Whitepaper: SERP Features

How Distance & Intent
Shape a Local Pack

Contents
The case for tracking local								4Defining geo-modification & geo-location					

5Methodology										

6High-level findings									

7How google interprets local intent 						

8The influence of geo-modification & geo-location 		10

Local packs								

10Organic results								

12Ranking factors									

13Distance from the searcher 						

13Google rating
Organic ranking								        14Advertising15        16How google handles competing needs 				

17Quality 									

17Affordability
Brand									        18Key takeaways & next steps						

19
20How Distance & Intent Shape a Local Pack

When every SERP is a local
SERP, understanding what
Google’s top priorities are isessential — which is why we’reunpacking the local pack.
In August 2017, a Think With Google piecestated that local searches without “near me”
had grown by 150 percent and that searchers
were beginning to drop other geo-modifiers —like zip code and neighbourhood — from theirlocal queries altogether.
Since we can’t always rely on a searcher tostate when their intent is local, we should
be looking at keywords where that intent is
implied. But, before we start optimizing, weneed to know whether Google is any goodat interpreting implicit local intent. And if it’streated the same as explicit intent.

Consider these queries: [sushi near me] would
indicate that close proximity is essential; and[sushi in Vancouver] seems to cast a citywide net; while [sushi] is largely ambiguous— hungry for general info or actual sushi? And
what happens with [best sushi], where quality
could take priority over proximity?
Google’s deciding what these queries mean, so
it’s importantto understand that decision. In this study,
we put local packs under the microscope todetermine how Google handles different kindsof local intent and what elements go into
shaping this local SERP mainstay.

In this study, we put
local packs underthe microscope todetermine how Google
handles different kindsof local intent.

3How Distance & Intent Shape a Local Pack

The case for local tracking

other major search engine routinely modify
search results based on location.

In some industries, the importance of local
SEO and local SERP tracking is immediately
obvious. These are typically products orservices that are inherently tied to location:
things like brick-and-mortar retail, real estate,
professional services, automobiles and heavyequipment, restaurants and hospitality, andso on.

Since every SERP is now a local SERP, every
business must pay attention to localized
search results. Even if you ship globally, only
sell digital goods, or are trying to attract new
app users, poor performance on critical, highvolume local SERPs will still result in lost trafficand lost conversions.

But what about businesses that are not as
closely associated with in-person encounters?

We just can’t keep denying localization as animportant factor — if not the most importantfactor — that Google filters its search results
through.

Not long ago, we could expect that tracking a“United States” SERP would give an accurate
depiction of what a searcher would see,regardless of where in the country they were.
This is no longer the case. Google and every

4How Distance & Intent Shape a Local Pack

Defining geo-modification& geo-location
For every individual search, there are two
distinct factors that determine whether andhow the search results are localized.
• Geo-modification is when the searcher
manually includes geographical terms in the
search query itself — for example,
in the search [best beaches in NSW Australia].
(Google calls
this “explicit location.”)• Geo-location is when the searcher’s device
automatically provides location data as a partof the search query — for example, in the
search [best beaches] when performed within
Sydney on a smartphone. (Google calls this“user location.”)Geo-location is essentially synonymouswith “location services.” The search provider
leverages data supplied by the device —including data related to GPS, cell towers,
Wi-Fi nodes, and IP address — to help serve
up relevant, local information without the user
having to manually modify their search. Just
about every device type employs this, whether
it’s a smartphone, tablet, laptop, or desktop
computer.
Because geo-location happens automaticallywhen location services are active, with nodirect intervention by the user, it is not byitself a strong signal of a searcher’s desire to
visit a physical location. Geo-modification, on
the other hand, is usually a very strong signalof a searcher’s local intent.

5How Distance & Intent Shape a Local Pack

The Methodology
So, when searchers aren’t being obvious about
their local intent, does Google still know what
they’re after? And does Google understand thedifferent kinds of local intent, or does it have a
one-size-fits-all approach?
To answer these pressing questions, we needed
to create a highly segmented keyword list andimplement one heck of a tracking strategy.
Creating a keyword list
First, we needed to create our “base” keywords.
These are non-geo-modified terms with implied
local intent and were pulled from 19 industries
and verticals that would require an in-person
visit.
We built out our base keywords in threesteps. Step one used the root industry term
as a keyword, like [restaurant], [mechanic],
and [nail salon]. Step two involved duplicating
those and adding, when appropriate, all kindsof related adjectives: [Chinese restaurant],[auto mechanic], [acrylic nail salon]. Step
three doubled that list and layered in various
qualifiers, which gave us [best Chinese
restaurant], [Porsche auto mechanic], and[affordable acrylic nail salon]. Altogether we
had over 100,000 non-geo-modified keywords.

