Do You Need Local Pages? – Whiteboard Friday

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Posted by Tom.Capper

Does it make sense for you to create local-specific pages on your website? Regardless of whether you own or market a local business, it may make sense to compete for space in the organic SERPs using local pages. Please give a warm welcome to our friend Tom Capper as he shares a 4-point process for determining whether local pages are something you should explore in this week’s Whiteboard Friday!


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Video Transcription

Hello, Moz fans. Welcome to another Whiteboard Friday. I’m Tom Capper. I’m a consultant at Distilled, and today I’m going to be talking to you about whether you need local pages. Just to be clear right off the bat what I’m talking about, I’m not talking about local rankings as we normally think of them, the local map pack results that you see in search results, the Google Maps rankings, that kind of thing.

A 4-step process to deciding whether you need local pages

I’m talking about conventional, 10 blue links rankings but for local pages, and by local pages I mean pages from a national or international business that are location-specific. What are some examples of that? Maybe on Indeed.com they would have a page for jobs in Seattle. Indeed doesn’t have a bricks-and-mortar premises in Seattle, but they do have a page that is about jobs in Seattle.

You might get a similar thing with flower delivery. You might get a similar thing with used cars, all sorts of different verticals. I think it can actually be quite a broadly applicable tactic. There’s a four-step process I’m going to outline for you. The first step is actually not on the board. It’s just doing some keyword research.

1. Know (or discover) your key transactional terms

I haven’t done much on that here because hopefully you’ve already done that. You already know what your key transactional terms are. Because whatever happens you don’t want to end up developing location pages for too many different keyword types because it’s gong to bloat your site, you probably just need to pick one or two key transactional terms that you’re going to make up the local variants of. For this purpose, I’m going to talk through an SEO job board as an example.

2. Categorize your keywords as implicit, explicit, or near me and log their search volumes

We might have “SEO jobs” as our core head term. We then want to figure out what the implicit, explicit, and near me versions of that keyword are and what the different volumes are. In this case, the implicit version is probably just “SEO jobs.” If you search for “SEO jobs” now, like if you open a new tab in your browser, you’re probably going to find that a lot of local orientated results appear because that is an implicitly local term and actually an awful lot of terms are using local data to affect rankings now, which does affect how you should consider your rank tracking, but we’ll get on to that later.

SEO jobs, maybe SEO vacancies, that kind of thing, those are all going to be going into your implicitly local terms bucket. The next bucket is your explicitly local terms. That’s going to be things like SEO jobs in Seattle, SEO jobs in London, and so on. You’re never going to get a complete coverage of different locations. Try to keep it simple.

You’re just trying to get a rough idea here. Lastly you’ve got your near me or nearby terms, and it turns out that for SEO jobs not many people search SEO jobs near me or SEO jobs nearby. This is also going to vary a lot by vertical. I would imagine that if you’re in food delivery or something like that, then that would be huge.

3. Examine the SERPs to see whether local-specific pages are ranking

Now we’ve categorized our keywords. We want to figure out what kind of results are going to do well for what kind of keywords, because obviously if local pages is the answer, then we might want to build some.

In this case, I’m looking at the SERP for “SEO jobs.” This is imaginary. The rankings don’t really look like this. But we’ve got SEO jobs in Seattle from Indeed. That’s an example of a local page, because this is a national business with a location-specific page. Then we’ve got SEO jobs Glassdoor. That’s a national page, because in this case they’re not putting anything on this page that makes it location specific.

Then we’ve got SEO jobs Seattle Times. That’s a local business. The Seattle Times only operates in Seattle. It probably has a bricks-and-mortar location. If you’re going to be pulling a lot of data of this type, maybe from stats or something like that, obviously tracking from the locations that you’re mentioning, where you are mentioning locations, then you’re probably going to want to categorize these at scale rather than going through one at a time.

I’ve drawn up a little flowchart here that you could encapsulate in a Excel formula or something like that. If the location is mentioned in the URL and in the domain, then we know we’ve got a local business. Most of the time it’s just a rule of thumb. If the location is mentioned in the URL but not mentioned in the domain, then we know we’ve got a local page and so on.

4. Compare & decide where to focus your efforts

You can just sort of categorize at scale all the different result types that we’ve got. Then we can start to fill out a chart like this using the rankings. What I’d recommend doing is finding a click-through rate curve that you are happy to use. You could go to somewhere like AdvancedWebRanking.com, download some example click-through rate curves.

Again, this doesn’t have to be super precise. We’re looking to get a proportionate directional indication of what would be useful here. I’ve got Implicit, Explicit, and Near Me keyword groups. I’ve got Local Business, Local Page, and National Page result types. Then I’m just figuring out what the visibility share of all these types is. In my particular example, it turns out that for explicit terms, it could be worth building some local pages.

That’s all. I’d love to hear your thoughts in the comments. Thanks.

Video transcription by Speechpad.com

 

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Glenn has been involved in a wide variety of Internet marketing over the last 20 years. He holds an MBA from the University of North Florida. He lives in Fernandina Beach, Florida with his wife and two children.

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