Glossary: Language-Led Differentiation

Most sales teams describe their product the same way every competitor does: generic features, generic benefits, generic category language. The Glossary exists so your team can own a deliberate vocabulary instead, and so practice reinforces that vocabulary until it becomes automatic.

Why owning your vocabulary matters

When everyone in a market uses interchangeable words, buyers cannot tell vendors apart and price becomes the only differentiator. A distinctive, consistent vocabulary does three things:

• It signals expertise. Precise, intentional language makes a rep sound like a consultant who understands the buyer's world, not a vendor reading a script.
• It makes you memorable. A buyer who hears the same sharp phrase from every rep on your team remembers your framing after the call ends.
• It keeps the team consistent. When ten reps explain the same concept ten different ways, your positioning blurs. A shared glossary aligns them.

What the Glossary actually is

It is a studio-level list of terms. Each term carries a definition, a short note on why your team uses it, and guidance on when to use it. You decide, per term, whether the AI should check for it during scored practice. That is the whole model: define the language, then let practice and feedback drive adoption.

How it connects to the rest of the studio

• Scored simulations use feedback-enabled terms to evaluate whether reps reached for your language. See "AI-Powered Feedback on Term Usage" below.
• Groups let you point specific scenarios (for example, certain Discovery tracks or Messaging / Pitch scenarios) at a focused subset of terms instead of the entire glossary.
• For articulating value in your own words alongside the glossary, see the Capability Map framework.

The goal is not jargon for its own sake. A term only earns its place if it makes your team clearer, sharper, or more distinctive than the generic phrase it replaces.

A glossary is only as good as the terms in it. Before you add anything, decide what each term is meant to accomplish: replace a tired generic phrase, reframe a problem in your favor, or give a fuzzy concept a name your team can rally around.

Start from real language gaps

The strongest terms come from listening, not invention. Review recent calls and notes and look for:

• Generic phrases every competitor also uses, where a sharper word would set you apart.
• Concepts your reps explain inconsistently, where a shared definition would align the team.
• Moments where the right framing would have shifted the buyer's perspective.

What goes into each term

The entry form has four fields, all required. Treat the last three as the coaching that travels with the term, not busywork.

Field (as labeled in the app)	What it is for	What good looks like
Word, vocabulary, or phrase	The exact term, spelled and capitalized the way you want it used	Short and specific. Examples in the field: "Practiced Playbook", "Out-of-the-Box", "Persona-Centred"
What it is	A clear, plain definition	One or two sentences. This is also the text the AI evaluator sees, so make it unambiguous
Why we use it	The purpose the term serves and the value it carries	Explain the differentiation or clarity it buys, so reps understand the intent, not just the words
When we use it	The situations or call moments where it belongs	Concrete triggers ("when a prospect asks how we compare to X") beat vague advice

Principles for terms worth keeping

1. Earn the swap. A custom term should be clearer or more distinctive than the generic word it replaces. If it only adds jargon, drop it.
2. Make it sayable. Reps have to use it out loud under pressure. Awkward or hard-to-pronounce terms do not get adopted.
3. Keep it honest. Language that overpromises erodes trust faster than generic words ever would.
4. Write the definition for the evaluator too. Because "What it is" is what the AI matches against, a precise definition makes feedback more accurate.

Start with a focused set of high-value terms rather than a sprawling list. A team can internalize a dozen sharp terms far better than fifty mediocre ones.

The management screen is where you add, edit, organize, and tune your terms. It has two tabs, Terms and Groups, each showing a live count.

Getting there

Go to Admin and open Glossary from your studio's module configuration. The page lists every term in your studio with its feedback status.

Adding and editing terms

1. On the Terms tab, click Add term (this opens the new-term form).
2. Fill in the four fields described in "Creating Your Differentiation Vocabulary": the term, what it is, why we use it, and when we use it. All four are required.
3. Leave Include this term in AI feedback checked if you want the AI to evaluate it during scored practice. It is on by default for new terms.
4. Save. To change a term later, click the edit icon on its row. Editing keeps the term's position in the list.

Terms must be unique within a studio. If you try to add a term that already exists, the save is rejected.

Ordering

Drag the handle on the left of any row to reorder terms. The order you set is the order the list shows everywhere, so put the terms reps reach for most at the top. There is no separate order field to type into. Reordering saves automatically.

Turning feedback on or off per term

Each row has a feedback toggle, and a badge that reads Feedback or No feedback. Use it to control which terms the AI checks during scored simulations without deleting anything. A banner at the top of the list shows how many of your terms are currently enabled for feedback, and warns you if none are (in which case the glossary is skipped during evaluation entirely).

