening

For years, marketers sat in boardrooms brainstorming blog topics, guessing what their audience might want. That guesswork was risky, often leading to irrelevant content that fell flat.

Today, the shift is clear: the best strategies are rooted in listening.

Every sales call, support ticket, chat transcript, or social comment is an untapped library of content ideas. These aren’t abstract “personas” or vague keyword lists. They’re the real worlds and struggles of your customers. When you build content directly from these insights, it resonates because it’s founded in lived experience.

Think about it: If ten customers in a row ask the same question, that’s a blog post, a video tutorial, a LinkedIn thread, and an FAQ page waiting to happen. Instead of inventing topics, you’re responding to proven demand.

2. AI Makes Insight Extraction Scalable

Here’s the problem: listening takes time. One person can’t possibly read every support email, transcript, or survey response.

That’s where AI steps in.

In 2025, leading companies are deploying AI tools that:

• Transcribe and analyze calls to surface recurring pain points and objections.

• Cluster common questions from customer service tickets to identify top priorities.

• Highlight language patterns that reveal how customers actually describe their needs (often very different from how companies describe them).

This isn’t about replacing human judgement. It’s about giving your team a superpower: the ability to instantly see patterns across thousands of conversations and translate those into content opportunities.

AI does the heavy lifting of synthesis. Your team brings the creativity, empathy, and strategic polish that turns those insights into assets.

3. Every Customer Question Is a Content Opportunity

Let’s make this practical. Imagine you run a Saas platform. On support calls, you keep hearing:

“How do I integrate your tool with the software I already use?”

That single question can become:

• A detailed integration guide on your blog.

• A shot-form video walking through setup.

• A LinkedIn carousel highlighting the top three integrations customers love.

• An FAQ update to reduce support volume.

• A sales enablement one-pager your reps can send instantly.

One customer question can be turned into five high-performing assets.

The magic here isn’t volume - it’s precision. Because you’re not guessing what might work. You’re answering exactly what you customers want to know, in the exact words they use.

4. From Interactions to Insights to Impact

Here’s a simple framework you can use to turn interactions into content:

Step 1: Capture

• Record customer conversations (sales calls, demos, support chats).

• Aggregate feedback from reviews, surveys, and social comments.

Step 2: Extract

• Use AI to identify recurring themes, FAQs, or emotional “hot buttons”.

• Highlight customer language that feels powerful or relatable.

Step 3: Create

• Build content around those insights: blogs, case studies, videos, or social posts.

• Mirror customer language so your content feels instantly familiar.

Step 4: Amplify

• Repurpose each insight across multiple formats and channels.

• Feed back into sales, product, and support so the whole company benefits.

This is how a single customer interaction evolves into a content engine that drives measurable results.

5. The Competitive Edge in 2025

Here’s the kicker: most companies still don’t do this. They continue brainstorming in silos, pumping out posts no one asked for, and wondering why engagement is low.

But the ones who listen? THey’re pulling ahead.

• Their content ranks faster because it’s aligned with actual search intent.

• Their social posts go viral because they echo real customer frustrations.

• Their email campaigns convert because they sound like they were written for the reader, not at them.

In a noisy market, listening isn’t just nice. It’s your unfair advantage.

What This Means For You:

This might be a bit overwhelming. But you don’t need a huge system overhaul to get started. Here are three quick steps you can take ASAP:

• Audit your customer service inbox. Look for the 5-10 most common questions and turn them into content.

• Record your next sales call. Use AI to transcribe and summarize. Highlight one objection or phrase that stand out, and build a post around it.

• Run a quick survey. Ask customers: “What’s the #1 thing you wish you knew before buying/using our product?” Their answers = instant content fuel.

Small steps compound quickly. Before long, you’ll have a repeatable process for turning raw conversations into a pipeline of customer-driven assets.

We can agree that it’s no longer the age of “more content”. It’s now time for smarter content.

By transforming customer interactions into high-performing assets, you’ll cut through the noise, serve your audience better, and fuel growth with content that feels inevitable, because it was built directly from what customers were already asking for.

So the next time you’re stuck staring at a blank content calendar, don’t brainstorm. Just listen. Your customers have already written the outline for you.

If you’re curious how this could work for your team, hit reply and let me know, I’d love to walk you through a real example.

Talk soon,

Marian 💚

Hi! 👋

I’ll let you in on a little secret: the best GTM strategies don’t come from brainstorming sessions or whiteboard workshops. They come straight from your customers.