With the base keywords in place, it was finallytime to geo-modify so we could see how
Google deals with two different types of statedlocal intent: near and far. We took our basekeywords and stuck “near me,” “in Portland,”and “in New York,” on each of them, giving us
keywords like [restaurant near me], [Porsche
auto mechanic in New York], and [acrylic nailsalon in Portland].
Implementing a tracking strategy
We then took all those keywords, stuffed theminto STAT, and tracked them in two different
zip codes within both New York and Portland.
We used two zip codes so we could measure
what a searcher might see depending on
where they’re standing within a city, and weused two cities because we wanted to confirm
trends and understand any weird outliers inour data.
Device-wise, we went 30 percent desktop
and 70 percent smartphone since Google ispushing mobile-first indexing and because we
expect most people who look for hyper-local
info do it from their phone.
When all was said and done, we’d tracked
just over 1.2 million keywords.

6

How Distance & Intent Shape a Local Pack

High-level findings
Looking at our 1.2 million SERPs, we saw that73 percent returned a local pack. This meansthat they’re a huge opportunity for exposure if
you’re a brick-and-mortar business and a big,
SERP-hogging annoyance if you’re not.
Then, we segmented our SERPs by locationand geo-modifier to see whether they affectthe appearance of a pack. Of our threeintent groups, “near me” surfaced the highest
percentage of local packs — almost every
keyword produced one. This is on par withwhat we’d expect. The query is clearly asking
for local results and Google is able to deliver
the goods.

Local pack appearance

100%

96%
96%

Surprisingly, our “in [city]” queries didn’t
produce a local pack as reliably as our “nearme” ones. The intent is also explicitly local
with these, so we expected behaviour that’s
a little more similar.
When it comes to our non-geo-modified
keywords, Google may be telling us thatthey have local intent, but it’s not willing togo all-in with that assumption each time.
This was the worst local pack performerof the group — showing up just over half
the time in New York and only 37 percentof the time in Portland. We wouldn’t be
surprised to see numbers grow for thiskeyword set, but in the meantime, Google
is still hedging its bets.

95%
79%

78%

75%
52%

50%

37%
25%

"near me"Base"in [city]"
New York"near me"Base"in [city]"
Portland7

How Distance & Intent Shape a Local Pack

How Google interprets
local intent
Next, it was time to interrogate whether,and how well, Google can understand theindividual asks behind our three different
keyword segments. Can it distinguish between“near me” and far away local intent, and where
does it put implied local intent on the map? To
do this, we had to get a little creative.
After a few different kicks at the can, we
settled on measuring the distance between
the centre point of the local pack map and thecentre point of each city’s zip code. We chosethe middle of the map because Google centres
its cluster of result pins around it, and we went
with the middle of the zip code because that’s
where our searcher happens to be standing.
The theory being: the closer the searcher is tothe centre of all the action, the more hyperlocal the results are.

Can Google distinguishbetween “near me” andfar away local intent,
and where does it put
implied local intent on
the map?

8

How Distance & Intent Shape a Local Pack

As we would hope, the zip code and map
centre points were closest together on our“near me” SERPs. This means that Google
knows the searcher is looking for nearby
businesses and surfaces results that fit the bill.
Our “in [city]” SERPs returned the largest
distances, which put their local pack results
further away from the searcher. Google
recognizes that by setting a city-wideboundary, the searcher is welcoming resultsfrom further away. Good job, Google.
When it comes to our implicitly local keywords,
Google produced businesses that were further
away from the searcher than with our “nearme” intent, putting them closer to the “in [city]”
results. To us, this is more evidence of Google’s
uncertainty in handling these keywords. Not
only will Google surface less local packs when
the intent is questionable, when they do makean appearance, Google will assume that the
searcher’s need isn’t immediate.

Google knows thesearcher is looking fornearby businesses andsurfaces results that
fit the bill.

