Calculating ROI on MobileMarketing Spend

2 Why Your Mobile App Strategy is Killing Your Business

&How to Calculate The ROI on Fixing It

3Introduction

If youre a consumer-facing business of any size, youve probably got a mobile app. You may well take a close interest in how well it functions, and even how many new or existing customers download it every day.

But if thats as far as your interest goes, your mobile app strategy - or, rather, your lack of one - is almost certainly killing your business. That may sound like an extreme proposition. But the numbers bear it out. In this short document, well take a look at those numbers and suggest some ways to quantify and change them.

By doing so, we hope to bring home the importance of developing a true mobile app strategy, and establish a method for delivering and measuring ROI on the back of it. We talk to leading app organizations every day who deal with just this challenge, so were delighted to present a document that helps answer the question How do I justify spend on mobile marketing automation?

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5Thinking About ROIThe economics of the mobile app are in fact relatively simple.

They can be expressed in equation form as follows:

Now, we all know it isnt quite that simple.

To state just one obvious caveat, it might not always be possible to clearly estimate the additional revenue that an app user generates, particularly in an app whose primary benefit is increased brand loyalty and awareness.

But regardless of those issues, the simple truth is that for many, many businesses, this equation cannot be made to stack up.

On the acquisition side of the balance, its more expensive than ever to get people to download your app, whether you are spending that money in direct pay-per-click advertising (on other mobile apps or social sites) or above-the-line in TV or print advertising or in-store promotions.

Meanwhile on the revenue per user side, there are certain numbers that illustrate just how tough it can be to generate long-term revenue from app users.

Try these stats for size:

19% of app installs are used precisely once Of those users who install on Day 0, as few as 10% are active on Day 7 Although the average smartphone user has around 85 apps installed on their phone, research suggests they only use around 26 in a month (and spend 90% of their time on fewer yet.)

Profit per user = lifetime value per user - acquisition cost per user

6So while theres obviously a huge loyalty and revenue benefit in securing - and keeping - a place on the consumers home screen, actually making that happen in a world containing millions of apps is hard.

But thats where youll have to focus your effort. Sure, we can and should make every effort to make our acquisition spend as efficient as possible. But ultimately theres no silver bullet that will make a significant and material difference to those costs.

Besides - enough has been written about determining ROI on acquisition spend over the years. The single biggest failing in mobile app strategy over the years has been the belief that success comes to those who build a great app (in their own subjective judgement) and then pay for people to start using it.

Fortunately we have the opportunity to change that. Once the app is downloaded, we are able to dramatically change the alarming numbers quoted earlier. Thats what mobile marketing automation makes possible.

7To make that happen, you need two things:

Firstly, you need a deep understanding of what your users do on mobile, at the individual level: How they behave, what they like, what they purchase and how they navigate around the app. You need to target users as individuals rather than segments: and that requires real-time data.

Secondly, you need the ability to talk to those users. Whether thats by personalizing the app experience itself, sending push campaigns, or delivering messages in the app: engaging in an ongoing conversation is the key to long lasting engagement.

A mobile marketing automation solution combines both of these abilities, and by doing so enables app businesses to control the customer conversation from a single platform, without reliance on engineering or the dreaded app store upgrade process. That means new possibilities in driving the metrics that matter to a mobile business: engagement, retention and monetization.

It also represents a move away from the focus on acquisition that so many app businesses have adopted to date. The belief that success depends on simply building a great app and paying for users to discover it has proved false. Mobile marketing automation moves the conversation and considers how we keep those new users engaged - which is what really delivers ROI on our development and acquisition spend.

What is Mobile Marketing Automation?

Mobile marketing automation is the process of building perfect conversations with your mobile users. That means making every mobile interaction meaningful, relevant and effective - both for the user and your business.

