The Advanced Guide to APP ANALYTICS & MARKETING

Transcription

1 The Advanced Guide to APP ANALYTICS & MARKETING

2 TABLE OF CONTENTS Introduction Revisiting the basics Getting past the Hotel Problem A deeper look at the five crucial metrics In-depth with attribution In-depth with segments In-depth with retention In-depth with events In-depth with funnels Discovering profile & behavioral data Advanced app marketing Using attribution for better acquisition Creating your app buyer personas Utilizing user segments Utilizing profile data Optimizing your funnels with messaging Working in automation What s next? Reading list

3 it means that by now you ve already started tracking and interpreting your app analytics. That s fantastic. It means you know that in order for your app to be successful you have to measure, translate and optimize to improve. With just a quick look at your metrics, it s easy to see that there s a host of data ripe for optimization. Diving into those analytics is tempting (and encouraged), but in order to gain the best insights possible, you need a keen eye and the right resources. Because even the best marketers can hit the analytics wall early on. You know that wall: the one that suddenly appears when it seems that despite the 20 reports you ve created, you still can t answer one simple question. And without that insight, you re missing an amazing opportunity to engage your users with truly smart app marketing. Using techniques like push and in-app messaging, you can retain, delight and encourage loyalty from your app users, impacting long-term results instead of concentrating only on downloads to assess app success. Analytics are the foundation of great app marketing, and you can t have one without the other. Using this guide, you ll be able to supplement your analytics knowledge even further with advance insights and how-tos. You ll also learn how to harness those insights to run app marketing that works. 1

4 REVISITING THE BASICS If you haven t already, consider reading both our Beginner s Guide to App Analytics and the Beginner s Guide to App Marketing. These guides will give you an introduction to some of the most important app analytics metrics, definitions, and techniques you need to know. USERS Tracking your users is an important first piece of the puzzle. Once you know your user base and current active users, you have a baseline for improving engagement to increase users across channels and identify those who have dropped out of a desired funnel or those within your market space who haven t yet downloaded your app. SESSION LENGTH Session length is measured as the period of time between app open and close, or when the app times out after 15 seconds. It indicates how much time your users are spending in your app per individual session. SESSION INTERVAL Session interval is the time between the user s first session and his or her next one, showing the frequency with which your users open the app. This can signal the immediate value gained from downloading and running the app. TIME IN APP Time in app tracks how long a user was in your app over a period of time, e.g. user X was in my app for three of the last 24 hours. It s another metric for identifying how often your app is being used, and is an indicator of how valuable your app is to users. ATTRIBUTION Attribution analytics represent the number of users who download and install your app from a certain location - essentially, it identifies the source of the acquisition. This metric is especially important to track when you run campaigns through paid partners like Facebook to promote app downloads. Attribution reports track how much money you re spending to acquire these users and what they re doing when they get into your app. 2

5 SEGMENTS Segments are groups of users who did or did not do certain events, or pair of events in sequence, and can be a helpful way to identify specific relationships of usage between different parts of an app. SCREEN FLOW Screen flow tracks exits by screen, progression through screens, and total occurrences of visits to screens, visualizing the typical visitor interactions in your app. With screen flows, you can look at a particular screen in your app and see both what users did while on screen and where they went afterwards. In looking at how users navigate your app, you can get a clear sense of problem areas, conversion road bumps, and drop off screens. EVENTS Events are the actions users take within your app, and can be individually defined by your goals, such as article reading or posting to a social network. Events also have attributes associated with them, which are added details describing the event action, and will help you get granular insights about those actions. FUNNELS App funnels are defined the same way as web funnels: they are the process you want your user to follow to convert on a desired action. Funnels are defined by the events completed to reach that desired action, so tagging events and defining the funnel flow should be a coordinated effort. This helps you identify where drop-offs happen in the conversion paths of your app. % RETENTION Retention is measured as the percentage of users who return to your app based on the date of their first visit. Retention tracking highlights your most engaged and valuable users, creating better targeting capabilities and allowing you to track in-app purchasing by level of engagement. LIFETIME VALUE Lifetime value is your primary revenue metric, representing the financial value of the app and how much each app user or customer is worth in his or her lifetime. It can be split out by average monthly value or value per customer, capturing worth over time financially and also in terms of loyalty and evangelism. 3