Searching and deleting

The search box filters by term, definition, why-we-use-it, and when-we-use-it text. Delete a term from its row (you will be asked to confirm). Deleting is permanent.

Groups: targeting feedback to a subset of terms

The Groups tab lets you bundle related terms so a scenario can be evaluated against just that bundle instead of your whole glossary. This keeps feedback relevant: a discovery scenario can focus on discovery language, a pitch scenario on positioning language.

• Click Create group, give it a name (required) and an optional description.
• Open a group's Manage terms dialog to add or remove terms. The dialog also lets you flip each term's feedback toggle while you are in there.
• Groups can be attached to scenarios such as Discovery tracks and Messaging / Pitch scenarios. Because of that, a group that is in use by scenarios cannot be deleted until those references are removed.

Groups are optional. If you do not use them, scenarios fall back to evaluating against all feedback-enabled terms in the studio.

This is where the glossary pays off. When a rep completes a scored simulation, the AI evaluator receives your feedback-enabled terms and reviews the conversation for how well the rep used them. Practice stops being just conversation reps and starts reinforcing your specific language.

What the AI receives and what it does with it

For each term enabled for feedback, the evaluator is given the term and its definition (the "What it is" field). It is instructed to note which terms were used effectively and which were missed opportunities. The feedback returned for the session includes a glossary breakdown with three parts:

• Terms used well in the conversation.
• Missed opportunities, where a glossary term would have fit but the rep used generic language instead.
• Terminology recommendations for next time.

This appears alongside the rest of the rep's simulation feedback, not as a separate live alert. There are no real-time prompts during the conversation itself; the glossary assessment is part of the post-session feedback.

What controls whether a term is evaluated

The single lever is the per-term Include this term in AI feedback toggle.

• Terms with feedback on are sent to the evaluator.
• Terms with feedback off are ignored during scoring (they still live in your glossary for reference).
• If no terms are enabled for feedback, the glossary is skipped entirely for that evaluation. The management screen warns you when this is the case.

There are no separate strictness or sensitivity modes. Inclusion is decided term by term, and (when you use groups) by which group a scenario points at.

Getting accurate feedback

Because the evaluator matches against the definition, the quality of your "What it is" text directly affects feedback quality:

1. Write unambiguous definitions. Vague definitions produce vague or inconsistent matching.
2. Enable terms deliberately. Turn on the language you genuinely want reps to adopt now, rather than every term at once, so feedback stays focused.
3. Use groups for focus. Point a scenario at a group so reps are coached on the language that fits that exact conversation, not the whole glossary.
4. Revisit terms that keep getting missed. If a term is consistently flagged as a missed opportunity, the issue may be the term itself (too awkward, unclear, or wrong for the moment) rather than the rep.

Heads up: there is no spreadsheet import or file export inside the Glossary management screen. Terms are added and edited directly in the app. This section covers the two realistic ways to build vocabulary at scale and reuse it, so you do not have to hand-type everything.

Build terms quickly with AI-assisted generation (studio setup)

During studio setup, the glossary step can draft candidate terms for you instead of starting from a blank list. It blends context from:

• Your studio's positioning and personas.
• Documents you upload (for example a PDF or Word file).
• A website URL or a YouTube link you provide.

You choose how many terms to generate, review the drafts, then select which ones to save. The AI is asked to preserve the structure and wording of a source document when one already reads like a glossary, so an existing terminology list comes across faithfully rather than being reshuffled. Generation produces drafts only; nothing is added to your studio until you pick the terms you want and save them. After saving, refine them on the Terms tab like any manually created term.

This is the closest equivalent to a bulk import: point the generator at source material you already have, and let it propose terms grounded in that material.

Reusing vocabulary across studios

The glossary is scoped to a single studio, so terms do not automatically appear in other studios. To carry vocabulary across studios today:

• Keep a master source of truth for your language (a shared doc or your positioning material) outside the app.
• When you stand up a new studio, run the setup glossary generator against that same source material so the new studio starts from the same vocabulary.
• Adjust each studio's terms afterward for any audience or product differences.

Keeping the glossary healthy over time

Because everything is edited in place, treat upkeep as an ongoing habit rather than a periodic import:

1. Prune dead terms. Remove language the team no longer uses so feedback stays relevant.
2. Tighten definitions. Sharpen any "What it is" text that has caused inconsistent feedback, since that field drives AI matching.
3. Re-check feedback toggles. As priorities shift, enable the terms you want reps adopting now and quiet the rest.
4. Rebalance groups. Make sure each group still maps to the scenarios that should be evaluated against it.