To take full strategic advantage of local SERP data, you first need to understand all of the ways in which people find stuff locally. Here we put the Armchair Researcher in the hot seat.


The search landscape is becoming ever more localized — and ever more complex as a result. To help unpack this complexity, we compiled seven essential search patterns that show how the majority of users perform local search.

“Building out a likely search scenario helps connect the pattern to the industries it serves, and allows us to better parse out the intent.”

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Since we’ll be discussing patterns rather than personas, it’s important to keep what the searcher does separate from who the searcher is. These patterns are simply seven different search hats that can be worn by anyone, whenever the situation calls for it.

But why do search patterns matter?

Because effective strategies are often built around established behaviours. If you can understand how and why someone finds your business with a local query, you can cater your SERP tracking strategy to the search. And by extension, the searcher.

First up on our list is the search pattern we like to refer to as “the Armchair Researcher.” We’ll give this pattern some real person context, touch on the industries and verticals it impacts, and take a look at the intent and geo-modification behind it.

#1: THE ARMCHAIR RESEARCHER

The Armchair Researcher pattern is an amalgamation of three key factors — a desktop computer, the use of geo-modification, and high local intent.

Local search factors for the armchair researcher
Local search factors for the armchair researcher

Six search factors: Armchair Researcher

Each search pattern is defined a combination of six factors.

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Given these three factors, we can be reasonable Judgy McJudgersons and make a few safe assumptions about the circumstances in which the search is performed. Building out a likely search scenario helps connect the pattern to the industries it serves, and allows us to better parse out the intent behind the query.

The search scenario

This pattern would typically be performed by a user who seeks out a specific activity or item in their area, but requires a lot of information before taking the plunge. Spontaneity would not the name of the game for the Armchair Researcher. A good example of this would be someone looking to buy a high-end road bike in their local area.

The armchair researcher
The armchair researcher

These are not impulsive searches

The Armchair Researcher pattern is characterized by lots of investigation and comparison in advance.

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As our highly imaginative name suggests, the Armchair Researcher is likely to conduct this investigation from the snug comfort of home and their desktop computer.

Of course, this person could also be shirking their responsibilities at work and searching while in the office. They could even be using their smartphone.

However, with the kind of research necessary for such an important, pricey purchase — checking reviews, comparing cost, looking at inventory, finding the right road bike image to Photoshop themselves into — they probably aren’t mobile in either movement or device.

(If, in an unexpected plot twist, this person is ruining their eyes with in-depth mobile phone research, this tracking pattern will also capture the geo-modified search queries performed on devices that don’t have locations services enabled. It’s two wins in one.)

Who should track this pattern?

With the above considerations in mind, we have a good idea who this type of search applies to.

Business, professional, and personal services would benefit from tracking this pattern of search, as would industries that operate on big-ticket items such as real estate, entertainment, automobiles, and appliances.

They are less on-the-fly and impulse-buy-friendly, and more suited to careful planning and research.

Local intent: the new kid on the search block

Your SERP tracking and optimizing strategy should be informed by the intent behind the query, so it’s important to figure out exactly what your searcher has in mind.

The three most common search intents are transactional, informational and navigational in nature and, sounding a lot like a self-actualization chant, are often referred to as Do, Know, Go.

Before local search made it big in the SEO scene, these labels did a fairly decent job categorizing most searches. Now they leave a sizeable piece of the search intent pie either somewhat mislabelled or completely unaccounted for. (Which is poor pie etiquette.)

Enter stage left: visit-in-person intent. Though we prefer to call it local intent because it’s less of a mouthful.

In its most recent (leaked but now legal) Quality Rating Guide, Google carved out this new space of intent to account for “finding coffee shops, gas stations, ATMs, restaurants, etc.” In other words, things or places you’ll, well, visit in person.

Visit-in-person intent
Visit-in-person intent

What is visit-in-person intent?

Different geo-located queries may or may not have local intent behind them. (Source: Google Search Quality Rating Guide.)

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Understanding this newest intent space is essential to creating effective keyword sets within your SERP tracking strategy.

Geo-modification and high local intent

Much like transactional (buyer) intent, local intent comes in high, medium, and low settings depending on how likely the searcher is to actually show up to the thing. Of course, this likelihood is easier to gauge in some local searches than others, and we can never be completely accurate. For our purposes though, close counts in horseshoes and local intent.

“The three most common search intents are transactional, informational and navigational and are often referred to as Do, Know, Go.”

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One factor that helps measure local intent is a geo-modified search query — when the searcher manually includes geographical terms — since it requires an extra step, indicating the importance of the location.

That said, much like everything in the world of SEO, relying on this one factor for a complete picture misses nuance. Sometimes it’s necessary to put on our critical thinking caps, argue semantics, and make a best guess.

Take, for instance, if you are a searcher in our rainy home of Vancouver, Canada (hi!):

  • You wake up in the morning and Google [Kafka]. It signals a Know search and low local intent, and your first result is info on the author Franz Kafka.
  • You revise your search to [Kafka’s]. The local intent raises as you could be referring to — surprise! — Kafka’s Coffee and Tea on Main St., though you could also be searching for something Franz has written. This is where best guessing comes in.
  • Finally, you geo-modify your search to [Kafka’s Vancouver]. The local intent signal is highest as the chances are good you’re looking for a hip cup of coffee.

When it comes to our road-bike-yearning Armchair Researcher, since there’s little semantic ambiguity within the search and desktop computers are increasingly equipped with location services, going the extra geo-modification-mile is a clear signal of high local intent.

We can even place a decent bet on high transactional intent because people who spend a lot of time researching something in a local area are more likely to go to that location, ready to convert.

But wait! There’s more!

For insight into how to employ this search pattern and six others as individual SERP tracking strategies (plus a schwack of other great local tracking info), download the full STAT Guide: Strategies for local SERP tracking.

STAT guide(PDF)

Also stay tuned for an in-depth look at our second search pattern: “the Mobile Time-Killer.”

Want to see just how local STAT can be? Say hello and request a demo!