---
title: Peach Analytics
slug: peach-analytics
docTags: 
createdAt: 2025-09-23T06:50:40.742Z
---

# Analytics Overview in Peach

The **Analytics tab** in Peach provides you with powerful insights into all the activities happening across your account. It allows you to monitor performance, track engagement, and evaluate both automated and human-led interactions.

This section serves as the entry point to understanding how your users, broadcasts, apps, and agents are performing. Below is a breakdown of the key areas available within Analytics:

### 1. Source

- View how users initiate chats through different channels connected to your WhatsApp numbers.
- Helps identify which sources are driving the most engagement.

### 2. Broadcasts

- Provides detailed information about all the broadcasts you have sent.
- Includes delivery and engagement status, helping you measure campaign performance.

### 3. Apps

- Similar to Broadcasts, this section highlights user engagement with the **apps you’ve built in Peach**.
- Useful for understanding app adoption and interaction trends.

### 4. Chat

- Track activities of your **human agents** connected to your account.
- Insights are available at both the **aggregate level** and **individual agent level**.
- If you have created agent teams, the data is separated and reported by team.

**4.1 Assignments**

- Displays the number of contacts assigned to your human agents.
- Useful for workload distribution analysis.

**4.2 Funnel**

- Shows the funnel flow:
  - Assignment to human agents →
  - Responses provided by human agents.
- Includes insights into assignments that occurred due to **AI Agent escalations**.
- Available at both **aggregate** and **individual** levels.

**4.3 Response Time**

- Track three key metrics across all human agents:
  - **Average First Contact Time**
  - **Average First Response Time**
  - **Average Resolution Time**
- Drill down to see these metrics at:
  - The **individual agent level**
  - The **specific contact level**
- Helps measure efficiency and identify areas for improvement in handling conversations.

**4.4 Activities**

- Provides a detailed view of all activities for each contact.
- Useful for exploring individual customer journeys and touchpoints.

 🎥 **Watch the video below** to learn about Analytics section in Peach

::embed[]{url="https://youtu.be/8rsJkCeReYQ"}

#

# Source

The **Source** section in the Analytics tab gives you an overview of how chats are initiated on the WhatsApp numbers connected to your account. It helps you understand whether conversations are starting from the user’s side or from the business, and through which channels.

When you open Analytics, the **Source** section is the first view you will see.

### Types of Initiations

There are **two types of chat initiations** visible in this section:

**1. User Initiated**

These are conversations triggered directly by the customer.

- **Total Sessions**: See the overall number of sessions that began with a user initiation.
- **Channel Breakdown**: Sessions are grouped into three channels:
  - **Direct**
    - A user sends a message directly to your WhatsApp Business number.
    - You can view the exact **keyword** used by the customer.
    - The dashboard also shows how many sessions were initiated by a specific keyword.
    - If a keyword field is empty, it means the initiation was through an **audio file or image** instead of text.
  - **Paid**
    - Sessions triggered when a user clicks through to WhatsApp from an active **Meta ad campaign**.
  - **Referral**
    - Sessions initiated when a user starts a chat from a **referral text** configured for a specific agent in Peach.

**2. Business Initiated**

These are conversations triggered by your business.

- **Campaign**
  - Sessions started by broadcasts you send through Peach.
- **Others**
  - Sessions that begin when:
    - A template is triggered via API.
    - A human agent manually shares a template from the **Shared Chat Inbox**.

### Example: Source Table

![](https://api.archbee.com/api/optimize/LSvaQ8v7MiAYpp8V288yP/lnKt5l0S3LzLbgAq5wFin-20250923-094259.png)

### Why Source Matters

The Source section helps you answer key questions like:

- How are most users starting conversations with my business?
- Which campaigns or referral setups are driving the highest engagement?
- Are users interacting more through direct messages, paid ads, or referrals?

This makes it easier to measure channel performance and optimize your user acquisition strategies.

🎥 **Watch the video walkthrough below** to see how to navigate the Source section in real time

::embed[]{url="https://youtu.be/tHdyzN3mIsU"}

#

# Broadcasts

The **Broadcasts** section in Analytics gives you a complete view of the messages you’ve sent to your users through Peach. It helps you track delivery, engagement, and user opt-outs for every broadcast campaign.

### Key Metrics

When reviewing your broadcast performance, you’ll see the following metrics:

- **Queued**
  - The number of messages waiting to be sent to users.
- **Sent**
  - Total number of messages successfully sent from your account.
- **Delivered**
  - Messages that reached the user’s WhatsApp inbox.
- **Read**
  - Messages that were opened and read by the user.
- **Engaged**
  - Refers to interactions with your broadcast messages through **CTA buttons**.
  - CTAs may:
    - Redirect users to a website.
    - Connect users with an AI Agent in Peach (based on your campaign setup).
- **Failed**
  - Messages that could not be delivered to the user.
  - Failures can occur for multiple reasons.
  - Example: For marketing messages, **Meta may cap delivery** to maintain a healthy user ecosystem, resulting in restricted delivery.
- **Unsubscribed**
  - The number of users who opted out of receiving further marketing messages from your business.

