In reality keyword research offers valuable insights into how your users think and express themselves, which can help your team make better product decisions.
1. It reveals users’ anxieties
One of the aims of user testing is to reveal your users’ anxieties.
In private conversation or on a search engine, anxieties are usually expressed as questions. Keyword research can flag these questions and allow you to answer them preemptively.
Example: Imagine you are launching a new line of vape pens with lower nicotine content pods. You want to know what you should include in the product copy:
Quickly discover user anxieties by filtering your keyword master-list by question words — who, what, why, when, how, and is.
Once you know the questions your users are concerned with you can write copy that allows them to make a quick and informed purchasing decision.
2. It helps you speak like a user
In conversation with others people may try to sound smart. But nobody’s trying to impress a search engine; search language is straightforward, literal, and unaffected — which is good news for product teams.
Example: Say you’re part of a team launching a new iOS app that algorithmically provides users with recipes based on their favorite foods, along with dietary tracking and health advice. You are dead set on describing your product as an ‘AI powered nutrition hub’ — the only term you believe reflects your product.
But you notice your product keywords receive zero monthly searches, while other, more straightforward descriptions of your features receive monthly search volume in the tens to tens of thousands.
This data may do more than just force your team to market itself in plain English — it may also them prioritize services within your app, designating the most searched service as a flagship feature, which others augment.
3. It informs related features
There are multiple tools to help SEOs find related clusters of keywords. The simplest is Google’s ‘Searches Related’ section at the bottom of every search results page. These keyword relationships may spark ideas on a natural feature extensions.
Example: Let’s go back to the example above, our ‘AI powered nutrition hub’ which is now a ‘smart recipe app’.
Apparently searchers interested in recipe apps are also interested in recipe organizer apps. This data may spark discussion in the product team about adding in an organizer feature, which allows users to sort recipes by time or cost.
4. It encourages order of magnitude thinking
The final product benefit of keyword research is the most simple: it encourages teams to think in orders of magnitude importance.
It is easy to label product related projects as high, medium, and low priority. But when posed at a verbal level the difference between the three priority tiers doesn’t feel dramatic.
As the three examples above illustrate, keyword research almost always yields order of magnitude differences in results. Keyword A is 200,000 monthly searches, keyword B a mere 20.
Bringing keyword research in as a data source in product decisions helps teams to think less in terms of high, medium, and low importance, and more along the lines of 10x and 100x importance — helping to enforce an equally dramatic allocation of effort.