6 APP MARKETING BASICS What we mean when we say app marketing today App marketing is best defined in two parts as: 1. A strategy that drives downloads and new users 2. The marketing campaigns you run to engage, retain, and convert app users From paid acquisition to purchasing, these campaigns work to move your user through your desired funnel, delivering higher long-term value and promoting engagement over time. In this sense, app marketing is strikingly similar to web marketing: both serve to drive value, revenue and loyalty over time. Four definitions to know Your app marketing will follow this basic progression: ACQUISITION INTERACTION (USING PUSH & IN-APP MESSAGES) PERSONALIZATION You discover new users, interact with them through the app to engage, and then graduate to personalized marketing based on historic data. Within that pathway, there are certain tactics you should employ: ACQUISITION The strategy of getting users to download and install your app from a certain location; through organic search, word-of-mouth, paid campaigns or in-app referrals. Many brands typically invest in and measure paid acquisition campaigns from channels like Facebook or ad networks. PUSH MESSAGING A notification a user receives when he or she is outside of your app or in another app. The message is pushed to his or her home screen. IN-APP MESSAGING A notification a user receives when he or she is inside of your app, currently interacting with it. PERSONALIZATION Creating an app experience or marketing campaign customized to an individual user s preferences. 4

7 TAKE ME TO THE Let s dive off the deep end into your analytics and explore the nooks & crannies that exist in mobile metrics.

8 GETTING PAST THE HOTEL PROBLEM First, let s tackle a common issue in analyzing user data. Say you have a customer who rents a room in your hotel for seven days. For all of those seven days, she s just one customer. However, if you were to count each day as unique, that customer is incorrectly counted as seven customers. This is the ever-persistent Hotel Problem, which surfaces often in SaaS analytics. How does it apply to your metrics? Well, if you re tracking unique app users in your analytics, this number is always going to be different from your total number of users within a given time (typically a day or month). Most analytics tools provide a daily breakdown of users but one area where different tools show varying behavior is measuring users over different time periods. CONSIDER THE FOLLOWING SCENARIO: 1. A user installs the app on Monday 2. On Tuesday the user comes back Looking at a daily usage chart will show two days each with one user. However, changing the time range to look at both days together should only show one user since Monday and Tuesday s usage was from the same user. A variation on this issue is when your new and returning users add up to more than your total user count. The definition of a new user is one who is using an app for their first time - the session immediately following that first one, even if it s on the same day, is a returning session. As a result, a user who uses the app for the first time and then a second time on the same day will be counted as both a new and a returning user. The Hotel Problem is, for the most part, unavoidable, so the best way to beat it is to be aware of it! Many tools sidestep the issue by only showing user counts on daily, weekly and monthly increments. (With Localytics, however, it is possible to select any arbitrary date range and the total user counts provided for those time periods will have all duplicates removed). 6

9 5 CRUCIAL METRICS #1 IN-DEPTH WITH ATTRIBUTION All app marketers know: you need to acquire users in order to have any analytics to track in the first place. The goal of any good acquisition campaign is always to drive app downloads and new users. If your app isn t being downloaded, you need to go back to the drawing board to design a more alluring acquisition strategy. But when it comes to tracking which campaigns are the most successful, you can t stop at downloads. If you like to frequent restaurants, you re a prime example of this. Maybe one day on your way to work you see a sign advertising a newly-opened restaurant in your town. A couple of nights later, you decide to stop in for a meal. While the meal isn t terrible, it s also not spectacular, so you don t plan on going back. If you were a restaurateur, would you call that one visit, that one transaction, the activity that should determine the profitability of your business? No chance. So, why would you count downloads, the first introduction to your app, as the primary metric for success? Someone can download your app without ever opening and interacting with it. Unless the user is engaged, returning again and again and actually using the app features, their download counts for nothing. That s why, when it comes to tracking attribution, you need to go further. Here s how: SEGMENT BY ACQUISITION CHANNEL (AND KEEP AN EYE ON BEHAVIOR) Segment the users you gain from different campaigns by channel, like Facebook, Greystripe, or Impact Radius, to see which source brought in the most new users and has the highest number of sessions per user, along with other key behavioral results that demonstrate campaign value. The goal here is to gain insight into how your paidto-acquire users act in-app (versus your organic users) and to see which groups of users from particular channels use the app more - or better. 7

10 For example, you can use behavioral analytics to determine if your paid-toacquire users are becoming powerful influencers or super fans, demonstrating a better ROI and helping you to pinpoint worthwhile channels. If, instead, these users are under-using your app, you can clearly identify which groups and campaign sources need revisiting, and test different paid channels, types of ads, and targeting techniques. ALWAYS MEASURE LTV You remember, LTV, right? The lifetime value of your user is going to be your #1 ROI metric. When deciding which acquisition campaigns were worth their salt, pair engagement metrics (number of sessions, session length, conversion events, etc.) with the user LTV broken down by each channel. ENGAGEMENT METRICS & USER = LTV ROI BY CHANNEL It s entirely possible that one campaign delivers a higher number of downloads and new users, but ends up with users who have a lower LTV than a campaign that resulted in fewer users. That s why it s so easy to misjudge an acquisition campaign early based on preliminary data. If you have a figure in mind, particularly a number of desired acquired users, it can be easy to write off a channel that didn t deliver based on your initial goals. Don t count your eggs before they hatch (or your downloads before they launch): always measure LTV. 8