8Determining ROI on Marketing Automation SpendIf we agree that mobile marketing automation (MMA) will primarily affect the revenue per user side of the equation, we can create a further simple equation for determining the ROI of investment in MMA:

Lets take a look at the bottom half of that equation first - because thats the easy bit! To find that number youll simply need to sum the costs of your MMA efforts. Just make sure to include:

Any software licensing costs incurred Your own time spent building, delivering and measuring campaigns Any value offered to users as part of these campaigns (vouchers, etc.)

Well go over some practical examples of what these numbers might look like below, but, for the moment, lets assume that summing them is relatively straightforward.

However, you do have to remember that if you are looking to determine ROI on just a software spend - because you are automating already existing programs - your time invested is probably a negative. By adopting an off-the-shelf platform, you are saving time spent on campaigns rather than using more.

That leaves the top half, which is where things get interesting. If we take number of users to be static, that leaves change in revenue per user as the variable here, and one that in most cases isnt as easy to determine as we might like.

change in revenue per user x number of users

cost of MMA

ROI of MMAinvestment x 100 =

9It first helps to break down revenue per user into the following:

Revenue per user = revenue per user per day x average lifetime of user in days

This equation reminds us of the essential truth that there are two ways to increase the revenue accruing from any given user: extend their activity levels (most obviously by getting them to spend more) or extend their lifetime (which includes reducing the number of one-time-only users but also reactivating of lapsed users).

By looking at the numbers at this level - and filling in our equation all the way up to costs, we can then have a reasonable approximation for the ROI on our MMA spend.

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Aspects Of ROI To ConsiderBefore we look in detail at three examples of ROI calculation in action, its worth remembering a couple of key points. First, there is no single bullet-proof way to calculate ROI. The discussion above is intended to give you a framework for understanding the effects of campaigns - but there may be other implications that need to be considered.

Similarly, it is important to understand that we can determine ROI on multiple levels. Perhaps the easiest way is to simply look at revenue per user numbers before and after the implementation of an MMA solution. This, in theory, will capture every effect of the multiple campaigns you run.

But on the other hand, it may also capture effects that are in fact unrelated to your MMA efforts. If, for example, the nature of your acquired users has changed during the same period, will it be possible to isolate this variable from your evaluation of mobile marketing campaigns?

The alternative is to look more closely, and specifically, at the individual campaign level. This will allow you to be revasonably confident that the changes you are observing are relevant (particularly if you are using A/B testing or comparing with well established benchmarks). However, you may miss other effects. An improved app experience, for example, can lead to improved acquisition via word-of-mouth.

Ultimately, a balance has to be struck. Perhaps the single smartest piece of advice, and one that is followed in the examples below, is to identify the metrics you wish to influence, and the effect you wish to see before you build out your campaigns. And then limit your analysis afterwards to these metrics. This is the best way to ensure that youre analyzing the effects you set out to analyze, the fire rather than the smoke.

In the remainder of this document were going to look at three typical app examples, from three different verticals, and demonstrate how that process might work.

In each case both the costs and benefits are very much examples. However, the numbers quoted are always similar to those we have helped Swrve clients to achieve when working on projects of this nature. If anything, weve taken a conservative view on the potential benefits of the mobile marketing automation approach.

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Example 1: A Mobile RetailerFor those app businesses that sell on mobile, and own the financial relationship with the customer (as opposed to using Apple, Google, etc. for payment processing), it is relatively straightforward to determine mobile ROI. In fact, in most cases these organizations will already have a fair idea of long-term customer value and costs of acquisition (or they should!)

On that basis we will assume that a clear understanding of current LTV and baseline numbers exist for comparison.

Lets look at some sample figures to establish how determining ROI would work, based on two campaigns that a retailer of this type might be expected to run. Of course the actual number of campaigns that can be run is infinite, so negative ROI at this stage would not necessarily mean the project should be abandoned, but rather expanded!

Campaign 1: Improvements to registration process via native content changes, interactive help and A/B testing.

Campaign 2: In-app messaging to 7 day browsers - users who have been with the app at least 7 days, spent at least 30 minutes browsing, but never made a purchase. Message provides 10% discount on first purchase.