The words they use. The reasons they buy (or don’t). The emotions driving their decisions.

These aren’t just nice-to-know details, they’re the difference between messaging that gets ignored and campaigns that actually convert.

If you’ve been feeling like your GTM isn’t quite clicking, chances are you’re overlooking a few of these customer signals. Let’s break them down, one by one.

Signal 1: The Words They Use (Not the Ones You Wish They Used)

You might think your product is all about “intelligent automation for operational efficiency.” But your customers might just say: “It saves me time when I’m swamped.”

The difference? It matters. The language you use can both alienate your prospects or bring your ideal customer closer.

Customer-led messaging starts by mirroring the real language your customers use to describe:

• Their pain points

• Their goals

• Their alternatives and competitors

• The way they measure success

How to collect it:

Review support tickets, demo calls, testimonials, online reviews, and customer interviews. Use a simple spreadsheet or a tool like Dovetail or Grain to tag common phrases and themes.

What to do with it:

Use those exact phrases in your landing page headlines, email CTAs, or ad copy. The more a customer feels like you’re describing their exact situation, the more likely they are to convert.

Signal 2: Who’s Actually Buying (and Why)

Many teams define their Ideal Customer Profile (ICP) based on what they think the market looks like. But what does your data say?

You might discover that:

• A different industry is gaining traction

• Your “mid-market” product is resonating more with enterprise teams

• A new segment is using your product in a totally unexpected way

These are all valuable GTM insights hiding in your CRM or support logs.

How to collect it:

Look at win/loss analysis, enrichment tools (like Clearbit), or even manual tagging of your active customer base.

What to do with it:

Refine your ICP and GTM campaigns accordingly. Shift budget or sales enablement to the personas that are actually closing and sticking around. Build use case-specific messaging on what these users care about most.

Signal 3: Why They Churn (and Why They Stay)

Retention is one of the most powerful growth levers, but it’s also one of the most underused when it comes to informing GTM.

Churn signals help you spot red flags early:

• “Didn’t see value fast enough” = This generally means there is a messaging mismatch.

• “Too complicated to use” = This signals that GTM should set better, more realistic expectations.

• “Switched to [insert the name of any of your competitors here]” = It might be time to focus on competitive repositioning.

On the flip side, loyalty signals tell you what’s working:

• “I recommend this to everyone on my team”

• “I love that you [insert feature/value]”

• “Customer support is incredible”

How to collect it:

Run exit surveys, NPS follow-ups, or check-in interviews. Tools like ChurnZero can help structure the data.

What to do with it:

Build messaging that amplifies loyalty drivers and addresses churn risks head-on. Update onboarding flows or marketing assets to highlight retention-worthy value faster.

Signal 4: The Feature Requests and Workarounds

Customers will always find ways to tell you what they want, sometimes directly (feature requests), sometimes indirectly (how they “hack” your tool to solve a problem).

This is gold.

How to collect it:

Check product feedback forms, support requests, community forums, or sales notes. Track feature mentions over time using AI tagging or manual review.

What to do with it:

Use those insights to inform positioning. You might discover a core job-to-be-done that’s not even in your current messaging, or a workaround that points to a major need.

When marketing, product, and sales align around these real use cases, GTM campaigns feel more relevant, and they perform better.

Signal 5: Emotional Drivers and Objections

Humans don’t buy purely logic. They buy based on emotion, and justify it with logic later.

The most effective GTM strategies understand not just the functional benefits of a product, but the emotional triggers that drive action.

Ask yourself:

• What are they afraid of? (Example: “I don’t want to waste money on another tool we won’t use.”)

• What are they dreaming of? (Example: “I want to look like a rockstar to my boss.”)

• What objections do they have? (Example: “This seems too complicated for my team.”)

How to collect it:

Listen to tone and phrasing in demo calls, surveys, or testimonials. You can also prompt your CS or SDR teams to document common objections and “has moments”.

What to do with it:

Speak directly to these emotions in your marketing copy, sales emails, and even your product UI. A good GTM strategy is rooted in empathy as much as it is in data.

Supercharging Your GTM with AI

Manually digging through thousands of customer interactions isn’t scalable. I get it. But that’s where AI comes in.

Natural Language Processing (NLP) and feedback analysis tools like Siena AI, Syncly, or Kodif AI can help you:

• Detect sentiment and intent at scale.

• Cluster qualitative data into themes.

