Post on 08-Jan-2023
Intent has replaced demographics as the driving force behind
searchers and search engines. According to Think with Google,
“demographics don’t help us understand what we really need to
know — what consumers are looking for in an exact moment.”
So how do we know what consumers want? By tapping into
the frontend of Google’s multi-billion dollar consumer research
project: the SERPs.
Through processing trillions of searches per year, Google has
evolved their algorithm to understand the intent behind each
query. And along with traditional organic results, they serve up
a veritable smörgåsbord of features — that often monopolize
the SERP — to help satisfy a searcher’s need.
Because of this, it’s more important than ever for SEOs to
understand what SERP features are appearing and how they
respond to intent. So in this study, we show exactly how to
uncover searcher-focussed opportunities in your space.
After all, if Google’s going to tell us what searchers want,
we should listen.
WHITEPAPER: RETAIL
USING SEARCH INTENT TO CONNECT WITH CONSUMERS
Through segmentation and SERP feature
tracking, you can uncover new ways to
connect with consumers.
BUILDING YOUR SEARCH INTENT FUNNEL 2
METHODOLOGY 3
HIGH LEVEL: HOW SERP FEATURES RESPOND TO INTENT 6
Informational intent 7
Commercial intent 8
Transactional intent 9
Local intent 10
SERP FEATURES BY PRODUCT CATEGORY & INTENT 11
Featured snippet (list) 12
Featured snippet (paragraph) 13
Featured snippet (table) 14
App download 15
Images 16
News 17
“People also ask” (PAA) 18
Places 19
Shopping 21
Videos 22
SUMMARY: HOW TO UNCOVER INTENT-BASED OPPORTUNITIES 23
APPENDIX A: SERP FEATURES BY PRODUCT CATEGORY 25
PAGE 1 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
BUILDING YOUR SEARCH INTENT FUNNEL
Before we get into the thick of it, we first want to shed a bit
of light on what we mean when we say “search intent.”
Tracking leads has traditionally been done through marketing
or sales funnels, with SEO supporting steps along the way.
Nowadays, many buyer journeys can start and stop within a search
engine. In order to follow those buyers from interest to purchase,
SEOs need to track the intent that motivates their searches.
Intent can be:
INFORMATIONAL The searcher has identified a need and is looking for the best
solution. [laptop]
COMMERCIAL The searcher has zeroed in on a solution and wants to compare
options. [best laptops]
TRANSACTIONAL The searcher has narrowed their hunt down to a few best options
and is getting ready to buy. [laptop price]
LOCAL
The searcher is considering an in-store purchase.
[laptops Dallas]
NAVIGATIONAL
The searcher wants to locate a specific website. [BestBuy]
Figure 1. Our search intent funnel.
LIKELIHOOD OF CONVERSION
INFORMATIONAL INTENT
COMMERCIAL INTENT
TRANSACTIONAL INTENT
+Local intent
LOW
LOW TO MEDIUM
MEDIUM TO HIGH
HIGH
DRAWING A LINE IN THE SAND
The way we've ordered intent for this study does not necessarily
create a "one size fits all" funnel.
For example, we’ve included local intent within transactional intent
because our keywords are retail in nature — a searcher would only
be interested in seeing a product first-hand if they were thinking
of purchasing it. We would also put navigational intent within the
transactional section because of the strong brand recognition
it shows, but have removed it entirely from this study so it won't
bias our data.
The keywords that occupy each intent category can also be highly
subjective. While some SEOs may disagree that the “free shipping”
modifier belongs in transactional intent, we think that if a searcher is
looking into shipping options, they’re highly likely to convert.
The bottom line is that intent should be structured and classified in
a way that makes sense to your business. Our methodology provides
a framework, but how you approach it may be slightly different.
You do you!
PAGE 2 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
LIKELIHOOD OF CONVERSION METHODOLOGY
Before we can get to the good stuff, here's how we structured our
study. This methodology can be easily reproduced and customized
to your business-specific data.
STEP ONE: SELECT CORE KEYWORDS
We created a list of 294 core retail product keywords. These are
things you might have kicking around your house, like [keyboard],
[refrigerator], [duvet], [garden shed], and [dog house].
We then took our 294 core products and, where it made sense,
added plural versions: [keyboards], [refrigerators], [garden sheds],
and [dog houses].
NOTE: Don't forget to build your keyword list carefully. When you’re
in the UK, you take the lift, not the elevator. You don’t wear a
sweater, you wear a jumper. These are just a few examples of why
it’s important to build specific keywords and modifiers for each
country you're tracking in.
DATA SET HIGHLIGHTS
KEYWORDS ANALYZED: 6,422
PRODUCT CATEGORIES: 14
KEYWORD MODIFIERS: 20
SERP FEATURES ANALYZED: 8,467
SEARCH RESULTS: 77,064
DEVICE: Smartphone
MARKET: United States, English (Google.com)
PAGE 3 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
HOW TO:
CREATE MODIFIERS TO MATCH YOUR CORE KEYWORDS
How do you come up with the modifiers to go with your
keywords? For this study, we used some pretty basic modifiers,
like “best” and “new,” that apply to a broad number of products.
But if you’re in something specific like, say, the business of
selling TVs, then you might be using more specific modifiers like
screen size or brand name.
If you want to get super crazy, you can apply multiple modifiers:
“best” “new” “samsung” [tv], or try moving them around as
prefixes and suffixes: “new” “apple” [tv] “deals.” In no time at
all, you’re going to find yourself in the middle of a modifier party.
