Why Web Search Data doesn't work for App Store SEO

February 04, 2015


If I told you there was a user acquisition channel that:

  • had a CPI of less than $.05
  • attracted the highest quality users
  • and created a competitive advantage the longer an effort was made in this channel

.... it would be crazy to attempt to go after this channel with unrelated data, with tools that are not built for the job. What if your competitors have identified and invested in enterprise-quality App Store SEO tools  and your team has not?

App Store Search is #1 in App Discovery....

It is estimated by several sources that search and browsing makes up at least 50% of mobile app downloads.  Neither Apple or Google release this data, but various polls show mobile app discovery is still driven by searching the app stores. [caption id="attachment_168" align="aligncenter" width="600"]recommendations A bit dated - but you can see the many ways users say they discover mobile apps[/caption] For the best monetizing mobile apps, their LTV>CPI spread is  large enough that almost every possible user acquisition channel from TV Ads to Outdoor advertising works for them. Looking at top grossing for today - 20 of the top 25 are Gaming Apps, with 3 of the other 5 subscription-based apps (Pandora, Spotify, Match, Zoosk). Your app is competing for paid users with these guys.  But not likely competing with them in search results.

.....and #1 in Acquired User Quality

According to an Appsflyer study - the user acquisition channel with the highest user quality (measured by app opens) was search. conversionrates

But popular ASO keyword tools use web data!

web data vs app store dataApp Store SEO is the process for positioning an app for discovery by these user searches. But several ASO keyword tools are using web data to show traffic, related keywords and suggested keywords. If you are frustrated with your mobile app store optimization efforts, or wonder how other mobile apps are getting so many organic downloads - using an ASO service that leverages web data could be the issue.

How is web search and mobile search different?

For starters - let's look at how people search the web versus how people search on a mobile device.

3 Types of Web Search Queries

According to moz.com there are 3 different search queries users generally perform:

1. “Do” Transactional Queries- Action queries such as buy a plane ticket or listen to a song.

2. “Know” Information Queries- When a user seeks information, such as the name of a band or the best restaurant in the area.

3. “Go” Navigational Queries- Search queries that seek a particular online destination, such as Facebook or a homepage of a sports team.

A search with the Google Keyword Planner for "edit photos" shows these results as being the most relevant: Google Web Data for ASOAs you can see web search results from the Google Keyword Planner fall into the 3 different types of web search queries.

1. “Do” Transactional Queries- “Edit photos” or “Edit photos online”

2. “Know” Information Queries- “How to edit photos”

3. “Go” Navigational Queries- “Program to edit photos”

Google Keyword Planner seems to confirm moz.com's framework for web search.

Mobile Search is 2-3 word Phrases about Features

According to data Gummicube has collected from mobile users since 2011, “80% of all search queries in the app store are 2-3 word phrases related to app features.” The balance is generally 1 word app/brand name searches.

  • Features - "chat", "share photos", "learn a language"
  • App/brand name - "Facebook", "Instagram", "Duolingo"

So how are users searching for mobile apps on their device? Using our software Datacube, the results for the same search term edit photos: gummicube asoSo for the same query using mobile search, you can see the results are feature and brand based:

  • Feature Queries - “photo blender”, “photo editor”, “photo effects”, “add text”, “photo collage”, “add music”
  • Brand Queries - “camera 360”

Does your keyword tool use web data?

Does the ASO or keyword tool you use to target keywords, phrases and features provide volume estimates?Bad ASO Tools I am sure I am breaking some internet rule posting two memes in one post - but I just figured these out and I think they hammer the point home...

You can't optimize your mobile apps using bad data!

Can't optimize for maximum exposure in the app stores....

...to acquire valuable, relevant organic installs....

...trusting your efforts to tools that are designed using the wrong data.

If you are using any “ASO Tool” which relies on web based search data then you are using the wrong dataset.

Modern Mobile App Store Optimization

Successful Mobile App Store Optimization relies on understanding user behavior when searching the app store. Web search and mobile search are not the same. Mobile search data from  Gummicube is the most effective way to find relevant and trending  keyword phrases. Search provides one of the most cost-effective user-acquisition channels available to mobile app marketers.

You are not going to be able to compete using ASO keyword tools that use web data.

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