• Highlight priority signals by volume or urgency.

By using AI to analyze your customer data, you can move from gut feelings to grounded strategy, faster.

What This Means For You:

Here’s a quick checklist of customer-led insights that should guide your GTM strategy:

• Real customers phrasing for your copy and ads.

• Buyer behavior trends across ICPs.

• Churn and loyalty patterns.

• Common feature requests or workarounds.

• Emotional motivators and objections.

If you start listening for even two or three of these, your GTM will immediately feel more aligned, and your metrics will show it.

And that’s all for this week!

I’m curious, has a customer ever said something that completely changed how you think about your GTM? If so, I’d love to hear it.

Talk soon,

Marian 💚

Hi! 👋

I don’t know about you, but the last few weeks have felt like a blur. Back-to-back calls, endless notifications, and an ever-growing list of to-dos. Somewhere in between managing deadlines and incoming messages, I’ve experienced first-hand how easy it is for the important things to get lost in the noise.

And if you’re leading a team, that noise can look like customer feedback. Emails, reviews, messages, comments, interviews, support tickets, you name it. They pile up fast and it can feel impossible to keep up. You know the insights are in there, but carving out the time (and brainpower) to sort it all? That’s another challenge entirely.

That’s why this week I want to dig into how top-performing are cutting through the chaos. How they are turning scattered, messy feedback into structured insights they can actually use. Even better, how AI is speeding up the process so you don’t have to choose between “getting by” and actually listening to your customers.

1. Feedback Is Only Valuable When It’s Actionable

You’ve probably heard the phrase: “Customer feedback is gold.” But like raw gold, it’s only valuable when processed. Unstructured feedback can be overwhelming, unclear, and hard to act on. Especially if it’s emotional or inconsistent.

Take this common scenario:

You run a customer survey or collect dozens of support conversations. There’s tons of commentary, but it’s all over the place. Some people love the product. Others are confused. A few are angry. Everyone’s using different language.

Without a way to structure and analyze that feedback, you’ll default to intuition. You’ll make guesses based on the loudest voices. Not the most meaningful patterns.

Takeaway: Feedback without structure leads to noise, not clarity.

2. Frameworks That Help You Make Sense of Qualitative Data

Before you bring in any tools, start by choosing a framework. A framework is generally described as an essential supporting structure in which other things are built on top of. In this case, you need a structured way to categorize and interpret what you’re hearing.

Here are three proven options:

1. Jobs-To-Be-Done (JTBD):

This method helps you organize feedback based on what customers are trying to achieve with your product. Every comment gets linked to a functional, emotional, or social “job”.

Example:

• “I wanted to share my designs quickly with my client.” The job here is to share creative work efficiently.

Use this to identify what outcomes your users care about most, and whether you’re delivering.

2. Thematic Bucketing

This is the simplest and most widely used approach. You define a set of categories based on your product or customer journey (e.g., onboarding, UI, pricing, customer support), and sort each piece of feedback accordingly.

This helps you see which areas get the most positive feedback, and where to prioritize fixes.

Example buckets:

• Feature Requests

• Setup Confusion

• Billing Issues

• Customer Support Experience

• Product Performance

Bonus tip: Track frequency. What themes are mentioned the most? What words keep coming up?

3. Sentiment x Theme Matrix

This method cross-references feedback sentiment (positive, negative, neutral) with themes. It helps you quickly identify where your strengths and weaknesses lie.

This matrix format makes it easier to present findings to leadership and prioritize roadmap changes.

Takeaway: When your feedback is structured, your insights become crystal clear, and decision-ready.

3. How AI Can Speed Up the Process

Manually tagging and categorizing customer feedback is time-consuming. That’s where AI tools come in.

Natural Language Processing (NLP) algorithms can review thousands of qualitative entries: tickets, calls, reviews. They can also categorize them based on topic, emotion, or intent.

Here’s what AI tools like Siena, Syncly, or Zendesk’’s AI capabilities can help you do:

• Auto-detect topics mentioned across feedback sources.

• Tag sentiment (positive, negative, neutral)

• Surface trends that are increasing over time

• Summarize lengthy comments into quick insights

• Create dashboards to share findings across teams

This allows even small teams to get the kind of insight that used to require entire research departments.

Takeaway: AI doesn’t replace analysis. It enhances it.