11 When you take into account all of the metrics that impact your acquisition strategy, you can determine results like: Users acquired through Facebook are more avid social sharers than organic users Your Greystripe campaign resulted in more male users than female The total revenue (based on LTV per user) of your Millennial Media campaign is 5% higher than that of other channels (In the marketing section, we ll talk about what to do with this acquisition data, and how to improve your campaigns. For now, let s keep going with our analytics deep-dive.) #2 IN-DEPTH WITH SEGMENTS It would be difficult to analyze your app without understanding your users. That s where segments come in. A segment is defined by users who did or did not do certain events, or pair of events in sequence, and can be a helpful way to identify specific relationships of usage between different parts of an app. A segment is created by determining three things: What time range you want to draw users from Example: Users from the last seven days... EVENT The first event a user needs to complete to qualify for the segment Example: Who shared an article... An additional action taken (only necessary if you want to create highly-targeted segments) Example: And then ed the article to a friend. Once you have the criteria set up, your segments will dynamically update as new users qualify. Segmentation allows you to answer questions about your user base and better understand the in-app behavior of various audiences. You can determine which users added an item to their cart, but never checked out, or users who ungated a premium feature, but haven t used it. YOUR SEGMENTS ARE 9

12 This means that you have complete control over creating the user segments that are most important to measuring your goals. Segments are also the tie that binds your analytics to your marketing - once you ve created a segment representing your target audience, loyal users or least active customers, you can engage those users with a marketing campaign specific to their historical behavior or interests. Here are some sample segments: $ $ $ ECOMMERCE SEGMENT: COUPON USERS These are people within a mobile commerce app that buy when there s a discount. You know them because you can look into their behavior and see that they have never made a purchase of a product that was full price, but they have made one or more purchases with a coupon or with a special offer. Understanding buying behavior is crucial to determining how to market to this segment. Second screeners engage with an app for a TV show or broadcast network while the actual show is going on. They re watching their favorite show and simultaneously they have their tablet or phone in front of them, discussing the show, perhaps voting on who to kick out, or maybe just looking up trivia about the show or actors. You can determine this group by the time that they re interacting with the app or, in the case of network apps, the time that they re interacting with a particular piece of content. A media junkie is not someone who reads the news, but rather someone who lives the news. Users in this segment want up-to-theminute, breaking news delivered to them at home, on their commute, at the office, and anywhere, really. You can create this segment by looking at something as simple as frequency of engagement, or alternatively the number of different locations they engage with your app during the day. If it s three or more, you can be fairly certain that they re engaging with your app at home, on the road and at the office. 10

13 ALL APPS: SOCIAL BUTTERFLIES A social butterfly is someone who is sharing or discussing your app, your brand or your content via social media. Often not just once, but multiple times. You can also create sub-groups based on the user s preferred social medium based on the specific events they re acting on within your app. If, for example, you have someone who is tweeting your content often, say three or more times per week, you can be fairly sure that they are someone who is influential or at least active on Twitter, and that it s their preferred method of sharing what they like with their friends. #3 IN-DEPTH WITH RETENTION There are two primary ways to measure user retention: 1. Users who used the app for the first time and then returned to the app 2. Users who did an event in the app, then returned and did another As you can see, one is based on tracking sessions and session interval, while the other is based on measuring two different app events. This is meant to highlight how often users return to the app and how many actions they take within the app - both important indicators of engagement. In both cases, your retention tracking will identify the start of the session or event, along with the total number of users and their repeat behavior. The first date associated (with the session or event) The number of users What percentage of those users returned after 1, 2, 3, 4, 5 + days Session-based cohorts give a high-level overview of app user retention based on app opens, while event cohorts allow you to take a more granular look at which specific events continue to engage users over time. For example, you can see which users added an item to their carts on June 1st, 2014 and then returned seven days later and completed their checkout. Or, you can see how frequently users who had their first session on December 14th, 2013 returned within a given time period (to get a sense of how long it takes new users to decide to come back to the app). They can also offer complementary insights. If you notice your session-based retention is declining, delving into event- 11

14 based cohorts can provide insight into the specific areas where usage is dropping off in your app. In a media app, for instance, you may see that retention for the article viewed event has fallen, while retention for the video played event has been improving. This could be a sign you should be serving up more video content as a way to keep users coming back to the app, boosting session-based retention. Ultimately, if you re tracking your number of users and sessions, you ll want some way to tie those together in a meaningful way. By tracking retention, you can report on not only your basic number of MAUs or app launches, but also how frequently your users return to the app and what features impact retention. #4 IN-DEPTH WITH EVENTS When tracking app events, you re able to see every action your users have taken in-app, and how those actions relate to your engagement and conversion goals. Each event you tag is one you have defined based on your business goals. If you re a fitness app, these could be workout completed, running goal hit, and workout shared with friends. If you have an app to complement your restaurant, events could be check-ins, redemptions of a free appetizer, or review left. Each of these is unique to the structure of your app, and should speak to the interactions you most want to encourage. To gain an accurate and powerful analysis, good tagging is key. But events analysis goes far beyond simply tagging events and watching the numbers roll in. Your events can actually show you a lot about the user s experience, without having to send them surveys or directly ask the questions. SOME KEY QUESTIONS YOU CAN ANSWER WITH EVENTS MIGHT INCLUDE: How many users are completing in-app events? Which events are completed more frequently? Which events lead to more conversions, or in-app purchases? Which events have the lowest conversion rates? What users favor certain events, and which user groups convert at a higher rate? Which events have more occurrences but fewer users? 12

