Overview
SAGA automatically selects and generates charts to support its analysis. Every chart follows a simple principle: one chart, one claim. SAGA picks the chart type based on the question being answered, not the shape of the data.
This guide explains the nine chart types SAGA can produce, what each one looks like, and when SAGA will use it in a report.
💡Tip: You can tell SAGA to include any or all charts in your analysis report, as well as specific insights you'd like to visualise. Just detail your specifications in your brief and don't forget you can chat back and forth with SAGA to tweak the charts until they display your data as you need it.
Spline
A smooth line chart showing how a metric changes over time.
SAGA uses this when: You need to see a trend, track conversation volume over a period, or understand how a topic is rising or falling. Ideal for showing momentum and trajectory.
Best for answering: "How has conversation changed over time?" / "When did this topic peak?"
Area spline
A filled version of the spline chart, where the area beneath the line is shaded.
SAGA uses this when: The focus is on cumulative volume or the weight of conversation over time, rather than just the trend line. The shading makes it easier to compare the scale of different periods at a glance.
Best for answering: "How much total conversation happened across this period?" / "How does volume compare week to week?"
Bar / Column
Vertical or horizontal bars comparing values across categories.
SAGA uses this when: You need a direct comparison between distinct items, such as brands, topics, platforms, or sentiment categories. Each bar represents one category, making differences immediately obvious.
Best for answering: "Which brand has the most mentions?" / "How does sentiment compare across platforms?"
💡Tip: Clustered bar charts are also possible, just specify that in your prompt.
Heat Map
A grid using colour intensity to represent values across two dimensions.
SAGA uses this when: The analysis involves patterns across two variables, such as day of the week versus time of day, or topic versus platform. Darker colours indicate higher concentration.
Best for answering: "When is conversation most active?" / "Which topics dominate on which platforms?"
Pie
A circular chart showing proportional share of a whole.
SAGA uses this when: The insight is about composition or share of voice. Useful for showing how a total breaks down into its parts, such as sentiment split or platform share.
Best for answering: "What percentage of conversation is positive versus negative?" / "What is each brand's share of voice?"
Ranking
An ordered list showing items ranked by a specific metric.
SAGA uses this when: The analysis needs to highlight a clear hierarchy, such as top themes, most influential accounts, or highest-performing content. Rankings make priority and order immediately clear.
Best for answering: "What are the top themes in the conversation?" / "Which accounts are driving the most engagement?"
Multiple Bar
A grouped or stacked bar chart comparing multiple data series side by side.
SAGA uses this when: You need to compare more than one metric across the same set of categories. For example, comparing positive and negative sentiment for each competitor, or volume versus engagement across platforms.
Best for answering: "How do brands compare across multiple metrics?" / "What is the sentiment breakdown for each competitor?"
Tree Map
A rectangular chart where each block represents a category, sized by its value.
SAGA uses this when: The insight involves showing relative size or dominance within a dataset. Larger blocks mean higher volume or share. Useful for quickly seeing which themes, topics, or segments dominate the conversation.
Best for answering: "Which themes take up the most conversation space?" / "What are the dominant sub-topics within this category?"
Stream
A flowing, layered chart showing how multiple categories change in volume over time.
SAGA uses this when: The analysis tracks several themes or topics simultaneously across a timeline. The width of each stream represents volume, making it easy to see how the composition of conversation shifts over time.
Best for answering: "How have different narratives evolved over the same period?" / "Which topics grew or shrank relative to each other?"
