If you need to show your team or your boss what’s working (and what’s not) in your call center, raw stats alone don’t cut it. You need clean, clear data and visuals that actually mean something. This guide walks you through getting performance data out of Balto, cleaning it up, and making it easy to understand—without wasting hours or ending up with a mess of spreadsheets.
Whether you’re a manager, analyst, or just the “data person” on your team, you’ll find practical steps here—plus a few honest warnings about common pitfalls.
Step 1: Understand What You’ll Get from Balto
Before you even touch the export button, know what Balto’s reporting can (and can’t) do. Balto is great at real-time call guidance and coaching, but its reporting tools are built more for quick snapshots than deep-dive analysis. The exports are usually CSVs—basically spreadsheets with a lot of columns, some clear, some...not so much.
What you’ll likely find:
- Agent performance metrics (talk time, script adherence, objection handling, etc.)
- Call outcomes (success/failure, tags, etc.)
- Time stamps and call IDs
What you probably won’t get:
- Pre-built dashboards or pretty charts
- Data that’s ready for pivot tables without some cleanup
- Long-term trend data unless you’ve been exporting regularly (Balto doesn’t always keep everything forever)
Pro tip: If you want more than Balto offers out of the box, you’ll need to bring your own spreadsheet skills or BI tools (like Excel, Google Sheets, or Power BI).
Step 2: Export Your Data from Balto
Here’s how to pull your data out:
- Log in to your Balto dashboard.
- Navigate to the reporting section. This is usually labeled “Reports,” “Analytics,” or something similar.
- Choose your data set. You can usually filter by:
- Date range
- Agent/team
- Call type or campaign
- Export as CSV. Look for an “Export” or “Download” button. You’ll get a CSV file—sometimes emailed to you, sometimes as a direct download.
Things that trip people up:
- Date/time filters: Double-check your date range before exporting. It’s easy to accidentally pull a week when you meant a month.
- Column overload: Balto likes to include all the fields (even the ones you’ll never use). Don’t panic—you’ll clean this up in the next step.
If you can’t find the export: Some Balto plans limit reporting. If you don’t see the right buttons, check your permissions or ask your admin.
Step 3: Clean Up the Data
Raw exports from Balto aren’t exactly presentation-ready. Here’s how to whip them into shape:
- Open the CSV in Excel or Google Sheets.
- Skim the columns. Delete or hide anything irrelevant—do you really need “Call UUID” or “Internal ID” in your summary?
- Rename columns for clarity. “Script_Adh_01” means nothing to most people. Call it “Script Adherence (%)” or whatever makes sense.
- Fix formatting weirdness.
- Dates and times may come out in odd formats.
- Percentages sometimes show up as decimals (0.85 instead of 85%).
- Text fields might have extra whitespace or weird characters.
Pro tip: Save a clean template so you don’t have to redo this every time you export.
Watch out for:
- Duplicate rows: Sometimes exports have accidental duplicates. Use “Remove Duplicates” in Excel or Sheets.
- Missing data: Balto sometimes skips fields if there’s no data. Decide if you want to fill blanks with zeros, dashes, or just leave them.
- Consistency: Make sure all your exports use the same column names and order—this saves headaches later.
Step 4: Decide What to Visualize (and What to Ignore)
Not all metrics matter equally. Trying to chart everything just muddies the water. Here’s how to pick what to show:
Ask yourself:
- What are the top 2–3 things my audience actually cares about?
- Am I tracking improvement, consistency, or just “big numbers” to impress?
Common metrics that are worth visualizing:
- Overall call volume (by day/week)
- Script adherence rates (by agent or team)
- Objection handling success
- Call outcomes: wins, losses, no answers
- Average call duration
Metrics to (usually) ignore:
- Internal IDs or call UUIDs (unless you’re debugging)
- Every single call tag (unless you have a very focused question)
- Raw transcripts (leave those for QA, not reports)
Pro tip: Less is more. If you can’t explain a chart in one sentence, leave it out.
Step 5: Build Your Visuals
You don’t need Tableau or a six-figure BI tool to make useful charts. Excel or Google Sheets are fine for most people. Here’s a simple workflow:
In Excel or Google Sheets
- Highlight your cleaned data.
- Insert a Pivot Table. This lets you summarize by team, agent, date, etc.
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Build your chart:
- Line or bar charts for trends over time
- Pie charts (sparingly) for proportions, like call outcomes
- Scatter plots if you want to show relationships (e.g., call duration vs. success)
-
Label everything. Don’t trust people to “get it.” Clear titles, axis labels, and legends are your friend.
- Format for clarity. Simple colors, no 3D effects, and readable fonts. You’re not making a sales deck.
If You Need Something Fancier
- Power BI or Tableau: Good if you’re doing this every week and want interactive dashboards. But there’s a learning curve and setup time.
- Google Data Studio: Free, connects to Sheets, and makes sharing easy—if your data is already clean.
Honest take: Unless you need interactive dashboards or have hundreds of agents, stick to Excel or Sheets. It’s faster, easier, and gets the job done.
Step 6: Share and Automate (If It’s Worth It)
Once you’ve got your charts:
- Export to PDF for easy sharing.
- Copy/paste into slides if you’re presenting.
- Share the live spreadsheet (with view-only access) for transparency.
Automating your reports:
If you’re doing this every week, it’s worth setting up a template. In Google Sheets, you can even use Google Apps Script to auto-import CSVs from an email or Google Drive folder. In Excel, Power Query can help—but expect a learning curve.
Don’t overengineer it:
If you only need reports once a month or for a specific project, manual is fine. Automation pays off when you’re repeating things often.
Real-World Tips and Gotchas
- Balto fields change: Occasionally, Balto updates their export fields or names. Double-check each new export before you rely on it.
- Data lag: Balto reporting isn’t always real-time. Don’t promise “up-to-the-minute” numbers.
- Compliance: If you’re reporting on sensitive data, make sure you’re following your company’s privacy rules.
- Backup: Keep an archive of each export. Balto doesn’t always store historical data forever, and you don’t want to lose last quarter’s numbers.
Keep It Simple, Iterate as You Go
Don’t get sucked into the trap of building a “perfect” dashboard on your first try. Start with the basics: export, clean, visualize, share. See what people actually use, and tweak from there. The fancy stuff can come later—if you still need it.
Remember: a clear, simple chart that answers a real question is worth more than a dozen “insights” nobody reads. Start small, stay practical, and keep your reporting as painless as possible.