Onboarding is the new “monitization” in that it’s the hot new topic as of late in the app community.
Coming from a web background this is nothing new. We used to extrapolate New (versus Returning) users in the analytics as our way of reviewing the first time visitor experience. We defined an expected end-task we wanted the user to have taken and followed the pages between their entrance to the site and that point, including noting all the early exits.
In many ways not much as changed. The analytics tools are able to slice up the data in many more ways as we collect much more data on individual users than ever before but it is the same basic premise of understanding where and interpreting why users drop off during their introductory experience. In the past few weeks I’ve attended a number of Meet Ups, online seminars and done quite a bit of reading on the topic because we have several new products in the pipeline which I know need some significant onboarding work.
How do I know this? Well, for starters, I could intuitively tell as a user myself something just didn’t “feel” right but since I hate using my gut I also observed it through both qualitative and quantitative user testing at the alpha phase that confirmed my suspicion we were leaving too many users behind.
Moving forward there are a series of steps I take when designing the optimization roadmap.
The opening caveat I have is that my personal belief goes against some of the current line of thinking regarding onboarding friction. Friction represents the steps within any process that slow it down, potentially stopping people from getting to the end goal you have for them in the process. The general rule of thumb being pushed by many in the industry is to eliminate as much friction as possible to get as many people as possible to the end point (you might hear it referenced as Zero Friction Onboarding). While as a theory this is good, not all users are created equal and therefore, I subscribe more to a pre-qualification theory of onboarding where some friction is intentional in order to eliminate low-value users earlier rather than carrying them.
There is no right or wrong answer from a theoretical perspective – good arguments can be made for both. A lot of times it can be simply boiled down to quantity versus quality. For example, let’s look very quickly at matchmaking (dating) applications. Tinder fosters a specific kind of superficial interest between people so the more photos they can have for users to swipe through the better. They offer a very low friction way of getting started because the end-task is a very simple one and if a large number of users do nothing other than make their photo available the app still functions fine. eHarmony’s value proposition is matching at a much more interpersonal level so they need to pre-qualify users who specifically will participate in their more intensive matching program and therefore their on-boarding includes a lot of forms and processes. It results in fewer signups than Tinder but each one is at a higher potential value because these users having survived the onboarding are heavily vested in participating. Vested users created through prequalification are the life blood to their app.
You’ll notice it comes down to a value proposition question and the reality is more based in being able to calculate the Return on Investment of one onboarding process over the other in your specific application. Chose the path you think is right and verify it through testing. Remember, the onboarding process is reenforcing the value proposition you initially present in your acquisition process, it needs to help make good on the promise you proposed.
Secondly, know the business need you’re solving for. Not all onboarding is meant to accomplish the same thing. One way to look at this is that different onboarding techniques work at different points in brand’s lifecycle. Take Twitter’s onboarding as an established social network versus that of upstart Ello. They need to accomplish two completely different business goals despite having what would appear to be very similar value propositions. Twitter already has a critical mass of users and a fairly high percentage are active content creators, what they need is interaction so they have to optimize for an onboarding flow that fosters actions like retweets and replies. Ello as a new platform needs to reach critical mass with what appear to be active users so they need to foster profile completions and friend invites first and foremost. If you identify the wrong need, or don’t take the time to define one at all, you could set yourself up for immediate failure. If you aren’t sure what you should be optimizing for it might be time to rethink your business plan.
From the identified business need then onboarding directly and influences a few specific KPI but inherently indirectly effects everything that happens on your product so it’s important to determine what you’re looking at in order to gauge results based on the stated need. We break our KPI into three key components from a high level perspective: Retention, Engagement and Monitization. We also view onboarding as the entirity of the process between Acquisition/First Install and completion of the primary task for the first time and not just the typical onboarding tasks like “complete tutorial” or “create profile.”
