A better approach to keyword research for content marketing
In this article, I challenge the classic approach to keyword research and propose a new approach.
SEO and Content Marketing are getting more competitive by the day. More content is created, more companies do it really well and Google gives less real estate to organic results. So why does everybody still follow the same process to create content? That doesn’t make sense!
The problem starts with keyword research.
I remember how I learned this back in the days:
- Take a couple of seed keywords
- Throw them into various tools, like Ubersuggest, to find permutations, variations, and related keywords
- Throw all that into Keyword Planner for search volume and competitiveness
- Prioritize keywords
- Create content
But that approach doesn’t cut it anymore. It doesn’t produce the quality of content necessary to compete. What we need is a better approach to keyword research so we can create content that stands out, overshoots user expectations and is attractive to search engines. That’s what I’m presenting you here: a better keyword research process for content marketing.
Every question is a problem
Good content answers questions and every question is a problem. Hence, if you want to create good content you need to focus on the problem it should solve. Keywords are only an expression of a problem but not every problem is well enough understood by the searcher to phrase it correctly. Since questions are problems, I call this approach problem-driven keyword research.
It doesn’t start on search engines but on social networks.
[bctt tweet="A synonym for “problem” is “question”" username="@Kevin_Indig"]
I recently worked on a content strategy for a toothbrush company. Instead of heading to the next SEO tool, I started on Quora, Twitter, Youtube, and Co. I wanted to find the topics related to toothbrushes that people really care about. Toothbrushes are a commodity, so it’s a bit harder to find the exciting, controversial stuff that makes content really interesting. Social networks are built around discussions and opinions, which makes them a much better tool than search engines.
So instead of looking for “toothbrush” on Google, I looked at the most relevant Tweets for the Hashtag “toothbrush”, Quora results and Youtube videos. That lead me to exciting questions like “Should you floss before or after brushing your teeth” and problems such as “gum health”, “bad breath”, and “bathroom hygiene”. It would have been so much harder to find that on Google or in an SEO tool.
[bctt tweet="People use search engines to solve problems and social networks to talk about them." username="@Kevin_Indig"]
The problem-driven approach to keyword research
Let me walk you through the exact process I use:
- Problem, topic, and query
- User intent
- Funnel stage
- Content ideas
The goal of this process is to have a spreadsheet with content ideas. I created a free Google Sheets template for you.
Collecting questions is the more unstructured but important part of the research. A solid list of questions is vital to discover the most relevant queries and topics in your space. Starting the research with questions makes it easier to put the pieces together and uncover the underlying problems and bigger topics.
In the first step, you add all the questions you found to a spreadsheet.
For the research process you can use:
- Quora topics
- Twitter hashtags
- Instagram hashtags
- Google search (surprise)
- Talking to friends and family
- Amazon questions on product pages
- Facebook groups
Using the advanced search function on Twitter can reveal some serious gems.
(Question research on Twitter. Look at the shares and likes of some of these examples!)
When researching on Quora, you should save links to the questions, so you can add your answer when you created the content.
(Question research on Quora. Notice that people follow certain questions)
SEMrush and AHREFs have recently added features that let you find the most important questions around a query. Even though you should not completely rely on them, they’re helpful.
We’ll stick to the toothbrush example.
In SEMrush you can use the Keyword Magic Tool.
After punching in your query, you can select a list of questions.
AHREFs has a questions feature in the Keywords Explorer section.
Like SEMrush, it helps you identify important questions and gives you metrics like search volume, competitiveness, and difficulty.
Use all platforms, not just a few. There’s always an angle, question, or trail that you find on one of these that makes your list of questions and queries better.
2. Topic, problem, and query
A good content marketing strategy considers topics, problems, and queries.
A problem is a real-life case behind the search. It helps us to understand what a user is trying to accomplish with a search. Sometimes the problem is obvious by looking at the questions. Other times it’s a bit hidden under the surface. In this case, you can use several root-cause analysis techniques to reveal the underlying problem:
- The “5 whys” technique, invented at Toyota: ask yourself 5 times why a question occurs.
- Put questions into a sequence: ask yourself what problem comes before and after the one you’re trying to find the root cause for. The root-cause is the first problem in the chain.
- Simplification: express the problem in the simplest terms as if you were talking to a 5-year-old. That can make the underlying issue more visible to yourself.
Let’s take UBER, for example. There are some very obvious problems it solves and some unobvious ones.
Obvious problems UBER solves:
- Getting from point A to B under time pressure
- Having to look for parking
- Owning a car in a crowded city
- Wanting to drink alcohol but having to drive
Unobvious problems UBER solves:
- Saving time
- Needing a drivers license
- Being able to drive (because of health issues)
- Having to pay for a car insurance
Can you feel how all of these problems already make great content ideas? Let’s develop them a bit further.
