Add the STR Key Terms condition first when using Circle Pack Visualization to prioritize documents

Let me explain a small but mighty truth about sorting through mountains of documents: the first move sets the tempo. In Relativity, when you’re working with Circle Pack Visualization together with STR - Key Terms, the very first step matters more than you might guess. It’s the moment you decide what “relevant” means, and that decision guides every cluster you’ll see next.

Circle Pack Visualization isn’t just pretty to look at. It’s a way to map lots of documents into colorful, bite-sized groups. Each circle is a cluster, and the size and color hint at how much of the group fits your goal. Now, pair that with STR - Key Terms — essentially the terms you’re watching for — and you’ve got a live, dynamic map of relevance. But here’s the catch: you have to set the rules before you start reading the map. And that’s exactly what the first step is all about.

What Circle Pack Visualization does on a practical level

Think of Circle Pack as a flexible lens. You glance at a mosaic of clusters and instantly see where the concentration of relevant documents lives. The visualization helps you answer questions like: Which groups have the highest share of relevant docs? Where should we focus our attention first? It’s a diagnostic tool that turns a flood of data into actionable insight.

What STR - Key Terms are

STR stands for the terms you decide matter most for your search. The STR - Key Terms are the filters you apply to flag documents as potentially relevant. They aren’t random words tossed into a search box; they’re a curated set that reflects the case, the subject matter, and the stakeholders’ priorities. When you pair these terms with Circle Pack, you’re basically telling the system: “Show me clusters where these terms show up most.”

The crucial first move: Add Condition - STR - Key Terms

If you skip this, you’ll be sorting with a foggy compass. Without a defined condition, the circles you see are informative, but they won’t align with your specific goals. The first step is to add the condition for STR - Key Terms. This does two things at once:

• It establishes the relevance criteria you’ll measure against as you scan the map.

• It seeds the data with a filter that makes the subsequent visualization meaningful and navigable.

Here’s how the logic plays out in practice

• You choose your STR terms carefully. Think about phrases that cover the core topics, typical document types, and any sneaky synonyms that tend to show up in your data. For example, if you’re focused on contracts, you might include words like “agreement,” “contract,” “amendment,” and “signature.” If you’re chasing financials, you add terms like “invoice,” “payment,” “net,” and “reconciliation.” The right mix helps the circles reflect real relevance, not just volume.

• You apply the condition as a filter. The circle pack then reorganizes around which clusters contain higher concentrations of documents matching those terms. In other words, you’re not just seeing where documents are; you’re seeing where the documents that matter cluster together.

A quick tour of what happens after you set the STR - Key Terms

With the condition in place, the Circle Pack view starts to feel meaningful. You’ll notice several practical shifts:

• Clusters light up with higher percentages of relevant documents. Some circles glow brighter because they’re full of material that matches your terms.

• The map becomes navigable. You can drill into promising clusters, compare one group to another, and avoid wandering aimlessly through pages of noise.

• It’s easier to plan your workflow. Once you spot high-yield clusters, you know where to focus your review team and where to apply mass tagging if needed.

From here, the next logical steps usually look like this:

• Locate clusters with the highest % of relevant documents. These are your “hot spots” where progress can be quickest.

• Right-click to select clusters you want to investigate further. This makes it easy to pull representative samples or to start tagging documents for review priority.

• Mass tag the selected documents for review priority. This helps your team triage efficiently, so the most important items get attention first.

A tangible analogy

Imagine you’re organizing a library after a big move. Circle Pack is like sorting shelves by genre and topic, but the STR - Key Terms are the color codes you assign to each shelf. You don’t just dump books on random shelves; you mark them with specific labels that tell you, at a glance, which stacks deserve a closer look. The first labeling pass—your Add Condition step—defines the entire sorting logic. Without clear labels, you end up with a beautiful but chaotic mosaic that doesn’t guide you to where the meaningful reads are.

Tips to make the first step even stronger

• Be precise, but practical. Start with a core core set of terms that capture the essence of what you’re after. You can always expand later if you find you’ve been too tight.

• Include relevant synonyms and common variants. People write things differently. A term like “invoice” might appear as “invoices,” “billing,” or “bill.”

• Test with a small slice. If you’re unsure about terms, run a quick trial on a subset of the data. It’s cheaper to adjust on a small scale than after you’ve scanned the whole map.

• Keep terms focused to avoid flood. Too many broad terms pull the map into noise. A crisp, meaningful set keeps clusters interpretable.

• Document your criteria. A short note about why a term is included helps teammates understand the filter and keeps your approach transparent.

Why this first step matters in the bigger picture

Prioritization isn’t just about finding relevant docs; it’s about doing so efficiently. When the STR - Key Terms are defined upfront, you set a clear target for your review team. The Circle Pack visualization then translates that target into a visual map that makes it easier to act on. You move from “there’s a lot here” to “this is where we focus first.” And when you know where to focus, you can allocate time, people, and tools with confidence.

Common missteps to watch for

• After you add the condition, you notice more clusters, not all of which are truly useful. If a cluster looks big but doesn’t actually hold relevant material, refine your terms or add a secondary filter to filter out noise.

• You forget to test variations. A term might be too broad in one matter and just right in another. Regular fine-tuning keeps the map accurate.

• You skip documenting your criteria. It’s tempting to wing it, but a quick note about why terms were chosen protects the workflow when teammates change or when you revisit the map later.

Putting it all together: your pathway to clarity

Let me recap in simple terms. The first step in prioritizing documents with Circle Pack Visualization and STR - Key Terms is to Add Condition - STR - Key Terms. That single action builds the foundation for every move that follows. Once you’ve defined the terms, you’ll see how clusters form around those terms, which helps you spot the most promising groups quickly. Then you can drill into those clusters, select them with a click, and mass-tag documents to kick off a focused review priority.

If you’re new to this, you might feel the map is a tad mysterious at first. That’s normal. The beauty is in the pattern. When you set the conditions, you’re not just naming terms—you’re shaping a roadmap. And that roadmap is what keeps the work focused, efficient, and ultimately more effective.

Ready to test the waters? Start with a concise STR - Key Terms set, apply it as a Condition in Circle Pack, and watch the visualization begin to reveal where your effort will pay off. The first step isn’t just a tick box; it’s your compass, guiding you toward clarity amid a sea of documents.

If you’d like, I can walk through a concrete example with sample terms and show how the circles respond step by step. It’s a quick way to internalize the flow and feel out how the map should look once your terms are in place. And yes, the payoff is real: a cleaner map, faster triage, and a more confident plan for how to approach the work.