Understand your buyers.
Grow your revenue.
Qonva connects sales conversations with CRM outcomes and marketing attribution to uncover buyer signals, revenue patterns and actions backed by evidence.
Customer warranty questions are associated with a higher close rate.
Qonva shows the sample size, confidence and revenue impact behind each finding.
From conversations to a growth engine.
Stop treating sales conversations as unstructured history. Connect what customers say with what they actually buy.
Analyze conversations
Separate customer intent from rep language and detect multilingual buying signals, objections and timing.
Connect the dots
Join conversations with won/lost outcomes, revenue and optional marketing attribution.
Measure the evidence
See close-rate difference, revenue per lead, odds ratio, confidence interval and evidence strength.
Test an action
Turn findings into experiments and compare the result with the next real-data upload.
See what is associated with revenue.
Qonva compares customer signals and sales behavior across resolved won/lost opportunities, then shows how strong the evidence is.
- Customer-originated buying signals
- Lost-deal and objection patterns
- Response-time impact
- Customer and rep performance segments
- Creative → revenue analysis when attribution is supplied
- Evidence-backed experiments
Example revenue opportunity
Price-first creative produces the lowest sample CPL but weaker sample revenue per lead. Qonva would suggest testing proof and warranty messaging rather than claiming causation.
Understand what happens inside the chat.
Practical guides and tools for teams selling through WhatsApp and other messaging channels.
WhatsApp Sales Chat Analyzer
See how Qonva detects buying signals, objections and follow-up opportunities.
Why leads stop replying
Seven conversation patterns to check before writing off a cold WhatsApp lead.
Sales conversation analysis
Learn how conversation data complements CRM outcomes and revenue reporting.
Malaysia SME guide
WhatsApp sales analysis for Malaysian teams using mixed-language conversations.
Property sales guide
Review viewing intent, buyer objections and follow-up gaps in property enquiries.
Solar sales guide
Investigate recurring solar objections, stalled quotations and project follow-up.
Teams that sell through conversations.
Especially useful when meaningful buying intent lives in WhatsApp, chat or sales transcripts instead of only in CRM fields.
Owner-led businesses
Find which customer questions, objections and follow-up behaviors are associated with wins and revenue.
Home services & solar
Analyze quote, warranty, urgency, competitor and price conversations across real outcomes.
Agencies & lead-gen teams
Connect campaign source and creative with the quality and revenue of the conversations they generate.
Small sales teams
Compare response speed, rep patterns, objections and follow-up outcomes without enterprise software.
Use exports from the tools you already have.
Qonva does not claim native HubSpot, Zoho, Meta Ads or Google Ads connectors today. Export the relevant fields to CSV and analyze them in Qonva.
Raw uploads stay in your browser.
Qonva reads selected CSV files in browser-side JavaScript. Raw message text and raw uploaded files are not sent to Qonva application servers in the current beta.
- Raw conversation text is not stored by Qonva application servers
- Only privacy-safe derived statistics are retained for your Sales Brain
- Cross-company benchmarks are opt-in
- PostHog session recording is disabled
- Product analytics uses local browser storage rather than analytics cookies
Free during the beta.
Beta users can analyze data and test the product without a credit card. Paid plans and limits will be announced before Qonva begins charging; beta users will be notified before any billing applies.
Before you upload anything.
Which languages does Qonva support?
Current browser-side signal detection covers English, Bahasa Malaysia/Indonesia, Simplified Chinese and common mixed-language/code-switched phrasing. Beta data will be used to improve coverage.
Does Qonva use an external LLM on my raw chats?
Not in the current beta analysis path. Raw CSV contents are parsed and analyzed in your browser. Qonva stores derived statistics, not raw uploaded conversation text.
How much data do I need?
Qonva can analyze smaller datasets, but it labels weak evidence as low confidence. Medium/high findings require stronger sample sizes and statistical evidence; the product does not promote low-confidence signals as opportunities.
What does “lift” mean?
It is an observed difference between groups, such as close rate with a customer signal versus without it. Qonva treats this as association, not proof that the signal caused the outcome.
What files are required?
For outcome-linked analysis, provide a Conversations CSV and CRM Outcomes CSV with matching lead IDs. Marketing attribution is optional.
Are HubSpot and Zoho connected directly?
No. Qonva is CSV-first today. Export from your CRM or ad platform and upload the CSV. Native connectors may be added later.
See what your existing conversations can teach you.
Use the public sample first, then sign in when you are ready to analyze your own exports.