100+ underserved topics in Aged Care – How to use AI to find low-competition keywords
In a previous post, I presented three topics in aged care that were underserved by Australian websites:
- Nutrition for the elderly
- Topic based on age that may include all the questions people ask about a 90-year-old person
- Q&A for caregivers
Once we have found underserved topics, we don’t necessarily just want to go write one article answering all the discovered search queries.
Instead, we want to build a comprehensive content strategy. And there is a tool available that can do that much better and much faster than our own brain; ChatGPT indeed.
Start by sourcing “People Also Ask Questions”
Let’s ask ChatGPT to build a comprehensive content strategy to target the Q&A for caregivers topic.
But first, we need to make sure that we have a nice database of keywords to feed ChatGPT with.
So we go to Google, and we search for a question a caregiver may search on Google such as “what does it mean when an elderly person sleeps a lot”.
And we use a tool called SEO Minion to download all the similar questions people also asked Google. We get these types of questions:
- What would cause an elderly person to sleep all the time?
- Is it normal for elderly people to sleep all day?
- How much sleep do 90 year olds need?
- How much is too much sleep for elderly?
- Why does my 80 year old mom sleep so much?
- Why is my mum sleeping all the time?
- Is it normal for an 80 year old to be tired?
And we have hundreds more of these. Not all of them are relevant, though. Many are redundant as well. And that’s where ChatGPT is going to be very helpful.
Get ChatGPT to clean up your database
First, I ask Chat GPT to review all the questions and to come up with an exhaustive list of unique questions. It returned only 62 results. Each question was unique.
I then ask ChatGPT to convert these questions into the simplest and most representative search queries.
This way, we have a broader query for each question that will be useful to group all the highly similar questions.
For example:
- How do you encourage an elderly person to eat more? =>> Tips to increase elderly appetite
- How much sleep is normal for a 95-year-old? =>> Normal sleep duration for over 90-year-olds
Having a simpler query representative of the question is helpful to build headlines, or to have a better understanding of the type of content needed to answer the question.
Once I had all the queries I needed, I asked ChatGPT to propose categories to regroup the questions and queries.
Unfortunately, the categorisation from ChatGPT is not always accurate. It requires a bit of a human touch to have the best category structure. So I had to edit them a bit. I was still pleased by most of the categories ChatGPT decided to allocate to most queries.
The categorisation allowed me to spot questions that were too broad for Aged Care such as “sleep disorder”.
Ask ChatGPT to generate new unique questions out of the current database
Once my spreadsheet with categories, questions and representative search queries was all clean and well organised, I asked ChatGPT to propose new ideas following the same query & categorisation pattern.
All the results were perfect. Here are a few examples:
Elderly Nutrition | What foods are good for elderly with diabetes? | Diabetes-friendly foods for elderly
Elderly Nutrition | What are the best foods to eat before bed for elderly? | Best bedtime snacks for elderly
Elderly Hygiene | How to properly care for an elderly person’s teeth and gums? | Oral care for elderly
Elderly Hygiene | What is the best way to help an elderly person shower? | Assisting with showering for elderly
All the other queries can be found in this spreadsheet.
If you are interested in knowing more about how to use ChatGPT for your own content strategy we would be more than happy to talk to you.
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