### Campaign-Level Data

Beneath the overall metrics, you’ll see a **list of all campaigns you’ve run**.

- Each campaign includes its own breakdown of performance.
- By clicking on a campaign, you can **drill down into a detailed view** of that specific broadcast, including engagement, failures, and unsubscribes.

### Example: Broadcast Performance Table

![](https://api.archbee.com/api/optimize/LSvaQ8v7MiAYpp8V288yP/if9PdtrkIkYdZ-OozlInm-20250923-094146.png)

### Why Broadcast Analytics Matter

This section allows you to:

- Monitor message delivery health.
- Track user engagement with CTA buttons.
- Understand unsubscribe patterns to refine future campaigns.
- Compare performance across different broadcast campaigns.

🎥 **Watch the video walkthrough below** for a guided explanation of Broadcast analytics

::embed[]{url="https://youtu.be/6K1kTJ_c25A"}



# Apps

The **Apps** section in Analytics gives you a detailed overview of how users are engaging with the apps you have built in Peach. It helps you track the progress of users through each app journey — from starting it, to completing and submitting it.

### Key Metrics

In this section, you’ll find the following insights for each app:

- **Started**
  - Number of users who have started interacting with the app.
- **In Progress**
  - Number of users currently filling out the app but have not yet completed it.
- **Dropped Off**
  - Number of users who abandoned the app before completion.
- **Completed**
  - Number of users who successfully finished and submitted the app.
- **Completion Rate (%)**
  - Percentage of users who completed the app, calculated against total users who started it.

### Example: App Engagement Table

![](https://api.archbee.com/api/optimize/LSvaQ8v7MiAYpp8V288yP/32823OIaFloErbFQXSUPV-20250923-094558.png)

### Why App Analytics Matter

Tracking app engagement helps you:

- Identify where users are dropping off.
- Understand which apps have higher completion rates.
- Optimize app flows to improve user experience.
- Measure the effectiveness of apps in achieving business goals (e.g., lead collection, surveys, eligibility checks).

🎥 **Watch the video walkthrough below** to learn how to analyze app performance in real time

::embed[]{url="https://youtu.be/be3lASGAvA4"}

****

# Chat (Agent Productivity)

The **Chat (Agent Productivity)** section in Analytics allows you to track the performance of all your agents in one place. It helps you understand how effectively agents are handling customer conversations over time.

### Key Metrics

- **Chats Started**
  - Number of conversations initiated between customers and agents.
- **Chats Closed**
  - Number of conversations marked as resolved/closed by agents.
- **Chats Dropped**
  - Number of conversations that were abandoned or dropped without resolution.
- **Total vs Unique Chats**
  - **Total**: The overall number of conversation sessions handled by agents.
  - **Unique**: The number of individual customers agents interacted with.
  - Example: If a single customer had two separate conversations (one yesterday and one today), it will count as **2 Total Chats** but only **1 Unique Chat**.
- **First Response Time**
  - The average time taken by agents to respond to the **first message** from a customer.
- **Resolution Time**
  - The average time taken by agents to fully resolve a customer’s issue.

### Example: Agent Productivity Table

![](https://api.archbee.com/api/optimize/LSvaQ8v7MiAYpp8V288yP/qmtZif-ZW_fJ8gFHh7-PI-20250923-095402.png)

### Why Agent Productivity Analytics Matter

This section helps you:

- Track the balance between **total workload** and **unique customers served**.
- Measure how quickly agents are responding to new chats.
- Monitor resolution times to improve customer satisfaction.
- Identify inefficiencies, such as high drop rates or long resolution times.

🎥 **Watch the video walkthrough below** for a step-by-step guide on analyzing Chat (Agent Productivity) metrics

::embed[]{url="https://youtu.be/T5plwyKQETs"}

#

# By Agent

The **By Agent** section in Analytics allows you to view performance and activity data at an **individual agent level** or for a **group of agents**. This helps you drill down into productivity, workload, and conversation outcomes.

### Key Metrics

For each agent (or group of agents), you can track:

- **Assigned Chats**
  - **Total**: Total number of chats assigned to the agent.
  - **Unique**: Unique customers whose chats were assigned.
- **Customer Outreach**
  - **Contacted**: Number of customers the agent has actively contacted.
  - **Yet to be Contacted**: Number of assigned customers not yet contacted.
- **Active 24-Hour Windows**
  - The number of **open 24-hour messaging windows** currently active for the agent.
- **Chats Closed and Dropped**
  - **Total vs Unique** breakdown of closed and dropped chats.
- **Other Metrics**
  - **Messages Sent**: Total messages sent by the agent.
  - **Escalated Chats**: Number of chats escalated from the agent (or to the agent, depending on role).