4. Avoid This Common Trap: Acting Without Context

Not all feedback should be treated equally. AI gives you patterns, but it’s your job to dig into the why. Here are a few quick rules to avoid misinterpreting data:

• Volume matters. One loud complaint does not equal a trend. Wait for recurring themes. And make sure they match. Just because you are getting more returns does not mean they are connected.

• Voice matters. Who is giving the feedback? A power user? A new lead? A churned customer? Context changes everything.

• Time matters. If a spike in negative reviews happened right after a release, the cause may be clear, and fixable.

The best CLG teams combine structured data with human intuition. AI points you in the right direction, but people decide what to do next.

Takeaway: Use AI for pattern recognition, not for final decisions.

5. How to Turn an Insight into Action: What Happens Next?

The final (and most important) step in this process? Doing something with the insights you uncover.

Once you’ve structured the data and identified key themes:

• Loop in the right teams (product, CX, marketing)

• Prioritize based on impact and frequency

• Create a feedback, then take action, and then set up an outcome system

• Close the loop with customers so they know they’ve been heard

Let’s say you discover that customers love your product but consistently mention a lack of integrations. Instead of simply tagging “integration” as a request, you:

• Share it with product and customer success

• Add a top integration to the roadmap

• Update your pricing and messaging accordingly

• Email customers once it’s launched, showing you listened

This is Customer-Led Growth in motion. Your customers told you what they needed. You acted. They stayed. This is the secret if you want to keep new customers coming and retain the one you already have.

Takeaway: Insights are only as powerful when paired with execution.

What This Means For You:

Here’s your action plan for turning qualitative feedback into strategic decisions:

• Choose a framework (Jobs-To-Be-Done, thematic bucketing, sentiment matrix)

• Centralize your feedback sources

• Use AI to speed up tagging, sentiment analysis, and trend spotting

• Share insights with cross-functional team

• Prioritize based on frequency, urgency, and business impact

• Take action, then close the loop with customers

When you treat customer feedback as a system, not a suggestion box, you build a business that evolves in real time.

And that’s a wrap!

Do you have a favorite framework you use to process feedback? Or a question about what tools are best for your team size or goals? Hit reply and let us know, we might feature it in an upcoming issue.

And if this sparked an idea or gave you a new way to think about feedback, pass it along to a teammate who could use it too. Sharing is how we all get better at this.

Thanks for spending a few minutes with me today, I’m glad you’re here.

Talk soon,

Marian 💚

Hi! 👋

The other day, I realized I spend more time asking my barista how their day is going than most companies spend asking their customers. ☕

And that’s wild. Because listening is where growth starts. In fact, you can’t be “customer-led” without, well…customers leading the way. The better you listen, the better you serve, and the faster you grow.

Here’s a quick thought experiment: What if you could sit in on 10,000 customer support calls, read every product review, and scan every sales transcript, all in a single afternoon?

Impossible, right? At least, it used to be.

Today, thanks to AI-powered feedback tools, it’s not just possible. It’s becoming a competitive advantage.

This week, we’re exploring how founders and CX leaders are combining customer feedback with artificial intelligence to unlock high-impact insights at scale. It doesn’t matter if you’re trying to improve retention, guide your roadmap, or write messaging that resonates. It all starts with knowing what your customers are really saying.

This edition is also brought to you by Syncly - and especially their newest launch: Syncly Social.

Here’s the reality: 80% of social conversations now happen in video. But no one has time to watch thousands of TikToks, YouTube reviews, and Instagram reels just to figure out what customers are saying.

Here’s the reality: 80% of social conversations now happen in video. But no one has time to watch thousands of TikToks, YouTube reviews, and Instagram reels just to figure out what customers are saying.

Syncly Social changes that. It’s an AI-powered social listening platform for video — helping brands like Neuro, Logitech, and Laura Geller uncover market, consumer, and creator insights without the grind of manual review.

From spotting emerging trends to understanding exactly how customers talk about your category, Syncly Social gives you superpowers in the video-first world of 2025.

Get early access to Syncly Social.

Get Started for Free

1. Feedback Is a Superpower, If You Can Access It

Every day, your customers are telling you exactly what they want. The problem? Their voices are scattered.

Feedback lives across a dozen platforms:

• Support tickets

• Chat logs

• Call transcripts

• Social media videos

• Online reviews

• Community comments

• Survey results

If you tried to manually go through all of this, you’d need a full research team, or several months. And by then, your product and customer needs may have already shifted. Or worse. You might have a crisis in your hands thanks to not catching things on time.

