USING SEARCH INTENT TO CONNECT WITH CONSUMERS

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 . [email protected] . @getSTAT

https://getstat.com/


https://twitter.com/getSTAT

https://www.thinkwithgoogle.com/articles/why-consumer-intent-more-powerful-than-demographics.html

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!




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)




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




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

• Twitter

• 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




https://getstat.com/blog/get-an-eyeful-with-google-html-serps/

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.




RESULT TYPE

Featured snippet (list)

Featured snippet (paragraph)

Featured snippet (table)

App download

Images

Knowledge graph

News

PAA

Places

Shopping

Twitter

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.




RESULT TYPE




App download

Images

Knowledge graph

News

PAA

Places

Shopping

Twitter

Videos

Figure 4. A breakdown of SERP results for all commercial queries across all product categories.


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.




RESULT TYPE




App download

Images

Knowledge graph

News

PAA

Places

Shopping

Twitter

Videos

Figure 6. A breakdown of SERP results for all transactional queries across all product categories.


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%




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




App download

Images

Knowledge graph

News

PAA

Places

Shopping

Twitter

Videos

Figure 8. A breakdown of SERP results for all local queries across all product categories.


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%




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.




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.




Figure 13. Featured snippet (paragraph) result for [air conditioner price].



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%


Average = 2.73%

Figure 15. We broke out our appliance queries to see which intent categories featured snippets

(paragraph) appeared in.


APPLIANCES




https://www.distilled.net/blog/interviews/positive-outing-interview-with-appliances-online/

https://www.distilled.net/blog/interviews/positive-outing-interview-with-appliances-online/

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.



Figure 17. The percentage of featured snippets (table) for each product category.

4%

3%

2%

1%

0%


Average = 2.30%

Figure 18. We broke out our computer queries to see which intent categories featured snippets

(table) appeared in.


4%

48% 48%

COMPUTERS

Figure 16. Featured snippet (table) result for [best wireless router].




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%



Figure 20. The percentage of app downloads for each product category.

6%

4.5%

3%

1.5%

0%


Average = 1.71%

Figure 21. We broke out our office queries to see which intent categories app downloads

appeared in.


OFFICE

Figure 19. App download result for [binder].




http://www.performics.com/how-growing-competition-from-app-results-in-serps-affects-organic-search-pc/

http://www.performics.com/how-growing-competition-from-app-results-in-serps-affects-organic-search-pc/

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].



Figure 23. The percentage of images for each product category.

20%

15%

10%

5%

0%


Average = 11%

Figure 24. We broke out our beauty queries to see which intent categories images appeared in.


14%12%

25%49%

BEAUTY

Google relies on images to help searchers narrow down their hunt.




https://www.volusion.com/ecommerce-blog/articles/the-ultimate-guide-to-selling-clothes-other-apparel-online/

https://www.volusion.com/ecommerce-blog/articles/the-ultimate-guide-to-selling-clothes-other-apparel-online/



Figure 26. The percentage of news for each product category.

8%

6%

4%

2%

0%


Average = 2.48%

Figure 27. We broke out our computer queries to see which intent categories news appeared in.


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.




"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].



Figure 29. The percentage of PAAs for each product category.

6%

4.5%

3%

1.5%

0%


Average = 2.62%


Figure 30. We broke out our computer queries to see which intent categories PAAs appeared in.

COMPUTERS






Figure 31. The percentage of places for each product category.

8%

6%

4%

2%

0%


Average = 3.45%


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.




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.”)




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%



Figure 35. The percentage of shopping boxes for each product category.

70%

52.5%

35%

17.5%

0%


Average = 57.06%


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.




http://www.seerinteractive.com/blog/recap-expert-shopping-day/

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.”



Figure 38. The percentage of videos for each product category.

20%

15%

10%

5%

0%


Average = 9.31%


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].




http://www.autodealermonthly.com/channel/internet-department/article/story/2013/08/youtube-sensation-google-auto-talks-video.aspx

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.




STAT is SERP tracking for the experts. Every location. Every result. Every language. Fresh every day.

BOOK YOUR CUSTOM DEMOGETSTAT.COM/DEMO

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.




https://getstat.com/demo/

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




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%







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%


COMPUTERS CLOTHING




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%


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%








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%


MUSIC




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%


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%








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%


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%





WE DO BIG SERP DATA FOR ENTERPRISE SEO.

Since 2009, we’ve equipped SEO professionals with fresh, location-based search data at

massive scale — all backed up by one-on-one expert service. That’s how we’ve built a client

base that includes some of the world’s largest online brands and nimblest SEO agencies.

704 Alexander Street

Vancouver . British Columbia . V6A 1E3

US & Canada (toll-free): 1.888.973.0301

UK (freephone): 0800.051.1282

Global: +1.604.568.3422

getSTAT.com . [email protected] . @getSTAT




USING SEARCH INTENT TO CONNECT WITH CONSUMERS

Documents

Transcript of USING SEARCH INTENT TO CONNECT WITH CONSUMERS