15 Answering each of these questions will give you insight into how users are interacting with your app and, more importantly, how to make the experience better. For example, events that have low conversion rates could signal that those features are hard to find, which informs a UX/UI change or an in-app messaging campaign. Similarly, if you see events that have more completed occurrences than number of users who have completed the event, this shows you that users are completing those events more than once - why is that? And what does that show about feature popularity or, on the opposite end of the spectrum, incomplete funnels? Ensure that events are completed because of their value, not because the user encountered an error and had to start the process again. SHARE THIS ARTICLE EVENTS BY ATTRIBUTE GROUPING EVENTS Depending on the depth of your data and the number of events you need to track, you can group events to create cleaner analytics, because some events are best explored together. For example, a media app may want to view all articles read, all videos watched, and all audio content as a single Media Consumed event. If you have multiple app versions all with an abundance of events to track, creating groups can be the best way to draw big-theme conclusions and not get lost in the analytics weeds. In this case, event groups can each represent one step in a funnel. Let s stick with the media app example: your Media Consumed group could be a funnel event that automates an in-app message to share that piece of content socially or via . We often like to say not all users are the same, and that becomes particularly true when analyzing events. While you can gain some insight by tracking completed events, they only become truly valuable when you know more details about the users behind those actions. 13

16 EVENTS ATTRIBUTES CAN HELP YOU TO: Identify the split of male vs. female events completed Discover that users from Massachusetts complete more events than those from California Measure product screen viewed vs. product added to cart events Learn more about the actions of new users (in comparison to returning, engaged users) If events are the verb ( Social Action ), then attributes are the nouns (think platform, content or action). Attributes serve to identify the details of each event, so that you can see exactly what went down. Event attributes can be broken down further into specific categories, and you can even track the original sources, be it organic acquisition, Facebook ads, or other mobile ad platforms and campaigns. #5 IN-DEPTH WITH FUNNELS Once you have a deep understanding of your events, you have the foundation for defining and analyzing truly successful funnels. Each event in your funnel is a step on the way to completing a big conversion event - or, the one you have identified as the conversion event in that funnel. Much like with events, funnels differ from app to app, and are entirely dependent on your mobile goals. Within your funnels, you can track users who completed certain events on the way to converting, as well as users who dropped out of that funnel, and where they went instead (either another screen within the app or exiting out entirely). FUNNEL ANALYSIS CAN REVEAL ANY NUMBER OF INSIGHTS, SUCH AS: Splitting by devices and discovering that the experience is much worse on a slower device or one with a smaller screen Having a funnel tracking registrations and discovering that users who start the process by signing in via quit more frequently than users who sign in via a social network Having a funnel tracking article readingto-sharing with friends and using attributes to find what sections are most likely to cause a user to share Splitting by acquisition campaigns to see if certain campaigns gain users who are better at converting than others Using country and language splits to see if region or localization is creating a barrier to success 14

17 ITEM ADDED TO CART ENTER SHIPPING INFORMATION ENTER PAYMENT INFORMATION FINAL ORDER REVIEW CHECKOUT COMPLETED ORGANIC FUNNELS One key use case for funnels is to discover how users are interacting with different steps and screens within your app organically. The best example of this is the check-out process in an ecommerce app: this funnel represents the various events that need to be completed in order to make an in-app purchase (the ultimate conversion step). If you have a travel app, your funnels could be similar, such as leading to the purchase of a flight, securing a hotel room, or booking a tour. These funnels track how users naturally navigate and convert when opening your app with that purpose in mind. It is all organic, and uninfluenced by marketing campaigns, messages or special offers. Often, you can create your funnels at any time, and your app analytics should retroactively gather the right event completions, conversion rates, and drop offs. This will allow you to see historically how users have interacted with your app now, through app version changes, and as new features are made available. You ll also be able to see how user expectations may have evolved over time, allowing you to adapt your strategy and stay ahead of the competition with new and engaging features. 15