Our first campaign is designed to move our revenue per user per day number. Specifically, non-registered users have an LTV of 0, whereas registered users provide all income at a particular LTV rate.

1

2

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Thus we simply follow the logic shown below, with figures in greyreflecting the existing reality of the app:

For our second campaign, we are looking at a way of increasing the number of paying users, and thus again increasing the average LTV for the product. Our benefit equation might look like this:

Registration success rate pre-project Registration success ratepost-project

Which Means...

Translates To...

Average LTV of registered

user

Additional Net gain per

month

Incremental Purchasers Per MonthPre-project app installs per month

20%

20.000 20,600

23%3%

3%

60045 +27K

Incremental Users

% 7 Day Browser segmentconverting to customers pre-campaign

% 7 Day Browser segment convertingto customers post-campaign

Which Means...

Translates To...

Number entrants to 7 Day Browser Segment per month

Average LTV of users at first

purchase

Additional Net gain per

month

Incremental Purchasers Per Month

4%

4,000 80

6%2%

2%

8065 5,200

IncrementalPurchase Per Month

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When we sum these campaigns we see a monthly benefit to the business of $33,700. Great! But is it worth it? Lets look at the cost:

If we then compare this number to our total benefit, we arrive at an ROI of 190%. And thats just on the back of two campaigns!

One-time campaign design / strategy cost (including A/B testing, and to be amortized over 6 months)

Ongoing campaign management and reporting

Monthly software licensing

10% discount cost

Total cost per month

$2,000

$1,000

$8,000

$240

$11,240

Example 2: Dating Company with In-App PurchasesIn this example, we look at two campaigns run for a dating app business. Crucially, this business does not control the financial relationship, with users instead buying credits as in-app purchases through the relevant app store.

This has a couple of consequences for the calculation of ROI. Firstly,it may be the case that a business in this situation does not have a clear understanding of the LTV of various user types.

If that is the case, a business of this type needs to ensure that revenue events are accurately recorded (including filtering out the fraudulent activity which is a common feature of the in-app purchase ecosystem) and can be associated with individual users. Once that is done - we can move on - and the logic will be similar to that for mobile retailers above

monthly

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Once comfortable with that concept, we can construct a benefit table as follows:

Lets look at another calculation based on these two campaigns:

Campaign 1: In order to encourage users to return after an absence of 7 days, a recurring push campaign is created notifying users of relevant content (new profiles etc) specific to them.

Campaign 2: A/B testing of the onboarding process is undertaken in order to assist users new to the app and improve Day 1 Retention rates

Our first campaign is designed to increase the lifetime of the user in days by bringing back those who have potentially lapsed. Remember when considering campaigns of this nature that users whove lapsed for 7 days (or indeed any amount of time) are not necessarily gone forever; it is important to have an understanding of organic return rate, which can be determined either by analysis of historical data or, alternatively, by simply withholding a small group from the campaign and observing their behavior.

1

2

Organic return rate for 7-day lapsed users

Post-promotion return rate for 7-day lapsed users

Which Means...

Translates To...

Users falling lapsed 7 days in month

Average LTV of reactivated

user

Net gain per month

Incremental registered users per month

2%

8,000 80

3%1%

1%

8015 1,200

Incremental Users

Our second campaign has the same objective - increasing the lifecycle of the user in days, and in this case doing so by reducing a large user fall-off on day 1. The logic might look something like this:

When we sum these campaigns we see a monthly benefit to the business of $9,200.

Costs of course will be slightly different. For one thing, as you may have noticed, with fewer MAU, the software licensing is likely to be reduced. Similarly a recurring push campaign is set and forget, so it has less ongoing cost.

In this instance we arrive at an ROI of 107%.

One-time campaign design / strategy cost (Including A/B testing, and to be amortized over 6 months)

Ongoing campaign management and reporting

Monthly software licensing

Total cost per month

$1,000

$500

$6,000

$7,500

Day 1 retention pre-campaign Day 1 retention post-campaign

Which Means...

