SparkToro V2 is Finally Here. It Can Do Incredible Things for SEO, Content Marketing, PR, and Ad Targeting.

It’s an exciting, relieving, high-anticipation day for all of us at SparkToro. Today’s launch—which we call “V2″—is the culmination of more than a year of work, including a complete rebuild of the infrastructure and data sources for our product. And though, for many months, Casey, Amanda, and I feared we might lose key pieces of V1’s functionality, the opposite is true…

V2 is, in every respect (including reviews from our beta testers and the customers who’ve switched over), vastly superior. It answers questions we know marketers care about, because you told us. It solves problems we know marketers struggled with, because you complained about them. It provides data we know marketers are hungry for, because you’ve been ordering off-menu for years to try and get it.

You can try the product right now, for free, here. And if you’ve got a SparkToro subscription, you’ll see even more new functionality than during our beta period. Lavall Chichester of Growth Skills summed it up quite nicely in a recent email to us (which he gave me permission to turn into this spiffy graphic):

At its core, SparkToro V2 does things we’ve never seen any other research tool in the marketing universe do. If I had to sum up the three biggest NEW additions, they’d be…

A) V2 shows *who* is searching for particular keywords and details about their online behaviors

Plenty of tools in the digital marketing universe serve a keyword research purpose. But not a single one I know of can tell you more about the searchers themselves. What websites do they visit (beyond just the sites that rank for that keyword)? What social networks do they use? Which accounts and publications do they follow? What are their demographics: gender, age, geography, skills, interests, professions, etc.?

SparkToro V2 answers these questions with data you can visualize, screenshot, export, and apply.

For example, in the screenshot above you can get a quick sense that searches for “data science” are being performed primarily by those looking to learn the practice. Their other searches include terms like “course,” “career,” and “classes.” They’re visiting data science learning sites like Kaggle, Codecademy, and Datacamp.

In seconds we’ve become impressively well-informed about who is behind these searches, and that means we can better craft content, conversion copy, and calls-to-action that appeal to this group. Or, we can rule out this keyword as being a poor match for the goals we want to accomplish (if, for example, we’re selling software to data science teams, this quick glance suggests we’re targeting the wrong group with this term).

B) V2 can tell you which social networks are more/less popular with your particular audience

“Show me which social networks are most popular with my audience!”
– Everyone who uses SparkToro

Over the last 3 years, this has been our most requested bit of data. Folks are hungry to know which networks are more/less popular with their audiences, and finally, with V2, SparkToro can deliver.

Searchers for “data science,” are far more likely to be on LinkedIn, Quora, and Github than the average web user. They’re less likely to be found on Twitter, Instagram, TikTok, and WhatsApp (not shown, but just below the screenshot). This makes intuitive sense, but intuition isn’t always right, and having data to back up your theories and suggested marketing priorities is a godsend.

For aspiring brands and creators, this can help tell you which networks to prioritize or consider, and for advertisers, it can be a helpful signal for investment and expectation-setting.

C) V2 reveals the search keywords, related questions, and trending searches any audience uses

SparkToro’s about audience research: gaining a deep understanding (fast) about any online audience. Historically, we’ve overindexed on data from social networks and the broader web of connections between social profiles, but with V2, we’re adding in significant information about search engine use as well.

The new SparkToro lets you see the keywords any given audience searches for. This is fundamentally different from how other keyword research tools work, as I explain in the video below.

SparkToro V2 isn’t “what searches are ‘related’ to each other?” but instead, literally “what searches are performed by the same group of people?”

We’ve got three kinds of search keyword tabs in V2: High affinity keywords (those that have the most usage/overlap with the searched-for audience), Related questions (the questions extracted from Google’s search results pages for the audience’s keywords), and Trending keywords (pictured below).

I’m especially excited about trending keywords because with these, you can get the jump on competitors who might be exclusively paying attention to the most “relevant” or “highest volume” terms instead of those that are attracting attention in the last 90 days (which is how we calculate “trending” – you can see the volume history for each keyword in the sparkline chart on the right).

Not too shabby, eh?

I’ll walk through the key features, use-cases, and answer questions like “how the heck do you do that?!” below.

SparkToro V2’s Underlying Data Structure

Under the hood of SparkToro V2 are three data sources:

  1. Clickstream panel data from our friends at Datos – the online behavior of millions of real, opt-in mobile and desktop devices, anonymized and aggregated, lets us calculate which sites are popular with particular audiences.
  2. Search ranking and keyword data from our friends at MarketMuse – we aggregate ~100 million English-language search results, updated quarterly. These enable us to build an index of keywords→websites and an inverted index of sites→keywords. MarketMuse’s volume and CPC data are also in SparkToro, giving us the ability to provide sorts, filters, and a Trending Keywords tab.
  3. Profile data from social networks – we’ve moved away from supporting Twitter (for a variety of reasons) and toward LinkedIn, Facebook, YouTube, Reddit, Instagram, and others. LinkedIn is now central to how we show demographics, and long-term we’re hopeful to add Threads and the wider Fediverse once Threads fully integrates with that protocol.

In addition to these, we have large-scale crawls of podcasts that are on iTunes, channels on YouTube, Reddit comments and subreddits, and connections between websites and their associated social profiles that fill out the SparkToro backend.

The results you see for any search are calculated using combinations of these systems. We don’t do any Generative AI to produce results or affinity scores , so you can trust that what you see aren’t just predictions of text based on inputs, but the true results of analyzing an audience.