18 20% DISCOUNT PUSH NOTIFICATION MESSAGE OPENED (CONVERSION) MARKETING FUNNELS When using push and in-app messaging to engage users and promote conversions, you can and should include those messages as separate events in your funnel, including individual events such as message received, message clicked, and click-through rate. They re not just one in a series of events; they re supplemental, and meant to produce a highly-specific result. Understanding how a message performs takes more than just stand-alone open metrics - it needs to be tied to greater funnels. What does it matter if 20% of your users clicked-through on an in-app message when only 2% converted? Plus, you want to know what those users do over time - do users who received your push campaign advertising new summer deals end up purchasing more in-app after a year? For this, you need not just initial metrics, but your marketing campaigns connected in a closed-loop system to your greater set of analytics. Without these details tied together, it becomes difficult to understand exactly what campaigns were successful and why. Sure, you ll be able to tell which campaign creative got more clicks, but which of those campaigns lead to future interactions, an in-app purchase, and the greatest customer LTV? For that, you need integrated analytics, and to read your app marketing when tied to a larger subset of data. 16

19 Until recently, the most advanced analytics possible captured only behavioral data: Gathered in-app, behavioral data represents all of the ways your user has interacted with your app over time, including sessions, screens viewed, conversions, push and in-app message opens, and funnel drop offs. This data is the crux of what we have covered in this guide, as it serves to inform most of your actionable app insights and marketing strategies. By segmenting users to learn about their common attributes, interactions, and engagement, app marketers have been able to learn more about app user patterns and similarities. Plus, with events and funnels, you know exactly which features those users enjoy most. Now, we ve reached a point where marketers want a complete view of their customers, across every channel, all housed in one analytics platform. So while behavioral analytics are critical to monitoring the success of your app, they only represent a portion of information about your user. This is why we ve created Profiles, or, the ability to collect profile data: Profile data is a collection of individual user attributes, such as location, gender, customer type, credit, opens, and more, that includes user data gathered across every channel (including your app, in-store, online, , and others). Using a tool like Profiles, you can collect, manage and share relevant data about your customers across channels, enabling you to capture a complete view of who your users are. You can gather profile information from outside of your app and integrate that data into your app analytics for one holistic view of your users. You can now capture behavioral data from outside of your app, as well - including in-store purchases and visits, loyalty card usage, social actions, or QR code scans. 17

20 ESSENTIALLY: DEMOGRAPHICS Age, Gender, Location USER PREFERENCES Settings, Favorites, User Sentiment ATTRIBUTION Subscription Level, Usage Tier, Referral Source, etc. APP FEATURE USAGE Reading an article, Listening to a song, Topics Viewed, etc. OUTSIDE THE APP Events attended, Store Credit, Loyalty card usage, etc. CONVERSION EVENTS Purcahsed items & dates, Upgrades, Social actions, etc. Your business operates across a host of different channels - so, how do you ensure that your analytics accurately reflect all of your efforts? Obviously, if you re currently running app analytics, you re collecting in-app behavioral data and certain details about your app users. Now what you have to do is combine this with user information sourced from outside of your app. A great source of profile information is your CRM, as this already houses all of your users web and offline (in-store) activity, including in-store purchases, visits, signups, and other metrics. You can send Profiles to your app analytics SDK in key value pairs tied to a particular customer ID. Key/value pairs are a set of two linked items - a unique identifier and a value. For example, if you want to send information about users who are male, you can send a key/ value pair that includes the unique identifier of gender and the value of male. HOW THIS INFORMATION INTEGRATES INTO YOUR APP ANALYTICS Yet again, we turn to the ever-important user segment! When you re segmenting your users, you can create groups based on actions and attributes from outside of the app. FOR EXAMPLE: Want to know which of your users attended an event you hosted and made an in-app purchase that same week? Let s go even further: want to know which of those users then had 3+ app sessions and became more engaged with your app? Profile data kick-starts this segment. Now, you have the ultimate user analytics - a set that is representative of every piece of information you ve received about your users, their interests, and their behaviors. Not only is this critical to gaining the most accurate insights possible about your users, but it also sets you up for highlytargeted and personalized app marketing campaigns. All in all, you ll have a complete view of your app users and the data necessary to run effective campaigns. 18

21 ON THE MOST CRITICAL INSIGHTS? It s true - even with a solid grasp of your app analytics, it can still be difficult to draw the conclusions that matter. What you need to do is approach your analytics with a business lense, one specific to your mobile goals. This means structuring your segments, funnels, campaigns and user insights according to the attributes most essential to your business. Employing the right structure to your data and reading it with an eye for your long-term goals is the best way to come away with the right insights 1. First, have an app analytics platform in place that tracks organic and marketing usage data 2. Second, integrate any profile information you have about users 3. Once you have a complete database of up-to-date data, use this interactive workbook to organize and interpret your analytics (and create the reports you need) 4. Use these insights to better your app with great marketing, which is covered in the next section! 19

