Data series settings

In this article, we will explain what Data Series Settings are and how to use them to customize the data displayed in your graphs.

What are Data Series Settings?

Data Series Settings allow you to define how each individual data series in your graph is displayed. Here, you can control everything from the aggregation level and color to whether value labels are shown. Adjusting these settings helps you make your graphs clearer, more accurate, and easier to interpret.

How to Access Data Series Settings

1. Open the graph you want to edit within a Topic.

2. Click on Data Series Settings.

3. Select the data series you want to adjust.

4. Make your changes and click Save changes when finished.

Common Data Series Settings Explained

Title

Give your data series a clear and descriptive title. This helps identify what the series represents — for example, “Brand Awareness – Total” or “Customer Satisfaction – Age 18–34.” A good title makes your graphs easier to read and understand, especially when multiple series are shown together.

Color

Set a color for each data series to make it easier to distinguish between different data sources or metrics.

Aggregation Level

Choose how your data should be summarized — for example, by month, quarter, or year. This determines the level of detail shown in your graph.

Rolling Average

Apply a rolling average to smooth out short-term fluctuations and highlight longer-term trends in your data. For example, a 3-month rolling average shows the average of the current month and the two previous months, helping you identify clearer patterns over time.

Value Labels

Enable value labels to display the exact data values directly on the graph. This makes it easier to read and compare results at a glance.

Tips for Best Results

• Use clear titles for each data series to make your graphs easier to read and understand.

• Apply consistent colors across similar metrics to improve visual recognition. Remember that colors shall help interperet the data, so use it in a smart way.

• Enable value labels when presenting or sharing results to make data easier to interpret at a glance. However, be careful when using value labels in trend charts with more than three data series — too many labels can make the graph look cluttered.

• Use filters to focus on specific target groups or regions and uncover deeper insights.

• Keep it simple — avoid overcrowding your graph with too many series or labels, which can make interpretation harder.