Onboarding will have a direct impact on short term retention: Normally that’s either Day Zero (same day, which is for apps that you expect multiple sessions daily on) or Day One (next day, which is for apps you expect at least once a day usage on). In the longer term such a Day Seven and Day 30 as well as One Week and One Month retention rates are influenced by a much greater range of inputs than those early retention numbers so it’s more difficult to isolate onboarding’s effects, but lets just say, if you retain more on Day One and all else was equal, you should retain more on Day 30. Since retention isn’t measured completely in a void, it’s important to view how changes to the Onboarding thus effect the cohort created in retained user’s engagement and monetization. Just because you retained more doesn’t mean who you kept were any higher quality as users.
Thus, onboarding will also affect engagement metrics. We’ll break this into components starting with the highest level which is identifying the single action that defines what engagement truly means to your product. This is a simple, repeatable task that all users should aim to complete on a regular basis, such as, in a game, reaching the End of Game or End of Level type screen. Don’t fall into the trap of that being a purchase unless you are a retailer, because an In-App Purchase is made by only a subset of users and the pathway is a subset within secondary user actions. Ultimately, optimized onboarding would allow a user to reach this for the first time more efficiently. You need to move the needle on this number ultimately, but how you get there is a series of incremental work.
Ideally, you’ll want to track every single stop of the onboarding process from the install onward to this core action you identified. Every point where a user has to take an action between install and that point is a potential experience to be optimized – remember, even if you’re intentionally introducing a level of friction that needs to function correctly. We typically subdivide onboarding into actionable groupings (or subsets of the onboarding process) such as intro, account creation, tutorial, other non-core but essential actions, core action initiation. Each than becomes an individual (sub) funnel to be optimized on its own as well as part of the entire process in its totality.
Optimization is holistic, it’s a complete experience, so zoom out and look at the bigger picture from time to time and consider how everything functions together, not just individually. For example, it’s important to remember too the order of operations matters as much as the operation itself so don’t discredit changing the order as a tool toward optimizing and not just the components of the operation itself. You can optimize the account creation flow all you want but if it’s in the wrong spot within the entire onboarding it’ll never work as best as it should.
Finally, typically, only a subset of your engaged users (players) are monitizable (become payers) in a free-to-play, IAP driven app, so it’s important to take a view on how your onboarding will influence this transition as well. Since most payers will make their first purchase early in their lifetime the first use experience can help set up the expectation that paying is part of the app’s core functionality. Knowing it’s only a small percentage that will respond to this call to action finding the right balance between converting players early while not losing non-monitizable but still valuable users is key. For example, an evangelical social sharer who might be lowering your CPI or in a competitive game a heavy challenge initiator who is driving the engagement ecosystem and both could be soured to being evangelical or being heavy challenge initiators if you drive the pay-to-play point too hard too early.
Obviously, if your monetization strategy or consumer base is different you’ll have to modify how you are viewing monetization in the onboarding. We leave it till last because it’s not a direct driver of conversion to paying for most of our apps but it’s quite possible if you’re a mature app further along in your lifecycle or a very aggressive new app in the beta phase maybe montizatin is front-and-center in your business objective.
Just because you optimized it once doesn’t mean you’re done. Your app is not static in the market place and onboarding, like everything else, requires constant tuning. This can happen for three main reasons:
External factors such as changes by the competition, though regulation and within distribution channels can all influence the need to re-optimize. Constantly evaluate all of these and be proactive in making changes. Subscribing to the ‘if it’s not broke don’t fix it’ mentality can leave you too reactionary to many of these outside sources .
Internal factors such as the natural progression in app lifecycle and adjusting business objectives will also influence your need to continuously adjust your onboarding approach. Know what the signs are for an app moving to a new life stage or that the business objective may be shifting and propose tests to help move onboarding into an aligning path rather than waiting until after these things happen and seeing your metrics tank.
And, on that last point, watch your metrics closely in general as changes in the feature set, in the customer’s being acquired, etc. should be immediate be evident in the onboarding KPI. If you know you’re going to be changing features or changing acquisition targets put on a parallel path the appropriate changes to onboarding and then measure the results in parallel. If you’re not sure, have a series of tests ready and test them post-script to work toward full optimization.