Know exactly why customers churn, convert, and come back
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See why leading product teams are replacing surveys with AI-powered conversations.
No engineering sprint. No month-long rollout. Just plug in and go.
Paste your website URL. Pulsepath scans your site and instantly learns your brand voice, products, and industry.
Give it a name, choose a personality, and define what you want to learn from your customers.
Share via email, embed on your site, or send a link. Themes, sentiment, and recommendations surface in real time.
Pulsepath doesn't just collect feedback. It organizes, analyzes, and prioritizes it — so you always know what to build next.
Add customer-reported fit data to product pages to reduce sizing uncertainty.
Simplify the checkout flow — 3 out of 4 complaints cite too many steps.
Add estimated delivery dates to the cart page to reduce post-purchase anxiety.
No context-switching. Insights flow directly into your workflow — so your team can act without leaving the tools they live in.
One-click install. Collect post-purchase feedback directly on your order status page and trigger outreach from new orders.
Push feedback events to Klaviyo profiles. Power segments based on sentiment, feature requests, and issue reports.
Sync feedback events into SMS journeys. Trigger personalized messages based on customer sentiment and feedback.
Trigger automated outreach via SendGrid or Mailgun. Reach customers at the right moment with personalized follow-ups.
Connect any tool in your stack. Trigger insights agent conversations from Stripe events, HubSpot deals — anything.
Weekly or monthly insight digests delivered straight to your inbox. Keep your whole team aligned without a single meeting.
Turn feedback into tickets with one click. Full conversation context, sentiment, and themes attached automatically.
Get real-time alerts in your team channels when new themes emerge, alarms trigger, or high-impact feedback arrives.
Sync insights directly into your CRM. Enrich contacts with feedback sentiment, themes, and conversation history.
Every company has blind spots. Here’s how Pulsepath finds them.
Your NPS is 87% positive, but enterprise customers are quietly churning. Exit surveys say “budget constraints” and “vendor consolidation”—but that’s not the real reason.
A insights agent has ongoing conversations with your enterprise segment and discovers a pattern: 11 customers mention “authentication complexity” in different ways. They got your feature working, but it took 3–5 days of engineering time and created friction with security teams. They’re not complaining because they assume this is normal—but competitors are pitching “native SSO out of the box” and winning deals.
You ship enterprise SSO integration in 3 weeks instead of building 6 months of “advanced features” that would’ve made the problem worse. Enterprise adoption jumps from 34% to 71% in one quarter. You retain $1.8M in at-risk ARR.
Your Customer Success team has a playbook: check in quarterly, ensure customers are “healthy,” renew them. But expansion conversations feel awkward—you don’t want to seem pushy. So you wait for customers to ask about upgrades.
Most never do. Your expansion revenue is 12% of total ARR when industry benchmark is 30%.
A insights agent has casual conversations with your highest-usage customers (top 20% of activity). Through natural dialogue, it discovers:
None of this shows up in support tickets. Customers solved the problems themselves.
You create three expansion plays: API add-on for the 8 hitting limits ($14.4K ARR), seat expansion for the 15 sharing logins ($42K ARR), and cross-sell Product B for the 12 who don’t know you offer it ($168K ARR).
Total expansion captured in 60 days: $224K ARR (18.7% increase).
Your free trial conversion rate is 18%. Industry average is 25%. You’ve tried better onboarding emails (no change), in-app tooltips (slight improvement), and live chat (people don’t use it).
Your hypothesis: “The leads aren’t qualified.” But 40% of trials never even complete setup. They sign up, log in once, and disappear.
A insights agent reaches out to 50 users who signed up but never completed onboarding: “We noticed you started setting up but didn’t finish. Mind if I ask what happened?”
You fix each blocker: “Concierge Onboarding” for integration issues (+24% conversion lift), “Quick Start” presets for decision paralysis (+31% completion), and gentle nudge sequences for forgotten trials (+18% reactivation).
Trial conversion rate: 18% → 29% in one quarter (+61% relative improvement).
You shipped “Advanced Analytics” after 6 months of development and $400K investment. Customers asked for it. Your advisory board said it was critical. Competitors have it.