### Example: Agent Performance Table

![](https://api.archbee.com/api/optimize/LSvaQ8v7MiAYpp8V288yP/kJ8ve0yZLK2EkePPwgEXC-20250923-101227.png)

### Roles and Access

The data you see depends on your **role** in Peach:

- **Manager**: Can view analytics only for their assigned team(s).
- **Admin**: Has access to analytics for all agents across all teams.

### Why “By Agent” Analytics Matter

This section helps you:

- Monitor workload and productivity of individual agents.
- Track team performance and identify bottlenecks.
- Ensure fair distribution of chats across agents.
- Gain role-based visibility into agent activities.

🎥 **Watch the video walkthrough below** for a detailed guide on the By Agent analytics section

::embed[]{url="https://youtu.be/5YqAx5mBQPs"}

# Assignments

The **Assignments** section in Analytics helps you understand how contacts are being distributed to your human agents. It combines daily trends, key metrics, and detailed breakdowns so you can track workload balance and AI escalations effectively.

### Daily Assignment Chart

- At the top of the section, you’ll see a **chart showing how many contacts were assigned each day**.
- You can adjust the **date range** to zoom in on a specific time period for closer analysis.

### Key Metrics

Just below the chart, three core metrics provide insights into assignment quality:

- **Total Assignments**
  - Overall volume of contacts distributed to your agents.
- **Reassignments**
  - Cases where contacts were moved from one agent to another.
  - This can indicate workload balancing issues or escalations.
- **Escalations from AI**
  - Number of contacts that AI agents escalated to human agents.
  - Shows when automation required human intervention.

### Table View

- Scroll down to view a **table of assignments by agent or team**.
- This allows you to see exactly who is receiving contacts and how many.
- Data can also be **downloaded as a CSV file** for use outside Peach.

### Example: Assignments Table

![](https://api.archbee.com/api/optimize/LSvaQ8v7MiAYpp8V288yP/K6pp306lb34T5S7bUXYom-20250923-103359.png)

### Escalation Breakdown

- On the right-hand side, you’ll find details of:
  - **Which AI agents** are escalating chats.
  - **Which human agents** those chats are being assigned to.
- If you’ve enabled **round robin logic**, escalated chats will be distributed evenly across agents.
- If not, assignments will follow the **specific agent mappings** you’ve set up.

### How to Use Assignments Analytics

1. Start with the **daily chart** to spot trends in contact distribution.
2. Review the **key metrics** to identify patterns in reassignments and escalations.
3. Check the **table view** for distribution across agents or teams.
4. Confirm your **AI escalation logic** by reviewing the agent breakdown.

🎥 **Watch the video walkthrough below** for a step-by-step explanation of Assignments analytics

::embed[]{url="https://youtu.be/vWiRdHJlMME"}

#

# Funnel

The **Funnel** section helps you understand how conversations progress from being **assigned to agents** to being **contacted** and finally **responded to by subscribers**. It includes a top-level funnel overview and a deeper **Agent-Level Funnel Analysis** so you can spot bottlenecks and optimize both human and automated engagement.

### Date Range & Global Controls

- **Date Range Selector (top-right):** Defaults to **Today**. Change to **Last 7 days**, **Last 30 days**, or set a **Custom Range**.
- Applying a date range **refreshes every number** on the screen for the selected period.

### Summary Metrics (Top)

- **Assigned to Agent:** Total conversations assigned to agents or teams.
- **Contacted by Agent:** How many assigned conversations were actually messaged by agents (**conversion rate shown below**).
- **Responded by Subscriber:** How many customers replied (**conversion percentage shown**).
- **Overall Response Rate:** Percentage of **assigned** conversations that ended with a subscriber response.

These four numbers give you a **quick health check** for the funnel.

### Conversation Funnel Flow (Visual)

A three-stage visual that makes drop-offs easy to spot:

1. **Assigned to Agent**
2. **Contacted by Agent**
3. **Responded by Subscriber**

Use this view to **quickly identify bottlenecks** between stages.

### Funnel Table (Stage Detail)

Breaks the funnel into three stages—**Assigned**, **Contacted**, **Responded**—with:

- **Count:** Volume at each stage.
- **Conversion Rate:** % moving from one stage to the next.
- **Drop-off:** How many fell off; **color-coded** (e.g., red/green) for instant visibility.