22 TURN MY METRICS INTO MARKETING In this next section, we ll look at how to run targeted marketing campaigns, what they tend to look like, and why keeping your platform closed-loop is essential. MATTERS If you ve gotten this far, it s because you understand the value of analytics in creating a better app. When it comes to app analytics and marketing, using a closedloop platform is having your cake and eating it too: you can gather and analyze your data and use that to run campaigns all from within the same system. It s easy to to get stuck creating a siloed system that separates your analytics and marketing functions. With that setup, you can export user data, organize it, and use it as the foundation for a campaign in your marketing tool, but what about the results of the campaign itself? Where do those live? And what if you have a data integrity issue with the constant importing and exporting? In order to run thorough app marketing, you need a closed-loop platform that is easy to use, completely integrated, and dynamically updates your data. USING ATTRIBUTION FOR BETTER ACQUISITION Acquiring new users should be like dating: it only works when you re both looking for the same thing. They re looking for a particular product or service, and you re looking to provide that to someone. It s a match made in heaven. Great acquisition campaigns are those that discover the perfect meeting place. You know by now that doing so requires attribution tracking for each of your acquisition channels, including Facebook or partners like Fisku. NOW, YOU HAVE TO DECIDE WHICH CAMPAIGNS ARE: Delivering the most new users Delivering the most engaged new users Delivering the users with the highest LTV 20

23 Use attribution and segmentation together to create these user groups and see how they behave over time. We ve found that, on average, your paid-to-acquire users should open your app as much or more than organic users. Use this as a benchmark in evaluating the effectiveness of your campaigns. Take a look at your retention numbers: are there channels or campaigns that have users who open your app more frequently? Who returned quickly after their first app open? Or who completed a couple of events within a short time frame? If so, these are the campaigns that are working. Even more important are the users from sources who have the highest LTV. For example: you re a marketer running two campaigns out of two different paid channels. Campaign A returns a larger number of downloads and initial users, while Campaign B delivers 25% fewer. The clear winner would be Campaign A, right? Not if you measure LTV over time. It could turn out that Campaign B, while it returned fewer downloads, delivered users who are more active and make more in-app purchases over time. Because of this, you ll see a greater ROI from Campaign B once you take into account LTV and the purchasing behavior of the acquired users. With insights like this in hand, you ll be able to categorize your campaigns into three key buckets: 1. This doesn t work - let s never do it again. 2. This channel has potential - how can we better optimize it? 3. This is our sweet spot - let s continue running these campaigns and try even more. Categorize your campaigns to determine where the successes were and how to build a better acquisition strategy for the kind of users you re looking to attract. After a while, you ll have a highly-targeted set of campaigns that bring in the best users. CREATING YOUR APP BUYER PERSONAS Like all good relationships, the real hurdles come only after you ve met someone. This is when you get to know them and put the work in to maintain a positive bond. Put yourself in the app user s shoes for a moment: you re a 30-year-old male who just moved to Boston, so you ve downloaded an app that alerts you to events, concerts and shows in the city. A few days after downloading, you receive a push notification for 10% off of tickets to a special showing of Sex and the City at your local theater if you book in-app. Now, there s nothing wrong with enjoying a varied selection of television, films, and art, but we re going to bet that this isn t the kind of push message you would enjoy getting - in fact, it might seem 21

24 so irrelevant and intrusive that you uninstall the app right then and there (it has happened). With that bad call, you and that app have already broken up. As app marketers, your primary job is to understand your users so well that your app fits seamlessly into their lives and seemingly sells itself, and your marketing is built on information they want to receive. In creating your set of ideal app users, you can do just that - all based on hard data. There are a variety of ways you can go about creating these personas, but when it comes to your app, we ve narrowed it down to these three steps: STEP #1 Gather qualitative and quantitative raw data about your current and prospective app users using analytics. Pair this with survey information, including profile and activity-based questions. a. Use in-app surveys to learn about who your users are, why they downloaded your app, when they use it, and what they like/dislike about it b. Interview customers in detail about their app experience c. Consider using incentives to make it easy for people to say yes to being surveyed or interviewed d. Extract app analytics data on how users are behaving - look at session lengths, screens viewed, conversions, push and in-app message opens, funnel drop offs, etc. e. If you do not have many app users, leverage your social networks and other referral channels to solicit feedback f. Ask your sales team about the kinds of leads they are interacting with g. When using forms on your app s website, include specific fields to capture additional information (for example, if company size is a factor of your persona, ask people how large their organization is) STEP #2 Look for patterns and similarities in the characteristics your app users share outside the app and in the behaviors they display inside the app. a. Who are your app users? What age groups do they fall into? What are their lifestyles like? b. What features do people use most in your app? When do people convert? When do they fall out of a funnel? c. What were common complaints? Are there any shared goals? 22

