How to use Google Trends to analyze your competitors’ brand engagement

Have you ever ever learn one thing within the press or on a media website after which searched Google to study extra in regards to the subject?

Virtually everybody has. 

After studying an article a few product or concept, many individuals use a search engine to seek out deeper particulars in regards to the subject or its components.

This workflow can drive short- or long-term model or non-brand key phrase search patterns.

By analyzing these patterns, you possibly can reply very strategic digital marketing, PR and SEO questions:

• What forms of media placements drove these search patterns?
• What product messaging and positioning is driving viewers curiosity?
• Ought to we constantly put money into PR or SEO as a substitute of short-term campaigns?
• How do I steal my competitor’s finest placements with our distinctive positioning?
• What publications ought to I exploit to check product positioning for a brand new go-to-market technique?
• How do I improve the brand search for a brand new product launch?

These questions simply scratch the floor of the way to use this evaluation to strategic search advertising, new class design or normal product administration.

First, let’s outline model search conduct within the context of digital media and search.

What’s model search conduct?

How an viewers searches out model particulars on account of both short-term or long-term engagement with model messaging throughout different platforms.

Model search conduct is a powerful indicator of name engagement.

Because the viewers learns about your model or facets of it, they may naturally search Google for extra particulars.

Model search conduct can work like this:

• Drawback consciousness: Search begins after the viewers identifies a necessity, challenge or potential answer from press, social or commercials, usually utilizing non-branded key phrases to study extra (e.g., “finest health tracker”).
• Model-specific search: After researching or studying about potential options, the viewers could seek for particular manufacturers utilizing branded key phrases (e.g., “Fitbit” or “Fitbit knowledge”).
• Deeper seek for validation: Shoppers evaluate manufacturers and search detailed info utilizing key phrases like “vs.” or “opinions” to guage choices.
• Buy resolution: The viewers may use search phrases centered on discovering one of the best worth, purchase or possibly contact (e.g., “purchase Apple Watch” or “Apple Watch worth”).
• Publish-purchase search: After shopping for, shoppers could seek for help, ideas or neighborhood engagement (e.g., “Fitbit telephone”).

This course of will present deep perception into what drove this model search conduct.

Evaluation course of overview

This course of identifies the messaging, sources and other people driving an viewers to seek for a model.

I exploit this device stack to research: 

• Google Tendencies.
• Glimpse. 
• Ahrefs.
• Grok on the X platform.

The steps are pretty easy:

• Choose competitor phasing: That is how folks seek for a competitor or your model title.
• Uncover search patterns: Discover short-term or long-term patterns for progress in model search patterns.
• Discover the supply of affect: Discover main indicators of these patterns. What’s driving model search?

Beginning by figuring out the phrasing used to go looking the competitor (e.g., model title) ensures you’re discovering the best key phrase phrases that an viewers makes use of to seek out the model web site.

The main indicators, or the supply of affect, can establish patterns for:

• Progress.
• Decline.
• Random adjustments.

An viewers can seek for a model title after simply studying one or a number of strategic placements or after fixed publicity to a model’s messaging. 

I’ll use Lectric eBike for instance to point out how this course of works. They’re an ebike model that has gone from 37,000 to over 210,000 organic clicks per 30 days, with over 150,000 clicks per 30 days from model searches. 

Their model search has grown within the short- and long-term over the previous few years.

1. Choose competitor and phrasing

Use Semrush to establish the highest variations of name key phrases. Go to Venture > Overview > Natural analysis > Positions.

Choose the highest variation or run reviews for all variations of the model or product names.

On this instance, the most well-liked model variation is “Lectric eBike,” however folks additionally use “lectric.” 

On this case, we see that search phrases get an estimated 33.1K searches per 30 days. 

However folks additionally seek for one of many ebike product traces, just like the “lectric XP 3.0.” 

These phrases are a place to begin for the way the model drives these searches.

Use these key phrases to seek for patterns in Google Tendencies.

2. Determine patterns with Google Tendencies

Earlier than beginning your search, use the Glimpse plugin (for Chrome) to replace the Google Tendencies UI and add some very helpful options. 

This device provides a trendline that reveals seasonality or year-over-year (YoY) developments in an easy-to-understand format. This has saved me a lot time over exporting and analyzing the information.

Determine progress patterns (e.g., spikes or upward developments) like seasonality, year-over-year progress or random spikes. 

The random spikes are my favourite as a result of they’ll present short-term influence on account of a selected occasion. Then, export the information to be analyzed later.

On this case, the expansion in model search curiosity began in the summertime of 2022 however grew considerably in 2024.

Main indicator questions:

• What causes the preliminary progress in the summertime of 2022?
• What media protection precipitated YoY progress in model search in 2024 from 2023 and 2022?

