How To Measure The Influencer Campaigns And Drive The App User Acquisition Effectively？

Some recent hot topics have focused on mobile advertising, data tracking and performance measurement in the mobile app market. The growth of social media in recent years has led more and more marketers to turn to influencer campaigns to increase brand awareness. And tap into an influencer's audience and use their influence to drive their user acquisition.

Normally, a properly executed influencer campaign can bring more users to your app and drive more downloads. However, measurement challenges still need to be overcome, such as quantifying users attracted by activity and CPI.

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How to advance your influencer campaign and what to focus on?

Let’s talk about how an influencer campaign can really help a mobile app’s user acquisition program. While it's easy to pay someone with a social media following to promote your app or game, the success of that promotion depends on a few key details and many variables to consider.

Two worth noting are:

• Make sure the influencer's audience is the people who actually want to interact with your app.

For example, users who using a child entertainer Youtube channel may not be relevant for a financial application.

• Make sure your plug is positioned correctly.

Showing up in the middle of a long 20-minute video can cause you to miss out on a lot of potential users who gave up early on in the video - which most people do. Ideally, your influencer will open the sponsorship details and insert your app at the beginning of the video.

After doing the above research and screening work, the next question we need to pay attention to is how to measure the effect.

The biggest challenge with using influencer campaigns is how to measure them. Many YouTube videos or Instagram Stories have links or swipe up features that allow viewers to quickly access product pages and download apps/games. But many users don't actually click those links or choose to swipe up, yet they do remember the promotion and may actually download because of it. As such, mobile marketers face the same measurement challenges as any offline campaign.

• How do we quantify the number of real users a campaign attracts?

• What is the actual cost per install (CPI)?

• Essentially how do we measure view-through attribution?

How to measure view-through attribution?

First, let's take a look at the user's browsing track.

When a user arrives to watch a certain video on their favorite YouTube channel, the user sees an influencer pushing the game, the user loves the look of the game because it is similar to other games they own, and they want to download it.

Because they are probably watching on a TV or computer, so they are extremely unlikely to click on a "link in a comment", but also because downloading an app or game may not be the reason they showed up to watch this particular video. More likely, the user will remember the app's name and to search for it later.

When users decide to search rather than click on links, we lose the ability to track them.

What is the solution?

We have to start looking at trends in the data and understand the lift in metrics such as organic search created by this type of activity. Two things to be clear:

• More people will search our app with valid activity.

• They will conduct a dedicated search using our app's brand name.

Using some smart tools can help us to do this.

Intelligent tools such as Polarbeam can generally clearly show the daily organic search downloads of the app. After the client launched a YouTube campaign, it was clear that there was a huge increase in traffic. Comparing the data for the two time periods before and after use, we can determine the improvement achieved through the campaign.

Alternatively, we can use forecasting tools to estimate what we might receive if we don't carry out the campaign. Polarbeam's AI uses historical data to predict alternative outcomes.

Any Apple Search Ads (ASA) campaigns currently running will also support this data. If the lift is indeed caused by influencers, then we would expect a related lift in branded paid search downloads.

The other half of the puzzle is how to view Google Store results.

Google's Organics is a more complicated affair than Apple's. They do, however, provide a detailed breakdown of the relevant data searched and acquired, allowing us to pinpoint the exact number of users who searched for any single search term and thus clicked the download button. General official data can help you get a clear picture of the number of users searching and downloading for very specific app brand terms, and you can see trends that match Apple's organic growth.

The data allows us to get a rough idea of the influence of our chosen influencers/influencers and ultimately assess the CPI.

How to measure detailed performance using multiple influencers at the same time?

If you choose to cluster multiple influencers together, you should be interested in the overall lift that clustering produces. Once you saturate the audience of a particular influencer, re-advertising with them will result in far less results. It can be six months before you decide to reuse their services, and the social media landscape can change a lot during that time.

If UA increases at the same time, how to be sure that the search lift is created by the influencer campaign?

Whenever we add additional marketing efforts, we create ambiguity about the reasons for our organic lift. In these cases, some smart tools are essential and are important to help us establish a baseline and pinpoint specific reasons for the improvement in organic KPIs we are seeing.