Are we speaking your language? That’s no accident. We choose our industries with intent—because no competitive advantage rivals experience.
We can’t tell you how often we talk to businesses who want to grow their marketing reach but haven’t invested in customer research. Or maybe they have, they’ve just looked in the wrong places and come up empty. Customer research is hard. It takes time, dedication, and attention to detail—otherwise you may miss important clues or fail to recognize key distinctions.
However, when done well, customer research pays off in more powerful messaging, higher engagement, and an increase in leads and sales.
We’ve spoken before about the importance of researching your audience—and your competition. It’s your best way of understanding their needs, providing the right solutions, and making sure your brand isn’t falling behind the times.
In fact, here are a few blog posts we’ve written, in case you want to read more on the subject:
Customer research is also a critical part of attracting new audiences. If you can find where your audiences go for information, for entertainment, and for trusted guidance, you can more effectively target them in your marketing and advertising.
The only problem is that finding your audience’s circle of influence is tough. That’s why we’re so excited about SparkToro and their new customer research tool.
SparkToro is basically a search engine for audiences. The user interface on this is really straight forward. You simply select from the dropdown what type of search you want to perform, then type in your keyword.
In this case, I picked “linguistics” as a topic I was interested in, and knew enough about to gauge the quality of my results.
This is what SparkToro showed me for my first round of results. The social results they pulled up were clearly on the right track. I was aware of the top results, and smiled to see Ben Zimmer pop up under the “Hidden Gems” category.
The podcasts list was also cool to check out, although the results didn’t seem very accurate. Strong Language & Violent Scenes made the top of most of my linguistics-related searches, even though it appears to be mostly about film. I would have to dig into some of these more carefully to learn more about how these results come up.
Next up I decided to perform a search of audiences that follow the Twitter profile of Gretchen McCulloch, recently of xkcd fame.
The top hashtags to me were really interesting. While the overview only shows so much, digging deeper on this brought up such gems as #twitterstorians, #medievaltwitter, and #womeninstem, among a lot of other political or highly time-sensitive hashtags.
Finally, I did a search for audiences who use the #linguistics hashtag. These brought up similar results to what I’d learned from my first search, although I also noticed this neat measurement:
I’d be interested to see how measurements like “Behavior Similarity” might change for larger groups. For instance, for broadly popular social accounts, my guess is that the behavior similarity would be more heterogeneous. This would be a useful measurement to know how niche you were getting with your research.
Having taken his software for a test drive, my next question was: How does this fit into the customer and competitor research that we already perform at build/create, specifically our CLAs?
One thing that felt very natural to me about using SparkToro was the methodology behind it. When I do competitor research, I’m often performing similar tasks by hand. While it’s somewhat tedious to compile an analysis of a range of competitor websites, looking at each of them in turn gives me insights into how they’re built that a computer algorithm would have a harder time delivering.
This is because websites are more different from each other than twitter accounts. A Twitter account is going to have marked and measurable public-facing data readily available, such as the number of followers and who those followers are. The data points we look for on websites aren’t so neatly marked.
However, because data on social media sites is organized so neatly, SparkToro can go a lot deeper and analyze it a lot faster than I ever could. Trying to compile a list of common hashtags used across social accounts takes more time than you would think. And I don’t think I could ever figure out what percentage of an audience was following other accounts. The fact that this tool can uncover that data opens up a lot of opportunities.
I see this tool being most useful in two places:
After using this tool for a little bit, I have to say, I really like it. Even beyond its obvious marketing applications, it’s a cool way to discover more influencers and resources within a sphere of interest. We probably won’t ever land a client specializing in linguistic research (sigh), but I’ve found a few new people to follow on Twitter and a couple more podcasts to listen to!
And there are obviously some things it can’t do. While it’s fantastic for researching social profiles and potential advertising spots, it’s not designed for some of the in-depth website analyses we perform when we do our CLAs.
At the end of the day, we look forward to testing this tool out further for social advertising and audience research. And it’s just one more reminder that you can’t ever stop looking for new tools to help you do your work better.