👀Google Trends to Spot the Next Big Thing in Fashion 4 steps👀

AI does have its ripple-out effects. Of course, that includes the fashion industry. Over the past decades, the fashion industry has experienced a rapid trend change yet it has its unique trait whereby its past trend sometimes makes a comeback. 

This would mean that whoever forecasts the come-back moment of a past fashion trend, they will go huge on the market.  

I have been working as a fashion designer over the last few years. With this post, I introduce you to a very simple, yet powerful tool – Google Trend in which you can leverage to read the trend earlier than anyone else. This will give you an idea of how you can plan out products knowing its shifting consumer preference in colours, fits and others. 

What does it do? 

Google Trends draws on search data from hundreds of millions of users worldwide, visualizing the “popularity flow” of specific topics (like colours, brand names, or style keywords). In the past, planning, sales, and marketing teams in fashion had to rely on manual market research reports, international street photos, or fashion shows to define trends. 

Now, Google Trends helps you answer these questions with data and you can immediately apply them to product planning and meetings. 

  •  Did searches for “wide-fit denim” soar in the past month?
  •  Are keywords like “navy color,” “red tones,” or “crop jacket” gaining popularity?
  •  How do popular keywords differ by region or age?

1. Go to Google Trends and create a Google Ad account.

2. Enter Your Keyword (refer image 1)

  • Type your keyword of interest (e.g., “navy,” “wide pants,” “crop jacket,” etc.) in the search bar at the top (refer image1) 

Image 1: Google Trend Main Page 

3. Set Region and Time Period (refer Image 2) 

  • Choose your desired country/region on the left.
  • And select the time range at the top of the graph.

Image 2: Search region and categories with its corresponding graph.

4. View the Trend Graph (refer Image 3) 

  • You’ll see a graph showing the search interest over time for that keyword (see the bottom section of image 2) 
  • You can easily check if the trend is increasing (rising), decreasing (falling), or stable.

Image 3: Comparing multiple keywords simultaneously

5. Compare Multiple Keywords (Optional – refer Image 4)

  • Click the “+ Compare” button to search multiple keywords at once,
  • And see which keyword has a higher or growing trend.

6. Check by Region or Category (Optional)

  • Explore further breakdowns by region, related topics, or audience demographics for finer insight.

Image 4: Pulling up the comparative analysis in a line graph format

With insights from Google Trend, one may know its trend, but it would be useless had they not known about how to bring them up in their workplace – below are the steps on how to use it in its practice. 

STEP 1. List Major Keywords: Colors, Fits, Categories 

STEP 2. Summarise Trends and Prepare for Planning Meetings 

  • Compile charts and location/age-based reports for each keyword.
  • Example:
    •  “Navy” has increased for three consecutive weeks, especially among teens and people in their 20s.  
    •  “Wide denim pants” are spiking in New York and Washington.  
    •  “Crop jacket” is rising, but less popular in southern america.

STEP 3. Reflect in Product Planning 

  •  Choose key colors and fits: Prioritise colours/fits with the clearest trends in new season lineups.  
  •  Product planning meetings: Bring data-driven arguments—minimising subjective guesswork.  
  •  Target segmentation: Design differentiated strategies for regions and age groups using data.

STEP 4. Use for Marketing and Sales 

  •  Marketing: Launch influencer and brand hashtag campaigns linked to trending keywords.
  •  Feature real-time popular trends on different O2O/online platforms to improve customer experience.
  •  When trend shifts are detected, quickly adjust inventory or production decisions.

 

  •  Changed from “I just have a feeling this will trend” to data-driven validation, improving planning accuracy.
  •  Minimization of unnecessary inventory or unsold products; increased hit-rate for bestsellers.
  •  Shortened time-to-market and enhanced responsiveness.

Note 

Many fashion brands routinely compare sales data from Salesforce, its own ERP, and external platforms (like ssense) with trend predictions from Google Trends. Ultimately, cross-referencing live sales and predicted trends reduces forecasting errors and improves results. 

In Conclusion 

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