And there ain’t no party like a modifier party, ‘cause a modifier
party don’t stop. Which is exactly why we kept our modifier
guest list tight.
But if you already have a solid idea of your core product keywords
and most-frequently used modifiers, there’s nothing stopping
you from doing this on a huge scale.
Best
Compare
Deals
New
Online
Refurbished
Reviews
Shop
Top
Used
INFORMATIONAL INTENT
Core and plural keywords (no modifiers)
COMMERCIAL INTENT TRANSACTIONAL INTENT
Affordable
Buy
Cheap
Cost
Coupon
Free shipping
Price
STEP TWO: ADD MODIFIERS AND SEGMENT BY INTENT
Next, we married the core keyword in each of our product
categories to modifiers like “affordable” and “reviews,” in order to
apply intent. We decided to keep things simple and only apply
a single modifier, but you can add as many and get as fancy as
you like.
Then we grouped our keywords into one of the four search intents,
giving us an intent funnel for each product category. Again,
navigational intent is not included in our study because brand-
specific keywords would bias our data.
We tracked the following modifiers and intents:
LOCAL INTENT
Chicago
Dallas
Near me
PAGE 4 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
STEP THREE: SEGMENT CORE KEYWORDS INTO PRODUCT CATEGORIES
Because our keywords were so diverse, we decided to group them
by product category so it would be easy to compare apples to
apples — or in this case, loofahs to loofahs. So, things like [litter
box] and [dog house] would be in our “pet supply” category, while
[armchair] and [mattresses] would live in the “home, kitchen
& bath” category.
We investigated the following product categories:
STEP FOUR : TRACK AND DIG INTO THE RESULTS
Our next move was to load our keywords into STAT and track
them on smartphones in the US. We focussed on mobile devices
because of Google’s recent shift to mobile-first indexing.
For our study, we tracked the following SERP features:
• Answers (list, paragraph, table) aka featured snippets
• App download
• Images
• Knowledge graph
• News
• “People also ask” (PAA)
• Places
• Shopping
• Videos
We let the data collect, then looked at a single day’s snapshot of
the top 12 search results for each of the 6,422 keyword variations.
That gave us 77,064 rows of data.
Once we got our mitts on all this data, it was time to dig in. We
wrote a lot of SQL queries, dug into the archived HTML SERPs,
and made all kinds of crazy spreadsheets.
• Appliances
• Automotive
• Beauty
• Cameras
• Clothing
• Computers
• Electronics
• Home, kitchen & bath
• Industrial & tools
• Music
• Office
• Patio, lawn & garden
• Pet supplies
• Sports & outdoor
PAGE 5 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
HIGH-LEVEL FINDINGS: HOW SERP FEATURES RESPOND TO INTENT
Alright. Now that we’ve got the housekeeping out of the way,
on to the good stuff.
First, we wanted to see which SERP features appear for each
stage of the intent funnel when all of our product categories are
grouped together. This gives a big-picture view of our SERPs,
providing a general sense of direction and a baseline comparison
when we drill down into individual SERP features and product
categories.
In the following pages, we break down what we found for our
full keyword set.
PAGE 6 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
RESULT TYPE
Featured snippet (list)
Featured snippet (paragraph)
Featured snippet (table)
App download
Images
Knowledge graph
News
PAA
Places
Shopping
Videos
Figure 2. A breakdown of SERP results for all informational queries across all product categories.
% OF TOTAL SERP FEATURES
0.10%
3.91%
0.20%
3.11%
14.23%
6.51%
12.83%
5.51%
0.00%
46.19%
0.40%
7.01%
Figure 3. The most common SERP features for informational intent.
14%
7%
13%
6%
46%
7%
8%
Images Knowledge graphNewsPAAShopping Videos Other
News made up over 12% of all SERP results for our informational keywords.
INFORMATIONAL INTENTGiven the retail nature of our keywords, a high percentage of
shopping boxes and images are to be expected — they help
searchers quickly narrow down what they’re looking for. Our
informational intent SERP is no exception — these features
made up 46.19 and 14.23 percent respectively.
But unexpectedly, we saw a lot of news results in this intent stage
— in fact 12.83 percent of all our SERP results were news. This is
likely because our keywords in this category are broad (they don’t
have any modifiers) and the intent behind them is ambiguous.
Google serves up all sorts of stories to help the searcher define
what they’re after. For example, if you’re on the hunt for a
new [fireplace] around Christmas time, in addition to all those
shopping boxes and images, you might see more than
a few news items about people getting stuck in them.
PAGE 7 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
RESULT TYPE
Featured snippet (list)
Featured snippet (paragraph)
Featured snippet (table)
App download
Images
Knowledge graph
News
PAA
Places
Shopping
Videos
Figure 4. A breakdown of SERP results for all commercial queries across all product categories.
% OF TOTAL SERP FEATURES
6.42%
1.67%
3.60%
2.16%
9.57%
4.42%
1.73%
1.93%
0.08%
55.82%
0.05%
12.56%
Figure 5. The most common SERP features for commercial intent.
Images Featured snippet (list)Shopping Videos Other
56%
6%
10%
13%
16%
Video is a pivotal tool for decision-making when it comes to commercial intent.
