Case study Google Trends

A one-stop-shop script to automatically pull google trends by exact keywords using Pytrends

COVID-19 has provided a boon for Google Trends usage in the U.S. (see chart below). After all, its a free publicly available tool that provides access to actual search requests across google search engine. More companies have leveraged Google Trends to gain insights on category trend, consumer top searched queries, competitors performance amid the black swan pandemic event.

Each Google Trends request consists of 5 unique parameters:

• KEYWORDS: Your keywords go here. You can use the prompt under the drop-down box to select the correct keywords.
• COUNTRY: Companies with an international footprint could use this function to get trends across countries.
• DATE INTERVAL: Choose the time range of the trend. Please note that google trends data is normalized based on location and time. Thus, different time ranges will yield various results.
• CATEGORY: Indicate what categories you prefer to search the keywords.
• SEARCH TYPE: Select the source of the search, i.e. Google Search, Image Search, News Search, Google Shopping, and YouTube Search.

CHALLENGES:

There are two main challenges to pull Google trends data in scale.

1. Individual keyword by keyword manually pulling is time-consuming.

Although Google Trends provides the Compare function to compare keywords, the downside is that it scales the results from 0 to 100 based on the most popular term entered. The less popular keyword will lose sensitivity quickly if you compare it with a popular one. For example, if you compare Nike brand with Supreme brand, you will basically get a flat line for Supreme. In this situation, youll get big errors when reporting Supreme search growth trend. Thus, it is suggested to pull Nike trend and Supreme trend individually and separately.

You can still afford the time until you have too many keywords to pull. E.g. when to compare 50 apparel and footwear brands, you need to download 50 excels and combine them together.

2. Current available automation python methods dont query exact keywords, meaning theyre not accurate.

There are many available methods to pull google trend data using python. However, none of them builds automatic codes that could pull EXACT KEYWORDS. Its not unusual that words often have multiple meanings. For example, Patagonia could either be a clothing company or a region in South American. Simply search Patagonia will give us ambiguous results as it contains both search terms. We need to make sure we search the right keywords.

GOAL:

The goal is to provide a solution to pull google trends data for multiple keywords exactly, individually, and automatically.

Specifically, well pull google trends data for six apparel/footwear brands (Nike, Adidas, Under Armour, Zara, H&M, Louis Vuitton) in three countries (US, UK, Germany). Using Python, there are four steps to achieve this:

• Step 1: Install pytrends API
• Step 2: Get exact keywords
• Step 3: Pull Google trends data by exact keywords by country
• Step 4: Visualize Google trends

Step 1: Install pytrends API

First of all, we need to install that package called pytrends, which is designed to pull google trends using python. Simply execute the following code from your Terminal. You could find the comprehensive documentation of the pytrends API here.

We will then import the necessary packages.

Step 2: Get exact keywords

As discussed earlier, we need to be precise on the keywords to avoid ambiguity. Pytrends provides a function called pytrend.suggestions that could return several suggestions for a keyword. Usually, the first suggestion is the most popular one. mid column contains those exact keywords wed like to search.

Step 3: Get Google trends data by exact keywords

Next, well set those 5 parameters.

Then, well write codes to pull google trends data by exact keywords by country using the above parameters.

And we will do some cleaning work and change those exact keywords back to readable brand names.

Step 4: Visualize Google trends

In the blink of an eye, we get our google trends data. Finally, lets visualize Louis Vuitton's google trends across countries. As we could see, Louis Vuitton clearly gets hard hit by COVID-19, just like many other brands and industries.

SUMMARY

Google Trends tool usages see surging growth as companies closely monitor shifting consumer behavior during COVID -19. To help with this, we build a light application to pull Google Trends data precisely and automatically.

Finally, stay positive, thanks for reading!