● Platform · Measure

Every conversation,
an actionable insight.

Analytics brings together volume, user journey, topic mix, team performance and phrases the bot doesn't understand in one dashboard. No exports, no spreadsheets, no guessing.

3 viewsDashboard, Interactions, Agents
12 monthsof compared history
1 exportCSV or BigQuery on the fly
Analytics Conversations · General Dashboard
Last 12 months ↓ Export
General Dashboard Interactions Agents
Period Volume Accumulated totals for the selected period
💬 Conversations
2.037
↗ 100%
Messages /conversation
1.237
↗ 100%
👤 Unique users
1.363
↘ 4% vs. 1.420 previous
User journey — time per stage ↓ lower is better
Period accumulated Each bar shows the average time for that stage
Bot conv.
36m 00s
3% of flow
+100% vs prev.
Bot + agent
39m 25s
3% of flow
+100% vs prev.
Agent
1m 24s
0% of flow
+100% vs prev.
Pending wait
11h 46m
60% of flow
+100% vs prev.
Agent wait
6h 28m
33% of flow
+100% vs prev.
01

Volume and journey at a glance

Conversations, messages and unique users with delta against the previous period. Below, the average time each user spends at each stage of the flow.

02

Live categories, not dead reports

The classifier taxonomy feeds directly into Analytics. Volume, satisfaction and trend by topic, with no manual work.

03

Agents and fallback, measured

Conversations handled by each agent against the team average. Monthly fallback against the target and the exact phrases that break the bot.

What Analytics measures

Five questions.
Five dashboards.

Period volume

How much did we talk this month?

Period totals with delta against the previous and daily sparkline. Conversations, messages per conversation and unique users, always visible at the top of the dashboard to know if we hit a peak or a dip.

  • Totals with delta vs. previous period
  • Daily sparkline per KPI
  • Range: 7d, 30d, 90d, 12m or custom
  • Filter by channel, bot or team
  • CSV export with one click
  • Comparison against your own baseline
Analytics General Dashboard
Last 30d ↓ CSV
General Dashboard Interactions Agents
💬Conversations
2.037
↗ 12% vs. previous
Messages/conv.
6.1
↗ 8%
👤Unique users
1.363
↘ 4% vs. 1.420 prev.
7d 30d 90d 12m Custom
User journey

Where the conversation gets stuck.

The average time at each stage of the flow — bot, hand-off, agent, wait — broken down by bars and with month-over-month evolution. Wait time is almost always 90% of the total; now you know exactly which and how much.

  • 5 stages: bot, bot+agent, agent, pending wait, agent wait
  • Delta per stage vs. previous period
  • Stacked, grouped or by stage view
  • Automatic bottleneck insight
  • Alerts when wait exceeds SLA
Analytics Conversations · Journey
↓ Export
General Dashboard Interactions
Time per month, broken down by stage Each bar sums the average time · color = stage
Stacked Grouped
Bot conv. Bot+agent Pend. wait Agent wait
100h75h50h25h0h
Oct
Nov
Dec
Jan
99.6h
60m
40m
Feb
Mar
Apr
May
Jun
Insight: Peak of 99.6h in Feb 26. Wait times account for >90% of the total flow time.
Recurrence and time of day

When they arrive and who comes back.

A donut separates recurring users from new ones. A monthly line crosses conversations, messages and unique users. And a heatmap by hour of day shows you the exact peak — so you can size shifts and campaigns against real demand.

  • Recurring vs. new with % of total
  • Monthly triple series: conv / msg / users
  • Heatmap hour × day of week
  • Automatic highlighted peak
  • Basis for shift planning
Analytics Conversations · Recurrence
↓ Export
General Dashboard Interactions
RecurrencePeriod distribution
33%recurring
Recurring 16533%
New 34267%
Total unique 507
Monthly volume
Conv. Msgs. Users.
Activity by hour of dayPeak Mon 16:00 · 371 conv.
MonTueWedThuFriSatSun
0h 4h 8h 12h 16h 20h 23h
0 371 conv.
Categories × satisfaction

The map of your operation.

The classifier taxonomy sorted by volume and contrasted with net satisfaction. The quadrants tell you where to prioritize: high volume with low satisfaction is your next improvement, high volume with high satisfaction is your strength.

  • Top 15 categories + long tail in "Others"
  • Volume × satisfaction scatter with quadrants
  • Month-over-month mix evolution
  • Prioritized insight: high volume, low satisfaction
  • Direct link to the classifier
Analytics Conversations · Categories
↓ Export
General Dashboard Interactions
Distribution by categoryTop 15 by volume
VolumeSatisfaction
conversational management
116 · 30%100pts
general information
36 · 9%12pts
monthly plan types
31 · 8%10pts
search and queries
29 · 7%8pts
web chatbot
29 · 7%14pts
product search
19 · 5%8pts
Volume vs. SatisfactionPriority quadrants
STRENGTHS PRIORITY target 70 pts 0 50 100 150
Agents and fallback

Who handles. What it doesn't understand.

Volume of conversations handled by each agent contrasted with the team average. In parallel, the bot fallback rate and the exact phrases that break it — the short list that, if you train, moves the needle fast.

  • Conversations per agent vs. team average
  • Double-click to see individual detail
  • Monthly fallback evolution with target
  • Top unrecognized phrases with % of total
  • One click sends the phrase to retraining
Analytics Agents · Interactions
↓ Export
General Dashboard Interactions Agents
Conversations per agentTeam average marked with line
VolumeName
MP
Matías Pérez
156conv.
CR
Camila Rojas
142conv.
AV
Antonia Vera
134conv.
FD
Francisca Díaz
110conv.
SM
Sebastián Muñoz
87conv.
Fallback rateTarget 10%
10% 15% 20% target 10% 11.8% Nov 25 12.3% Dec 25 12.9% Jan 26 13.6% Feb 26 13.4% Mar 26 14.2% Apr 26
Top unrecognized phrasesClick → send to retraining
"I want to talk to a person"
142 · 24%
"when does my order arrive"
118 · 20%
"change delivery date"
97 · 16%
"my coupon doesn't work"
81 · 13%
"I need an invoice"
68 · 11%
Action: the top 5 account for 61% of fallbacks. Training these intents would bring the rate closer to the 10% target.
One dashboard, three engines

Analytics doesn't live alone. It feeds from and returns work to the rest of the platform.

Getting started

From raw data to decisions, in one week.

01
Metrics onboarding
We define the 5–8 metrics that matter to your operation and their targets.
02
Base dashboards live
Volume, journey and agents are available from day one.
03
Taxonomy plugged in
When the classifier is ready, categories and evolution appear automatically.
04
Monthly review
Joint session to read insights and prioritize improvements to the bot and team.

Stop watching your operation from the corner of your eye.

Databot Analytics shows you, in one dashboard, what is being asked, who responds and where the conversation gets stuck.