Reputation into Revenue
Your customers' reviews are worth more than you think.
Recens Up analyzes every review, replies on your behalf, and measures the revenue you're losing from customers who decided not to come back.
AS SEEN IN
The problem
Every month you lose customers you don't know you're losing.
Your systems measure orders and traffic. They don't measure customers who've stopped coming back. Reviews say it clearly — Recens Up turns that into revenue at risk, before the customer is gone for good.
Your systems measure
Orders
Traffic
Conversions
Aggregate NPS
Recens Up measures
Who's decided not to return
LTV lost per customer
Customers still recoverable
Competitor benchmark
How it works
A system to intercept, manage, and win back unhappy customers — location by location.
We intercept unhappy customers
- Automatic analysis of reviews and surveys
- Instant alerts for every location
- Early detection of churn signals
€102K
Estimated LTV lost per location (grocery retailer case study)
We reply with professional Webcare
- Fast, personalized replies
- We turn unhappy customers into Promoters!
- Brand reputation protected
79%
of unhappy customers recovered before churn
We grow your
Lifetime Value (LTV).
- See LTV at risk for every location
- More sales from existing customers
- Reduce customer acquisition cost (CAC)
82%
of customers retained with intervention within 72h
COMPETITOR INTELLIGENCE
Know exactly where you're losing customers — and why.
Competitor grid map within a 2 km radius of every location. See in real time where you're strongest and where you're falling behind.
- Grid map of your location and every nearby competitor
- Direct comparison: where to attack, where to defend
- Real-time growth tracking, location by location
- Become #1 in your area — automatic alert if you drop
BEFORE
AFTER RecensUp
#1
Become the first
REAL RESULTS
Where lost revenue hides
Reputation → Revenue
Grocery Retailer
79%
Retention
€0
estimated lost revenue per location / year
Reviews analyzed
4.152
At-risk customers
68
Real reviews analyzed
★★☆☆☆
🔴 Negative
"colonnina sempre occupata"
★☆☆☆☆
🔴 Critical
"sconsiglio vivamente"
Methodology applied
Real dataset
4,152 Google reviews, 12 months
Linguistic analysis
Churn markers identified
LTV-based model
AOV × frequency × churn probability
72h intervention
Estimated 79% retention
DIY Retailer
Home Improvement · Physical retail · E-commerce
79%
Retention
€0
LTV lost in one week from 4 tracked customers
| Customer | Signal detected | Average spend | LTV lost |
|---|---|---|---|
| Marco R. | stated intent to leave | €290 | €870 |
| Giulia V. | deep disappointment | €210 | €630 |
| Andrea P. | competitor mentioned | €380 | €1.140 |
| Sara M. | won't be back | €80 | €240 |
Total LTV lost in one week
€2.880
Methodology applied
Real dataset
4 tracked customers, 1 week
Linguistic analysis
Churn markers detected
Residual LTV model
Total LTV − first purchase
72h intervention
Estimated 79% retention
Raw review
→
Serena algorithm
→
Task to Manager
NO MATTER WHO. WHAT MATTERS IS:
Don't leave money on the table
E-commerce
- Review management across every channel
- Automatic alerts on at-risk customers
- Customer recovery starting from negative reviews
Retail & Franchising
- All-in-one platform for 500+ locations
- Local-radius competitor analysis
- Recurring issues by product/service category
The team
The people behind Recens Up
"Reputation is the most underrated dataset in the world. Recens Up will be the infrastructure that makes it usable."
— @OtthoFIND OUT
How much revenue you're leaving on the table!
Enter your Google Business profile
in 60 seconds, get a preview of Serena's algorithm
No account required · Real data from Google · Result in 60 seconds
🔍 Retrieving Google Business profile
📋 Analyzing the last 5 reviews via Apify
🧠 Sentiment classification with Claude AI
📊 Calculating LTV at risk
Analysis complete
Revenue at risk over the next 12 months
—
annual estimate (industry benchmark)
Unlock the full report
See the LTV for every customer identified, the response plan, and the competitor benchmark.
Exact LTV for every at-risk customer
Recommended reply for every review
Competitive benchmark in your industry
LTV simulation with your real data
12-month recovery projection
Add your data for a precise LTV estimate (optional)
No spam. Your data is only used for your personalized report.
FEBRUARY 3, 2026
First time on a big stage🥹
4:42
Book a call
Virtual coffee chat?☕️
20 minutes with one of our founders. Let's talk!
PRODUCT MARKET FIT
We want to hear from you !
Answer our survey in 180 seconds and tell us what you think of Recens Up
2.350.000⭐️+
Reviews analyzed
<2h
79%
Retention rate with intervention
Guaranteed average response time
FAQ
Frequently asked questions
How does review analysis work?
Recens Up connects to the main review channels (Google, Trustpilot, Shopify Reviews) and applies a proprietary NLP engine to classify every feedback. It identifies churn markers — phrases like "I won't be back", "disappointed", "I prefer [competitor]" — and calculates residual LTV at risk for every tracked customer. All automatic, updated in real time.
Do you reply to reviews, or do we?
We handle the replies, applying the principles of professional Webcare: no generic templates, every reply is contextual to the review content and to your brand's tone. If you prefer direct control, you can use the platform in suggestion mode: we propose the reply and you publish it. Either way, average response time stays under 2 hours.
How many locations can I manage at once?
There's no fixed limit. Recens Up is built for multi-location networks: from 5 to 500+ stores. Every location has its own reputation profile, its own competitive benchmark within 2 km, and its own LTV indicators. The centralized dashboard lets management see an aggregated view and drill down location by location.
How is revenue at risk calculated?
We use an LTV-based methodology: we multiply average order value (AOV) by annual purchase frequency and by the churn probability estimated from linguistic analysis of negative reviews. For retail we apply a 4.2% churn rate per location, calibrated on industry data. The result isn't a theoretical estimate — it's the revenue you're losing, customer by customer.
What is Webcare?
Webcare is the strategic, timely and professional management of reviews and online customer interactions. It doesn't just reply — it turns feedback into marketing tools to improve brand reputation and grow revenue.