Sixteen comparable cases.
What actually happened.
Reception, outbound, reviews, pipeline, marketing ROI, retention, manual processes and visibility: each one with the problem as the owner described it, what got built, and the number it moved.
We don't promise the same for you. We show what happened when a comparable solution operated well in a case from your vertical or size.
Showing all 16 cases.
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ReceptionMid-marketRegional hotel group · 12 properties · ~USD 2M monthly revenue · EN/ES
+22% booking conversion 90 daysEvery inbound answered in 60 seconds, 24/7, EN/ES. Booking conversion +22% vs the prior quarter. Outsourced answering service cancelled. Two reception shifts redirected to on-property guest experience.
The problem
Bookings falling into voicemail after 7pm and on Sundays. Spanish pre-arrival queries got answered by whoever was near the phone. Two reception shifts per property plus an outsourced answering service routing 3–5% of calls to the wrong destination.
What operated
24/7 bilingual reception.
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ReceptionSmall businessHome services · ~USD 3M revenue · 11 trucks · single province
+20% same-day jobs 90 days~120 emergency inbounds captured per month that used to go to voicemail. Same-day jobs +20%. The owner sleeping at night from week 5 onward.
The problem
The owner handled after-hours emergencies personally, typically 4–7 per night. About 30% were lost: asleep, on another job, talking to a customer. Each missed call: ~USD 850 in emergency service going to the competitor.
What operated
After-hours emergency call capture.
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OutboundMid-marketUS service operator · 30+ cities · EN/ES mix · USD 8–14M revenue
893 qualified leads 90 days893 qualified leads delivered across 36 cities, EN/ES. Reply rate 12.4% vs a prior baseline of 1.8% with cold templates. Cost per qualified meeting USD 42, against the in-house rep's loaded cost of USD 187 the prior year.
The problem
The last dedicated outbound rep left mid-quarter. The pipeline went from 40+ qualified meetings a month to 8 in six weeks. The CRM had 12,000 cold contacts; no one had touched them in over a year.
What operated
Outbound lead generation and qualification.
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OutboundMid-marketWholesale brand · B2B export · multi-category catalog · ~USD 5M GMV in US channel
31 qualified meetings 90 days · 24% above target31 qualified meetings booked against a target of 25. Weekly pipeline visibility. The tools the brand was already paying for finally delivering outcomes: same retainer, no extra licenses.
The problem
They were targeting retail buyer accounts in 12 specific US states. The outbound stack (Apollo, Outreach, Sales Navigator) had been idle for six months because they couldn't find anyone to operate it.
What operated
Outbound campaign execution on the tools they already had.
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ReviewsMid-marketMulti-location professional services · medical/dental/legal · 8 locations · ~USD 12M revenue
4.2 → 4.6 rating 90 daysAverage rating 4.6. Review velocity +210% across the portfolio. The two lowest locations pulled to within 0.1 stars of the corporate average. Negatives now answered in 47 minutes on average.
The problem
Average brand rating 4.2 across Google, Yelp and sector platforms. One-star reviews routinely went unanswered for 4–7 days because no one owned the task. Booking conversion at the weak locations ran 12–18% below the corporate average.
What operated
Centralized review monitoring and response.
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ReviewsMid-marketMulti-location retail/hospitality · 24 branches · 5 metro markets
4.2 → 4.5 brand rating 90 daysThe two weak locations crossed above the corporate average. Brand rating back to 4.5. Corporate marketing stopped fielding branch-specific reputation complaints.
The problem
Per-location review velocity ranged from 4 reviews a month at strong locations to 0–1 at weak ones. Two low-performing branches dragged the corporate rating from 4.5 to 4.2.
What operated
Unified review generation across locations.
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PipelineSmall businessHigh-volume services · ~280 leads/month · single province · USD 4–6M revenue
+21% lead‑to‑close 120 daysLead-to-close conversion +21%, from a baseline of 14% to 17%. Cold-lead reactivation captured ~USD 340K of pipeline that would have died. The owner stopped calling it a sales problem and started watching the right metric.
The problem
CRM full but only the easy deals were closing. Reps followed up on day 1 then abandoned the rest: 60% of pipeline value never got a second touch. The owner had been calling it "a sales problem" for two years.
What operated
Automated lead follow-up and nurturing.
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PipelineMid-marketB2B · 30–90 day sales cycles · deals USD 25K–150K
~10% of dead pipeline back 90 days~10% of dead pipeline reactivated. No deal sitting more than 4 days past its stage commitment. Reps stopped triaging which deals were alive: the system tells them.
