Google has announced that it will shut down Correlate on December 15th 2019 due to low usage. Be sure to get your data while you can! I’ll leave this post up because I think the approach is useful – even if you have to “hack” new tools (like Trends & Ahrefs) to get similar-ish data that Google Correlate provides.
Since it’s launch it has received some buzz and become a useful tool among academics, but it’s never become a part of the standard toolset among marketers the way Google Trends has.
There are a lot of reasons for that. Google hasn’t publicized Correlate the way it has the general Trends toolset. Correlate even has features that sporadically break. But I think the slow adoption is because marketers don’t realize the potential of Google Correlate – or even how it works.
According to Google, it is –
a tool on Google Trends which enables you to find queries with a similar pattern to a target data series. The target can either be a real-world trend that you provide (e.g., a data set of event counts over time) or a query that you enter.
In other words, the pattern generates the keywords rather than the keywords generating the pattern. So you do have to think in reverse.
Before we go into specific use cases for Google Correlate – a couple notes on caveats.
First, Google Correlate does not pull absolute search volume. Just like Trends, it is based on the share of total volume. All terms are relative to each other. You still need to use Keyword Planner or another keyword research tool to find search volume.
Second, correlation does not equal causation. Just because terms correlate with each other does not mean they share a causal relationship. There’s a lot of noise in the Correlate data, but plenty of hidden gems too. You’ll have to use your best judgment.
Here are five ways to use Google Correlate and integrate it into your marketing research toolset.
Market & Persona Research
In Google Correlate, you can find correlations across time AND space. If you trying to define your target personas for a new product or service, you can use each correlation to get deep insights about your audience.
First – finding audience correlations across space.
Sounds generic and boring, right?
What if I told you that you could find out what US State to start rolling your product out with Google Correlate? That’s what the Compare US States feature is for.
Imagine you are trying to roll out a new Pu-erh tea brand. You want to focus your marketing efforts on a geographic area.
Put Pu-erh tea into Google Correlate. Select the term that you think most aligns with it (chinese herbal in this case), and Google Correlate will show what states most closely correlate with those interests.
Today you learned that Washington state has an outsized interest in Pu-erh Tea and Chinese herbals and that New Mexico looks like a very interesting test market as well.
Imagine you have a gardening blog and are writing about tomatoes. You need to know how to best customize growing directions. Head to Google Correlate and search “grow tomatoes” select a complementary term such as “how to grow tomatoes” and check the map.
You just learned that the southern Plains and western Southeast correlate most closely for growing tomatoes.
Second, from those same searches, you can use the correlations for a window into your personas.
Look at the tomatoes search again –
Note how highly the terms “Mid size truck,” “online homeschool,” “prophecy,” “lyrics amazing grace” all correlate with “grow tomatoes.”
Those terms alone can define a highly specific reader persona. If you can’t figure out the audience for your gardening website, it’s probably someone who drives a mid size pickup truck, lives in Oklahoma, homeschool’s her kids, is a Baptist Christian, and reads books like Left Behind. She has plenty of land, sun, and water for growing tomatoes, has a DIY streak, and is conservative politically.
Now you know who you are writing for.
For your Pu-erh tea startup, let’s look at it again –
Alright, so your target persona is someone who lives in the Western US. He loves Anthony Bourdain, high-end photography, and experimenting with new tea brands. He is into astrology and all aspects of traditional Eastern thought. He’s very left-leaning politically and a bit conspiratorial. He also likes organic certification on all products from soaps to teas.
Once you know your personas, you’re approach to research should change. For example, if a persona is tied to a geographic region, then you should do your keyword research based on geography. For a midwestern client, I’d use a VPN (CyberGhost or ExpressVPN) to switch up my location for Google to get better / subtly different autosuggestions.
Don’t guess at personas and market research. Use Google Correlate.
Content Strategy & Buyer Journey Mapping
“Buyer Journey Mapping” is marketing jargon for “people do research before they buy.” In the traditional marketing funnel, customers become aware of your product, they move to interested, then to desire then to action. At each stage, they have different questions and concerns.
Marketing campaigns and content strategies are generally built around one or a sequence of stages. If you want to target customers in the “interested” phase, then you’ll create content that focuses on how to use a product. If you are targeting customers in the “desire: phase, then you’ll create comparison or get-a-deal type content.
Either way, the goal is to always be there as customers are moving down the funnel. If you’re there from the time they become aware through interest and desire, then you’ll be the one they buy from.
Google’s Correlate Time Series shift is a perfect fit for this type of research. It works best for seasonal companies. However, any business can use it provided you have some sort of time cycle or event.