Adoption after 3 months: 8%. Nobody knows why because nobody asked the 92% who aren’t using it.
A insights agent reaches out to 40 customers who haven’t activated it: “We noticed you haven’t tried Advanced Analytics yet. Just curious—what’s holding you back?”
You make it visible (main nav, not buried in settings), rename it to “Revenue Forecasting” with a clear subtitle, and offer setup help with auto-populated templates.
Adoption: 8% → 34% in 60 days. 12 customers say it’s now their most-used feature. 3 upgrade to higher plans. The feature you almost killed becomes a differentiator.
Your bestselling bomber jacket has 4.8-star reviews on 847 orders. Sales are strong. Returns are only 8%. Everything looks healthy.
But 23% of customers who buy the jacket never purchase again. Your repeat rate for other products is 41%. Something about this jacket is killing lifetime value—but reviews don’t tell you what.
A insights agent reaches out to 50 recent buyers. The 4.8-star reviews are hiding two experiences:
18 of 50 mentioned color/photo mismatch, 14 mentioned sizing, 9 mentioned fabric weight. None left negative reviews—the jacket isn’t bad enough to return. They just quietly shop elsewhere.
Three simple changes in 2 weeks: updated photos with natural lighting, sizing guidance (“Runs small—size up”), and accurate descriptions (“Lightweight 8oz cotton blend”). Returns drop from 8% to 4%, repeat purchase rate jumps from 23% to 38%, overall store repeat rate increases from 41% to 47%.
Your damage rate is 6% (120 out of 2,000 monthly orders). Those customers get an immediate replacement and $10 store credit. Problem solved, right?
But repeat purchase rate for customers who received damaged items (even if replaced): 12%. For undamaged orders: 43%. Something about receiving a damaged item kills lifetime value—even when you fix it.
A insights agent reaches out to 50 customers who received damaged items:
Better internal protection (+$0.80/order), prepaid return labels with replacements shipped BEFORE returns arrive, and a proactive insights agent asking ALL customers “How did your order arrive?”
Damage rate: 6% → 2.5%. Repeat purchase rate for replaced orders: 12% → 31%. Net impact: +$180K annual revenue from retained customers.
Your #2 return reason (18% of returns): “Color didn’t match the photo.” You’ve tried professional photography, color swatches, and “colors may vary” disclaimers. Nothing works.
A insights agent reaches out to 60 customers who returned items for color mismatch. It’s NOT a photography problem:
Multi-context photos (bright/natural/dim lighting), screen calibration warnings, and brutally literal color names (“Forest Green” → “Olive Green”).
“Color mismatch” returns: 18% → 7% in 90 days. Saved: $31K/year in return shipping + restocking.
You run a monthly subscription box. Month 1 retention: 77%. Month 6 retention: 41%. Your cancellation survey says “too expensive” (34%), “didn’t like the products” (28%), and “other” (38%). So you focus on better curation and lower pricing—but churn stays high.
A insights agent reaches out to 50 customers who canceled after 1–2 boxes conversationally: “What would’ve made you stay?”
Pre-renewal reminders with one-click skip (−68% forgotten cancellations), product preference personalization (−41% inconsistency cancellations), and easy flex controls for skip/pause/swap (−55% control cancellations).
Month 1 retention: 77% → 86%. Month 6 retention: 41% → 59%. Annual revenue impact: +$340K from reduced churn.
Your cart abandonment rate is 72%. There’s a strange pattern: customers abandon carts at $48–$49 at 2x the rate of carts at $35–$40. They’re $2 away from free shipping—why not just pay the $6.99?
A insights agent reaches out to 50 customers who abandoned carts between $45–$49:
Dynamic messaging at $45+ (“You’re $X away from free shipping!”), real-time cart updates with a visual progress bar, and streamlined guest checkout with express payment.
Abandonment for $45–$49 carts: 82% → 54%. Overall cart abandonment: 72% → 64%. Revenue impact: +$89K/month.
Your product has a 4.2-star average. The distribution is weird: 58% five-star and 9% one-star—lots of love AND hate, very few in between. Both extremes talk about “quality.” Is it inconsistent? Are some units defective?
