Yesterday I started an ASO challenge for one of our apps that has been abandoned.

This app is in the mother-baby niche, heavily targeting new parents. If you didn't read the challenge post, you can find it here . Let's go!

The first step is checking competitors' ranked keywords. I chose 2 competitors with good brand awareness and 2 competitors that invest heavily in ASO without brand awareness.

That's because I want to find all available keyword gaps and opportunities. I will use Appfigures for this. But you can use any tool to find competitors' keywords.

With the 4 competitors I selected and my app's ranked keywords for the US, there are more than 3K keyword combinations.

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competitor keywords 

The keywords are ordered by popularity score. As you can see, there are many junk keywords in this list. Keywords are not just words; there is a context and search intent behind them.

For example, look at the "sleep tracker" keyword. It's very popular and has a popularity score of 58. There are 1785 apps listed for this search in the US.

However, my niche is babies and new parents. Many adults are searching for a "sleep tracker," which is not my target audience. This is just an example; you should find keywords that have high relevancy and search intent for your app.

"baby tracker" looks like the most popular one relevant to my niche. There are 1934 apps, including ours, already listed for this query. Additionally, my competitors have good rankings for this keyword. Huckleberry is listed at rank 5, and Sprout's Baby Tracker app is listed at rank 1!

Let's dive into this keyword.

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search results for \"baby tracker\" 

Okay, there is no opportunity here :/ Everyone in this niche, targeting this keyword. It's not easy to rank in the top 10 for the keywords like this.

But there is a huge search traffic here. As part of my ASO strategy, I will definitely target this keyword even if I can't rank in the top 10 at the beginning.

Why?

Because some apps in the top 10 made major ASO mistakes. I will talk more about it later in this series.

What's next?

We need to find the main keywords that can appear in many combinations. You can brainstorm or try to identify key phrases using ChatGPT.

Here are the search queries from ChatGPT. Not bad huh?

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ChatGPT suggestions 

These queries don't need to have a high search volume; we are aiming to identify single-word roots that will frequently appear in other keyword phrases.

We can simply list the following:

  • baby
  • tracker
  • sleep
  • milestone
  • care
  • newborn
  • parent | parenting
  • schedule
  • breastfeeding
  • development

Let's go back to Appfigures and search each one in the Competitor Keywords.

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keywords that contain \"baby\" 

  • baby: 233 keywords out of 3,248
  • tracker: 280 keywords out of 3,248
  • sleep: 325 keywords out of 3,248
  • milestone: 15 keywords out of 3,248
  • care: 28 keywords out of 3,248
  • newborn: 20 keywords out of 3,248
  • parent: 31 keywords out of 3,248
  • schedule: 41 keywords out of 3,248
  • breastfeeding: 27 keywords out of 3,248
  • development: 21 keywords out of 3,248

Ok, you can extend the list further if you want, but that's enough for me.

What did we say? Context and search intent are the most important. Even if you rank #1 for a keyword that is not relevant to your app, it's impossible to stay there for long.

Because people will find you irrelevant and won't download you, conversion rates will drop, and the algorithm will slowly start to drop you from that ranking.

Therefore, we choose our target keywords wisely. For instance, a query containing the keyword "breastfeeding" will be a perfect match for me, allowing me to target it confidently.

We've picked out the main words we'll aim for. If we focus on these keywords for our ASO strategy, we'll cover over 1,000 searches that relate closely to our app. Right now, our app is only showing up for 146 search terms. This is a good starting point for us.

That's it for today. In the next post, we will try to find which queries have opportunities and gaps by using the main keywords we found.

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