The problem
Each rep carried 40–60 active opportunities. "I'll call you back" deaths happened silently: nobody noticed until the quarterly close-rate report. The average deal sat 2.3 weeks past its stage commitment before anyone touched it.
What operated
Deal tracking with stage-based alerts.
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Marketing ROIMid-marketDTC ecommerce · USD 1M–10M annual GMV · primarily Meta + Google
Meta CAC −33% 90 daysMeta CAC USD 39, down 33% from baseline. POAS turned positive on 6 of the 9 SKUs that had been negative. Landing conversion 1.7%, from a baseline of 0.7%.
The problem
Meta CAC had been climbing quarter over quarter for 18 months, from USD 34 to USD 58. Landings were converting below 1%. The agency kept reporting that spend efficiency was within target while CAC kept rising.
What operated
Meta optimization and landing conversion work.
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Marketing ROISmall businessLocal services · USD 5–15K/month in Google Ads · single region
Cost‑per‑lead −25% 90 daysCost-per-lead USD 46, down 25%. Quality score climbed from 5.3 to 7.8 across the account. Content inbound contributing 22% of new leads by month 6.
The problem
Quality score below 5 on half the keywords. Cost-per-lead climbing from USD 42 to USD 61 over 14 months. The owner convinced that Google was simply getting more expensive.
What operated
Google Ads account rebuild and content strategy.
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RetentionMid-marketMulti-property hospitality · regional brand · 14 properties · ~26,000 guest records
Returning guests +18% 90 daysReturning guest rate +18%, from a baseline of 23% to 27%. Cross-property bookings +34%. Newsletter retired; targeted lifecycle generates 4× the revenue per send.
The problem
No cross-property tracking. The same loyal guest got treated as new on every visit to a different property. Lifecycle marketing was a generic monthly newsletter going to all 26K with a 7% open rate.
What operated
Cross-property guest tracking and targeted lifecycle.
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RetentionMid-marketDTC ecommerce · mature catalog · ~45,000 customers · 14% repeat rate
Repeat rate 14% → 19% 90 days~2,400 dormant customers reactivated, 7.5% of the dormant base. Repeat rate climbed to 19% within the active base. LTV/CAC improved from 2.1 to 3.4.
The problem
Customers bought once and vanished. ~32,000 customers had never been touched after their first transaction.
What operated
Dormant customer reactivation.
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Manual processesSmall businessServices business · ~22 people · single region · USD 5M revenue
~70 hours a month gone 60 days~70 hours a month of manual work eliminated. The office manager redirected to a client-success role; she stayed. The forecast for two more admin hires was killed.
The problem
The office manager and ops coordinator were drowning in invoicing, scheduling and weekly reports. The owner had two more admin hires forecast to cross USD 7M. The office manager was a flight risk: they'd already lost two in the past year.
What operated
Process automation for invoicing, scheduling and reporting.
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Manual processesMid-marketMulti-store ecommerce ops · 4 stores · two platforms · ~USD 15M GMV
2× capacity, same headcount 90 daysTwice the volume capacity without adding ops headcount. The projection for four more people went to zero: the next hires went to merchandising instead.
The problem
Order exceptions, returns and supplier coordination handled by hand. The ops lead's projection: we can't scale to 6 stores without adding 4 more ops people.
What operated
Ops workflow automation across both platforms.
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VisibilityMid-marketMulti-store ecommerce · USD 5–25M annual GMV · two platforms
Anomalies caught in hours 60 daysDashboard in active weekly use. The first two alerts: a returns spike on one SKU, caught 19 days before it would have hit the monthly P&L, and a conversion drop at the biggest store, caught in hours. The monthly P&L stopped bringing surprises.
The problem
Level-2 contribution margin, POAS, inventory and churn all in separate spreadsheets. Numbers always 2–3 weeks out of date. The monthly P&L review surfaced problems that had been growing for 4–6 weeks.
What operated
One dashboard with anomaly detection.
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VisibilityMid-marketMulti-property hospitality · 19 properties · ~USD 2.1M monthly revenue
4–5 days → 6 hours 60 daysMonth-end reconciliation from 4–5 days to 6 hours. A single executive view replaces three weekly ops calls. ~10,000 monthly transactions auto-reconciled.
The problem
P&L, pricing, booking profitability and reconciliation scattered between PMS exports and Excel. Reconciliation alone consumed 4–5 days every month-end across the central ops team.
What operated
Centralized reconciliation and P&L visibility.
Does any of these look like yours?
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