Our client is an online retail brand in Colombia, with a high and growing volume of inbound WhatsApp enquiries. When demand grows faster than response capacity, the problem is not a sales problem: it is a conversational infrastructure problem. Every extra minute before the first reply is a sale going cold.
We compared two equivalent ten-day windows — 1–10 July and 1–10 August 2026 — on Kommo's analytics dashboards, after optimising the CRM operation. The result: more than double the handling capacity, without giving up speed.
- Across equivalent ten-day windows, the brand handled 40.4% more WhatsApp messages without losing response speed.
- Average response time dropped from 2 minutes to 8 seconds — 15× faster — and 118 sales were activated where previously none closed.
- Follow-up reached order and payment: 151 orders, 13 pending and 4 confirmed in the measured window.
The challenge: more demand, without losing speed
The most common scenario in brands with high WhatsApp volume is this: demand grows, the sales team does not grow at the same rate, and first response time starts stretching. A customer waiting two minutes for a reply is still there. One waiting ten is already talking to another supplier.
The goal was not "reply faster" as an isolated target, but holding that speed while message volume kept climbing — making handling capacity scale alongside demand instead of breaking against it.
The numbers: from 2 minutes to 8 seconds
In the compared window, inbound messages rose from 23,822 to 33,444 — 40.4% more real demand. Despite that jump, average response time fell from 2 minutes to 8 seconds: 15× faster. And where no lead closed in the earlier period, 118 were won.
Source: Kommo Analytics dashboards. Comparison of 1–10 July vs 1–10 August 2026. Figures exclude monetary values, due to visible inconsistencies in the source dashboard's amounts.
From conversation to sale: order and payment
Replying fast is worth nothing if the conversation is lost afterwards, somewhere between interest and purchase. That is why the most relevant indicator in this case is not just speed: it is that, for the first time, the funnel showed visible progress through to order and payment. Where there had been no recorded activity at that stage, the compared window closed with 151 orders, 13 pending and 4 confirmed.
The increase in "leads with no task" —conversations that come in and are left without assigned follow-up— also dropped, from +6,736 to +2,923, a 56.6% fall. It signals more operational control, though the team knows the historical backlog in that queue remains an active area of improvement.
How a conversational CRM like this gets optimised
When the problem is response speed at high volume, at DotsCom we work on three fronts that hold over time, not on a one-off fix:
- Auditing the inbox and how conversations are distributed, to find where unanswered messages pile up.
- Automating the first reply and prioritising conversations with no assigned task, so none is left waiting through oversight.
- Tracking the funnel through to the concrete commercial stage — order and payment — not just to the first answered contact.
Data following this kind of implementation shows a consistent pattern: more capacity to absorb demand, faster replies and better commercial results — without volume growth displacing response speed.
Before and after, over a ten-day window
|
Metric |
Before |
After |
|---|---|---|
|
Inbound messages |
23,822 |
33,444 (+40.4%) |
|
Average response time |
2 min |
8 s (-93.3%) |
|
Leads won in the period |
0 |
118 |
|
Increase in leads with no task |
+6,736 |
+2,923 (-56.6%) |
|
Order and payment progress |
No visible activity |
151 orders · 13 pending · 4 confirmed |
With 40.4% more inbound demand, the brand cut average response time to eight seconds and activated commercial movement through to order and payment.
