FAQ — Qualone
About the product
What is Qualone?
Qualone is automated quality control for CRM sales teams. The AI reads managers' comments in deals, gives every manager an objective daily score, flags process violations and stalled deals, and shows the sales leader who performs well and who is slipping, without manual spot-checking.
Who is it for?
For sales-team leaders and agency owners who need an objective picture of every manager without listening to calls or reading every deal by hand. Built first for real-estate agencies (long deal cycle), but fits any CRM-based sales team.
Which CRM does Qualone work with?
Currently Bitrix24: deals, comments, and pipeline stages are pulled from your portal. The architecture is built to connect other CRMs.
What do managers have to do, and will they work differently?
No. Qualone evaluates what managers already write in their CRM deal cards. No new tools, habits, or manual data entry. It fits the existing process.
How is it set up, and how long does onboarding take?
An integrator connects it through a Bitrix24 inbound webhook, with no code needed on your side. Once connected, scoring runs automatically in the evenings.
Scores and evaluation
What do the scores and colors mean?
A quality score runs from 0 to 100: green (65 and up) is high, silver (40–64) is medium, red (below 40) is low. The same applies to the total and each sub-score. Percentage shares (win rate, conversion) have their own thresholds: in real estate high percentages are rare, so green starts earlier there.
What makes up a manager's total score?
Comment quality in deals is 40%, deal closing 20%, SLA compliance and response speed 15% each, conversion 10%. The formula is the same for everyone and is laid out in the app.
What is "comment quality" and how does the AI score it?
The AI reads every comment and assesses how fully the manager qualified the client: budget, property type, timing and next step, client context, location. The score is adjusted for the deal stage.
Why doesn't a long comment mean a high score?
The AI judges substance, not volume. A short note with budget, property, and next step scores higher than a paragraph of "had a call, the client is thinking."
What does the "not enough data" flag mean?
It appears when, over the period, a manager has fewer than three scored comments or fewer than three working days. On such a short sample the score jumps around and is unreliable.
Trust and privacy
Where do the scores come from, and can they be trusted?
From comments in the CRM and the actual deal timings, not from eyeballed judgments. The formula is the same for everyone and is open. A score is a guide, not a verdict: every score has an AI "why so" explanation, and the source deal is always available in the CRM.
Is this employee surveillance?
No. The system looks only at the work records in deal cards, which a manager is meant to see anyway. It does not touch messenger chats, calls, or time in the office.
Can someone be fired or punished based on the score?
The score is a signal for attention, not grounds for personnel decisions. The score gives the overall picture; the deals give the specifics; the final word stays with the leader.
And what if the AI got a comment's score wrong?
Every score has a "why so" explanation. The comment text, the score, and the explanation are visible in the manager's card, and the source deal is in the CRM. The decision always stays with a person.
Who can see our data?
Only you. Each agency is isolated: the dashboard shows the data of your portal alone; data from other companies never reaches it.
Setup and pricing
Can the formula or weights be tuned for us?
Not from the dashboard: the formula is the same for everyone, for comparability. Tuning for a particular deal cycle is possible on the integrator's side during setup.
How much does it cost?
Connection terms and pricing are discussed with the integrator based on your scope and needs. Get in touch and we'll suggest an option.
Who sets up the system and is responsible for it?
An integrator deploys and configures it (access, CRM connection, notifications) and is the point of responsibility for data correctness.