5 signals for keyword expansion beyond volume and difficulty

What really matters in keyword expansion isn't how many keywords you add but where you expand. Put a seed keyword into a keyword tool and hundreds of related terms pour out, but it's hard to tell which ones to add based on search volume and difficulty alone. This post covers the 5 signals that decide the direction of expansion, plus an evaluation method you can use right away.

Why volume and difficulty aren't enough

Keyword expansion is the work of finding and adding new related keywords based on your existing keyword list. The problem isn't expansion itself; it's direction.

Neither criterion answers the question "do we really need this keyword?" That's why you need 5 signals that layer strategic context on top of volume and difficulty.

Signal 1: Buyer proximity

The core question is "are the people searching this keyword potential customers?" Taking a CRM SaaS as an example, it breaks down like this.

Don't automatically exclude keywords just because proximity is low. Concept keywords like "what is CRM" are needed to build authority across the topic, and they can score again on the next signal, topic depth.

Signal 2: Performance gap

This signal checks whether your existing data shows a need to expand. Comparing the last 28 days with the previous 28 days in the Search Console Performance report reveals three patterns ^[2].

When one keyword declines, other keywords in the same cluster are often affected too, so it's more efficient to check at the cluster level.

Signal 3: Topic depth

This signal looks at whether adding the keyword thickens a thin cluster. Search engines tend to treat sites that cover a topic comprehensively and in depth as more trustworthy sources ^[3].

When you add keywords to a thin cluster, don't pile in keywords with the same intent. Real topical authority builds up when you mix different search intents, like definitional, action-oriented, and comparison.

Signal 4: AI citability

This signal looks at whether content built around the keyword is likely to be cited by AI search engines. The Princeton GEO study showed experimentally that content with statistics and citations is chosen for AI answers more often ^[1]. Applied to keyword expansion, citability splits by format.

Ask an AI search tool like ChatGPT about your candidate keywords directly, and watch whether it answers with a comparison table or a step-by-step explanation. The more a topic draws those formats, the more likely content on it is to be cited. With a diagnostic tool like TRAIL Search, you can track this observation repeatedly at the prompt level.

Signal 5: Search realism

This signal checks whether real people actually type the term into a search box. Many of the keywords that keyword tools suggest are "planner language."

To verify, judge a keyword as "realistic" if it's confirmed in at least 2 of these 4: Google autocomplete, PAA (People Also Ask), related searches, and AI engine queries.

A combined scorecard for the 5 signals

Put the five signals into one table and it looks like this.

Confirming keywords that pass 3 or more and holding those with 2 or fewer for re-evaluation next quarter works well in practice.

Strategy by signal combination

The 5-Signal results tell you more through which combination a keyword passes than through how many signals it passes. The approach differs by combination pattern.

This combination analysis lets you build a more precise strategy than simply "confirm if 3 or more." For example, a keyword that's high only on depth and AI citability but low on buyer proximity shouldn't be expected to convert right away; place it first as authority-building content and connect it to conversion pages through internal links.

3 practical tips

Tip 1. Adjust signal weights to your industry. For B2B SaaS, it pays to weight buyer proximity and AI citability more heavily. For e-commerce, search realism is key. Applying the same weights to every industry blurs your direction.

Tip 2. Don't throw away "held" keywords either. Keep keywords held at 2/5 or below in a separate sheet. If you re-evaluate them every quarter, some will score higher as the market changes. AI citability scores in particular often change as AI search features expand.

Tip 3. Team agreement matters when filling in the scorecard. Evaluating alone introduces bias. If possible, have the marketing, sales, and product teams each rate buyer proximity. Keywords where the teams' ratings diverge are actually the ones most worth discussing.

3 common mistakes

Relying only on search volume is the most common mistake. A keyword with 3,000 searches isn't always better than one with 300. Low-volume keywords with high proximity often contribute more to conversion than high-volume keywords with low buyer proximity.

Expanding in only one direction is also common. If you keep adding only "comparison" keywords or only "definition" keywords, the cluster loses balance. Real topical authority comes from mixing keywords with different search intents in one cluster.

Ignoring AI search could become more damaging going forward. Even if you rank well, traffic can gradually decline if AI engines don't cite you. Including AI citability in your expansion criteria is no longer optional; it's essential.

What to check when turning expanded keywords into content

Even for keywords that pass the signals, there's one more check before turning them into content. First decide whether a similar post already exists in the same cluster and, if so, whether to create a new post or reinforce the existing one. Adding new posts blindly can actually cause cannibalization, where your own pages compete with each other inside the cluster.

It's also best to follow the format you identified in Signal 4 (AI citability) when deciding how to present an expanded keyword. For a comparison keyword, gather material with a comparison table in mind from the start; for a checklist keyword, design it as a step-by-step structure. Deciding the format up front cuts writing time, and the finished post ends up with a structure that's more favorable for AI citation, too.

In the end, keyword expansion is a question of "how precisely," not "how many." If you start by turning keywords that pass the 5 signals into content, you can move in a more precise direction with fewer resources.

For related reading, see Intent-based keyword research in 6 steps: the 4 search intents and long-tail criteria, What is GEO (generative engine optimization)? Which pages to start with, and in what order, and A 4-step framework that unifies SEO and GEO: should you split or merge the teams?.

You can continue with An SEO and GEO keyword strategy framework.