From ad spend to closed revenue
Intelligence
Cost per qualified lead rather than cost per form fill, computed over a single graph rather than reconciled between four dashboards.
Attribution you can audit
Walk any deal backwards
Revenue to opportunity to lead to conversation to touchpoint to campaign to audience, with no missing link.
- Every touch is recorded in the same graph as the revenue
- Attribution is frozen at close, so history does not rewrite itself
Closed won · ₹2.4L
Attribution frozen at closeOpportunity
Mumbai–Jebel Ali lane, weeklyConversation
WAWhatsAppTouchpoint
Click-to-WhatsApp ad, signed tokenCampaign
Meta · Exporters – Gujarat
Numbers next to their limits
Deliverability against its thresholds
Bounce and complaint rates shown next to the lines that trigger an automatic pause. A rate on its own is a number; a rate next to its limit is a warning.
- The pause is automatic — nobody has to be watching
- The same thresholds the send path enforces, not a separate copy
The rest of intelligence
Attribution is a query, not stored state
Nothing writes an attributed campaign onto a lead. It is computed over the touchpoint history, so switching between first-touch and last-touch actually recomputes rather than relabelling.
Closed revenue does not move
At the moment a deal closes, the resolved attribution is snapshotted. Change the model later and history stays where it was — live dashboards move, the past does not.
Four metric groups
Acquisition, conversation, sales and full-funnel. Response times and AI resolution rate sit alongside pipeline and win rate, because in a conversational business they are the same funnel.
Recommendations with evidence
Recommendation, evidence, expected effect, required action. The evidence is what makes it arguable rather than something to nod at.
See it with data in it
The demo is the real product, seeded with two businesses that sell completely differently.