Most service businesses ask for reviews inconsistently โ after some jobs but not others, from some customers but not all, at whatever time the technician happens to remember. HieCOR automates the entire review request workflow โ triggered at job completion, filtered to exclude complaint-risk customers, timed by AI for maximum response, and sent by the channel that actually gets replies.
No commitment required ย ยทย US-based implementation team
Review Request Lifecycle
Review requests fail when they go to the wrong customers, arrive at the wrong time, feel generic, or send replies into a dead inbox. HieCOR connects every step from job completion through performance tracking in one automated review generation platform.
The moment a service ticket is closed, a delivery is confirmed, or a job is marked complete in HieCOR, the review request workflow begins. HieCOR checks whether the customer had any unresolved complaints, open issues, or active disputes โ and if not, schedules the review request at the AI-optimized timing. No one on your team has to remember to send it.
HieCOR checks every completed job against your qualification rules before sending a review request. Customers with an unresolved service ticket, an open dispute, a complaint in their recent message history, or a partial payment are excluded automatically. Only customers with a fully confirmed positive completion receive the request โ protecting your rating from complaints that should have been resolved first.
Morgan AI analyzes your historical review response data by job type, customer segment, time of day, and day of the week โ and sends the review request at the timing that generates the most responses. A 48-hour wait after a furniture delivery. A same-day request after a washer repair. A morning send for commercial accounts. The timing is optimized per customer type, not one-size-fits-all.
Review requests go out by SMS with a direct link to leave a review on Google, Yelp, or your preferred platform. The message is personalized with the customer's name, the technician's name, and the specific job completed โ so it reads like a personal message from your business, not a bulk review blast. Every request is logged on the customer record.
When a customer responds to a review request โ whether with a positive message, a question, or a concern โ the reply arrives in the HieCOR 2-way inbox with their full service record, job details, and the original review request already visible. Taylor AI routes complaint-adjacent replies to the service manager before they become a public negative review. Positive replies are logged on the customer record.
HieCOR tracks every review request โ sent, opened, clicked, and converted to a review โ per job type, technician, and customer segment. Morgan AI surfaces the technicians with the highest review conversion, the job types that generate the most responses, and the customers who received a request but did not respond. Review performance improves every cycle.
From every completed job to a growing review profile โ automated, qualified, timed, and tracked.
See a 30-minute demoCore Capabilities
HieCOR connects job completion triggers, complaint-risk qualification, AI timing optimization, personalized SMS delivery, reply routing, and performance tracking in one review generation operating system.
Every service close, delivery confirmation, and installation completion triggers the review workflow automatically. No manual action needed from your team.
HieCOR checks every completed job for unresolved tickets, open disputes, complaint history, and partial payments before sending. Only clean completions proceed.
Morgan AI optimizes send timing per job type and customer segment based on your historical response data. The request goes out when that customer type is most likely to respond.
Review requests go out by SMS with the customer name, technician name, and job type in the message. Direct link to Google, Yelp, or your preferred review platform.
All review request replies arrive in the 2-way inbox. Taylor AI flags complaint-adjacent replies for service manager review before they become a public negative review.
Sent, opened, clicked, and converted tracked per technician, job type, and customer segment. Morgan AI surfaces improvement opportunities every cycle.
AI Employees
HieCOR AI Employees qualify completions, time requests, route replies, and improve your review generation performance โ without adding manual work for your team.
Morgan
Revenue Growth & Marketing AITaylor
Customer Support AIMark
Service Technician AIJordan
Delivery & Field Operations AIWhy HieCOR
The operational gaps most field service businesses live with every day โ and what HieCOR does differently.