25 STEP #3 Write up a detailed overview of your ideal app user based on the data you gathered. At the same time, consider who your negative or exclusionary app user may be. You can include the following elements: a. Background information and some speculative personal history b. Think of a story for what their usual day looks like and when they re likely to use your app c. In-app behavior: what do they do inside your app, how much time do they spend on certain screens, what is their typical conversion path like d. Communication preferences: how do they find and digest information e. Goals: what is the primary and secondary goal or action users want to achieve with your app? f. Challenges: what stops people from returning to your app or completing a conversion? g. Common sound bites: what praise or objections do you regularly hear from your ideal user? h. If easily possible, include most of the information listed in step 3 above, but focus on identifying the actions you do not want people to take inside your app and what motivates these bad in-app behaviors i. Think about people who are too advanced for your app, too expensive to acquire, or those who churn the most frequently At the end of the process, you should come away with at least 3-4 key buyer personas representing your ideal app users. And they could surprise you. You may end up with personas that include interactions with in-app actions or features you wouldn t have previously considered important, but do after surveying current users. With buyer personas in hand, you have the foundation necessary to determine what kind of app marketing (which content, offers, and language) is most accessible (and successful) with your users. Buyer personas directly influence the user segments you create, as they should be a representation of different user groups, their engagement levels, and their individual attributes. When you re building segments, think about which of your ideal buyers would fit into that segment, based on their behavior or profile attributes. 23

26 UTILIZING USER SEGMENTS: HOW TO CATER APP MESSAGING TO Let s go back to that Sex and the City example: chances are, the app marketer decided to send the offer to all app users - and why not? That way anyone who is interested sees it, and more eyes mean more conversions, right? You ve got it: that s not the case. We ve found that 52% of users enable push messaging on their mobile devices, but 54% of users actually convert from a segmented push message (one that is tailored to their interests) compared to only 15% for broadcast messages. Your app users are expecting a certain experience: one that suits their interests, and doesn t bother them with irrelevant marketing. Because of this, you can t treat them as one homogeneous group. Data shows that 20% of users only open an app once, and tactics like impersonal broadcast push notifications can quickly and easily turn first-time users off. When you use segments to determine relevant audiences for your marketing efforts, you re not just improving your chances for better click-throughs, conversions, and maybe even purchases - you re also engaging users on their terms. First thing s first: use your buyer personas and frequent (or desired) in-app actions to inform your user segments. Some segments you might use only for tracking purposes - others will be the target audience for your messaging campaigns. MESSAGING CAMPAIGNS THAT Running surveys Delivering discounts or mobile-specific offers Introducing new app versions Alerting users to updated features Engaging users in rewards programs Driving attention to new products Making critical information more accessible There are a number of new and creative ways you as a marketer can employ app messaging to increase retention and engagement, and improve your in-app conversion rate. But they all start with good segmentation. 24

27 Remember those four common user segments we outlined in the Analytics section? Those are the perfect place to start in creating and running highly-targeted campaigns (and using segments to inform marketing offers). SEGMENT MCOMMERCE COUPONERS CAMPAIGN MOBILE DISCOUNTS Think back to buyer personas: if you re an ecommerce app, it s likely you have a customer persona of the frugal shopper, or the discount-seeker. If so, this is your segment. To grab their attention, use inapp messaging to target them specifically with a coupon. You don t necessarily need to create a full site-wide sale or coupon, but rather you can specifically target the people you know will react to a special offer. SEGMENT MEDIA NEWS JUNKIES CAMPAIGN SUBSCRIPTION OFFERS Mobile users don t often like to flip between sources for news, so if they ve chosen to open your news app frequently, you might want to convert them as fullfledged subscribers. They re clearly getting value out of your app, so a targeted offer for a reduced subscription could be useful. Trigger an in-app message that appears while they re reading an article with an offer for a discount subscription, clearly outlining the benefits of becoming a paying subscriber. SEGMENT VIDEO SECOND SCREENERS CAMPAIGN TIMELY REMINDER AND THE INTRODUCTION OF SOMETHING NEW With Second Screeners, capturing and maintaining their attention is the key. Once you ve determined these users, you can send them push notifications to let them know that their favorite show is starting, or use in-app messages to invite them to watch the next show based on their entertainment tastes. SEGMENT SOCIAL BUTTERFLIES CAMPAIGN PROMPT A FOLLOW Not all marketing campaigns have to end in a conversion or purchase - some work to encourage a brand relationship across other marketing channels. In this case, you have a segment of users who are actively sharing your app or content from within your app, and you can even create segments based on which social platform they typically post to. Using this insight, you can create an inapp message specifically for their preferred social network. With this Twitter user, you can say Hey, thanks for tweeting about us, and prompt them to follow you on Twitter for updates and news on your brand. This is a great way to get social tastemakers and brand ambassadors into your social circles. 25