COMMERCIAL INTENTAs searchers slide down the funnel and get closer to making a
purchase, Google starts presenting them with more opportunities
to complete a transaction. This rings true for our commercial
intent keywords, as shopping boxes increased by nearly 10 percent,
making up 55.82 percent of all commercial SERP features.
More interestingly, we saw quite the jump in video results,
making them the second-most prominent SERP feature in our
commercial intent category at 12.56 percent. This indicates to us
that Google sees video, like images, as a pivotal tool for decision-
making when it comes to commercial intent keywords. And
when we dug into our archived SERPs, we saw mostly vloggers
and review sites pumping out comparative videos for our retail
products.
PAGE 8 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
RESULT TYPE
Featured snippet (list)
Featured snippet (paragraph)
Featured snippet (table)
App download
Images
Knowledge graph
News
PAA
Places
Shopping
Videos
Figure 6. A breakdown of SERP results for all transactional queries across all product categories.
% OF TOTAL SERP FEATURES
1.30%
5.12%
2.14%
0.76%
11.13%
2.18%
0.59%
3.06%
0.00%
66.88%
0.00%
6.84%
TRANSACTIONAL INTENTAs we reach the bottom of the funnel, where a searcher’s queries
are far more refined and their likelihood of purchasing is high,
shopping boxes have taken over SERPs, making up nearly 67
percent of our transactional intent features. Google is serving up
more ways to help searchers cross the purchase finish line.
Figure 7. The most common SERP features for transactional intent.
Images Shopping Videos Featured snippet (paragraph)Other
5%
11.%
67%
7%
10%
PAGE 9 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
LOCAL INTENTShopping boxes, images, and videos have been the belles of the
ball in each of our intent categories, and our local intent category
is keeping that trend alive — but also bringing a new guest to the
party. This is the first real appearance of the places pack, and it
makes up 25 percent of our SERP features. With searchers looking
to make an in-store purchase at this stage, Google serves up the
result that will point them exactly where they need to go.
RESULT TYPE
Featured snippet (list)
Featured snippet (paragraph)
Featured snippet (table)
App download
Images
Knowledge graph
News
PAA
Places
Shopping
Videos
Figure 8. A breakdown of SERP results for all local queries across all product categories.
% OF TOTAL SERP FEATURES
0.26%
0.35%
0.00%
0.96%
12.84%
3.06%
0.00%
1.57%
25.24%
50.39%
0.09%
5.24%
Figure 9. The most common SERP features for local intent.
Images Places Shopping Videos Other
13%
25%
50%
5%6%
PAGE 10 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
DRILLING DOWN: SERP FEATURES BY PRODUCT CATEGORY & INTENT
While looking at high-level, product-blended SERPs provides
some insight, it's not until we dissect the SERP features by our
segments (product category and intent) that we start to spot
trends and patterns.
The information in the following section is foundational for
discovering SERP feature opportunities. Once you know what's
appearing, you can then determine the viability and make sure
the opportunity lines up with your company’s target personas and
business objectives. From there, you can create strategies and
approaches to snag these features.
To keep this whitepaper from ballooning to 300 pages, we’ll
look at how often each SERP feature appeared for our product
categories, then zoom in on intent for the category that returned
the most of each feature.
But we believe that sharing is caring, so for you keeners out there,
we’ve included an appendix with the intent breakdown of each
SERP feature, for all 14 product categories.
NOTE
KNOWLEDGE GRAPH & TWITTER BOX
While we looked at knowledge graphs and Twitter boxes in this
study, they didn't lend themselves to any particular insights, so
we've left them out of the in-depth analysis.
We still recommend tracking these features to see whether they
have a significant presence for your unique keyword sets. If they
do, you should investigate them further to see if they hold any
opportunity.
PAGE 11 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
Figure 12. We broke out our computer queries to see which intent categories featured snippets
(list) appeared in.
Figure 10. Featured snippet (list) result for [best laptop].
Informational Commercial Transactional Local
15%
3%
82%
FEATURED SNIPPET (LIST) In figure 11, we can see the highest number of list snippets
appear for our computer product category (5.83 percent), with
cameras and electronics close behind. Keywords in our patio,
lawn & garden category hardly returned any list snippets (1.38
percent).
Looking at our computers category and breaking the queries out
by intent stage (see figure 12), we can see right away that a huge
majority of list snippets appear for commercial queries. Since
consumers at this stage in the funnel are typically on the hunt
for top ten lists and product reviews, it makes sense that Google
would pull that type of content into a snippet. Our commercial
intent modifiers included words like “best” and “reviews,” and
this kind of technical, comparative information can easily be
displayed in a list format, like we see with [best laptop] below.
Appliances Automotive Beauty Cameras Clothing
Computers ElectronicsHome, kitchen & bath Industrial & toolsMusic
Figure 11. The percentage of featured snippets (list) for each product category.
5%
4.5%
3%
2.5%
0%
OfficePatio, lawn & gardenPet suppliesSports & outdoor
Average = 3.40%
COMPUTERS
List snippets are the best SERP feature to display top ten lists and product reviews.
PAGE 12 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
Figure 13. Featured snippet (paragraph) result for [air conditioner price].
Appliances Automotive Beauty Cameras Clothing
Computers ElectronicsHome, kitchen & bath Industrial & toolsMusic
50%
3%
47%
Figure 14. The percentage of featured snippets (paragraph) for each product category.