| Situation | Without HieCOR | With HieCOR |
|---|---|---|
| Asking for reviews after every job | โTechnician sometimes remembers to ask verbally at the door. Customer says "sure" and forgets. No text sent. No review posted. | โReview request sent automatically by SMS at AI-optimized timing โ every qualifying completion, every time, without the technician having to ask |
| Sending review requests to unhappy customers | โNo filter โ everyone gets the request. An unhappy customer gets the message, clicks through, and leaves a 1-star review about the problem that should have been resolved first. | โComplaint-risk qualification checks every completion โ unresolved tickets, open disputes, and complaint history excluded before the request fires |
| Review request response rate | โGeneric "please leave us a review" text sent to everyone at 9am regardless of job type, customer, or completion time | โAI-optimized timing per job type โ 48 hours after furniture delivery, same-day after repair โ personalized with customer and technician name |
| Customer replies to the review request with a complaint | โReply goes to a general inbox with no context. Nobody responds. Customer posts the complaint as a public review. | โTaylor AI flags the complaint-adjacent reply, routes to service manager with full job context โ team resolves before the customer posts publicly |
| Knowing which technicians drive the most reviews | โNo visibility โ review volume is tracked on Google but not connected to specific jobs or technicians | โReview conversion tracked per technician, job type, and customer segment โ Morgan AI surfaces the patterns that drive the highest response rates |
| Following up with customers who did not respond | โNobody follows up โ the window closes and the opportunity is lost | โUnresponded requests surfaced by Morgan AI for manual follow-up โ ranked by job value and relationship strength |
Use Cases
HieCOR Review Requests works for appliance repair, HVAC service, plumbing, electrical, garage door, furniture delivery, and any service business that completes jobs at customer sites.
Appliance repair
Your 6 appliance repair technicians complete an average of 8 jobs per day. HieCOR triggers a review request for every qualifying completion โ checking for unresolved tickets and complaint history first. Each customer receives a personalized SMS with their technician's name and the specific appliance repaired. Response rate is 4x what you were getting from a manual "please review us" text.
HVAC installation
HVAC installation customers are most likely to respond to a review request 48โ72 hours after installation โ enough time to feel the result but close enough to remember the experience. Morgan AI identified this pattern from your historical data and set the optimal timing automatically. Complaint-risk customers who had a challenging install day are excluded before the request fires.
Multi-technician operation
You have 12 technicians with widely different review conversion rates. HieCOR shows you which technicians have the highest review response rate, which job types generate the most reviews, and which send timings perform best for your customer base. Morgan AI surfaces the patterns from your top performers so you can apply them across the team.
Most service businesses see review volume increase 3โ5x within 90 days of deploying HieCOR automated review requests.
See a 30-minute demoFAQ
Everything buyers ask before deciding whether HieCOR is the right platform.
AwarenessDoes HieCOR automatically exclude unhappy customers from review requests?
Yes. HieCOR checks every completed job for unresolved service tickets, open disputes, complaint history in the customer's recent message thread, and partial payment status before sending a review request. Only customers with a confirmed positive completion receive the request.
AwarenessCan review requests be sent by SMS?
Yes. HieCOR sends review requests by SMS with a direct link to Google, Yelp, or your preferred review platform. The message is personalized with the customer's name, the technician's name, and the specific job type. Email is available as a fallback for customers without SMS opt-in.
AwarenessHow does HieCOR optimize the timing of review requests?
Morgan AI analyzes your historical review response data by job type, customer segment, time of day, and day of the week โ and sends each review request at the timing that has historically generated the most responses for that customer type. The timing is different for a furniture delivery than for a washer repair.
EvaluationWhat happens when a customer replies to the review request with a complaint?
Taylor AI monitors all review request replies in real time. If a reply contains a complaint, dissatisfaction, or negative sentiment, it is immediately flagged and routed to the service manager with the full job record and customer history loaded โ giving your team a chance to resolve the issue before the customer posts a public negative review.
EvaluationCan HieCOR track which review requests convert to actual reviews?
Yes. HieCOR tracks the full review request funnel โ sent, opened, link clicked, and converted to a posted review โ per technician, job type, and customer segment. Morgan AI surfaces the patterns that drive the highest conversion rates and the opportunities to improve underperforming segments.
EvaluationCan I see which technicians are generating the most reviews?
Yes. Review request performance is tracked per technician โ conversion rate, response rate, and review volume. Morgan AI surfaces the message, timing, and approach patterns from your top-performing technicians so you can apply them across the team.
DecisionHow is HieCOR Review Requests priced?
HieCOR Review Requests is included as part of the broader HieCOR service platform. Message volume and the number of configured review workflows are factored into overall platform pricing. Pricing is discussed during the demo.
DecisionWhat does implementation look like for review requests?
HieCOR's US-based implementation team handles trigger event setup, complaint-risk qualification rules, review platform link configuration, SMS template creation, reply routing configuration, and performance dashboard setup. Most businesses are live within 45 days.
Most service businesses who go through a HieCOR demo immediately see the gap between how many reviews they could be generating from completed jobs versus how many they are actually getting โ and what consistent, qualified, AI-timed outreach would change.
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No commitment required ย ยทย US-based implementation team ย ยทย Average onboarding: 45 days