As a marketing professional, you’re more than aware of the fact that mobile devices are a powerful instrument to connect to a wide range of audiences from across the world. Developers and marketers alike have been going by the “mobile first approach,” which refers to beginning initiatives by optimizing everything under the user experience umbrella with the mobile experience in mind.
Of course, this approach goes way beyond web design, app design, multi-screen experiences and the like. It also extends to elements surrounding most branches of marketing campaigns, such as growth efforts.
You know that saying… if a tree falls in a forest, and no one is around to hear it, does it still make a sound? The same thing kind of applies here, especially for apps. If there’s an awesome app in existence, and its target audience isn’t aware of it, is it still any good? There’s about five million apps out there, surely there are plenty of apps that are not on the top 10 lists, which absolutely deserve to have their time to shine. What are these apps supposed to do to get the ball rolling?
Mobile app user acquisition is simply built differently from the rest. Unlike a little over a decade ago, publishing an app on the app store won’t naturally lead to a bunch of downloads. There’s so much more to consider, such as your data strategy, and how to optimize your campaigns for virality.
Then there is also that saying, “Haste makes waste.” Rushing into too many initiatives that initially sound good, but without actual direction, will most certainly lead to unpleasant (and costly) pitfalls.
With that in mind, our team put together the following list of mistakes you definitely wouldn’t want to make in your mobile marketing and user acquisition campaigns.
It’s really not a good idea to make a slew of quick changes once anything goes live. Most marketers are aware of how that applies in terms of general SEO, but it also applies to app store optimization, and for ad networks as well.
Absolutely everyone in your team, including the most junior members, need to be aware of the fact that major marketing channels need time for their algorithms to absorb ad behavior patterns. Each channel is designed to deliver best results possible based on the amount spent, but good things do take time. If you end up making too many changes too quickly, you’ll only disrupt the flow needed to accrue the right amount of data, severing the spend pattern needed to generate result data. So with every change made, testing pretty much goes right back to square one, creating a whole different kind of test, essentially stripping away the performance marketing power of assessing whether or not to move forward with an ad set or campaign.
“Sustainability” goes beyond saving the future of the planet, it’s also about saving the future of your app! Because simply existing in the app store isn’t enough to garner huge downloads, or even to keep existing users coming back for more. You need that element of *wow* built in, and social sharing, and you must must MUST implement the growth loop approach to dramatically increase your chances of virality. Just to be clear, the concepts of virality and growth loops are not limited to gaming. In fact, any app that provides a good reason for their users to invite friends/colleagues etc... can get in on the growth loop action, which leads to virality.
Yes, I know. A lot of people cringe over promises of going viral, because it typically happens by chance, but hear me out. Marketers actually can set the building blocks for virality by switching over to the growth loop approach.
Unlike the traditional funnel approach, the growth loop is more of a closed system where the input (through a series of steps,) leads to an output that is naturally re-invested as the input of the next cycle of the loop.
Here’s a visual representation of what I’m talking about:
FYI- the most efficient virality growth loops are those that have the backing of data, especially data that stems from previous engagements and paid campaigns. That’s because the targets would be the users who engaged with your brand the most, and demonstrate higher LTV. They are the ones that are more inclined to share your app and promote vitality, both in the short and long term.
I guess we’re all more/less guilty of getting a little too comfortable with a good thing, especially in our line of work. For instance let’s consider marketing efforts that have proven to fare well time and time again. You really need to change things up with new campaigns.
Granted, it’s critical to be as organized as possible when it comes to campaign management, especially with efforts in scaling. As such, evergreen campaigns (those that have already proved themselves successful) best be handled differently from test campaigns, especially if you’re not using a predictive marketing solution.
Evergreen campaigns should be treated differently as they offer more consistency with little need to pause within the first few days- even if they are displaying a slightly lower performance. They have already proven their worth so you can allow them a longer amount of time to perform.
If you’re not using a predictive marketing solution that helps with LTV forecasting, you might want to consider capping your testing budgets at 20 percent. Pre-defining test budgets can prevent volatile performance; as the targeting mix will not change too much- you are effectively capping your risk. Engaging in many tests can hold a lot of risk for the activity, especially when not acting on user-level LTV data.
There is a dangerous misconception amongst marketers and advertisers alike, that a successful ad on one channel will automatically translate to another, but that this is simply not true.
In this day and age with so many channels hosting different formats and different audiences- a substantial amount of time needs to be allocated to each channel. One channel might have short term success and long term failure. Creative assets might work across one channel and under-perform across another.
Not only should you be aware of all the features and settings available across all channels and ad networks, you should also be on top of all the updates across each channel and ad network—so you can pounce on them!
For example, the changes that came with iOS 15 really blew me away, because unlike its predecessor, it actually offered a few good improvements for mobile marketers, such as product page optimization.
For marketers, this means having the ability to tailor the content on product pages based on audiences. Marketers can also A/B test pages and see what clicks. As needed, they can also swap out screenshots, app icons, or highlight certain features to see if that drives conversions or increases downloads in particular categories. Pretty awesome! For paid UA campaigns, they also unleashed the ability to create custom product pages—sweet!
The sooner you’re in-the-know of such changes, the sooner you can capitalize on them!
Also, there are tons of marketing channels out there, and I’m sure the higher-ups want you to cover as much ground as possible. But maybe you can consider showing them the chart below, to let them see (at a glance) that the “pure mobile,” and “mostly mobile” marketing channels are the ones worth investing more time and resources in.
As the header above indicates—you really need to understand your ROAS curve, because it will help your team better understand and optimize all user acquisition efforts accordingly. It will also help you match up other campaigns and goals accordingly.
For instance, understanding your ROAS curve will help answer questions such as is most of the revenue (per specific cohort) generated on the first couple of days? Or the first week? Maybe the first month? Also—understanding your user's purchase behaviour can help you optimize both UA efforts and in app monetization. Win!!!!
Once you have a good understanding of your ROAS curve - there's room for further drill down and exploration. It will open the doors for you to understand user patterns and their behavior throughout the cohort timeline. This understanding will answer questions such as whether your ROAS curve is driven by the same users that purchased at a high price and keep purchasing. Or perhaps it’s driven by new first time depositors? Or maybe it’s the users that make frequent small purchases at a steady pace?
See what I mean? In theory this might seem like whatever… but in practice, it’s the key to a treasure chest of marketing gold!
It goes without saying that the LTV of your users is one of the most important success metrics for your team. As I’m sure you’re aware, “LTV” refers to the measure of the revenue your users will bring during their lifetime of using your app. It comes in particularly handy when you’re able to obtain this data down to the individual level. This is made possible with the backing of an LTV predictive platform, which can be developed internally, or by using plug-and-play solutions.
Using an LTV predictive platform will also be handy for hyper-targeting and ROAS optimization. I mean, can one get any more efficient than capitalizing on optimization models to hyper-target only the users they want? By using such a solution, marketers can manage and diversify their strategies on a sliding scale to balance risk-reward between short-term ROI and long-term LTV to achieve the best outcomes.
The road to UA success is often laid with pitfalls, triumphs and most importantly, lessons. Watching out for these common UA mistakes can put you and your team in the right position for success in all your mobile marketing campaigns.