Buyer Intent Keywords Study

In this study of 85,000 search queries, I analysed buyer intent keywords and keywords in the other stages of the buying process.

I primarily wanted to find out.

“What percentage of keywords have buyer intent”?

Key Findings

• 92.4% of search queries keywords have buying intent.
• 7.6% of search queries or keywords don’t have buying intent.

However, 9.1% of search queries have purchase decision intent.

OK, Fraser, you’ve confused me.

What is the difference between buying intent and purchase decision intent?

Buying intent is any search query that falls into the 4 stages of the buying funnel.

• eg: how to, help, need
• eg: best, top
• eg: compare, alternative
• eg: buy, nearest, shop

And purchase decision intent is the search query that falls into that bottom part.

Buying Funnel Visualised

Here’s how the buying funnel has been historically visualised.

Based on my analysis of 85,000 keywords, the buying funnel is more like this.

Which sort of falls into alignment with Google’s analysis of the buying process.

It’s very messy and competitive in the middle of the buying funnel.

• 7.6% of queries don’t have buying intent.
• 4% of queries are top of funnel keywords ie: in the problem recognition stage
• 77.9% of queries are middle of the funnel keywords ie: in the informational search stage
• 1.4% of queries are in the evaluation of alternative stage
• 9.1% of search queries have purchase decision intent.

Buying Funnel across 17 search categories

You can see the 17 search categories I analysed that form the 85,000 total search queries at the foot of the graph.

Upon first looking at the graph, nothing stands out or is particularly insightful.

However, I noticed that people evaluate and compare broadband and mortgages more than the other categories.

Both services are vital, not quite life and death but of very high necessity.

Next, broadband and car search queries appear to have the highest purchase intent rate than the other categories.

If you look at the bank, cat and baby columns, they all have a high percentage of non-buying keywords.

There are a few reasons for this :

• Lots of bank holiday queries in the bank search category
• Lots of cat meme and gif queries
• Lots of searches for songs containing “baby” in the baby search category

Informational Search Query Cloud

The following is a word cloud based on the most popular keyword modifiers in the informational search stage of the buying process.

When you put words into a word cloud, you get a visual indicator of the most prominent.

So, for example, “calculator” is very prominent because many people search for “mortgage calculators” and other searches containing calculators.

“Best” is very prominent because it appears in searches across all these search categories, e.g.:

• best cat litter
• best coffee machine
• bet gaming chair
• best carpet cleaner
• best car insurance
• best broadband provider
• best bread maker
• best sports bra
• best time to book flights
• best bicycle lock
• best alcohol free beer
• best business bank account
• best baby changing bag
• best apple crumble recipe
• best apple watch
• best advertising agencies london
• best mortgage rates

Since informational searches account for 77.9% of searches, you can use some of the most prominent words in the count to guide your content strategy.

At the informational search stage focus on topics about

• Brand + products
• Brands + services
• Product Types
• Service Types
• Colours
• Sizes
• Shops

At the informational search stage also focus on search topics that include these keyword modifiers

• For
• Best
• Top
• Ideas
• In
• Calculator
• Recipes
• Free
• Parts

Ps: since I can’t research every topic, my results will not be entirely representative.

However, search queries containing “calculator” and “free” have appeared prominently whenever I do client research on other topics.

Research Methodology

Ahrefs keyword explorer tool was used as the data source for this study.

The first 5000 UK phrase matched keywords for selected keywords were exported and dropped into Google Sheets for analysis.

I chose a selection of 17 popular consumer and business seed keywords.

85,000 keywords is not a representative sample of the 7 billion daily searches on Google.

I’m not sure even 850,000 keywords analysed would change the insights from this research.

Then a list of keyword modifiers was chosen and assigned to each stage of the buying process funnel.

E.g., if “how ” appeared in the search query, that keyword would be assigned to the problem recognition stage of the buying process.

Likewise, if “compare” appeared in the search query, that keyword would be assigned to the evaluation of alternatives stage of the buying process.

Then I manually reviewed all unmatched results and assigned the keywords to each stage to the best of my knowledge.

Manually matching keywords took me 3 ½ days of work.

Buying vs non buying keywords

For this research, there are either buying or non buying keyword searches.

Someone searching “cat memes” or “cat gif” has no buying intent.

So these would be “unmatched” or non-buying keywords.

Keywords such as “login” and “id” were deemed post-purchase keywords and assigned unmatched non-buying keywords.

So non buying keywords fall outside the buying process or funnel.

Buying Funnel explained

Marketers had used the buying funnel or the consumer buying process model for decades before Google even existed.

The model helps to understand the steps and searches that consumers make before, during and after a buying decision and which keywords to target.

The model helps a business or brand understand what the user is searching for and where and how to show up in front of these users by serving relevant content or adverts.

Google published a 95-page paper to try and decode purchasing behaviour only to conclude that “People are doing what they’ve always done.” 

This study concluded that 60% of shopping queries are upper-funnel searches.

You have to go back to 2007 to find that 80% of queries are informational, split almost equally between navigational and transactional queries.