That’s where Natural Language Processing (NLP) and AI come in. These tools can analyze thousands of data points, in seconds, and return clean, actionable insights.

Takeaway: Your most valuable customer intelligence is already in your ecosystem. It just needs to be unlocked.

2. From Chaos to Clarity: What AI Tools Can Actually Do

Let’s get specific. AI isn’t just about automation. It’s about augmentation. It helps you see patterns humans might miss or surface red flags before they explode into churn.

Here’s what modern AI feedback tools can do:

• Sentiment Analysis: AI can determine whether your customers are happy, frustrated, confused, or neutral, at scale. Instead of sorting by “positive” or “negative” manually, AI can flag the tone of every message.

• Theme and Topic Detection: Recurring themes, like complaints about onboarding, billing confusion, or missing features, are surfaced automatically. You can track how often these show up over time and whether they spike after product changes.

• Early Issue Detection: AI can highlight issues before they’re widespread. For instance, if five customers suddenly start mentioning a bug or billing error, the system can alert your team before it becomes 50.

• Dashboard and Reporting: Some tools create beautiful, shareable dashboards that give your whole team, from product to support, a unified view of what’s really going on.

• Feedback Intelligence: Platforms like Syncly go a step further by connecting feedback from multiple channels, like support tickets, reviews, and surveys, into a single source of truth.

Takeaway: There’s an AI platform for every need. Try different AI platforms to find the perfect fit for your brand’s needs and leverage AI to catch the red flags before they explode into churn.

3. Why Founders Should Care

If you’re a founder or CX lead, you don’t have time to wait for quarterly reports. You need feedback now so you can act on things as soon as possible, way before they become a big issue or a crisis.

AI-powered feedback analysis lets you:

• Prioritize product updates based on real user pain.

• Spot churn risks in customer language early.

• Write messaging that mirrors customer terminology

• Align your team around what customers actually want.

Let’s say you notice a spike in phrases like “confusing to set up” or “needed more help in onboarding.” That tells you two things:

1. You need to refine your onboarding experience.

2. Your marketing should not emphasize “easy setup” until it truly is.

Takeaway: Real-time feedback lets you iterate faster, reduce guesswork, and move with confidence.

4. The Human Touch in an AI World

While AI excels at processing vast amount of data, remember that it’s a tool to enhance, not replace, human understanding.

The goal isn’t simply to categorize feedback, but to truly empathize with your customers’ experiences. AI gives you the “what”, but your team provides the “why” and the “how”. It frees up your time thanks to manual sorting so you can focus on deep-diving into critical insights and crafting truly customer-centric solutions.

Takeaway: The future of customer experience isn’t about ignoring the human element. It’s about leveraging technology to amplify your ability to connect and respond with genuine care and precision.

5. Listening Is the New Selling

In a world flooded with automation and generic messaging, the brands that win are the ones that feel closest to their customers. Not the loudest, not the flashiest, but the best listeners.

Using AI to analyze customer feedback at scale doesn’t mean you’re replacing empathy. It means you’re empowering your team to understand more deeply, respond more personally, and build better solutions faster.

This is what Customer-Led Growth looks like in action. You listen, you learn, and then you lead with exactly what your customers need, when they need it. This is what sets you apart in today’s competitive market.

Takeaway: Listening at scale gives you clarity, speed, and direction: the three ingredients every growing brand needs.

What This Means For You:

Here’s how to start listening to your customers at scale, even if you’re a small team:

• Audit where feedback currently lives (tickets, reviews, transcripts, etc.)

• Choose one NLP or AI tool test. Start small and focus on one channel.

• Look for recurring phrases, emotional language, and early red flags.

• Share insights across teams: product, marketing, CX, and leadership.

• Close the loop by making small, fast improvements based on what you find.

The more consistently you listen, the quicker you get at identifying things on time, and the clearer your growth path becomes.

At the end of the day, Customer-Led Growth isn’t about shouting louder than your competitors. It’s about being the brand that listens better.

If you found this helpful, consider forwarding it to a founder or CX lead who’s ready to stop guessing and start listening.

Talk soon,

Marian 💚

Brought to you by

Hi there! 👋

Last week was nothing short of crazy, in the best way possible. I had the chance to attend my very first conference, and to top it all off, it was in Vegas. ✨

From networking with inspiring people to soaking up new ideas (and maybe a little bit of too much shopping), it was an experience I’ll never forget.

