Google Trends for Marketing Analytics

Tutorial 1 - Part 1 - A Hands-On Tutorial Using gtrendsR

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Course Context: This tutorial is designed for marketing students learning how to leverage publicly available search data for consumer insights, competitive intelligence, and campaign planning.
GitHub: github.com/utjimmyx

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1 What Is Google Trends?

Google Trends is a free, publicly available tool from Google that tracks the relative search interest for any keyword or topic over time. Rather than reporting raw search volume, Google normalizes data on a scale of 0 to 100, where 100 represents the peak popularity of a term within the selected time range and geography.

Why does this matter for marketers?

• It reveals when consumers become interested in products or categories
• It helps you spot emerging trends before competitors do
• It supports seasonal planning for promotions and inventory
• It enables geographic targeting by showing where interest is highest
• It surfaces related queries that inform keyword and content strategy

Key Concept: Google Trends data is relative, not absolute. A score of 50 means the term had half the search interest compared to its peak — it does not mean 50 searches occurred.

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2 Required Packages

We will use the following R packages. Install any you don’t already have.

# Run once to install
install.packages(c("gtrendsR", "tidyverse", "ggplot2", "scales",
                   "lubridate", "knitr", "kableExtra"))

library(gtrendsR)     # Pull data from Google Trends
library(tidyverse)    # Data manipulation and plotting
library(ggplot2)      # Visualization
library(scales)       # Axis formatting
library(lubridate)    # Date handling
library(knitr)        # Tables
library(kableExtra)   # Enhanced table formatting

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3 Understanding the gtrends() Function

The core function in gtrendsR is gtrends(). Here are its key arguments:

Argument	Description	Example
keyword	Search term(s), up to 5 at a time	c("Nike", "Adidas")
geo	Country or region code (blank = worldwide)	"US", "CA", "GB"
time	Time range of the query	"today 12-m", "2020-01-01 2024-12-31"
gprop	Search property	"web", "youtube", "news"
category	Restrict to a Google topic category (0 = all)	0

Common time values:

"now 1-H"        → Past hour
"now 4-H"        → Past 4 hours
"today 1-m"      → Past 30 days
"today 3-m"      → Past 90 days
"today 12-m"     → Past 12 months
"today+5-y"      → Past 5 years
"all"            → Since 2004

4 Let’s test to see if the gtrendsR package works normally (see my notes at the beginning)

# test <- gtrends("coffee")

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5 Tutorial 1: Single Keyword — Brand Search Interest

Let’s start simple: track search interest for “Starbucks” in the United States over the past 12 months.

# Query Google Trends
starbucks_trend <- gtrends(
  keyword = "Starbucks",
  geo = "US",
  time = "today+5-y"
)

# Extract interest over time
iot <- starbucks_trend$interest_over_time

ggplot(iot, aes(x = date, y = hits)) +
  geom_line(color = "#00704A", linewidth = 1) +
  geom_smooth(method = "loess", se = TRUE, color = "#1E3932",
              fill = "#D4E9E2", alpha = 0.3) +
  scale_x_datetime(date_labels = "%b %Y", date_breaks = "2 months") +
  labs(
    title    = "Google Search Interest: Starbucks",
    subtitle = "United States | Past 5 years | Web Search",
    x        = NULL,
    y        = "Relative Interest (0–100)",
    caption  = "Source: Google Trends via gtrendsR | github.com/utjimmyx"
  ) +
  theme_minimal(base_size = 12) +
  theme(
    plot.title    = element_text(face = "bold", size = 14),
    plot.subtitle = element_text(color = "gray50"),
    axis.text.x   = element_text(angle = 30, hjust = 1)
  )

Marketing Insight: Look for dips and spikes. Dips may correspond to off-peak seasons or PR crises. Spikes often align with new product launches, promotions, or viral social media moments.

6 References

• Google Trends. (2024). Google Trends Tutorials [YouTube series]. Google Search Central. https://developers.google.com/search/blog/2024/09/google-trends-tutorials
• Massicotte, P., & Eddelbuettel, D. (2023). gtrendsR: Perform and Display Google Trends Queries [R package]. https://cran.r-project.org/package=gtrendsR
• Chan, M. (2019). Vignette: Google Trends with the gtrendsR package. https://martinctc.github.io/blog/vignette-google-trends-with-gtrendsr/

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Jimmy Zhenning Xu, Ph.D., AIS Doctor, Principal Consultant | github.com/utjimmyx