I used the Wikipedia definition as criteria for each stage of the buying process.

https://en.wikipedia.org/wiki/Buyer_decision_process

Here are how each stage is defined and the keyword modifiers. 

Problem recognition stage

At this stage, the user recognises the problem or need is with a particular product, service or situation.

The modifiers used for the problem recognition stage are shown in the image below.

Informational search

The user researches the product (service or brand), which might solve the recognised need.

The modifiers used for the informational search stage are shown in the image below.

Evaluation of alternatives

The consumer evaluates the searched alternatives.

Generally, the information search reveals multiple products for the consumer to evaluate, and they understand which products might be suitable.

The modifiers used for the evaluation stage are shown in the image below.

Purchase decision

The user has found a solution, product, and service to solve their problem, explored alternatives, options, and pricing; now, they are trying to make up their minds before buying.

The modifiers used at this stage as shown below.

Ps: there’s a bias towards UK retailers since the research is based on UK search queries.

There’s a 5th and 6th stage to the buying process that I’ve omitted; the purchase and post-purchase behaviour.

Finally

The following word clouds were created using keywords at the informational search stage for each keyword.

The word cloud displays the top 100 most frequent words in each category I researched.

Apple Informational Search Query Cloud

When you examine the top UK informational search queries containing “apple”, you see the most prominent.

• iphone
• watch
• store
• cider
• vinegar and so on.

Advertising Search Query Cloud

When you examine the top 5000 UK informational search queries containing “advertising”, you see the most prominent.

• Facebook
• Agency
• Free
• Agencies
• For
• Online
• Marketing
• London

Baby Search Query Cloud

When you examine the top UK informational search queries containing “baby”, you see the most prominent.

• Clothes
• Boy
• Girl
• Monitor
• Shower

Bag Search Query Cloud

When you examine the top UK informational search queries containing “bag”, you see patterns, trends, and topics emerge about what is most prominent.

• sleeping
• bean
• clutch
• leather
• cabin
• tote

Bank Search Query Cloud

When you examine the top UK informational search queries containing “bank”, you see what is most prominent.

• We see top brand names
• account
• online
• number
• banking
• business

Beer Search Query Cloud

When you examine the top UK informational search queries containing “beer”, you can see how prominent keywords containing festivals are.

Other standouts are :

• Craft
• Ginger
• How
• As well as a few supermarkets who sell beer

Bicycle Search Query Cloud

When you examine the top UK informational search queries containing “bicycle”, you see what is most prominent.

• Helmet
• Wheel
• Shop
• For
• Best
• Repair

Book Search Query Cloud

When you examine the top UK informational search queries containing “book”, you see what is most prominent.

• World
• Jungle
• Appointment
• Driving
• Test
• Log
• How
• New
• And
• Mormon

Bra Search Query Cloud

When you examine the top UK informational search queries containing “bra”, you see patterns, trends, and topics emerge about what is most prominent.

• Sports
• Strapless
• Size
• Push
• How
• And
• Nursing

Bread Search Query Cloud

When you examine the top UK informational search queries containing “bread”, you see what is most prominent.

• Recipe
• Pudding
• Banana
• And
• Free
• How
• Butter

Broadband Search Query Cloud

When you examine the top UK informational search queries containing “broadband”, you see what is most prominent.

• Deals
• Phone
• Sky
• Virgin
• And
• Best
• Fibre
• Test
• Vodafone

As I mentioned, early topics such as bank and broadband are dominated by major brands until most other topics in this research.

Car Search Query Cloud

When you examine the top UK informational search queries containing “car”, you see what is most prominent.

• Insurance
• Hire
• Park
• Sales
• Parts
• Near
• Check

Carpet Search Query Cloud

When you examine the top UK informational search queries containing “car”, you see what is most prominent.

• Cleaning
• Cleaner
• How
• For
• Shops
• Red
• Remove

Cat Search Query Cloud

When you examine the top UK informational search queries containing “cat” you see what is most prominent.

• Food
• Litter
• Rescue
• Black
• How
• Cafe
• Flap
• Breeds

Chair Search Query Cloud

When you examine the top UK informational search queries containing “chair”, you see patterns, trends, and topics emerge about what is most prominent.

• High
• Gaming
• Office
• And
• Dining
• Ikea
• Leather
• Swivel

Coffee Search Query Cloud

When you examine the top UK informational search queries containing “coffee”, you see what is most prominent.

• Table
• Machine
• Best
• Shops
• Costa
• Bean
• Cup
• And

Mortgage Search Query Cloud

When you examine the top UK informational search queries containing “mortgage”, you see that the word calculator is extremely prominent.

As are

• Rates
• Interest
• Buy
• How
• Much

And, of course, lots of brand names.

Conclusion

I hope this research was insightful.

Whilst search queries at the problem and evaluation stages are only a small part of the total search queries; they still represent huge traffic potential.

Also, just because you get traffic from purchase intent queries, do not necessarily people will buy.

Likewise, a search at the informational search stage can very quickly result in a purchase.

The only true way to understand purchase intent is to get inside the mind of consumers, which is impossible or work at Google; they know more than anyone else.

Here’s the full set of data used if you wish to analyse or use it yourself.