The simplest example is a costume store. People buy costumes a little before Halloween. What type of content could you publish to get in front of people in the weeks leading up to Halloween?
To do that we’ll shift the time series back by 1 week.
And let’s go 1 month.
If I were a Halloween retailer, I would invest in evergreen content around local festivals and helping plan parties & crafts. Both allow you to get in front of customers and place a retargeting pixel on their browser a few weeks before the sudden rush to buy costumes.
Note that Google Correlate’s data is very sparse. You have to look at it as a whole to create content ideas that make sense.
For industries that aren’t seasonal – you’re not out of luck. You just have to focus on industry events or anything in your industry that might have a time window.
Once you have that “hook,” it’s just a matter of cycling through time series to find ideas.
Suppose you are a phone retailer. People may buy phones in December or September more than other months, but the business has demand throughout the year.
To create a content strategy or a buyer journey map, you have to pick a term that would have a definite pattern that is related to your business.
Let’s look at iPhone 6. It launched and had a lot of buzz at a specific point in time.
The week of launch has the highest correlation have plenty of “bottom of funnel” ideas. You need to have plenty of content on specific questions.
But let’s shift back 2 weeks.
Now, this type of data is very interesting. You could use this for content strategy or for timing a retargeting campaign.
Promote content around simple ways to replace your iPhone 5 battery, then run retargeting on that audience for 2 weeks later to buy an iPhone 6.
You can also shift the time series forward to get ideas on upsells or content to retarget to purchasers of your product.
There’s noise, but still plenty of opportunity with the right hooks in Google Correlate.
General Keyword Research
Keyword research is foundational to search engine optimization. But it’s also gotten more difficult in the past few years with the shift to (not provided) keywords, the shift to Keyword Planner and the death of Google Autosuggest API.
The best keyword researchers I’ve seen do a couple things differently than others in the industry.
First, they generate a ridiculously huge list of potentially useful keywords to curate.
Second, they research laterally, digging into topics and platforms that are related to but not exactly similar to the set of common sense target keywords.
Both techniques lead to finding high volume, high-quality keywords to target while also providing an angle of attack so that you aren’t competing head to head against the Amazons and Wikipedias of the world.
Google Correlate helps on both.
First, Google Correlate generates lists that correlate with your target keyword by default. It won’t generate hundreds and hundreds that you can copy and paste. But, it does offer a CSV export.
What I like to do is to take my initial “seed” keyword list, and run several through Google Correlate to see what it generates. I’ll export all the keywords and combine it with other sources like Reddit, Wikipedia, and others to get a giant list to edit down.
Second, Google Correlate generates lists that, obviously, correlate. By definition, these are terms that have the same search trends as your target keyword but are different.
It’s very useful in industries that you aren’t very familiar with. Again, enter your known target keyword into Google Correlate and see what shares a pattern.
Instead of exporting them right off though, look through the terms that complement or share some relation to your target keyword.
There will be a lot of noise, but also lots of hidden gems that you would have never found otherwise.
These are the type of suggestions you’re looking for in keyword research. Productivity tip – there’s a link to Google Search by each term.
If you’re the type of SEO to go beyond just keyword planner, start using Google Correlate in your research.
Find Trending Topics
If you are trying to develop content around a trending topic, Google Correlate can provide great insight, especially since you can “teach” it to give you the exact type of trending topic.
First, you need to define a trending pattern, so a pattern that goes rapidly up and to the right in a short timeframe.
Second, you upload your own data or upload a drawing for a custom made pattern, and let Google find keywords that match that correlation.
This will show terms that had a rapid rise, a plateau, then a surge of new interest. You’ll get some noise, but all the terms that you see will have the same trending growth pattern.
Other Complementary Uses
Google Correlate also makes a great complement to other tools. You can use it to make informed decisions on everything from PR outreach to cross-sells in your online store.
For example, take the ideas from the marketing funnel earlier. A lot of PR outreach has to do with planning and timing. You’re not going to get a Christmas PR placement if you do outreach in December. You can, however, use Google Trends and Google Correlate together to pinpoint how interest moves through the year.
For cross selling products, use Google Correlate to see what products have the same search patterns as your main product. Factor those into your recommendation engine.
As a corollary to persona research, you can use Google Correlate for competitive analysis. Search for big brands or competitors and see what terms align with those branded searches.
Lastly, keep in mind that you can customize and search based on a single time series to get cleaner or different data. For example, search IKEA correlations only in the Fall:
Google Correlate is an incredibly powerful tool. It’s counter-intuitive to use, but can be as useful as more well-known tools like Google Trends or Google Autosuggest.
The best way to learn to use it is to go use it and play around with it.
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