I’m still catching my breath from all the energy, lessons, and late nights that came with the trip, but that’s what makes it so exciting. And now, I get to take you along for the ride by sharing a newsletter that is very much inspired by the conversations I had on my trip.

So, let’s dive into today’s newsletter:

This week’s newsletter is brought to you by Syncly.

Customer feedback is everywhere: support tickets, reviews, surveys, tweets, TikToks… but if you can’t see the full picture, you can’t act on it.

That’s where Syncly comes in. Syncly unifies feedback from every channel and uses AI-powered tagging and dashboards to turn messy conversations into actionable insights. Imagine being able to:

• Spot exactly what’s driving customer complaints or product love.

• Ask questions like you would with ChatGPT and get real, data-backed answers.

• Align your marketing, product, and CX teams on what customers actually want.

Brands like Kimberly-Clark, Brita, and Buldak Ramen rely on Syncly to move faster and stay closer to their customers.

Want to see how Syncly can help you?

Book Demo

Have you ever read a brand’s website or seen an ad and thought, “Wow. That’s exactly how I feel”?

It’s not magic. It’s not coincidence. It’s Customer-Led Positioning.

Customer-Led Positioning is the practice of building your brand voice around the exact words your customers use. Instead of guessing, you’re extracting phrases directly from interviews, reviews, and conversations.

It’s one of the simplest but most powerful ways to stand out, connect, and convert in a noisy, fast-paced market.

This week, we looked into why messaging built around customer language performs so well, and how you can tap into the same strategy to make your brand feel magnetic.

Here’s how:

1. The Brands You Love Are Listening

There’s a reason certain brands feel like they speak directly to you. It’s because they actually do. And not just in tone, but in words. The very same words you’ve used to describe your problems, your goals, and your ideal outcome.

Brands like Airbnb, Duolingo, and Shopify didn’t create their messaging in a vacuum. They mined reviews, analyzed support conversations, hosted interviews, and pulled exact phrases from these sources into their copy.

This approach is called Customer-Led Positioning, and it flips traditional advertising on its head. Instead of guessing what messaging will resonate, you let your customers tell you, then use their exact words to craft copy that feels tailor-made.

Takeaway: Positioning built on assumptions creates distance. Positioning built on customer language builds trust.

2. Why This Works (Psychology + Conversion)

Let’s talk about why customer-led language isn’t just a nice to have but a real conversion driver.

Here’s what happens when people read copy that mirrors their own language:

• They feel seen and understood.

• Their trust increases.

• They believe you understand their problem, and can solve it.

This emotional recognition creates what psychologists call the mirror effect. When a person recognizes themselves in your messaging, they’re more likely to believe you’re the right fit. And that makes them far more likely to buy.

In fact, research from behavioral economics shows that people are more influenced by language that reflects their current internal state than by abstract promises or benefits.

So when your ad says, “Tired of switching between five different tools to do one job?”, and that’s exactly what the customer is feeling, it triggers an instant sense of alignment.

Takeaway: When customers see themselves in your words, they see your product as the obvious solution.

3. It’s Not Just About Marketing, It Aligns Your Whole Organization

Customer-Led Positioning doesn’t just benefit marketing. It helps your entire company speak the same language.

Here’s why that matters:

• Sales teams close faster when they use messaging customers already resonate with.

• Product teams prioritize better when they understand how users talk about pain points.

• Customer success and support can tailor communication more effectively.

When everyone from marketing to sales to product is working from the same source of truth, meaning your customer’s words, you create consistency and alignment across the entire customer journey.

No more miscommunication. No more brand voice whiplash. Just a unified, clear experience from the very first touchpoint and beyond.

Takeaway: Internal alignment leads to external clarity. That starts with listening.

4. How to Start (Even If You Have Zero Data Right Now)

If this is your first time thinking about Customer-Led Positioning, don’t worry. Getting started is easier than you think.

Here’s a simple framework to begin using customer language to fuel your messaging:

Step 1: Gather Raw Voice-of-Customer Data

Listen to 5-10 recent sales calls, demo recordings, or support conversations. If you don’t have recordings, start with public sources:

• Product reviews

• Reddit or Quora threads

• Testimonials

• Survey responses

Step 2: Highlight Emotionally Charged Language

You’re looking for phrases that reflect frustrations, desires, comparisons, or “aha!” moments. These phrases are gold. They reveal the real emotional drivers behind purchase decisions.