3

2.81

Distance in miles

2.41
2

1.78
1.37
0.99

1
0.62

"near me"Base "in [city]"
New York"near me"Base "in [city]"
Portland9

How Distance & Intent Shape a Local Pack

The influence of
geo-modification &geo-location
Finally, it was time to investigate just how
much geo-modification and geo-location
change a local pack. Is Google putting more
stock in what the searcher’s asking for orwhere they happen to be standing? And how
do these two factors work together?
We already know that Google responds todifferent geo-modifiers accordingly, and thatthe appearance of a local pack can dependon the geo-modifier used, but understanding
this relationship will help us determine which
geo-modifiers we want to use and why. It will
also give us a sense of how many locations ina city we may want to track and where theyshould be.

Local packs
Getting to the bottom of all this involved a lotof slicing, dicing, and side-by-side comparing.
Geo-modification
To measure just the effect of geomodification, we compared local packs where
the location is the same but a different
geo-modifier is used with each search. For
example, let’s say that two roommates arechillin’ on their couch, hunting for a cheapnight out in New York City.

One roommate’s looking for the closest venue,[cheap night clubs near me], and the other wants
to see what the whole city has to offer, [cheapnight clubs in New York] — how different will
their local pack results be? Turns out they’ll see
near-identical results, as geo-modifiers alone
don’t create overly unique local packs.
“near me” vs. “in [city]”“near me” vs. base“in [city]” vs. base		

81.02% similar

80.84% similar

77.99% similar

We found that geo-modification changed our
local pack results by roughly 20 percent, which,while not an insignificant amount, is certainly
less than we anticipated. And since the level of
local pack similarity is fairly steady across theboard, we can say that no one modifier has more
influence than the others.

10How Distance & Intent Shape a Local Pack

Geo-location
Next, it was time to layer in the location of thesearcher to see how much of an impact it has
on a local pack. Does it diversify the results
or are only a few businesses making it inregardless of modifier and location?
This involved comparing local packs fromdifferent zip codes where the same query wasused. In this case, our roomies are across town
from each other, looking for a cost-effective
night out close to their respective locations,[cheap night clubs near me], in the hopes ofluring the other out their way — are they stillgoing to see the same results?

“near me”
zip 1 vs. zip 2

Base
zip 1 vs. zip 2“in [city]”zip 1 vs. zip 2

26.17% similar        49.36% similar         63.66% similar

That said, location didn’t affect our geomodifiers equally. Results are more unique,and therefore more localised, the closer in ourquery is searching (“near me”) and less uniquethe further out its searching (“in [city]”).
Essentially, if you’re on one side of the city anda friend is on the other and you both search[sushi places near me], your local packs will
return substantially different results. However,
if you both decide to only search [sushi places]from your respective zip codes, suddenly, itmatters a little less to your local pack how far
apart you are. And, if you’re performing a citywide search for sushi places, well, you’re closer
to standing right next to each other like theparty-people in our first example.
Putting it all together
Our findings here indicate that the searcher’slocation is the starting point that Google uses
to select eligible local packlistings. The intent of the query thendetermines how far away
the businesses are that Google will choose
from. Essentially,
local packs prioritize where the searcher isbefore considering what they’re asking for.

Here, we found much less similarity, telling usthat the location of the searcher has a huge
influence on local packs — way more than geomodification does.

As such, if you’re in the local SEO game,
tracking multiple locations within a city is likely
a good strategy — if only at the beginningto see how far your reach is. Geo-modifiers
obviously still play an important role here, but
you can afford to be a bit choosier with them.

11How Distance & Intent Shape a Local Pack

Organic results

Geo-location

Even though this study is all about that local
pack, we’d be remis not to take a quick peekat the organic results that appear below it. We
just can’t trust Google to treat all result types
equally.
In order to measure the influence of geomodification and geo-location on organic
results, we did the same kind ofside-by-side comparing as before.
Geo-modification
Looking at the effect of geo-modification in
isolation (when our searcher’s in the same spotusing different geo-modifiers), we didn’t see
near as much duplication as we did for local
packs, which were roughly 80 percent similar.
“near me” vs. “in [city]”“near me” vs. base“in [city]” vs. base 		

32.18% similar           39.77% similar       19.29% similar

In this case, geo-modification was responsible
for changing our results by anywhere from
60–80 percent, which is huge. This tells us that
Google considers our three local intent queries
to be highly distinct searches. Our “near me”
and base keywords had the most in common
with just 40 percent overlap.