FEATURED SNIPPET (PARAGRAPH)The appliances category brings in the most paragraph snippets
(5.37 percent) by a large margin (see figure 14). On the other hand,
the clothing category seems to drum up the least (1.21 percent).
Looking at the appliance keywords that return a paragraph snippet
by search intent (see figure 15), we can see that there’s a fairly
even split down the middle between commercial and transactional
intent. These two stages are when consumers embark upon
specific research in hopes of a purchase.
Up ‘til recently, many consumers have been hesitant to purchase
large appliances online — picking out a fridge is something you do
in person. According to a Distilled interview with Matthew Lawson
of Appliances Online, the main reason for this was because
consumers “had a lot of questions at the research stage that
weren’t being answered by websites.”
So Lawson and his team built out customer-focussed content
like Q&A pages and top five products. “We have discovered
that if we are the source of information at the research stage
for customers, they will come back to us when it comes time to
purchase their product.”
This was a smart move by Lawson because it’s exactly the kind
of content that Google pulls into paragraph snippets. He’s hitting
consumers at the right time with the right information
in the right format.
6%
4.5%
3%
1.5%
0%
OfficePatio, lawn & gardenPet suppliesSports & outdoor
Average = 2.73%
Figure 15. We broke out our appliance queries to see which intent categories featured snippets
(paragraph) appeared in.
Informational Commercial Transactional Local
APPLIANCES
PAGE 13 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
FEATURED SNIPPET (TABLE) Tables are a great tool for technical comparisons, and Google
confirms this by serving up the most table snippets for our
computer (3.74 percent) and office (3.62 percent) product
categories, and handing out the least to our clothing category
(0.35 percent).
Much like our appliance keywords with paragraph snippets,
table snippets seem to appear evenly for our commercial and
transactional intent computer keywords (see figure 18).
There’s a lot to know before buying a computer or computer-
related products, and by dishing out an equally high number of
table snippets for commercial and transactional search intent,
Google shows us that consumers are hungry for more information
at the mid-to-high intent stages of their searches.
Appliances Automotive Beauty Cameras Clothing
Computers ElectronicsHome, kitchen & bath Industrial & toolsMusic
Figure 17. The percentage of featured snippets (table) for each product category.
4%
3%
2%
1%
0%
OfficePatio, lawn & gardenPet suppliesSports & outdoor
Average = 2.30%
Figure 18. We broke out our computer queries to see which intent categories featured snippets
(table) appeared in.
Informational Commercial Transactional Local
4%
48% 48%
COMPUTERS
Figure 16. Featured snippet (table) result for [best wireless router].
PAGE 14 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
APP DOWNLOADIn figure 20, we see app downloads appearing the most, by a wide
margin, for our office category (5.17 percent). Our industrial & tools
SERPs returned a very low number (0.17 percent).
When they say, “there’s an app for that,” they’re not kidding.
We saw app downloads for keywords like [binders], [cash boxes],
and [staplers near me]. Google is serving all sorts of apps that
contain our keyword — even if they're not specifically aligned with
the intention behind the query.
This broad interpretation by Google is likely why, when we look
at our office keywords by search intent (see figure 21), twenty
percent of app downloads appear on informational SERPs. Since
the intent behind those keywords is unclear, the searcher could
just as easily be looking for the Binder app as they could for where
to buy binders.
App downloads on the SERPs are becoming a more regular
occurrence. Chris Chapa, Senior Content Strategist at Performics
recently wrote in "How Growing Competition from App Results in
SERPs Affects Organic Search" that “as brands open up more of
their apps to crawlers, and more deep links flood into the search
results, they should expect to see a portion of their organic search
clicks shift to their app.” This means that for brands who don’t
have an app, more of their traffic may be diverted to competing
apps, and their results will be pushed down the SERP.
13%
10%
57%
20%
Appliances Automotive Beauty Cameras Clothing
Computers ElectronicsHome, kitchen & bath Industrial & toolsMusic
Figure 20. The percentage of app downloads for each product category.
6%
4.5%
3%
1.5%
0%
OfficePatio, lawn & gardenPet suppliesSports & outdoor
Average = 1.71%
Figure 21. We broke out our office queries to see which intent categories app downloads
appeared in.
Informational Commercial Transactional Local
OFFICE
Figure 19. App download result for [binder].
PAGE 15 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
IMAGESFigure 23 shows that the beauty and clothing product categories
returned the most images with 19.6 percent and 19.55 percent
respectively. And the appliances and computer categories had the
least with 3.94 percent and 3.59 percent.
Similar to what we saw in the big-picture view at the beginning of
this whitepaper, images for our beauty keywords appeared across
all levels of search intent (see figure 24). We even saw a similar
percentage breakdown in our clothing category.
This reinforces how much Google relies on images to help
searchers narrow down their hunt, and how it pays attention to
the needs of various industries. Fashion and beauty are fuelled
by visuals. Far fewer people want to gaze at glamour shots of
computers than of makeup or scarves — and those visuals are
most helpful for mid-funnel queries when comparisons are afoot.
In their article, " The Ultimate Guide to Selling Clothes and Other
Apparel Online", Volusion (an online store builder) explains this
image-obsessed world: “[The fashion and apparel industry], built
on the notion that aesthetic is everything, is now even more
reliant on visuals. Why? Because the latest social networks have
birthed a new obsession with pictures and visual content.”
Figure 22. Image result for [compare eyeshadows].