Translates To...

Number entrants to 7 Day Browser Segment per month

Average LTV of Day 1 Retained

Users

Net gain per month

Incremental users per month

27%

8,000 320

31%4%

4%

32025 8,000

monthly

Incremental Users

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Example 3: Brand App for AirlineOur last example represents a significant challenge. In this situation, we are considering a travel companion app that aims to make flying as straightforward as possible - providing guidance at the airport, flight information notifications, luggage tracking and so on. The app also supports the purchase of flights for the future.

One might think that in the latter case, measuring ROI is easy, and in a sense it is. But this example raises the issue of cross-channel reporting. To state the obvious, there is more than one way to book a flight. To the greatest degree possible, we would like to integrate multiple channels to give us a 360 degree view of the customer. How that happens is outside the scope of this document (and in most cases an airline will already have addressed this problem), but if youd like more information drop us a line at sales@swrve.com.

Similarly, in the former case it will be necessary not just to understand the effect of improved loyalty on app purchases, but on all purchases made in any channel. Again, with a single system of record we can do this as in the example worked out below. It is worth remembering, however, that it will be necessary to mark all app users rather than necessarily those making purchases via the app. To do this may require the sharing of non-purchase information from a mobile marketing automation platform with the system of record.

In this case lets perform our ROI calculation based on the following two campaigns:

The addition of a push notification feature alerting passengers of imminent check-in - hoped to improve customer loyalty.

In-app messaging campaigns intended to advertise hotel options to travellers who did not reserve one at the time of their booking - with the intention of increasing affiliate revenue.

In the case of user loyalty campaigns such as our first item, it is necessary to determine a realistic measure or definition of user loyalty. In this example, well compare app retention rates rather than overall business loyalty. Although the latter could be used, it is preferred to get as close to the effect as possible - the effect on app users themselves.

Our second campaign is easier to measure. Weve added a new, hopefully revenue driving feature:

This time the sum of these campaigns sees a monthly benefit to the business of $9,900.

Day 30 retention rate pre-campaign Day 30 retention rate post-campaign

Which Means...

Translates To...

New app users per month

Average LTV of day 30 retained

user

Net gain per month

Incremental 30 day retained users per month

11%

4,000 40

12%1%

1%

40120 4,800

% hotel bookings per flight booking pre-campaign

% hotel bookings per flight booking post-campaign

Which Means...

Translates To...

Flight bookings per month

Average revenue (to airline) from

hotel booking

Net gain per month

Incremental hotel bookings per month

6%

17,000 510

9%1%

1%

51010 5,100

New Bookings

Incremental Users

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The costs are again calculated in the same way, with perhaps a reduced cost for set up due to the absence of A/B testing:

In this instance we arrive at an ROI of 132%. Not too bad!

The three examples included are just that - examples. And in each case weve looked quite specifically at the direct effects of specific campaigns. However, the principles involved in each should help you get a handle on understanding the ROI of your own mobile marketing programs.

One-time campaign design / strategy cost (Including A/B testing, and to be amortized over 6 months)

Ongoing campaign management and reporting

Monthly software licensing

Total cost per month

$500

$1,000

$6,000

$7,500

monthly

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About SwrveSwrve is the world leader in mobile marketingautomation. Our solutions help many of the worlds leading brands deliver outstanding mobile app user experiences and build profitable, long-term customer relationships on mobile.

As an open, extensible platform, Swrve integrates with the entire marketing and tech ecosystem to make omni-channel marketing a reality. And it does this at scale, handling over 5 billion events across 1 billion devices every day.

The Swrve Mobile Engagement Platform delivers everything businesses need to keep their mobile app users engaged. This includes user experience A/B testing, personalized in-app messaging campaigns, targeted push notifications, and ultra-granular segmentation and targeting.

Learn more about Swrve and our engagement solutionsfor mobile app users.

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