Key differences between search terms and topics
In Google Trends, search terms and topics are different ways of querying data.
A search term represents exactly what we type into the Google search bar. It is case-sensitive and includes only the specific phrase we entered.
For example, searching for “apple” (as a search term) will show data for all searches that include the word “apple,” whether people are looking for apple the fruit, Apple the tech company, or anything else related to the word “apple.”
A topic, on the other hand, is broader and encompasses all searches related to a particular subject, even if the exact wording varies. It aggregates data across different languages and variations of the same concept.
For example, searching for “Apple Inc.” as a topic will give us data that includes searches for terms like “Apple iPhone,” “Apple company,” “AAPL stock,” and even foreign language equivalents like “Apple empresa” in Spanish.
Comparison of Apple (Company), Apple (fruit), and apple (search term) on Google Trends
Here's a list to condense the differences:
Literal vs. conceptual: Search terms are exact matches, while topics group related concepts.
Language specificity: Search terms are language-dependent, whereas topics can include foreign language equivalents.
Contextual differentiation: Topics try to differentiate similar words with different meanings (e.g., Apple the company vs. apple the fruit), while search terms are purely literal.
Data accuracy: In general, search terms yield significantly more accurate data as the algorithm Google Trends uses to cluster keywords is a "black box." This means users cannot see what is being included or excluded and therefore have no idea if it is giving them the results they are looking for.
Search terms (a.k.a. queries)
Search terms, also referred to as queries, are the exact words or phrases that users type into Google Search. When we use search terms in Google Trends, we're looking at the specific language used by searchers - no foreign languages, no synonyms, and no misspellings.
Key characteristics:
Literal interpretation: If you use "apple" as a search term, Google Trends will show data for all searches that include the word "apple," including both the company and the fruit. This also means that if your search term has different meanings in other languages, it can make it harder to measure interest in your specific topic. For example, if you're researching the Spanish word 'pan' (meaning 'bread'), your results might be skewed by English searches for cooking pans..
Sensitive to variations: Different forms of the same concept are treated as separate search terms. For example, Google Trends would consider "electric car" and "EV" as distinct search terms despite referring to the same concept.
Language specific: Search terms are language-dependent. The term "chaussure de course" (French for "running shoe") would be a completely separate search term from its English counterpart.
Quotes and ordering matter: How you input the search term can affect the results. Using quotes or changing the order of words in a multi-word term can yield different data.
Topics
Topics are Google's attempt at a more conceptual approach to search interest. However, it's crucial to understand that while topics offer certain advantages, they come with significant data quality concerns that can impact their reliability.
According to Google Trends's documentation, a topic is "a group of terms that share the same concept in any language." But there's more to it than just language, and the process isn't without its pitfalls.
Key characteristics of topics:
Conceptual grouping: A topic encompasses various related terms and phrases that refer to the same concept, regardless of the exact wording used. For example “ketogenic diet”, the topic, includes searches for “keto diet”.
Language agnostic: Topics include searches in all languages that relate to the same concept. For example, a topic about "running shoes" would include searches for "chaussures de course" in French and "laufschuhe" in German.
Context aware: Google's algorithms attempt to understand the context of searches. For instance, a topic about 'Java' would attempt to distinguish between searches related to the programming language and the island in Indonesia.
Broader coverage: Topics often provide a more comprehensive view of search interest because they capture various ways people might search for the same thing.
Data quality issues: Topics can provide less reliable or accurate data compared to search terms. Note that the algorithms used to group searches into topics may not always be perfect. These algorithmic limitations can lead to misrepresentation of search interests in the data. If you encounter data quality issues, it's likely due to Google not disclosing the specifics of their topic clustering algorithm. This lack of transparency makes it difficult to understand or predict inaccuracies in the data.
Due to these data quality issues, topics should be used cautiously, especially for critical decision-making. It's advisable to cross-reference topic data with search term data and other sources to ensure accuracy.
To illustrate the issues with topic data, let's use “Starbucks”, as a topic search:
The Google Trends graph for Starbucks the topic and Starbucks the search term are wildly different. The topic graph is missing a huge chunk of data for unexplained reasons.
When to use search terms vs. topics
Understanding when to use topics versus search terms can significantly impact the insights you gain from Google Trends.
Use search terms when:
You're interested in how people are searching for something verbatim (i.e. you only want to see searches for “keto”, not “ketogenic” because, for example, you’re trying to figure out which keywords to include in your content or ads).
You want to analyze searches that were made in a specific language.
You want the most accurate data.
Use topics when:
It’s okay if the data isn’t perfect. If it needs to be perfect, use Search Terms.
You're doing international research on a non-branded term and want to account for different languages.
You're not sure about all the ways people might search for your subject (i.e. “keto” vs “ketogenic”
You're dealing with ambiguous keywords (e.g., differentiating between Apple the company and apple the fruit).
Get the benefits of Topics without the quality issues
Being able to isolate search activity for things with multiple meanings – apple the fruit, not the company – is very useful but, as you now know, Topics are not reliable in terms of data quality.
If you want to have the benefits of topical isolation, without the data accuracy issues, you can use boolean search operators. We’ll walk you through it below, but if you want to learn even more about it, check out our full guide on Google Trends’ boolean search.
1. Adding different languages into the same graph
To capture interest across languages, you can combine terms using the '+' operator. For example:
coffee + kaffee
This search will show the combined interest for "coffee" in English and German.
Apple + google
This search will show the combined interest in google and apple.
2. Using boolean searches to isolate intent
Let's say you want to see searches for the fruit apple and not the company. Here's how to do it:
Get a list of the top searches related to Apple. You can do this by using the Glimpse Chrome extension, searching “apple” then looking in the People Also Search section. Find the top keywords people use that are associated with the company (ex: “apple stock”, “apple store”, etc.) then construct a boolean search to exclude company-related terms using the minus sign for each:
apple -stock -store -iphone -watch
Note that you cannot do minus on a multi-word keyword. For example you can’t subtract searches for “iphone 13”, you can only remove “iphone” and “13” separately.
3. Combining inclusion and exclusion
You can also use '+' to include specific terms alongside exclusions. For example:
apple + google -iphone