Appliances Automotive Beauty Cameras Clothing
Computers ElectronicsHome, kitchen & bath Industrial & toolsMusic
Figure 23. The percentage of images for each product category.
20%
15%
10%
5%
0%
OfficePatio, lawn & gardenPet suppliesSports & outdoor
Average = 11%
Figure 24. We broke out our beauty queries to see which intent categories images appeared in.
Informational Commercial Transactional Local
14%12%
25%49%
BEAUTY
Google relies on images to help searchers narrow down their hunt.
PAGE 16 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
Appliances Automotive Beauty Cameras Clothing
Computers ElectronicsHome, kitchen & bath Industrial & toolsMusic
Figure 26. The percentage of news for each product category.
8%
6%
4%
2%
0%
OfficePatio, lawn & gardenPet suppliesSports & outdoor
Average = 2.48%
Figure 27. We broke out our computer queries to see which intent categories news appeared in.
Informational Commercial Transactional Local
4%
55%
42%
COMPUTERS
Figure 25. News result for [tablets].
We see far fewer news results as search queriesbecome more specific.
NEWSThe computer product category cleaned up when it came to news
results (see figure 26), generating more than three times the
average across all categories. On the other end of the scale, only
.68 percent of all patio, lawn & garden SERP features were news
results.
Digging into our computer category news results by search intent
(figure 27), we see that almost half appear for our informational
queries, keywords like [laptop], [tablet], or [gps]. And just over
half appear for our commercial keywords, like [best laptop], [tablet
reviews], and [compare gps].
As we mentioned earlier, news story headlines tend to match with
broad queries, which is why we see such a high percentage in our
top- to mid-funnel queries. The more specific queries get as they
head down the intent funnel, the less likely news results are to
match with them. This explains why we saw very few news results
appear in our transactional intent category, and why none show up
on our local intent SERPs.
PAGE 17 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
"PEOPLE ALSO ASK" (PAA)Figure 29 shows that the computer product category had the
most “People also ask” (PAA) results with 5.98 percent. At the
time of our data pull, the clothing product category returned zero
PAA results.
For our computer keywords, we see a pretty even showing of
PAAs across all levels of search intent (see figure 30).
When it comes to finding the right computer, there’s a lot to
know. Google seems to understand that searchers rely on PAAs
throughout the intent funnel, helping to expand their search and
surface questions they hadn’t thought of.
That said, PAAs are still one of the new kids on the SERP block,
and this even distribution could be due to Google testing the
feature. We may, as time goes by, see that PAAs start to favour a
certain level of intent as Google learns more about how searchers
use them.
28%
30%
25%
18%
Figure 28. PAA result for [best graphics card].
Appliances Automotive Beauty Cameras Clothing
Computers ElectronicsHome, kitchen & bath Industrial & toolsMusic
Figure 29. The percentage of PAAs for each product category.
6%
4.5%
3%
1.5%
0%
OfficePatio, lawn & gardenPet suppliesSports & outdoor
Average = 2.62%
Informational Commercial Transactional Local
Figure 30. We broke out our computer queries to see which intent categories PAAs appeared in.
COMPUTERS
PAGE 18 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
Appliances Automotive Beauty Cameras Clothing
Computers ElectronicsHome, kitchen & bath Industrial & toolsMusic
Figure 31. The percentage of places for each product category.
8%
6%
4%
2%
0%
OfficePatio, lawn & gardenPet suppliesSports & outdoor
Average = 3.45%
Informational Commercial Transactional Local
Figure 32. We broke out our office queries to see which intent categories places appeared in.
100%
OFFICE
PLACESOur office category was the big winner, garnering the most places
results (7.59 percent) out of all our product categories (figure 31),
while the camera category had the lowest (0.47 percent).
When we dug into search intent for our office keywords (figure
32), 100 percent of places results appeared within local intent.
Looking at other product categories, only a few had places results
appear elsewhere (see appendix). This disparity is due to the way
we tracked our keywords.
Technically, every search is now local thanks to geo-location —
your mobile device automatically provides location data as a part
of your query. So, if you do an informational search like [jeans]
on your phone, there’s a good chance you’d see a places pack
because Google does know where you are.
For this study, we chose to track our keywords at a national,
not local, level, which strips away specific location data. This
produces fewer places results, but provides a good baseline to
compare against other national or local markets — which is why we
recommend you track both.
Places packs appearing in local intent for our office category are
the result of our “Dallas” and “Chicago” keyword modifiers. By
specifying the location, or “geo-modifying” the query, Google
understands the local intent of the search, and returns places
packs. This tells us that geo-modified keywords should be
optimized for places.
PAGE 19 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
Figure 33. Places result for [copiers dallas].
DEFINITION
GEO-MODIFICATION VS. GEO-LOCATION
For every individual search, there are two distinct factors that
determine whether and how 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 part of the search query —
for example, in the search [best beaches] when performed
within Sydney on a smartphone. (Google calls this “user
location.”)
PAGE 20 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
SHOPPINGShopping boxes are a money-maker for both retailers and Google.
Offering local ads, merchant promos, and product ratings, they sit
right at the top of the SERP and are highly measurable.
It’s no surprise then, that these results showed up the most
across all our product categories — on average, making up 57.06
percent of all SERP features (figure 35).
Appliances brought in the highest number of shopping boxes
(68.69 percent), and while our beauty category brought in the
least (46.46 percent), they’re still had a significant presence.