**Download CSV** (top-right) to analyze in Excel or share with other teams.

### Example: Funnel Table 

![](https://api.archbee.com/api/optimize/LSvaQ8v7MiAYpp8V288yP/CVoHebiyLiOHU_WNJ3vYP-20250923-104053.png)

![](https://api.archbee.com/api/optimize/LSvaQ8v7MiAYpp8V288yP/MwbHhZaOojldHILg9BvPu-20250923-104206.png)

### Agent-Level Funnel Analysis (Drill-Down)

Use this view to compare performance **by agent or team**.

**Controls**

- **Search:** Find a specific agent or team.
- **Filters:** Refine data further (e.g., team, timeframe).
- **CSV Export:** Download for deeper analysis.

**Columns / Insights**

- **Agent/Group Name & Team:** Identify who you’re reviewing.
- **Assigned / Contacted / Responded:** Stage counts per agent/group.
- **Overall Rate:** Effectiveness converting assignments into responses (**color-coded** for easy comparison).
- **Messages Sent:** Outbound effort from the agent/group.
- **Escalated by Bot:** How often the system bot had to step in.

### How to Use Funnel Analytics

1. **Set the Date Range** to the timeframe you want to review (e.g., last 7/30 days).
2. **Scan the Summary Metrics** for a quick health check—especially **Overall Response Rate**.
3. **Use the Funnel Flow Visual** to spot stage drop-offs at a glance.
4. **Review the Funnel Table** to quantify conversion and drop-off by stage.
5. **Drill into Agent-Level Analysis** to see who’s performing well, who needs support, and where the **bot is intervening**.
6. **Export CSV** if you need to share, audit, or run custom pivots.

🎥 **Watch the video walkthrough below** for a guided tour of the Funnel dashboard and the Agent-Level drill-down

::embed[]{url="https://youtu.be/up6u10WpDjE"}



# Response Time

The **Response Time** section in Analytics helps you measure how quickly your human agents are handling conversations. It provides both an overall view across all agents and the ability to drill down to individual agents or even specific customer contacts.

### Key Metrics

You can track three important time-based metrics:

- **First Contact Time**
  - Average time taken for an agent to first contact or acknowledge the customer after chat assignment.
- **First Response Time**
  - Average time taken by an agent to respond to the customer’s first message.
- **Resolution Time**
  - Average time taken by an agent to fully resolve the customer’s query or issue.

### Example: Response Time  Table

![](https://api.archbee.com/api/optimize/LSvaQ8v7MiAYpp8V288yP/OwiLYQmfiYYRUA1OrCUCY-20250923-104418.png)

### Drill-Down Options

- **By Agent**: View these metrics for an individual agent to evaluate their efficiency.
- **By Customer Contact**: Analyze response times for a specific customer to understand their support experience.

### Why Response Time Analytics Matter

Tracking response times helps you:

- Measure the speed and efficiency of your agents.
- Identify potential bottlenecks in handling customer conversations.
- Improve customer satisfaction by reducing wait and resolution times.
- Benchmark team performance at the aggregate and individual level.

🎥 **Watch the video walkthrough below** for a step-by-step explanation of Response Time analytics

::embed[]{url="https://youtu.be/H5WqKf3G7D0"}

# Chat Activities

The **Chat Activities** section in Analytics provides a detailed log of all chat interactions. It lets you both **view high-level overviews** and **dive into specific chat details** to understand customer journeys and agent actions.

### Filters & Search Options

You can refine the chat activity view in several ways:

- **By Agent or Group**
  - Focus on chats handled by a specific agent or an entire team.
- **By Status**
  - Filter by whether chats are **Open**, **Closed**, or **Pending**.
- **By Activity Type**
  - Narrow down by specific actions, such as:
    - When a chat was assigned to an agent.
    - When a journey or flow was completed.
- **Search Bar**
  - Directly look up a contact by **name** or **phone number** for fast access.

### Chat Details View

Once filters are applied, you can see detailed information for each chat, including:

- **Contact details** (e.g., name, phone number).
- **Activity type** (assignment, flow completion, escalation, etc.).
- **Time of conversation**.
- **Source of conversation** (e.g., Direct, Paid, Referral, Campaign).
- Other contextual activity logs for a full conversation history.

### Date Range & Export

- Apply a **date range** to view chat activities for a specific period.
- Download the filtered data instantly as a **CSV file** for reporting, auditing, or sharing with other teams.

### Example: Chat Activites Table

![](https://api.archbee.com/api/optimize/LSvaQ8v7MiAYpp8V288yP/83xTaLKEZtjqm0enlrO9y-20250923-105941.png)

### Why Chat Activities Matter

This section helps you:

- Trace the **complete journey** of individual customers.
- Audit agent performance and activity timelines.
- Analyze chat patterns by status, type, or source.
- Export raw data for further analysis outside Peach.

🎥 **Watch the video walkthrough below** for a demonstration of how to filter, search, and export chat activities

::embed[]{url="https://youtu.be/eZeoYaM1L9M"}