A insights agent reaches out to 30 customers who left 1-star reviews citing “quality issues”:
The 1-star reviews aren’t quality issues—they’re use case mismatch.
Clear use-case guidance on product pages (“Best for: hot yoga, studio practice. Not ideal for: outdoor use, concrete floors”), sizing quiz, and cross-links to alternative products for mismatched use cases.
1-star reviews: 9% → 3%. Average review score: 4.2 → 4.6. Return rate: 11% → 6%. Bonus: you launch an Outdoor line—new $180K/year product line.
Influencer campaign: $5K paid, 847 orders, $67K revenue. Looks like 13x ROAS. But 90 days later: 71% returns (vs. 8% average), 4% repeat purchases (vs. 43% average). Net revenue after returns: $19K (3.8x ROAS). The influencer sent traffic, but almost everyone returned or never bought again.
A insights agent reaches out to 50 customers who bought via the campaign:
New influencer playbook: vet content for accuracy before launch, limit deep discounts (offer “free gift” instead), and test with small campaigns first. Re-run with new guidelines: 624 orders, 14% returns (vs. 71%), 38% repeat purchases (vs. 4%). Net ROAS: 9.6x vs. 3.8x.
You run a service business. The pattern: onboard a client ($10K–$50K project), week 1–2 great, week 3–4 slower to respond, week 5+ radio silence. Your ghosting rate: 18%. “Checking in” emails get ignored. Partial work goes unpaid. Time wasted.
A insights agent reaches out to 20 clients who went dark mid-project conversationally:
Micro-feedback loops (small pieces for quick review instead of big deliverables), proactive check-ins at risk points (week 3, after big deliverables), and budget transparency (weekly spend updates).
Ghosting rate: 18% → 6%. Projects completed on time: 64% → 81%. Client NPS: 42 → 67.
Revenue: $480K/year. Gross margin: −12%. Hours worked: 65/week. The pattern: client asks for “a quick thing,” you say “sure, no problem!” Project scope doubles, budget stays the same, your margin disappears. You know you need to say no, but you don’t want to lose clients.
A insights agent asks current clients mid-project: “How’s the project going? Anything you wish we were doing differently?”
Clients don’t expect free work. They just don’t know what’s in/out of scope unless you tell them.
“Scope Checkpoint” emails at kickoff, “quick thing” pricing ($500 for <2 hours), and monthly retainers for ongoing clients ($3K/month for up to 10 hours).
Gross margin: −12% → +38%. Hours worked: 65/week → 45/week. Client retention: 81% (unchanged—they didn’t leave!). Revenue: $480K → $520K.
Your NPS is 78. Clients say “best agency we’ve ever worked with.” But your referral rate is 4% (benchmark: 15–20%). Referral programs, direct asks, and hoping for organic referrals—nothing works.
A insights agent asks your 10 happiest clients conversationally: “Do you know other companies who might benefit from what we do?”
Your clients WANT to refer you. They just don’t know who, what to say, or how to protect their reputation.
Share an Ideal Client Profile so they know who to refer, provide a simple “referral script” they can copy/paste, and offer a “free 30-min strategy session” for referrals (removes risk for the referrer).
Referral rate: 4% → 23% in 6 months. New clients from referrals: 14 ($280K in new revenue). Cost: $0.
Your close rate is 35%. You lose 40% of deals with “price is too high.” You’ve tried lowering prices 20% (margin tanked, close rate barely moved), payment plans (slight improvement), and adding more value (didn’t help). Even when you lower prices, some prospects STILL say it’s too expensive.
A insights agent reaches out to 30 prospects who said “no” due to price: “If price wasn’t an issue, would you have moved forward?”
When prospects say “too expensive,” they mean: “I don’t trust this will work,” “this is more than I need,” or “not the right time.”
Build trust before talking price (case studies + guarantee), create modular pricing (Starter $8K, Growth $18K, Premium $30K instead of one $30K package), and address timing directly (“Want to lock in this price now and start in Q2?”).
Close rate: 35% → 48%. “Price objection” deals: 40% → 12%. Total revenue: +$240K/year.
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