Looking at intent, our high-level SERPs at the start of this
whitepaper showed the most shopping results in transactional.
When we dug into our product categories (which you can do in the
appendix), we saw that shopping boxes, while prominent in each
intent stage, tend to favour commercial and transactional, and in
some rare cases, local. Our appliance keywords are a good example
of the former (figure 36).
As SEOs, shopping boxes are an important feature to track, and as
retailers, they shouldn't be overlooked as part of your strategy. As
our friends over at Seer Interactive say, “no matter your industry
or product category, you need shopping ads in your paid search
arsenal.”
13%
41%
12%
34%
Appliances Automotive Beauty Cameras Clothing
Computers ElectronicsHome, kitchen & bath Industrial & toolsMusic
Figure 35. The percentage of shopping boxes for each product category.
70%
52.5%
35%
17.5%
0%
OfficePatio, lawn & gardenPet suppliesSports & outdoor
Average = 57.06%
Informational Commercial Transactional Local
Figure 36. We broke out our appliance queries to see which intent categories shopping
appeared in.
APPLIANCES
Figure 34. Shopping result for [buy refrigerator].
Shopping boxes appear most often for commercial and transactional queries.
PAGE 21 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
VIDEOSAutomotive scores the most video results (18.42 percent) out of
all our product categories, while the home, kitchen & bath
category came in last with 3.06 percent (figure 38).
It was surprising to see automotive snag the most video results,
but when we looked into it further, we found “review” style videos
for car parts and accessories, like in figure 37.
And while videos appear in each intent stage for the automotive
keywords (figure 39), the majority were for commercial queries,
where our modifiers include things like “reviews,” “compare,”
and “best.”
In an interview with Auto Dealer Today, Google’s Lindsay
Schultz says, “There’s a lot of opportunity to create short videos
specifically for YouTube. For example, you could do a video about
'Is it time to get your tires rotated? Here are a few tests you can
perform...' It’s clear that the YouTube community is interested
in car-related content, so it’s a great place for dealers to connect
with consumers and build on that interest.”
Appliances Automotive Beauty Cameras Clothing
Computers ElectronicsHome, kitchen & bath Industrial & toolsMusic
Figure 38. The percentage of videos for each product category.
20%
15%
10%
5%
0%
OfficePatio, lawn & gardenPet suppliesSports & outdoor
Average = 9.31%
Informational Commercial Transactional Local
Figure 39. We broke out our automotive queries to see which intent categories videos appeared in.
18%
55%
18%
9%
AUTOMOTIVE
Figure 37. Video result for [best steering wheel covers].
PAGE 22 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
SUMMARY: HOW TO UNCOVER INTENT-BASED OPPORTUNITIES
1. CREATE STRATEGIC KEYWORD LISTS
Apply business-specific modifiers that make sense. Use
your core keyword list and add prefix and suffix modifiers
that are specific to your business and customer searches.
2. SEGMENT, SEGMENT, SEGMENT
Use proper segmentation to help you uncover the secrets
of the SERPs. Product categories and even intent
are only the tip of the iceberg. You can go deeper,
splitting out sub-categories like location, device, and
more. The better you segment, the more data points you
can pivot on, and the deeper your insights will be.
3. TRACK SERP FEATURES
Gone are the days of ten blue links. When you track the
ever-changing SERP features, you can uncover a whole
new world of opportunities.
4. OPTIMIZE FOR SERP FEATURESTHAT MAKE SENSE
Identify and zero in on the realistic opportunities in
your space. Just because a SERP feature appears in high
volumes doesn’t mean you should go after it. Research
the viability of getting into that feature by looking at
who’s appearing, how they’ve structured their content,
how often they appear, and how well you’re ranking.
PAGE 23 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
STAT is SERP tracking for the experts. Every location. Every result. Every language. Fresh every day.
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5. SERVE UP THE RIGHT CONTENTLike the folks from Appliances Online have shown, it’s
imperative that organizations understand the needs of
their customers, and serve up the content to help move
them down the funnel, be it blog posts, FAQs, category
pages, or product pages.
6. IMPLEMENT A COMPLEMENTARYPPC CAMPAIGNWe saw throughout our study that shopping boxes
make up a huge majority of retail SERP features. If it
makes strategic sense for your business, this is a tactic
that should be researched, planned, and implemented
alongside your SEO efforts.
