Expert Interview Series: Michael Oiknine Of Apsalar On Measuring The Use And Effectiveness Of Mobile Apps for Glance

9 min read
Aug 23, 2017

In the early days of mobile apps, for many companies it was simply enough to put out an app to say they’d done it. They didn’t think about long-term usefulness and longevity.

As the market has developed and become more competitive, app developers have had to get more business savvy. If that doesn’t happen, all their hard work might be for nothing if the app languishes in the app store.

We talked to Michael Oiknine, the CEO for the mobile marketing firm Apsalar, about measuring the use and effectiveness of mobile apps to help your apps stand out from the competition.

Counting the number of downloads used to be good enough to measure an app’s engagement. What are some reasons why this approach isn’t good enough anymore?

Installs (launched downloads) are often the first figure that app marketers focus on. The ranking systems in the app stores encourage this because installs are a primary metric that determines an app’s visibility in the app stores.

It’s also important to remember that in the early days and in categories beyond gaming, launching an app was often more motivated by a desire to check a box (“Me innovative! Me have app!”) than to create a sustainable business channel. When you are just checking a box, a big-number vanity metric like install counts makes people puff out their chests and feel powerful.

But the dynamics of apps and app marketing have changed in a big way. In the US, mcommerce is growing 23 times faster than offline retail, according to comScore. And growth rates in countries outside the US, from post-industrial countries like the UK to developing economies like India, are often even higher. In every market, companies are looking at apps as a high potential revenue channel. Whether you make games or sell airline tickets, it’s all about making money these days.

Savvy app marketers know that an install is only part of the battle to get your app into the routine of a user. Whether you make gaming apps or offer an entire catalog of products in a retail app, the real driver of success is how many engaged and/or transacting users you have. More than 80% of apps have fallen out of usage by 30 days after the install date. Such inactive installs have no long-term business value.

An install is necessary for revenue to be generated, but the quality of installs varies enormously. One of the most basic things we tell our clients is to make sure they analyze their marketing spending based upon the quality of installs rather than simply the raw number of installs.

For companies to ultimately know how an app is performing, they need to measure engagement. What are some of the most useful metrics for measuring engagement?

In my view, you should measure every action that relates to your core business objectives. When in doubt, measure it out. If a consumer does something in an app, it can be measured. And it should be.

We classify consumer actions or events into four big buckets:

Validation Events: Events that help identify the user (anonymously, of course).
Engagement Events: Actions that a consumer takes that indicate involvement in the app and presage long-term usage.
Intent Events: Actions that indicate that the user is considering and preparing for a purchase.
Conversion Events: Actions and information that are communicated after a purchase takes place. These include characteristics of what was purchased – i.e., specifics that help us get a richer and more comprehensive understanding of each customer.

The actions that fall into each “bucket” vary by category and your KPIs.

For an ad-supported gaming app, launches, time spent and gaming milestones like level completions can all be great indicators of engagement. For freemium games, every step in a potential in-app purchase (IAP) should be measured. So searches, adds to cart, and each step in a buy process are critical things to measure.

For a retail app, it’s important to measure each of the steps in a buy process, including product searches, clicks on items, examinations of available colours, availability checks, explorations of sizes, adds to cart, and then every stage in the buy process.

For travel apps, I’d say flight and hotel lookups, destinations, classes of service, price checks, and so forth.

We have actually published a white paper on the things you should measure by category entitled “Getting Started with Mobile App Measurement and Attribution” that provides easy-to-use grids to identify the engagement measures that are most important by category.

How can some of those insights be leveraged into making an app more profitable and desirable to users?

The million dollar question. How is measurement actionable? Engagement measures are fantastic ways to analyze your audience and create high-performing audiences for remarketing.

The simplest example here is reactivating cart abandons. When an individual places an item into a cart, it’s clear that they are getting closer to making a purchase. But many apps lose 90%+ of their potential sales due to abandons. Data and audience segmentation tools can help you “close” abandoners.

Another example is driving heavy buyers to make an incremental purchase. You can actually identify and focus custom marketing efforts specifically on these individuals with offers and messages tailored specifically to them. We simply identify people who have made >N number of purchases and deliver that finite audience to your partners and platforms. 

When in doubt, measure it out. If a consumer does something in an app, it can be measured.Click To Tweet

Still another example is reactivating lapsed users by using segmentation to identify users that haven’t launched the app in N days and then delivering push notifications, CRM emails, and even advertising specifically to these people so that they return to the app.

One additional way to use engagement measures is to analyze where users appear to drop off in excessive numbers. This can help you spot bottlenecks in your buying processes or content. You can fix them, thereby eliminating major barriers to your potential success.

One of the metrics app developers have been paying attention to is how much time a user is spending on the app. What are some different methods for tracking how much time users are spending on the app?

The thing is, in most cases time isn’t directly related to the KPIs of an app; so it’s not something we usually recommend as a primary measure of app vitality. In addition, time is also a potentially deceptive metric because often teams are inclined to compare app-time-spent to web-time-spent, when the two experiences are fundamentally different. The other thing is that more time spent isn’t always a good thing as it can mask real problems like poor app responsiveness.

