Search Insights: Spotting Category Trends and Opportunities

01/11/202101/15/2021

Search data can be a brand marketer’s dream. It’s a near limitless source of consumer insights – behaviors, interests, sentiments and trends. This information can be analyzed from any number of angles; here we focus on category dynamics. Across industries, from automotive to tech to food and beverages to retail, search data can help you monitor category trends, delve into category associations, understand fast-rising topics, or discover geographic patterns. This can inform business decisions large and small, whether it’s a new way to promote a product, or a new product line altogether.

Search captures the interests and intents of millions of people over time, moment by moment—across every topic imaginable. In turn, the breadth and depth of that aggregated data—and its timeliness—make search an incredibly revealing and useful tool for brand marketers to examine what’s happening in their categories. Across industries—from automotive to tech to food and beverages to retail—search data can help you track and affirm existing category dynamics or shed some light on new opportunities you’re considering.

We previously explored search’s reflection of cultural moments and movements. Here we take a look at several applications of search data for category insights: monitoring macro and seasonal trends within a category, examining how a category (or player within a category) is associated with certain attributes, understanding rising searches in a category and discovering geographies with heightened category interest.

Pouring over macro and seasonal trends

Let’s take a look at some search data for the non-alcoholic beverages category. Within seconds, we get a snapshot of the landscape and see how it’s changed over time. We can see that relative search interest in “water” leads the pack, but there’s been a dramatic increase in relative interest for “smoothie” in recent years, with that term rising to prominence over “juice,” “milk” and “soda”—particularly during summertime search peaks.

Indexed Search Query Volume, United States, Non-Alcoholic Beverages Category

When “coffee” and “tea” are layered into the exploration (and “water” and “milk” are removed in order to maintain a five topic comparison), new category dynamics emerge altogether. We see that both search terms have brewed up significantly more search interest relative to the others and in recent years, “coffee” has started to break further away from the pack. Overall, you can see that search interest for these terms dwarfs the others, shedding new perspective on category players and the relative search competition.

Indexed Search Query Volume, United States, Non-Alcoholic Beverages Category

We can also see predictable seasonal patterns in the data, with pronounced December spikes for “coffee” and “tea.” This suggests what you might expect: that the holidays and cold weather drive demand for these types of beverages and related products. You can use this data to inform distribution and advertising decisions. For example, a coffee brand will want to make sure it has enough ad budget to capture search demand at the end of the year. It might also grant holiday-specific promotional offers and advertise against keywords such as “gifts” and “holiday celebrations.”

It’s worth pointing out that most people do not buy these particular beverages online but are turning to search for a variety of non-e-commerce activities. They’re looking for everything from reviews to health benefits to recipes to how-to guides for brewing at home. Across the range of these consumer moments, brand marketers have the chance to control how they play in the category conversation well before someone browses the aisle at the supermarket.

Grounding associations within the category

Delve deeper and you can explore the way in which people are searching within a category—for instance, the words people use together. By exploring how terms are “co-searched,” we start to see how consumers naturally associate certain topics or categories. Looking at “coffee,” we can see whether people are searching this category for specific brands, beans, places to purchase and so on.

Comparing the co-searched terms of “coffee” vs. “tea” for 2013, we see that “tea” is associated more with things such as “recipes,” “diet” and “gourmet,” whereas “coffee” edges out its share of co-searching with things such as “decaf” and “flavors.” Perhaps most interesting, they both are highly co-searched with “calories,” indicating a broader consumer need for this type of information for the category. Explorations like these can help marketers monitor the strength of core associations and related topics for their categories or help them identify new associations that might inspire messaging, content or even new product ideas.

Attribute Interest Share for “Coffee” vs. “Tea”
United States, Non-Alcoholic Beverages Category, 2013

(Each bar in the chart indicates the share of that attribute searched with the selected beverage, out of all the searches of any of the attributes with either of the two selected beverages.)

Seeing what’s on the rise

You can also look for fast-rising topics to spot new opportunities within a category. Back to our coffee example: While coffee maker” and “Starbucks” lead in top related searches over the time period (2004 to present), we can see that weight-loss products, such as green coffee (beans, extract, etc.), are gaining interest, which is consistent with “calorie” co-searches. Also gaining ground are newer brands, such as Keurig, and the iced coffee craze. This information can guide both existing and potential players in the coffee category in terms of new products to develop or how to position existing health benefits. The data might also inform the type of coffee stocked or promoted by restaurants, cafes and grocery retailers.

Rising Searches Related to “Coffee”
United States, Non-Alcoholic Beverages Category, 2004 to Present

Brewing up geographic opportunities

Similarly, a marketer can look into geographic patterns to identify areas of high search intensity. This can inform potential category expansion, place-driven promotions or even product extensions. For example, Seattle has long been a city full of java connoisseurs, coffeehouses and high-end coffee roasters. This fully plays itself out in the geographic search data. A coffee marketer might confirm that the city of Seattle has outpaced others in relative search interest in coffee through the years and then do additional research to dig into Seattle-specific tastes. More interestingly, though, she or he may look to discover other cities and regions with growth potential—those with a higher propensity to search for “coffee”—and then use that data to do some location-based marketing or geo-specific promotional brews.

Indexed Search Query Volume for “Coffee”—Top Cities
United States, Non-Alcoholic Beverages Category, 2004 to Present

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