Some examples are:

• “I just wanted something that worked right out of the box.”

• “It felt like I was piecing together five different tools.”

• “We finally stopped losing deals once we implemented this.”

Step 3: Build a Swipe File of Phrases

Create a spreadsheet or a Notion page where you collect all the best quotes and snippets. Label them by category: pain points, desired outcomes, objections, product love, etc.

Step 4: Plug and Play

Take those exact phrases and use them in:

• Landing pages

• Ads and email headlines

• Sales scripts

• Social media copy

• Onboarding flows

Pro tip: Don’t edit the phrases or tweak the language. Leave the phrases raw and conversational. That’s what makes them feel real and powerful.

Example: If your customer says, “I don’t want to spend 6 hours setting this up,” your headline could be: “Set up in minutes, not hours.”

5. The Result? A Brand That Feels Like a Friend

When your copy uses the words your customers actually use, it creates a sense of familiarity. It stops sounding like “marketing”. It starts sounding like a conversation.

And in 2025, where AI-generated content is everywhere, authenticity stands out. The brands that connect will be the ones that feel human, and customer-led messaging is one of the easiest ways to do that.

One of our favorite examples is Notion. Their positioning evolved over time based on how real users described it: "your second brain”, “all-in-one workspace”, “notes that talk to each other”. Those phrases didn’t come from a branding agency. They came from the community.

Takeaway: Great copy doesn’t come from creativity alone. It comes from listening.

What This Means For You:

Ready to start speaking the language that sells? Here’s your quick checklist:

• Listen to your customers: in reviews, interviews, calls, and support tickets.

• Highlight emotional and specific language (pain points, goals, outcomes).

• Use those exact words in your marketing, sales, and product messaging.

• Create a living swipe file that your whole team can access.

• Refresh your messaging regularly based on evolving customer input.

Customer-Led Positioning isn’t just a one-time tactic. It’s a long-term habit. And the more you use your customers’ words, the more powerful your brand becomes.

And that’s a wrap on our second edition!

Have a great example of CLG in action? Or want help applying this framework to your team? Just hit reply, I’d love to hear from you. ✨I’d love to feature real, personal stories in a future issue.

And if this helped you think differently about how you position your brand, would you forward it to a teammate or a friend? The more we center the customer, the better we grow.

Also, don’t forget to share your conference or Vegas tips. I would really appreciate them!

Talk soon,

Marian💚

Brought to you by

Hello! 👋

Welcome to the Customer-Led Growth: The Newsletter, your one stop for growth information.

This is a new adventure for me. And now, it’s one for you too. One where we will talk A LOT about what it takes to grow, especially in a world where it’s more complicated than ever.

Because let’s be honest: AI is evolving faster than we can blink. Customer expectations are higher than ever. And traditional growth playbooks? They’re starting to feel outdated.

So I took a step back and started looking for what’s ACTUALLY working in 2025. I read case studies. I analyzed strategies. I listened to the voices of actual customers (lots of them).

And here’s the big insight that kept coming up: The most successful companies aren’t just using AI, they’re using it to get closer to their customers.

They’re not louder. They’re not faster. They’re just listening better. And in this market, that makes all the difference. You’ve probably felt it yourself. That moment when a brand makes you think, “Wow. They get me.”

That’s not luck. That’s customer-led growth.

So, in this first issue, we’re kicking things off by breaking down what CLG really looks like in action. And how you can start applying it right now.

1. Growth Playbooks Are Being Rewritten

Over the past decade, we’ve seen two dominant growth models: Product-Led Growth (PLG) and Sales-Led Growth (SLG). Both have their merits. PLG focuses on product experience to drive adoption, while SLG puts energy into outbound efforts and closing deals.

But both models often have one flaw in common: they center the business first, not the customer. Products are built based on assumptions. Sales motions are driven by internal quotas. And customer feedback? It’s often a box to check, not a guiding principle.

Customer-Led Growth (CLG) changes the game.

It’s not about what you want to sell, it’s about what your customers actually want and need. It’s about creating feedback loops that fuel your strategy at every stage. This means building strategies with your customers, not just for them.

CLG isn’t a tactic. It’s a mindset shift, and a leadership-level one at that.

Takeaway: Growth isn’t about pushing harder. It’s about listening better.

2. Customer Signals Are the New North Star

Your customers are your most accurate growth signals. Their needs, frustrations, and desires give you real time insights into what is working and what isn’t. This information gives you an advantage when it comes to what you build and how you sell.