The first thing I ask when people want to measure time is to ensure that time is directly related to their KPIs. I prefer hard metrics to surrogate metrics. If you have an ad-supported game app, for example, time may be a useful measure, though often it is the number of rounds played that relates directly to ad views, not time. For apps primarily designed to sell goods, I would recommend customer actions versus time.

The point is to measure the right things, not necessarily the easy things; though in reality, mobile app measurement tools should make it pretty easy to measure whatever you need to. There are ways to measure time, but I’d rather leave it that time isn’t a terribly relevant measure for the VAST majority of apps. User actions or “events” are a far more useful metric.

Long-term engagement is ultimately the goal for app developers, which can be measured by how many times a user opens the app. How many times does someone have to use an app to make them a loyal user?

We hear this question a lot. People want a magic number (like “6”). But the reality is, it depends on:

• The purpose of the app
• Its utility
• The target audience
• Its emotional benefits or payoff
• The level of time commitment required per use

I think first about the utility an app delivers and how often that is relevant in someone’s life.

For example, a game’s utility relates to entertainment and diversion, which can be relevant one or more times a day if the gaming experience can be enjoyed in short bursts.

By contrast, one fast-growing app sector is “companion travel,” where (for example) a hotel chain creates an app to make it easier to check in, reserve hotel facilities, get restaurant recommendations, etc. Clearly, we shouldn’t expect those apps to be used much when someone ISN’T traveling.

As app marketers, what we want is to routinize the use of an app when it is relevant. The cadence and triggers for marketing actions should be connected to the relevant moments of opportunity for that category and user.

One trend I will note, however, is that some apps are proactively increasing the number of occasions where the app can be relevant to an individual’s life. We have lots of retail clients in the developing world, for example, that employ huge content teams to provide advice, entertainment, and category-specific news that people turn to even when they aren’t looking for a new pair of jeans.

The standouts produce content that is every bit as good as what you would find on fashion editorial pages, but tailored specifically to user personas in their developing markets. India, in particular, is often way ahead of the rest of the world in this regard. We work with most of the leading retailers there who are developing content that sells but are also draws for daily app usage. And given the impulse nature of category segments like “fast fashion,” daily use also drives considerable revenue.

Apsalar measures an app’s performance across a wide range of networks, from Facebook to advertising networks. How do you measure these insights, and what are some ways the numbers can be interpreted?

We work with more than 700 media companies who share data with us about the consumer actions that they drive. Most app media is purchased on a cost-per-install (CPI) or cost-per-remarketing event basis. A vendor wants to maximise the number of installs or events it drives, because that’s the determinant of how much they get paid. Through data-sharing agreements, we identify the vendor that drove a particular install or event. If more than one company drives a click before an install, we de-duplicate the reporting so only one vendor is credited for a purchase. De-duplication alone can save clients 20% or more of their total media costs.

But it doesn’t stop there. As I mentioned earlier, our goal is to provide measurement metrics so that clients can optimise their businesses to the KPIs they care about most. Our approach is to measure every media vendor a client uses based upon metrics that relate specifically to the client’s business objectives.

Many clients are focused foremost on revenue generated per dollar invested, or return on ad spend (ROAS). These companies choose us because of the ability to measure ARPU across long periods of time, not just one month or three months as some competing platforms are limited to. For most apps, measuring ARPU over 30 days is patently absurd; in many categories, it takes more than 30 days to make a first sale! So we enable companies to track sales over two years or more.

Optimising to the right metrics has transformative effects on businesses. Let me illustrate with an example right from our data. A retail client of ours is focused on driving maximum revenue for every marketing dollar invested. It has lots of media vendors, but let’s focus on two for simplicity. One drives installs at $4 each, and one charges $6 per install. But the average LTV per install is $214 for the first vendor and $545 for the second vendor.

When we began working with that client, they were pouring more and more money into the FIRST vendor because their CPI was 1/3 lower. But when they were able to optimise their spend based upon ROAS, they reallocated spending, shifting dollars to the SECOND vendor. Because the second vendor actually drives $91 per install ($545/$6) versus the other vendor that drives $53.50 ($214/$4).

By measuring every vendor based upon metrics that relate specifically to a client’s KPIs, you can see which are most efficient and change your media allocations accordingly. You can also compare the efficiency of driving incremental installs versus remarketing to existing users in order to drive specific actions.

What are some of the best examples of useful, effective apps that are especially popular? What lessons can developers learn from these examples?

The best apps combine rational utility with emotional payoff. I’m a big believer in that model.

If you look at the casual gaming sector, the winning titles are drop-dead-simple to play, but quite hard to master. They are great distractions from the stresses of life, and pay off emotionally with early encouragement PLUS a shiny brass ring at the end that stays just out of the user’s reach for a long while.

I mentioned earlier that a growing number of retail apps in the developing world are delivering the ability to buy goods virtually anywhere, which is particularly important where retail infrastructure is uneven. But they also provide this astounding layer of content that entertains, informs, and helps people feel better about themselves.

And I love a great deal of what’s happening in the travel sector, where airlines, hotels, and car rental companies are adding features to take stress out of traveling experiences. Sure, you can book a room; but you can also get restaurant recommendations in a couple of swipes, and can check in and out without waiting in line.

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