a use case of your own analyst

Trial sign-up qualification: who to call today

Q: How does it know who our ideal customer is?

From your ideal customer profile, which we move into the knowledge base at onboarding: industry, team size, role, source, signs of in-product activity. A score comes with an explanation, so it can be challenged in the thread, and your own analyst refines the rule. Without a profile it scores by activity only.

Q: Does it research the company on the web?

Not today. It works with the sign-up data, Amplitude activity and Stripe payments. Web research on a company is discussed at the demo as a separate connection. For most subscription products, activity in the first days predicts payment better than brand recognition.

Scores every new sign-up against your ideal customer profile and in-product activity and highlights the ones worth a call.

Build your AI agent Everything your own analyst does

Trial sign-up qualification is a use case of your own analyst from sviy.ai for products sold through a team: it reads the sign-up form data and Amplitude activity, scores every trial against your ideal customer profile and every morning posts to Slack or Telegram who is worth a call and why.

your customer profile
a list every morning
a score with an explanation

Your own analyst · Slack

34 sign-ups in the last day. Worth a call today — 4.

1) Olena, a finance company, 40 people, imported data and invited three colleagues within 2 days — profile match 9 of 10. 2) Marek, an agency, 12 people, source: referral, opened reports 6 times. The other two are in the thread.

What hurts

Dozens of sign-ups a day, and we pick who to call at random.

Promising trials without a known brand get lost in the list.

By the time a manager gets to a sign-up, the trial has already ended.

What your own analyst does

Takes the sign-ups

Reads new sign-ups from a spreadsheet or the form's webhook: company, role, team size, source.

Adds the activity

From Amplitude it takes what the user did in the first days: data import, invited colleagues, the first report.

Scores against the profile

Checks against your ideal customer profile and the rules in the knowledge base and gives a score with an explanation.

Posts in the chat

Every morning, the high-score list in Slack or Telegram: who, why and what to offer. The manager replies "mine" right in the thread.

Sources and channels

Google Sheets or the form's webhook
Amplitude
Stripe
Slack or Telegram

Before → after

Before: Who to call — at random

After: A morning list with a score and an explanation for each

Before: Promising trials get lost

After: Scored by profile and activity, not by a known brand

Before: A call after the trial has ended

After: An alert on day three when activity is high

What it looks like in the chat

09:0034 sign-ups in the last day. Worth a call today — 4.

Sign-ups by score · 7 days

I'll take Olena. Why isn't Marek a 10 of 10?

Team size is below the threshold of 15 in your profile. If agencies have a different threshold, tell me — I'll update the rule in the knowledge base and rescore the week.

Questions

Does it call or write to customers itself?

No. Your own analyst only scores sign-ups and notifies the team in Slack or Telegram. The call, the email or the offer is made by a manager. If you need a draft of the first email, it writes one in the thread, and you send it. No contact with a customer without a person.

How does it know who our ideal customer is?

Does it research the company on the web?

Updated: October 8, 2026

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