Now think of all the places your customers are telling you what matters:

• Support tickets

• Sales calls

• Product reviews

• Community forums

• Social media threads

There’s a goldmine of insights waiting to be tapped. And yet. More often than not, these signals are siloed across departments. Or worse. Ignored completely.

The smartest companies in 2025 are building systems to gather, analyze, and act on customer signals. They treat feedback not as a “nice to have” but as the core driver of product, marketing, and sales decisions.

Take Figma, for example. Before it became the design world’s darling, it was a team obsessed with learning directly from designers. They didn’t design what they wanted to see in the world or just guess what users wanted. They embedded designers into their product process, held deep user interviews, and built exactly what their audience needed.

Takeaway: Your next big idea is already living in a customer complaint or suggestion.

3. AI Supercharges Your Ability to Listen

If you’re wondering, “But how do we scale all that listening?”: good news: AI is here to help.

In the past, it would’ve taken entire teams weeks to manually read through customer reviews or call logs. Today, with the right tools, AI can surface key themes, emotions, urgent issues, and more, in minutes.

Voice-of-customer analysis, sentiment tracking, and trend prediction are just some of the features that help AI enable CLG at scale. Instead of relying on lagging indicators like churn, you can detect friction before it becomes a problem. You can spot patterns and proactively improve experiences.

What’s key here is not using AI instead of human empathy, but alongside it. AI can amplify your understanding, but you still need humans to interpret and act with nuance.

Takeaway: Let AI be your ears. Your team still needs to be the heart.

4. Retention is the New Acquisition

Acquiring new customers is 5x more expensive than retaining existing ones. You’ve probably heard this before. And CLG companies get this.

When you focus on delighting current customers, they don’t just stick around. They help you grow. They upgrade. They refer. They advocate for your brand without being asked. And in today’s digital age, your reputation and the trust of your customers are worth its weight in gold.

In fact, we’re seeing a shift where expansion, retention, and referral revenue are outpacing new logo acquisition as growth levers. And customers only do those things when they feel genuinely valued.

This means going beyond flashy dashboards or one-off NPS surveys, and building systems where customer insights actually shape decisions, such as roadmap prioritization, messaging, and onboarding flows.

Keep in mind that when your go-to-market motion aligns with real points, you convert faster and retain longer.

Duolingo nails this. Their team constantly iterates based on how real learners interact with the app. They focus on refining UX, tone, and even humor, which keeps users engaged longer and turns them into vocal brand fans that keep coming back for more.

Takeaway: CLG turns customers into your most powerful sales and marketing channel.

5. Human Connection > Hype

In 2025, we’re all moving fast. Automations are everywhere. But what customers still crave is simple: a human connection.

The companies that lead with empathy, transparency, and genuine listening? They stand out. Even if their tech isn’t the flashiest.

Customer-Led Growth works because it prioritizes relationships over reach. It builds trust. And trust compounds.

Even the most cutting-edge AI can’t replicate the feeling of being heard, understood, and valued. CLG ensures your company doesn’t lose that, even as you scale.

Takeaway: Your customers are at the center of it all. CLG helps you focus on them and makes your brand more human, and that’s your edge in an automated world.

What This Means For You:

Here’s your mini playbook for putting Customer-Led Growth into practice:

• Shift your team’s mindset from “customer-focused” to customer-led. Invite customers into your decision-making process.

• Use AI tools (like voice-of-customer platforms, call summarizers, and review analyzers) to identify patterns, pain points, and ideas in real time.

• Rethink your go-to-market strategy: prioritize retention and expansion just as much as acquisition.

• Build feedback loops into every part of your org: product, marketing, sales, support. Ask: What are customers saying, and how are you acting on it?

• Most importantly: stay human. Use tech to get closer, not further, from the people you serve.

Let 2025 be the year you move closer to your customer, not further.

And that’s it for our first edition ever! Wild, right?

If you’ve seen a company doing Customer-Led Growth well, have questions about how to implement this mindset in your team, or simply would like to leave some feedback, I’d love to hear from you.

And if this resonated with you, feel free to forward it to a friend or teammate. Let’s spread the CLG mindset together, one conversation at a time.

Talk soon,

Marian 💚

P.S. In the next issue, we’re diving into how to actually speak your customer’s language, and why the words they use matter more than the ones in your brand book. You won’t want to miss it.