When it comes to how much a searcher’slocation can change up organic results (whenthe same geo-modifier is searched in two
different locations), we saw way more overlap.
“near me”
zip 1 vs. zip 2

Base
zip 1 vs. zip 2“in[city]”zip 1 vs. zip 2

75.22% similar         80.07% similar         81.32% similar

Again, this is the opposite of what happens
with local packs, where the similarity ranged
from only 26–64 percent. This reveals that thelocation of the searcher isn’t having as huge ofan impact on organic results as we may haveinitially thought, which mirrors what Darren
Shaw from Whitespark found in his February
2017 study.
Putting it all together
When it comes to organic results, Google
cares more about what the searcher is asking
for than where they’re searching from. So,
if tracking in multiple locations in each city
is out of the question for you, our findings
here indicate that you can get a fairly decent
picture of organic results by tracking in lesslocations, but diversifying the geo-modifiers
you optimize for.

12How Distance & Intent Shape a Local Pack

Ranking factors
With a firm understanding of how Google
handles things on the searcher’s end — theirlocation and local intent — the time was rightto dig into how it handles things on yourend. We looked at a few factors that help
determine how you place in a local pack.
Distance from the searcher
Using the distance away from the searcherthat Google (sometimes) serves at the end of a
local pack result, we found a clear trend of thefirst business in the local pack being closest
to the searcher, the second being further
away, and the third being the furthest. On thesurface, it might seem that your position in thepack is entirely based on how close a searcher
is to you, but we discovered that density plays
an interesting role.
Breaking things down by location, we saw that
Portland followed this overarching trend. New
York, on the other hand, showed us somethingelse: that the first local pack result can be as

far away as the third. What’s likely happening
here, is that because New York has way moreof everything, Google can prioritise a better
place that may be further away over a worse
place that happens to be closer. So, scoring
the top spot in a local pack doesn’t necessarily
depend on the luck of close proximity if you’rein a more dense area.
Aside from “good to know,” how do you makeuse of information that’s dependent on thelocation of a searcher, especially when you
never know where they are? Well, you doknow where your bricks and mortar sit and,as we’ve shown, you can find roughly how far
your keywords’ local packs are reaching. In
other words, you can make yourself the centreof Google’s universe and work outward.
For example, we found that the most common
distance away from a searcher that our queries
returned was 0.3 miles in New York and 0.7
miles in Portland. So, if we’re a business ineither of those areas, we’d look for competitorsthat fall within that radius and do a little
reconnaissance.

13

How Distance & Intent Shape a Local Pack

Google ranking
After a top-level analysis, we found that thefirst result in a local pack typically has a higher
Google rating than the second, with the third
receiving the lowest overall. But these were
only slight differences, telling us, at most, thathaving the highest rating has a decent chanceof landing you a first place spot. Things got
interesting when we segmented our ratings by
local intent.
It turns out our “near me” keywords returned
the lowest local pack ratings of the group.
When dealing with hyper-local requests,
Google seems to satisfy the location-need,delivering results that are closest but notnecessarily best.

On the other end of the spectrum was our“in [city]” queries, which raked in the highest
ratings. Thanks to the query’s wider reach,
Google is free to go further to get higherrated businesses, allowing the best rise to
the top.
Putting everything together, it appears that
Google first considers the distance requestedby the searcher when compiling its results,
and then layers in rating info. So, while a highGoogle rating is important, you have a little
leeway depending on which keywords you
optimize for.

14How Distance & Intent Shape a Local Pack

Organic ranking
Curious as to whether your organic rank makes
any difference to how you wind up in a local
pack, we were a little surprised by the results.
We found that only eight percent of our local
pack results had a website that searchers could
access from the SERP itself. One reason forsuch a low number is that not every businessthat appears in a local pack has a website. The
second, likely more prevalent reason is that
Google wants to keep searchers on its stuff,
not your stuff. To do this, it will frequently hidea website in the Google My Business listing,forcing searchers to click a result in the local
pack to find your website link. Foot traffic
aside, this raises some questions around how
much web traffic a local pack is good for.
Of that eight percent, only 12 percent had
an organic rank in the top 20. So, getting a
top 20 rank isn’t essential to appearing in
the pack. That said, the most common rank
positions that local packs pulled from wereon the first page and varied slightly by intent.
Our “near me” and base local pack results were
found most often in the fourth spot — directly
underneath the local pack — while “in [city]”
results were typically in rank seven.

