Understanding the Tag Report: How to analyze conversation distribution

Papo's Tag Report (https://papo.global/) is an analytical tool that consolidates and quantifies the frequency with which each tag is used in conversations, allowing your company to clearly visualize the main reasons for customer contact. By transforming individual interactions into aggregated data, the report helps identify trends, bottlenecks, and opportunities for improvement in your service and product.

Understanding why your customers get in touch is fundamental for any business. The Tag Report transforms daily organization into business intelligence, showing which topics, such as "Sales," "Technical Support," or "Billing Inquiry," demand more attention from your team.

What are tags and why are they important for reports?

Tags are markers you apply to conversations to categorize them. They function as a digital filing system that allows you to organize, filter, and most importantly, analyze your interactions. Each time an agent applies a tag like "Urgent," "Follow-up," or "Interest in Gold Plan," they are generating valuable data.

These tags can be applied in two ways in Papo:

1. Manually: By agents during or after the interaction, directly on the conversation screen.
2. Automatically: By Papo's Artificial Intelligence, which can be configured to identify the subject of a conversation and apply the corresponding tag, such as "Payment Inquiry" or "Access Issue."

The Tag Report gathers all this information, providing a complete overview of your operation. It allows you to move from assumptions ("I think many people ask about X") to facts ("35% of our contacts last month were about X").

How to access and interpret the Tag Report

To find this analysis, navigate to the Reports module within the Papo platform. There, you will find different metric dashboards. Look for the section dedicated to conversation or tag reports.

While the exact layout may vary, a Tag Report typically includes the following components:

• Distribution Chart (Pie or Bar): A visual representation showing the proportion of each tag relative to the total. This allows for quick identification of the most frequent topics.
• Data Table: A detailed list of all tags, with the exact count of how many times each was applied in the selected period.
• Period Filters: Tools to select the time range you want to analyze (today, last 7 days, last month, etc.), allowing you to compare performance over time.
• Additional Filters: Options to filter data by inbox, agent, or team, helping to understand how contact reasons vary across different channels or teams.

When interpreting the data, look for patterns. A sudden increase in a tag like "Website Down" is an immediate alert. A consistent decrease in the "Registration Inquiry" tag after publishing a tutorial indicates that your action was successful.

Using insights to optimize your operation

The true power of the Tag Report lies in action. Use the data to make strategic decisions that improve efficiency and customer satisfaction.

1. Identify content needs: If a tag about a specific query is very frequent, create a Help Center article, record a video tutorial, or prepare a Quick Reply so agents can resolve the issue with a click.
2. Allocate resources intelligently: If the report shows a large volume of conversations with the "Sales" tag, it might be time to reinforce the sales team. If "Technical Issue" is the top tag, invest more in development or specialized support.
3. Provide product feedback: Tags like "Improvement Suggestion" or "Bug Report" are a direct channel for customer feedback. Compile this data and present it to your product team to guide future updates.
4. Evaluate team performance: Analyze the distribution of tags per agent to identify training needs. An agent might be incorrectly classifying conversations, or may need more support in a specific area.

Frequently Asked Questions

How can I ensure my team uses tags correctly?

Consistency is key. Create a clear guide defining what each tag means and when it should be used. Conduct regular training sessions and use the Tag Report itself to audit usage and correct deviations, ensuring the quality of your data.

What's the difference between a tag and a custom attribute?

A tag categorizes the topic or status of a specific conversation (e.g., "Billing Inquiry," "Resolved"). A custom attribute stores lasting information about the contact (e.g., "Customer ID," "Subscribed Plan"). The Tag Report focuses on conversation topics.

Can AI create and apply tags automatically?

Yes. Papo allows you to configure automatic categorization by Artificial Intelligence. The system analyzes the content of new messages and applies relevant tags, ensuring consistency and saving agents' time. These automatic tags are counted normally in the report.

What happens if a conversation has multiple tags?

This is common and desirable, as a single conversation can cover multiple topics. In the report, the conversation will be counted for each of the tags it has. For example, a conversation with the tags "Billing Inquiry" and "Improvement Suggestion" will appear in the statistics for both.

Can I export the Tag Report data?

Data export options may vary. Generally, customer service platforms allow you to export reports to formats like CSV or Excel, enabling deeper analysis and data cross-referencing in other BI tools. Check the available options in your reports dashboard.

Read also

• Anatomy of the Conversation Screen: Sending messages, notes, and tags
• Reports Overview: Where to find each metric in Papo

Start using for free →

The first user on your account is free, allowing you to organize and analyze your customer interactions at no initial cost.