An app can have thousands to millions of users. Identifying and understanding app users by segmenting them into niche segments, improves the effectiveness of promotions and more importantly allows app publishers to personalize the app for users. Marketers have known and incorporated segmentation in their strategy since the 1950s.
How do various segmentation and targeting techniques apply to mobile apps? But first, let’s recap various segmentation and targeting techniques we have come to know.
“who they are”
Segmenting users by who they are, for example, if a mobile commerce app want to target to shoppers, you may think of women between 26 and 42 as a primary segment to target.
Demographic segmentation has been in use since 1950’s and it’s effectiveness is questionable as it can be easily be replicated by competitors. See why relying on demographics alone is limiting in this well researched think with Google article.
Organizational demographic is a segmentation technique that bring the enterprise into the mix – “who they work for”. Segmenting based on the industry, revenue, number of employees. For example, People who work for MasterCard.
“where are they from”
Segmenting users based on their geo-location, locale or region, for example, people from NY are more likely to sign up for weather alerts app in winter.
“what technology do your users use”
Segmenting based how users are using your app in terms of device model, device manufacturer, cellular carrier, size of screen etc. for example, people using Apple iPhone with AT&T versus people using a value phone over metroPCS
“what users say”
Segmenting based on user’s expressed beliefs. For example, people who responded to a survey saying they have a subscription to WSJ. On mobile, it is much harder to ask survey-like questions.
Polls and rating are common, but why ask if you can figure it out? An app should not ask anything it could work out using sensors available in a mobile device. Sensors profoundly change what an app can know.
“what are their values, interests, opinions and lifestyles”
Segmenting based on users values, opinions and lifestyle. For example, people who use fitness apps, or have a huge music collection, or have multiple photography apps. Psychographic data is not always attitudinal, i.e. collected as an expressed belief. For instance, an app can collect psychographic data based on what users click on in a content feed.
“how users behave and what they do, in your app”
- Do they respond to specific push notifications and in-app messages?
- Do they research before buying in a mobile commerce app?
- What in-app purchases have they made in the past?
For example, people who are engaged with your app and read at least 2 articles on WSJ app on a daily basis.
Generally, what users are doing your app is a much better way to determine meaningful segments than demographic, geographic, technographic or psychographic segmentation alone.
Relying on demographic, geographic, technographic or psychographic segmentation alone? Sorry, you missed the candy-crush-saga-playing 76yr old male & calculus-loving 10yr old girl.
Marketers who try to reach their audience solely on demographics risk missing more than 70% of potential mobile shoppers – Mobile search & video behavior analysis, Millward Brown Digital, U.S., January-June 2015
See why relying on demographics alone is limiting in this well researched think with Google article.
See how Pyze does automatic segmentation using Intelligence Explorer.