Percent of local packs"near me"Base"in [city]"

0.2%

0.1%

0%

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

Rank

15

How Distance & Intent Shape a Local Pack

Advertising

Here, as we’ve seen time and time before,
different local intents exert different levels of
influence. Our “near me” local packs returned
the most ads, followed by “in [city],” and ourbase keywords brought in the least at sevenpercent. In other words, you’re more likely
to see ads in a local pack by geo-modifying
your queries, and you’re less likely to be
shoved out of a pack by an ad on a non-geomodified SERP.

100%

Percent of local packs

Lastly, we took a quick peek at the top
spot you buy instead of earn. And, for now
anyway, it seems that most local packs
aren’t subject to betting games — ad listings
showed up in only 16 percent of them.

75%

50%

25%

26%

19%
7%

0%

"near me"Base"in [city]"

You’re more likely to
see ads in a local packby geo-modifying
your queries.

16How Distance & Intent Shape a Local Pack

How Google handles
competing needs“recommended,” “excellent,” “expert,” “trusted,”“professional,” “highly-rated,” “five star,” and“#1”).

Our final look at local packs involved a subset
of keywords with modifiers whose needs might
compete with location — in other words, iswhat they’re asking for more important thanlocation? For example, when you’re looking
for the [best dentist near me] are you actually
willing to go as far as necessary to get the
top tooth doc, or are you willing to settle for
whoever’s the best of the closest bunch? And
what’s Google going to serve up?
We looked at modifiers that fell into threedifferent topics: quality, affordability, andbrand.

Originally, we expected to see only a few
places being chosen as the best in the city (highsimilarity), but Google seems to think there
are lots of bests, regardless of where you’researching from.
“near me”
zip 1 vs. zip 2

Base
zip 1 vs. zip 2“in [city]”zip 1 vs. zip 2

Quality
keywords

24.17%
similar47.61%
similar61.50%
similarOther
keywords

26.79%
similar50.37%
similar64.69%
similarSince the differences were small, to confirm
that these modifiers were actually having an
impact on our search results, we also looked atthem from a ratings perspective. We found that
quality-modified keywords returned higher-rated
items in the places pack. We also discovered thatthe average number of ratings those businesses
received was slightly higher than our non-quality
group, suggesting you may need more ratings to
be considered a “best” business.

Quality
When people think of the best anything intheir city, it’s typically a smaller, independent
shop — it’s rarely a large national chain serving
the best grub around. This would explain
why we saw more variation in local packresults from zip code to zip code when quality
modifiers were added (terms like “best,” “good,”

Percent of local packs

Quality keywords

Other keywords

16%
12%
8%
4%
0%

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

2.8

3

3.2

3.4

3.6

3.8

4

4.2

4.4

4.6

4.8

5

Google rating

17

How Distance & Intent Shape a Local Packin the local pack were further away for these
keywords — they had results sitting 1.20 miles
away, while all others were at 1.17 miles. This
helped confirm that Google is struggling to finda nearby affordable option and has to widen
the net.

Affordability
When looking at keywords concerned withpricing, we saw more local pack overlap
from location to location across our intent
segments. This is the exact opposite of what
our quality modified keywords revealed andtells us that there are fewer businesses that
Google feels it can put in this category.

Unsurprisingly, we also found that businesses
that appear in a local pack for price-related
queries had consistently lower ratings.

“near me”
zip 1 vs. zip 2

Base
zip 1 vs. zip 2“in [city]”zip 1 vs. zip 2

Affordability
keywords

27.16%
similar50.76%
similar65.49%
similarOther
keywords

25.97%
similar49.15%
similar63.29%
similarSo, if we’re a business that sells itself onaffordability, we now know that competition
is a little less fierce and ratings aren’t asimportant for these types of keywords(which, for us, included terms like “cheap,”“inexpensive,” “budget,” “deals,” “discount,”“free,” “sale,” “affordable,” and “subsidized”).