PAGE 24 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
APPENDIX: SERP FEATURES FOR ALL PRODUCT CATEGORIES BY INTENT
Featured snippet (list) 0.00% 7.35% 0.00% 0.00%
Featured snippet (paragraph) 1.45% 5.71% 9.80% 0.00%
Featured snippet (table) 0.00% 4.49% 2.61% 0.00%
App download 5.80% 1.63% 0.00% 0.00%
Images 7.25% 2.86% 5.23% 2.17%
Knowledge graph 1.45% 0.41% 0.00% 1.09%
News 14.49% 0.82% 1.96% 0.00%
PAA 5.80% 2.45% 2.61% 0.00%
Places 0.00% 0.00% 0.00% 30.43%
Shopping 57.97% 69.39% 76.47% 61.96%
Twitter 0.00% 0.00% 0.00% 0.00%
Videos 5.80% 4.90% 1.31% 4.35%
SERP FEATURE INFORMATIONAL COMMERCIAL TRANSACTIONAL LOCAL
0.00% 3.72% 0.59% 0.00%
1.43% 0.74% 8.82% 0.00%
0.00% 2.60% 1.76% 0.00%
2.86% 0.74% 0.00% 4.92%
21.43% 11.15% 10.00% 9.84%
7.14% 1.86% 0.59% 3.28%
7.14% 0.00% 0.00% 0.00%
4.29% 1.49% 3.53% 1.64%
0.00% 0.00% 0.00% 27.87%
42.86% 51.30% 62.35% 45.90%
0.00% 0.00% 0.00% 0.00%
12.86% 26.39% 12.35% 6.56%
INFORMATIONAL COMMERCIAL TRANSACTIONAL LOCAL
AUTOMOTIVE
Featured snippet (list) 0.00% 9.06% 1.95% 0.00%
Featured snippet (paragraph) 1.79% 2.68% 7.79% 0.00%
Featured snippet (table) 0.00% 4.36% 0.00% 0.00%
App download 0.00% 2.01% 0.00% 0.00%
Images 25.00% 19.46% 19.48% 17.17%
Knowledge graph 12.50% 5.03% 0.00% 6.06%
News 21.43% 1.01% 0.00% 0.00%
PAA 3.57% 0.34% 1.30% 1.01%
Places 0.00% 1.01% 0.00% 27.27%
Shopping 25.00% 42.95% 64.29% 41.41%
Twitter 1.79% 0.34% 0.00% 0.00%
Videos 8.93% 11.74% 5.19% 7.07%
SERP FEATURE INFORMATIONAL COMMERCIAL TRANSACTIONAL LOCAL INFORMATIONAL COMMERCIAL TRANSACTIONAL LOCAL
CAMERAS
APPLIANCES
BEAUTY
0.00% 10.45% 2.87% 1.82%
8.70% 2.09% 3.35% 0.00%
0.00% 1.74% 0.96% 0.00%
6.52% 2.79% 0.96% 0.00%
16.30% 9.76% 13.40% 14.55%
1.09% 4.53% 1.91% 5.45%
10.87% 2.09% 1.44% 0.00%
13.04% 2.44% 4.78% 1.82%
0.00% 0.00% 0.00% 5.45%
39.13% 53.66% 55.50% 65.45%
1.09% 0.00% 0.00% 0.00%
3.26% 10.45% 14.83% 5.45%
PAGE 25 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
Featured snippet (list) 0.00% 3.04% 0.00% 0.00%
Featured snippet (paragraph) 1.85% 0.00% 3.18% 0.96%
Featured snippet (table) 0.00% 0.38% 0.64% 0.00%
App download 0.00% 1.90% 0.00% 0.00%
Images 24.07% 19.77% 20.38% 15.38%
Knowledge graph 3.70% 4.18% 3.82% 2.88%
News 12.96% 0.76% 0.00% 0.00%
PAA 0.00% 0.00% 0.00% 0.00%
Places 0.00% 0.00% 0.00% 33.65%
Shopping 50.00% 59.32% 67.52% 45.19%
Twitter 1.85% 0.00% 0.00% 0.00%
Videos 5.56% 10.65% 4.46% 1.92%
SERP FEATURE INFORMATIONAL COMMERCIAL TRANSACTIONAL LOCAL INFORMATIONAL COMMERCIAL TRANSACTIONAL LOCAL
COMPUTERS CLOTHING
Featured snippet (list) 0.00% 8.16% 4.05% 0.00%
Featured snippet (paragraph) 7.35% 0.68% 5.20% 1.61%
Featured snippet (table) 0.00% 5.10% 1.73% 0.00%
App download 1.47% 3.40% 2.89% 3.23%
Images 13.24% 7.48% 8.09% 3.23%
Knowledge graph 2.94% 4.76% 2.31% 6.45%
News 11.76% 5.10% 3.47% 0.00%
PAA 7.35% 2.72% 4.05% 0.00%
Places 0.00% 0.00% 0.00% 12.90%
Shopping 47.06% 51.02% 61.27% 69.35%
Twitter 0.00% 0.00% 0.00% 0.00%
Videos 8.82% 11.56% 6.94% 3.23%
SERP FEATURE INFORMATIONAL COMMERCIAL TRANSACTIONAL LOCAL INFORMATIONAL COMMERCIAL TRANSACTIONAL LOCAL
HOME, KITCHEN & BATHELECTRONICS
0.00% 7.38% 1.15% 0.00%
3.33% 0.74% 4.60% 0.00%
0.00% 4.06% 1.15% 0.00%
0.00% 0.37% 1.15% 0.00%
15.00% 12.18% 15.52% 16.67%
6.67% 5.90% 1.72% 2.38%
11.67% 0.00% 0.00% 0.00%
1.67% 0.00% 1.72% 0.00%
0.00% 0.00% 0.00% 17.86%
61.67% 64.94% 71.26% 59.52%
0.00% 0.00% 0.00% 0.00%
0.00% 4.43% 1.72% 3.57%