[bctt tweet="Focusing on problems instead of keywords helps you find exciting content ideas faster!" username="@Kevin_Indig"]
Group problems into a topic because Google measures topical relevance. It’s smarter to create content for one topic first and then advance to the next one to forge expertise. When trying to identify the topic, look at the connection between questions. Try to abstract the group they belong to. You could also replace topic with “entity” if you’re more familiar with that concept. Google also measures entities, instead of keywords, by the way.
Every problem must also be targeting a query to add up to an SEO strategy. Like problems, queries add up to topics as well. To find them you want to reduce a question to the simplest formulation of the problem you can think of. Add classic keyword research metrics to queries, such as search volume, competitiveness, etc.
The problem-driven keyword research process isn’t linear, it’s explorative. With every new query, you find more questions, with every question you discover more topics. Every new piece of the puzzle paints the picture a bit clearer, and the more shape it takes the easier it becomes to find the missing pieces.
I often start with a few questions, identify their queries, look at related queries, then find more questions from that, etc. When I threw only 5 queries from our example into AHREFs, I found lots of questions I hadn’t seen before.
3. User intent
Once you have identified topics, questions, and queries, it’s time to look at user intent. As I explained in User Intent mapping on steroids, Google mentions 6 basic user intents:
“Know and Know Simple
Do and Device Action
SERP features like a featured snippet or Google shopping ads can tell us what user intent Google sees for a query. In the linked article above, I provide an overview of the user intent each SERP feature indicates. It should be easy to throw your queries into AHREFs of SEMrush and export the SERP features.
This is the export from AHREFs:
If you want to make absolutely sure it’s accurate, you can manually check a few of the SERP features. Or, if you don’t have access to any of those tools and not too many queries you can do the whole step by hand.
This is what it looks when we add SERP features and user intent to our list of topics, questions, and queries:
4. Funnel stage
User Intent and buyer’s funnel look similar but they’re not the same. While User Intent is the intention behind a search, the buyer’s funnel is the sequence of intents mapped to a business. To create the best content possible and connect several pieces of content to a journey, we need both on our list.
In Creating an SEO strategy from scratch, I introduced the “See-Think-Do-Care framework”. It's a helpful tool to map queries to different funnel stages.
For blogs and landing pages, I personally like the “See-Think-Do-Care” framework, originally invented by Avinash Kaushik . It’s a segmentation of the buyer funnel:
See – Awareness
Think – Consideration
Do – Intent to buy
Care – Post-sales
You can apply this framework to your content and keywords to understand your gaps. It allows you to identify whether you have too much or too little content in one of the stages.
The more a question or query signals a clear decision to buy a product, the lower it is in the funnel. I’m not aware of a specific framework that helps you mapping funnel stages to queries. It’s something you have to understand from looking at the query.
Here is the final spreadsheet with funnel stage, topics, questions, queries, SEPR features and user intent (Check out the template).
5. Content ideas
The last step is to translate all this research into concrete content ideas. Each question should become a piece of content. If we’re thinking of “topic clusters” as invented by Hubspot, topics are perfect pillar pages and questions cluster content.
After looking at all the factors we researched in the previous steps, it should be easy to come up with content ideas. Remember that content is also widgets, visuals, videos, gifs, etc. - not only text.
If you want to create high-quality content you should also consider the situation connected to the problem(s). A dress can be bought for a nice dinner, the office, or leisure time. A toothbrush can be bought after a cold. An UBER is called when you need to get somewhere fast.
Each situation is connected with a different emotion that should be reflected in the content, title, and description for optimal click-throughs and rankings. The better you can understand the situation of the searcher, the better you can build something that speaks to them on an emotional level.
[bctt tweet="The problem-driven approach to keyword research is built on empathy." username="@Kevin_Indig"]
Look at the two titles, for example, and think about which one would get more clicks:
1: “Dresses for Women - Shop the Latest Styles | Brand”
2: “Beautiful dresses that make you look your best self | Brand”
The first is an example from a real site (not saying who). When you look at things from a problem-perspective, you realize that you should change titles according to the season because women look for different dresses in summer vs. winter. So, you could do something like “Beautiful summer dresses for YOUR style | Brand”.
Content must solve problems
SEO for large vs. small sites is very different, not only from a technical but from a content perspective. Large sites can capitalize on their product inventory or user-generated content for SEO. Sites like Airbnb, Pinterest, Facebook, eBay, or Eventbrite have a big natural contingent of pages that they can target all sorts of queries with.
But small sites that cannot scale in the same fashion and rely much more on Content Marketing. Think of companies like DollarShaveClub, Salesforce, Hubspot, Mailchimp, Buffer, and many Shopify stores. The problem-driven keyword research process is more suited for them than others, even though not exclusive.
You can also use the problem-driven approach for paid campaigns, social media strategies and video optimization. Not just the content that comes out of the research, but also the questions and problems themselves. That’s the beauty of problems-driven marketing: it’s channel-agnostic.
The classic approach to keyword research is outdated. The problem-driven approach leads to higher-quality content and looks beyond the search engine. When content solves real-life problems, you feel the business impact.