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Not all search platforms are created equal. Developers frequently find themselves using web-backed information to guide their mobile marketing decisions. This is a common, yet avoidable faux pas. According to Apple, 70% of all app downloads come from search. So, wasting precious time and resources on web data for mobile success just yields a dead end in any efforts to increase visibility and discoverability on an app store. On the surface, web and mobile user search queries have some similarities, but their respective search capabilities and platform-specific user behaviors vary drastically.
Understanding user behavior across both web and mobile is quintessential in knowing how, why, and what users search. Yet, sometimes these differences are difficult to identify depending on a developer’s experience with web and mobile search behaviors.
Mobile marketers and developers need mobile-backed data to guide their decisions. Using web data for mobile marketing decisions is a lot like using a fork instead of a spoon to eat soup; both have utility, but for very specific situations and reasons. Let’s explore some of these differences more closely, so you can further understand the requirements of mobile-specific search to further guide your App Store Optimization (ASO) strategy.
Google Ads Keyword Planner is an invaluable tool for Search Engine Optimization (SEO). Google Ads Keyword Planner uses three categorical descriptives for all user search queries. Web queries by nature, are usually a place users stuff as much information and keywords in as possible. And let’s be honest, we’ve all popped in vast amounts of text equal to the size of the dictionary in a search bar before. Moreover, users expect pinpointed and hyper-specific information directly derived from their search query. How, what, and why users search what they search for relies on a multitude of factors; however, there are three different search queries Google Ads Keyword Planner categorizes on web platforms:
The “Do” transactional query
“Do” transactional queries typically include an actionable verb, such as, “buy a red dress”, “record live video”, or “buy a concert ticket”. Users expect to find results that enable them to perform their desired action, and they expect the results to be relevant to their needs associated with that action.
The “Know” information query
The “Know” Information query search is a go-to for users looking for specific and relevant information regarding their search query. As the name aptly suggests, a “Know” query typically looks like, “retail store near me”, “who sings ‘everybody’s working for the weekend’”, or “nail salon hygiene standards in Idaho”. Users performing this type of search query expect to find a plethora of information that directly answers their intended question and any possible supplementary information related to the query.
The “Go” navigational query
In the “Go” Navigational Search query, users expect their search query to help them “go” to their desired web destination or platform. Users could be searching for broad terms or more specific terms to perform a “Go” query. Typically, a “Go” query looks something like, “Lady Gaga Facebook page,” “Chicago Bulls merchandise store” or “Free online games.” While some of us may be guilty of Google searching “Google” once in a while, “Go” searches are one of the most popular search queries among users who want direct access to what they’re looking for simply and easily.
Web search queries in their aggregate, are simultaneously more specific and often employ more terms and phrases. Unlike mobile search queries, web search queries can be longer, more specific, and drawn out to pinpoint exact user phrases and terminology. On mobile, search queries are short, to the point, and typically have to do more with a lot less.
Mobile search queries
A study reveals that 80% of all search queries in the app store range between 2–3-word phrases — a vast difference compared to the often drawn-out and lengthy web search query. As you can see, mobile searches and web searches are, in fact, very different. What works for the web simply does not work for mobile.
The fundamental difference lies in user intention; this helps explain why user search behaviors often differ between web and mobile search queries. For mobile, developers and mobile marketers must strike a balance between highlighting app features and app branding to adequately capture user intention.
To illustrate, let’s look at the following example for a popular and hypothetical app called Widget King. Widget King is an app that allows users to buy and sell valuable widgets and lets them exchange their widgets for concert tickets, gift cards, and other cool experiences or things.
On paper, Widget King may assume their user search queries look like this:
Search queries: “buy and sell widget,” “buy a widget,” “sell a widget” and “buy widget app”
However, it’s important to remember that mobile search queries must capture user intent. In reality, users may actually be performing searches more attributed to some of Widget King’s specific offerings, or they may be using different terminology altogether:
Search queries: “buy gift card,” “widget exchange,” “concert widget” and “trade my widget”
But how exactly can mobile marketers and developers target these terms? How should they know which terms their users are using? While it may be difficult to capture user intent, the process of ASO allows users to more accurately identify which search queries, terms, and words best match their app with the user’s intent. ASO yields more chances for discoverability, visibility, and relevancy on an app store — much like what SEO does for web pages.
Making the switch to mobile
Users initiate a search query in mobile expecting web-like results, so it’s up to mobile marketers and developers to deliver those expected results in the best way they can. Web results often have the ability to target adjacent terms without the constriction of limited search query population.
Breaking up with web search data is hard to do, yet it’s one of the most important shifts a mobile developer can make to improve app performance. Developers and mobile app marketers can effectively increase their visibility and organic performance on the app stores just by shifting their search data strategy. However, making the switch to mobile data requires developers to gauge their audience’s search behaviors on a more granular level.
To do so, developers must capture user intent by optimizing their app metadata assets to include any relevant terms a user may be searching for. While capturing user intent is fundamental to effective mobile search targeting, developers should still aim for relevancy and target market refinement. If a developer decides to target a broad range of terms and keywords that aren’t related to their app or brand, they lose their opportunity to increase their visibility to an audience that is the most receptive to their value and features.
Mobile search requires app metadata and keywords to do a lot more with a lot less. User intention is the foundational difference between web search and mobile search. Thus, mobile marketers and developers must go above and beyond web data to more accurately and effectively capture their users.
Dave Bell is CEO of Gummicube.