• Tip: Constant media protection can present YoY progress, particularly throughout peak shopping for seasons. When analyzing progress, take a look at media protection from the previous 12 months, not simply the month when the expansion occurred.

Discovering main indicators will be difficult. Generally, a number of media mentions can result in a big spike in curiosity. At different instances, ongoing advertising efforts over a number of months or years could lead to gradual YoY progress.

With the questions prepared, use the device stack to research the information and establish the media driving the search.

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3. Determine the supply of affect

Use the device stack to establish the supply that influenced the expansion patterns.

This doesn’t usually embrace evaluation of YouTube movies, Instagram/TikTok or kinds like Reddit, however it would present quick insights into the messaging and trusted media sources.

For every sample you wish to perceive, establish potential main indicators.

Right here’s the method:

• Grok for Twitter search: Ask Grok for media protection of the model title. Use this to establish potential developments in messaging or product launches.
• Ahrefs model mentions: Run reviews in Content material Explorer to establish model mentions over time. I haven’t discovered a greater device to do that course of.
• ChartGPT evaluation: Analyze all three Ahrefs reviews to establish model mentions to research.

Search X with Grok

Grok has real-time entry to X’s content material, so you may get latest details about X’s content material and have Grok summarize the findings. 

You will be inventive with the prompts, however I wish to ask for a abstract of name mentions.

When Grok summarized mentions of “Lectric eBikes” on X, it supplied extra particulars that will require intensive analysis.

Grok rapidly reveals the brand new product launch protection. The messaging of “high quality at a low worth” is constant across the model.

Grok has some insights, however I exploit Ahrefs to research the media protection extra deeply and validate Grok’s output.

Ahrefs model mentions

Use the Content material Explorer report in Ahrefs to establish historic developments in protection of the model on press, blogs and a few message boards. Export the total record of publications to be uploaded to ChatGPT for evaluation.

On this evaluation, the Ahrefs bar chart illustrates the media story. 

Mentions in 2021 have been extra constant, whereas late 2022 noticed a concentrate on vacation promotions. Each developments deserve additional evaluation.

Tip: 

• Check utilizing phrase (use ” ” for phrase) or actual (use [ ] for actual) match Boolean queries to seek out extra exact mentions. With “lectric,” Ahrefs returned a whole lot of mentions for “electrical,” which was not a related model point out.

Analyzing this knowledge manually will be very laborious, so I exploit ChatGPT to take a lot of the work out of the evaluation and discover particular insights.

ChatGPT evaluation

Add the Google Tendencies and Content material Explorer exports to ChatGPT (I used 4o for this text) to research patterns within the model mentions and model search developments.

For this instance, I rapidly recognized some key insights from correlation in Google Tendencies and model mentions from Content material Explorer.

From ChatGPT evaluation, I discovered that the model centered on some high-authority (e.g., Forbes) and likewise vertically focused publications (e.g., Electrek). But additionally their constant messaging about low price and top quality is interesting to the viewers on these publications. 

I discovered these outputs from ChatGPT helpful for understanding the media influence on patterns or figuring out media to research additional.

• Get key insights into main indicators of random patterns/spikes or long-term developments

• Discover normal developments in media varieties that correlate with spikes or developments

• Determine what particular websites may have pushed spikes

A giant limitation is that this mannequin doesn’t embrace bigger market developments that may affect. However you should use Google Tendencies to assist establish these as properly.

Bonus

It’s possible you’ll wish to use the PEST (political, financial, social, technological) mannequin to establish main market elements that might contribute to those progress patterns. I do know this doesn’t embrace competitors, however it may fall beneath every of those classes.

The better societal developments can have a huge impact on demand for sure services or products. 

Google Tendencies seek for “ebike” grew considerably after the pandemic began in 2020. 

It is perhaps attributable to a rising variety of persons are occupied with a more healthy life-style, which helps to drive this demand.

• Tip: When importing, describe the information and the supply to ChatGPT and ask for the sector names. Then ChatGPT will doubtless have to scrub the information.

Analyzing model engagement with Google Tendencies

This text serves as a information for conducting your personal competitor search conduct evaluation.

By making use of the insights shared right here, you possibly can uncover efficient methods to surpass your opponents in natural search and drive sustainable income progress.

Notes on knowledge and evaluation high quality

• Ahrefs: Whereas helpful, it doesn’t account for promoting, social media, or bodily publications.
• Grok: Gives real-time entry to X knowledge, however it’s unclear what number of manufacturers are talked about past content material from the corporate or its staff members.
• Google Tendencies: Doesn’t seize all searches and consists of some crawler knowledge. The “observe” markers may affect progress, however there’s no sturdy proof of serious distortion over time.
• ChatGPT: Lacks entry to real-time net knowledge and should generate inaccurate insights (“hallucinations”). This may be mitigated by manually verifying media placements.