SUPPORT SIGNAL EXTRACTION

Support Miner

Enter recent support conversation patterns to get a calculated product-risk score and which issue type to prioritize.

  • Uses your inputs in a transparent calculation
  • Instant result with practical next steps
  • No signup required

Planning guidance only. Validate important decisions with customer evidence and your delivery team.

How it works

1

Enter recent support patterns

Bug report share, recurring complaint topics, churn mentions, and feature request clustering are each scored.

2

We calculate a product-risk score

Signals are summed and boosted if weekly ticket volume is 100 or more, since higher volume makes the patterns more reliable.

3

Get the top signal to act on

The tool names the single strongest signal from your support conversations so you know what to prioritize.

Frequently asked questions

What counts as a 'recurring complaint topic'?

The same underlying issue showing up across multiple, separate support tickets — not just a busy week for one customer. You supply this judgment based on your ticket history.

Is this a replacement for support ticket analytics?

No. It's a fast, rule-based check using patterns you already know. A dedicated support platform with tagging and NLP-based theme extraction will surface these signals automatically and with more precision.

Why does ticket volume affect the score?

The same pattern is more statistically reliable when it comes from a larger number of tickets, so a 100+ weekly volume boosts confidence in the flagged signal.

How We Compare

Feature MVPHub IntercomZendesk
Quick single-check support signal scan Included Limited Limited
No signup or helpdesk integration required Included Not included Not included
Automated NLP extraction across all tickets Not included Included Included
Continuous theme and sentiment dashboards Not included Included Included

Intercom and Zendesk can automatically extract and cluster themes across your full ticket history once integrated. MVPHub gives a fast, manual product-risk check using patterns you already know.

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