We do use a bit of ChatGPT to help find related audiences on the query side, but only when an initial search doesn’t produce enough matching profiles. In the future, we might find other applications for genAI to expand on audiences, sources, or data points, but we’re strongly against providing results that are purely predictive text. If you want to know what the amalgamation of a bunch of online copy says, you can go directly to the LLMs themselves. SparkToro is here when you want reliable, provable data about an audience’s real online behaviors and demographics that comes directly from real, aggregated human activity.

The New Affinity Score

In almost every part of the V2 application, you’ll see a column for “affinity.” That score is on a scale from 1 to 100, where 1 means: “this attribute has very little behavioral/demographic overlap with the audience you searched for,” and 100 means: “this attribute has extremely high behavioral/demographic overlap with the audience you searched for.”

We’ve chosen to use relative affinity rather than absolute numbers (like V1’s “percent of audience”) because it enables more consistent numbers for comparison across audiences, more flexibility when attributes have more/less fluctuation, and we can combine multiple groups in an audience (e.g. when absolute percent of audience numbers are used, we can’t reasonably combine two different groups’ percentages without loss of clarity).

In the screenshot above, for example, we can see that /r/Environment is likely to be 50-75% more subscribed-to and visited-by this audience (environmental scientists) than r/NatureIsMetal and r/DataIsBeautiful. The affinity scores in the websites, keywords, YouTube channels, podcasts, social media, and demographics sections all work this way.

Key Features in V2

Beyond just the remarkable types of data you can gather about an audience, V2 has a few other wonderfully useful bells and whistles:

  • Lists – as with V1, you can select any number of rows in SparkToro, create lists, and add them to those. Your Lists are tied to your account, and any items you save to them will be exportable and manageable inside the Lists tab.
  • Contact Info – When you add websites, social accounts, podcasts, and/or YouTube Channels to a List in V2, we’ll automatically fetch contact information via our partnership with These include email addresses (when available) and social media accounts as well.
  • Advanced Search – Want to search for environmental scientists but not those who have oil/gas in their bios? The magic of the advanced search tab can do exactly that. Just build your query (similar to a Google Advanced Search) and run it to get results.
  • Custom Audiences – I’m truly proud of this one, or rather, truly proud of Casey for re-engineering custom audiences to support lists of websites and keywords (or a mix of the two). Upload a CSV (of at least 50 keywords/websites) and we’ll analyze them as an audience. I generally recommend more (we can support thousands, so feel free to export directly from Google Search Console, GA, or your ads account), but have seen solid results with even the minimums.
  • Exports – any search you run can be exported easily into CSV format so you can build charts, graphs, presentations, or transform/modify the data to your heart’s content.

We’re still in the process of rebuilding the “comparison” feature from V1, but hope to have that out in the months ahead, and overhauled in a far more friendly, useful, and screenshot-able way.

Early FAQs

What’s happening to the old V1?

If you’re a SparkToro subscriber at the personal/basic plan level, you’ll have access to the old V1 of SparkToro for the next 30 days. After that, it will be retired and only V2 will be accessible. If you’ve got a higher tier plan (Professional/Agency), we’ll keep V1 available for a longer duration (at least 90 days, and possibly more if folks need continuing access). If you’ve got questions or need more access to the old version, drop a line to [email protected].

What should I do if I see V2 results that don’t make sense?

Sometimes, affinities between audiences and behaviors can seem strange or even like errors. Usually, that’s not the case. Remember that even carefully chosen audiences are human beings, too. They do things on the web we might not expect, and those random affinities (data scientists following cute penguin accounts on Instagram, B2B marketers having affinities for search keywords around Scottish whiskies, or visitors to a weightlifting forum listening to video game podcasts) might be surprising, but aren’t incorrect!

As an example, above, SaaS retention specialists seem to be searching for PDF and other filetype converters a good bit more last quarter. That might not feel particularly relevant to their jobs, nor especially useful for a content marketer’s targeting (though perhaps someone in that field would have applications I haven’t thought about!), but it’s not incorrect data. My advice would be to keep scrolling and find the trending terms that are relevant (e.g. “captive product pricing” is a little further down the list and probably a terrific bit of insight for a content creator, SEO, or PPC marketer targeting this audience).

NOTE: One issue we are aware of, but don’t yet have a solution for is when homonyms (words that are spelled the same but have different meanings) overlap. Our system looks for matches based on the words and phrases you enter, so using variations, different terms, websites, or uploading a custom audience can be a workaround.

If you see surprising, unexpected, or irrelevant results in a SparkToro V2 tab, and you’re convinced it’s not just overlapping interests but a true error or incorrect bit of data, please drop us a line: [email protected].

Where can I send feature requests?

We love these! You can send to me ([email protected]) or drop us all a line: [email protected].

Do you offer educational/nonprofit pricing?

We do. Contact us via [email protected] and we can share the details (we’ll just ask for proof of your nonprofit or educational status).

What’s Next for SparkToro

We’ve got a handful of improvements and new data coming soon to the product. With this launch, we can finally start adding features we’ve long wanted to include, and Casey’s pretty excited to roll out a few new data points and functionality bits over the next few weeks.

Amanda, Rand, and Casey at a 2023 planning meeting for SparkToro V2

After that, our goal is to eventually provide audience tracking again: the ability to tell the software that you care about the weekly/monthly changes an audience exhibits in behaviors and demographic composition, and we can automatically update you as that happen and keep a historical record of the past, too. We believe this is invaluable, especially for website owners who want to know more about what their visitors are doing on the rest of the web. Stay tuned!