0.00% 10.36% 3.19% 1.39%
5.00% 1.29% 4.79% 0.00%
1.00% 3.88% 6.38% 0.00%
2.00% 0.32% 0.00% 0.00%
3.00% 1.94% 3.19% 12.50%
3.00% 12.94% 7.45% 0.00%
22.00% 9.39% 1.06% 0.00%
11.00% 3.24% 6.38% 9.72%
0.00% 0.00% 0.00% 12.50%
41.00% 47.57% 64.36% 63.89%
1.00% 0.00% 0.00% 0.00%
11.00% 9.06% 3.19% 0.00%
APPENDIX: SERP FEATURES FOR ALL PRODUCT CATEGORIES BY INTENT
PAGE 26 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
Featured snippet (list) 0.00% 5.80% 0.60% 0.00%
Featured snippet (paragraph) 1.54% 1.02% 2.41% 0.00%
Featured snippet (table) 0.00% 3.75% 1.81% 0.00%
App download 0.00% 0.00% 0.60% 0.00%
Images 7.69% 5.80% 7.83% 13.16%
Knowledge graph 0.00% 3.07% 2.41% 1.32%
News 15.38% 0.00% 0.00% 0.00%
PAA 7.69% 2.39% 0.00% 1.32%
Places 0.00% 0.00% 0.00% 10.53%
Shopping 58.46% 62.12% 72.89% 60.53%
Twitter 0.00% 0.34% 0.00% 0.00%
Videos 9.23% 15.70% 11.45% 13.16%
SERP FEATURE INFORMATIONAL COMMERCIAL TRANSACTIONAL LOCAL INFORMATIONAL COMMERCIAL TRANSACTIONAL LOCAL
MUSIC
Featured snippet (list) 0.00% 4.12% 0.00% 0.00%
Featured snippet (paragraph) 6.35% 0.75% 2.65% 0.00%
Featured snippet (table) 0.00% 5.99% 3.31% 0.00%
App download 9.52% 6.37% 2.65% 3.03%
Images 12.70% 8.24% 9.93% 7.07%
Knowledge graph 7.94% 3.37% 0.66% 5.05%
News 11.11% 1.50% 0.00% 0.00%
PAA 1.59% 1.12% 0.66% 2.02%
Places 0.00% 0.00% 0.00% 44.44%
Shopping 50.79% 58.80% 72.19% 36.36%
Twitter 0.00% 0.00% 0.00% 1.01%
Videos 0.00% 9.74% 7.95% 1.01%
SERP FEATURE INFORMATIONAL COMMERCIAL TRANSACTIONAL LOCAL INFORMATIONAL COMMERCIAL TRANSACTIONAL LOCAL
PATIO, LAWN & GARDEN
INDUSTRIAL AND TOOLS
OFFICE
0.00% 5.74% 1.56% 0.00%
6.38% 1.35% 7.29% 0.98%
0.00% 3.72% 3.65% 0.00%
5.32% 2.03% 0.52% 0.00%
4.26% 5.07% 6.77% 19.61%
21.28% 7.77% 7.29% 2.94%
8.51% 0.34% 0.00% 0.00%
8.51% 3.72% 9.38% 1.96%
0.00% 0.00% 0.00% 29.41%
35.11% 50.00% 57.29% 38.24%
0.00% 0.00% 0.00% 0.00%
10.64% 20.27% 6.25% 6.86%
0.00% 2.62% 1.12% 0.00%
1.67% 3.75% 3.93% 0.00%
0.00% 2.25% 2.81% 0.00%
1.67% 1.87% 0.00% 1.20%
25.00% 11.61% 13.48% 12.05%
5.00% 2.25% 0.00% 2.41%
6.67% 0.00% 0.00% 0.00%
0.00% 0.37% 1.12% 0.00%
0.00% 0.00% 0.00% 30.12%
58.33% 65.54% 69.66% 48.19%
0.00% 0.00% 0.00% 0.00%
1.67% 9.74% 7.87% 6.02%
APPENDIX: SERP FEATURES FOR ALL PRODUCT CATEGORIES BY INTENT
PAGE 27 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
Featured snippet (list) 1.25% 4.97% 0.00% 1.25%
Featured snippet (paragraph) 0.00% 1.55% 2.37% 1.25%
Featured snippet (table) 0.00% 3.73% 1.78% 0.00%
App download 3.75% 4.97% 1.78% 2.50%
Images 18.75% 9.63% 10.65% 20.00%
Knowledge graph 5.00% 0.93% 0.00% 2.50%
News 13.75% 0.93% 0.00% 0.00%
PAA 0.00% 2.48% 3.55% 2.50%
Places 0.00% 0.00% 0.00% 15.00%
Shopping 43.75% 53.11% 73.37% 48.75%
Twitter 0.00% 0.00% 0.00% 0.00%
Videos 13.75% 17.70% 6.51% 6.25%
SERP FEATURE INFORMATIONAL COMMERCIAL TRANSACTIONAL LOCAL INFORMATIONAL COMMERCIAL TRANSACTIONAL LOCAL
SPORTS & OUTDOORSPET SUPPLIES
0.00% 6.15% 0.00% 0.00%
4.48% 1.54% 6.08% 0.00%
1.49% 4.23% 0.68% 0.00%
1.49% 1.54% 0.00% 0.00%
17.91% 9.62% 13.51% 13.16%
11.94% 3.46% 0.68% 1.32%
10.45% 1.15% 0.00% 0.00%
4.48% 3.85% 1.35% 1.32%
0.00% 0.00% 0.00% 36.84%
46.27% 56.92% 74.32% 38.16%
0.00% 0.00% 0.00% 0.00%
1.49% 11.54% 3.38% 9.21%
APPENDIX: SERP FEATURES FOR ALL PRODUCT CATEGORIES BY INTENT
PAGE 28 February 2017 getSTAT.com . info@getSTAT.com . @getSTAT
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