28 Profile data has three primary marketing functions: 1. It gives you the ability to target campaigns based on user attributes (and not just in-app behavior) 2. It gives you the ability to target campaigns with both user attributes and behavior 3. It allows you to target based on customer data from across different channels What does this all mean? That personalizing your app messaging to drive better results (and appeal to users) just became substantially more sophisticated. Now, you can run campaigns that speak to your user as a whole, instead of just the fragment of their app experience. You can easily, and successfully, target a campaign based on just attributes from user profile data. But, truly advanced marketing best pairs attributes with behavior as its foundation in this equation: PROFILE DATA + BEHAVIORAL DATA = PERSONALIZED CAMPAIGN This equation is the most robust foundation for creating personalized campaigns that work. Not only does it work from in-app behaviors, but it also incorporates individual user attributes and actions they ve taken outside of your app. For example, say you re looking to drive purchases in your ecommerce app - it s a fairly common goal we ve reviewed before, but marketers still encounter problems making it happen. Think of it in terms of personalization: You can target male users between the ages of (profile data) who purchased a winter coat in October (behavior data) and send them a push message to view related winter clothing items in your app (personalized campaign). AGES PURCHASED WINTER COAT PUSH WINTER BOOTS 20% OFF That s not the only campaign you can run from this set of information - you could try sending an in-app coupon to incentivize them to make another purchase, or use location data to alert them to special instore sales happening in their area. 26

29 You can collect a host of different user attributes to inform and specify your campaigns, everything from age, location and gender to last purchase data and item, rewards points or in-store credit, and web LTV. Another benefit is that you are in charge of the frequency of these marketing campaigns. This differs from online retargeting, which can make your users feel as those they re being followed around (seemingly endlessly) online because of one visit and cookie tracking. This makes your marketing both more relevant and less invasive. OPTIMIZING YOUR FUNNELS WITH We ve previously discussed the difference between organic and marketing funnels within your app, so you know that some user funnels are those that are impacted in some way by a messaging campaign. But how do you know when and where to run these campaigns within the funnel? This is where your analytics and marketing again work closely to inform your efforts. Let s say you have your group of users who often read, then share, posts about destination weddings or honeymoon locations in your travel app. They re clearly a high-value segment; one you might be hoping will end up booking a trip in-app. You ve created a funnel in your analytics to track this, and see that, organically, only a small percentage (2%) of those users end up actually converting. To overcome this challenge and present booking in-app as an attractive option, you can trigger an in-app message to appear at a certain point within the funnel (say, after the user has read 2+ articles concurrently) that contains an accommodation voucher when you book in-app, or offers free insurance on all flights booked through the app. Not only are these relevant to the user segment you ve created, they also appear at the optimal time during that funnel, capitalizing on timing and in-app actions. Triggering app messages based on position within the funnel gives you the opportunity to convert users when the desired action is top-of-mind. All of your funnel-based marketing campaigns should aim to convert the user on some step within that funnel. WORKING IN AUTOMATION TO STREAMLINE YOUR MARKETING (NOT TO ANNOY YOUR USERS) Marketing automation prompts different feelings in different marketers. Some view it as a helpful, but not crucial, function; others, as a tool that causes more harm than good. If you re like us, you see it as a necessity to modern marketing. The concept of automation deserves more overt praise because it has been nothing short of revolutionary for many brands. Automation (particularly smart app marketing automation) can be a time- 27

30 saving, revenue-maximizing, and delight-eliciting addition to your mobile marketing plan. Contrary to mainstream beliefs, app marketing automation does not do your marketing for you; it helps you scale your efforts. The biggest hesitation marketers often have when it comes to employing automation is the fear that they will come across as a mechanical, impersonal brand on the world s most personal marketing medium the smartphone. But with the introduction of personalization, you can use automation strategies to speak to users on an individual level, negating any semblance of a robotic presence. 5 USE CASES IN WHICH APP MARKETING AUTOMATION WORKS BEST App marketing automation can be successful in all parts of your marketing strategy from top-of-the-funnel new user acquisition tactics, to middle-of-the-funnel engagement ones, to helping you achieve bottom-of-the-funnel conversion goals. Below, we outline five scenarios where you can use automation to enhance your app s marketing and user experience. CAMPAIGN #1 CONGRATULATORY IN-APP MESSAGE WHEN NEW USERS COMPLETE THEIR PROFILE SET-UP (TOP-OF-THE-FUNNEL) Many apps have users create a profile by completing an in-app registration process. Often, this is so that you can store your preferences or billing information, find friends, etc. One way to make this less tedious for your users is to automate a Welcome or Congratulations in-app message, which appears once they ve gone through the steps, and acts as a warm greeting. This message can also introduce new features or next steps to set your user on a clearlydefined conversion path.user experience. GOAL: Make a great first impression and showcase the features new users can now fully use to motivate interaction. CAMPAIGN #2 PUSH NOTIFICATION REMINDING NEW USERS TO COMPLETE THEIR REGISTRATION (TOP-OF-THE-FUNNEL) Having difficulty getting users to even make it through in-app registration? In this case, you re in danger of users exiting your app without finishing the set up process. This can happen often, so having an automated response can not only help bring users back, but it can also act as an immediate response to a bottleneck. Push messages can be triggered when a new user only has one or two remaining steps that need to be completed and these notifications can highlight the benefits that await once registration is complete. This reminder can help to re-engage dropped users in the process. GOAL: To drive latent users back to the app and convince them of the value of signing up/in with an automated push message. 28