Again, though, these were small differences, so
we looked to the median distance away fromthe searcher. There we saw that businesses

Percent of local packs

Aﬀordability keywords

Other keywords

18%
14%
9%
5%
0%

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

2.8

3

3.2

3.4

3.6

3.8

4

4.2

4.4

4.6

4.8

5

Google rating

18

How Distance & Intent Shape a Local Pack

Brand
Lastly, we took a peek at brand modifiers.
These included “Ford,” “Mazda,” “Hyundai,”“Honda,” “BMW,” “Mercedes,” “iPhone,” “Sony,”“Samsung,” “Pixel,” “Apple,” and “Blackberry.”

We also saw a large increase in the median
distance from the searcher, which means thatthese results were much further away than for
non-branded terms.

First, we saw a large increase in the amountof similarity that local packs had from one zip
code to the next.

This stands to reason, since the places thatare triggered by a brand keyword are likely
extremely specific. Think of how many
Porsche-only mechanics you might find in agiven city compared to the number of everycar mechanics. Google is giving these branded
terms a definitive weight, so if you aren’t
already segmenting and optimizing for them,
you should.

“near me”
zip 1 vs. zip 2

Base
zip 1 vs. zip 2“in [city]”zip 1 vs. zip 2

Brand
keywords

45.57%
similar62.65%
similar72.64%
similarOther
keywords

23.34%
similar47.62%
similar62.22%
similar

1.8

1.77

1.35

Miles

1.17

0.9

0.45

0

Brand keywords

Other keywords

19

How Distance & Intent Shape a Local Pack

Key takeaways & next steps
If you’re looking for the TL;DR or a quick recapof what you just read, we’ve got you covered:

1. Choose your favorite Geo-modifiers
We went with “near me” and “in [city],” but you
don’t have to. How about:• Every SERP is a local SERP.

• near by• downtown• An increase in search terms without geomodifiers doesn't equal a decrease ingeo-modifier use — searchers still use themand Google still interprets and treats themdifferently.

• nearest• in [neighborhood]• near• close• local• close by• Google can distinguish between “near me”
and far away local intent,and implied local
intent sits somewhere between the two.
• Local packs provide huge opportunity
for exposure if you’re a brick-and-mortar
business.
• Distance, Google ratings, and organic rank
all play a role in determining the makeup of
a local pack.
• Local packs consider where the searcher isbefore what the searcher's geo-modifier isasking for.
• Organic results care more about the
searcher’s geo-modifier than where thesearcher is standing.
Since local packs and organic results are bothsubject to the whims of geo-location and geomodification, incorporating them into yourtracking strategy is a must. Here’s how you’dgo about doing that:

Just keep your locale, your searchers, yourbusiness, and your budget in mind.
2. Track multiple, hyper-local locations
Google cares a lot about location and so shouldyou. The closer you can get to a point on a map,the better; the more locations you can track,
the more searchers’ SERPs you’ll cover.
We recommend a combination of any of the
below to both narrow down your location andavoid ambiguity when the same names crop
up multiple times in your market — Main St.,
anyone?
• Geo coordinates• Neighbourhood• Street address• City• Postal code or
ZIP code• State, province, orcounty20

How Distance & Intent Shape a Local Pack

For example, in this study, two of the locations
we tracked were 10038 New York, NY and97204 Portland, OR.
If you’re ecommerce-only, we know it feels
strange to pick a physical location when yourbusiness lives online. But, as the saying goes,
one SERP that searchers actually see in thehand isworth two make-believe market-level
SERPs in the bush.
Figure 21. Segmenting by city.

3. Segment your keywords. A lot.
You may have noticed that our findings werelargely dependent on how we chose to sliceand dice our keywords. This goes double foryou.
Let’s say we’re an e-commerce business thatsells bed & bath and kitchen accoutrements,
and we know that most of our online sales
come from New York City and Portland. We
could segment our keywords by city, geomodifier, or product (see figures 21 – 23) — oreven all three — depending on what we want
to focus on.

Figure 22. Segmenting by geo-modifier.

4. Get analyzing & optimizing
Once you've got your keywords segmented
every which way, sit back and let the insights
roll in. With enough data under your belt, you'll
be able to build the right local SEO strategy foryour business.
So, what are you waiting for?
Figure 23. Segmenting by product.

21

About Moz
Moz is the leader in search engine optimization(SEO) technology and local search management.
Founded in 2004 and headquartered in Seattle,
Moz was the first company to bring together
SEO experts to help marketers learn how toreach their customers in a more efficient way by
improving their visibility in search results. For more
information, please visit moz.com and follow us attwitter.com/moz.

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