To understand App tracking and how it differs from website tracking, it is important to know how both work. We’ll quickly look at how web tracking works and then move on to App tracking. We’ll end with some solutions that are on the market that you can utilise to help your App tracking efforts as well as help improve your online marketing activities. 

Website Tracking vs App Tracking

The most basic way of website tracking is working with utm tags. These tags are added on the url to see where your traffic is coming from. Once people are on the website, your general analytics tool can take care of the heavy lifting and, if consent is given, can track the behaviour of your users on the website. This can give you useful insights on how people interact with your website and what are potential blocking points for them in the flow of the website.

For App tracking it is very similar, with a basic analytics tool it is very easy to correctly see the behaviour of people in your app. This can be done with several tools such as GA4, Appsflyer, Adobe Mobile App Analytics, etc. The problem for App tracking is the acquisition of your traffic. If people don’t have your app yet, they will get redirected to the App store or the Google Play store. As this isn’t your domain, you can’t follow behaviour here. This is where a Mobile Measurement solution might come in handy. The attribution partner can see what happens in the app thanks to its SDK. They can then link this information to an ad platform or campaign via a variety of methods: Device ID matching, referrer ID, Probabilistic modelling, SKAdNetwork, etc. The following image can makes this visual:

Getting started with App Tracking

Now that the main concept has been explained, we’ll take a deeper look on what you can do to track your app (behaviour). You’ll need an analytics tool to be able to see what happens in your app. For this, there are a variety of tools on the market to help you tackle this challenge. This ranges from very basic and free solutions to more advanced and paid tools. The most well-known is Firebase that is now being integrated into GA4. Adobe Analytics also has a module for App tracking. There are also solutions focused on more than solely analytics such as AppsFlyer that also has deep linking capabilities.

Once your tool is in-place, usually by implementing the Software Development Kit (SDK), you’ll be able to see what happens in the app. Depending on the solution you opted for the default in-app events that are tracked will vary. For some custom actions that need to be taken in your app, additional development or implementation may be required. The most important thing to keep in mind is to plan ahead. Before implementing everything that you can think of, take a step back and reflect on what is useful: What actions do we want a user to take, what is the flow within the app, … ? You should plan out your data needs and architecture. This will make it easier in the long run on what you are tracking and why. This will also reduce overflow of your analytics platform and keep you focused on the most important metrics for you.

Some tools also go further than just analytics but also give you options for building App links, SDK management, audience building, etc. More general analytics tools can be very useful for seeing what happens in your app but if you are looking to activate this data to advertise some additional steps will need to be taken.

Advertising possibilities with App Tracking

When you have an analytics tool with all your events tracked, the next step is activating this data for your online marketing activities. Luckily, this can be done quite easily for the 2 biggest players in the digital landscape: Google & Meta.Google has several native integrations with tools other than GA4. You can check this in the Linked accounts section in Google Ads itself. When you have linked-up the analytics with your ads campaign, you’ll be able to not only optimise your campaigns towards app downloads but also several in-app actions which can be more worthwhile for your application than just a simple download.

For Meta, the implementation is also simplified but will require an SDK to be implemented. In this SDK you’ll be able to capture the basic events but custom events might need custom implementation. Important here will be the registration of your application via Facebook for Developers. Otherwise you won’t be able to capture the needed data. After that you can start setting up your App campaigns and start optimising towards your (in-)app events.

With current developments in tracking (ATT) and privacy (GDPR and Privacy Shield between US and Europe), this has become a much more complex topic. In the beginning of this article we discussed the differences between web and app tracking, later we discussed why you need an analytics tool for tracking and we ended on how you can then use the analytics data to enhance your advertising efforts. The next thing for you to do is finding an App Attribution tool that fits your business' needs, creating a tracking plan, and start the implementation. As you gather more data, you’ll be able to better optimise your different marketing activities.

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The digital media platforms have grown enormously in recent times and have also become more intelligent. Real-time bidding is a must for many DSPs and many platforms also come up with smart algorithms that can maximise performance. However, the whole concept of algorithms is often a black box, which makes it more difficult to estimate how to optimise your campaigns. To get the best out of the algorithms, one principle is very important: give the algorithm as much room as possible to optimise. This is also called liquidity. In this article, some best practises will follow to maximise liquidity and get the best out of these algorithms.

Let the algorithm compose the best creatives

Both Facebook and Google have features to assemble different creatives for campaigns. With Facebook's Dynamic Ads and Google's Responsive Display Ads (RDA), you have the option to enter multiple images and multiple copies. Facebook and Google then compile different combinations of these texts and photos in order to show different versions of advertisements to users. The algorithms' estimations concerning the user will allow the ad to be "personalised" to the user and his predicted behaviour in a relatively easy way.

With responsive search ads (RSA), you create ads for Google Search Engine Advertising by setting up multiple headlines and descriptions. Here too, Google serves the most ideal combination as an advertisement to the user. As of June 2022, this will be the only usable form of search ads. It will no longer be possible to create expanded text ads (ETA). In this way, Google forces advertisers to let go of control and put more power in the hands of the algorithm. 

Experiment with broad targeting

The more room an algorithm has, the more it can learn and the greater the probability of optimal performance. Therefore, try experimenting with broad targeting. This means that you once again loosen the control by setting broad (or even no) audiences when you set up a campaign. By using a smart campaign objective such as maximising conversions, the algorithm will use its knowledge of the users and the type of content to target the right audiences. Modern media channels such as Meta, Google, Pinterest, TikTok... know from each user what websites they visit, what content they interact with and what products they buy. This makes an algorithm much smarter than any human media buyer, allowing the algorithm to select audiences where the media buyer's gut feeling or data falls short.

For search, this principle can be applied by experimenting with broad match types and introducing Dynamic Search Ads (DSA).

Aggregate campaigns and ad groups

The days when campaigns and ad groups had to be composed in a very detailed and granular way are fortunately behind us, thanks to machine learning. To give the algorithm as much room as possible to optimise, campaigns and/or ad groups should be aggregated where possible. 

In the past, it was recommended to group campaigns according to content, but nowadays it is best practice to group by objective.

Provide sufficient feed to the algorithm

In order for an algorithm to learn optimally, it also needs sufficient signals. Therefore, always foresee sufficient budget for a campaign so that the campaign can collect the necessary volume of conversions to draw its conclusions and get out of the learning phase. Sometimes, it is necessary to set up a micro conversion as a campaign objective (e.g. Step 1 of the checkout process instead of a completed purchase). If you take a "too difficult" conversion as an objective, the algorithm does not have enough conversion data to draw its conclusions. Therefore, it can be rewarding in that case to lower the bar and optimise for a conversion that occurs more often. Finally, you can also increase the conversion volume by adjusting your attribution window. For example, a post-view window will count for more conversions than a post-click attribution window. Choose an attribution window that makes sense to you, but can still collect enough data to give the algorithm enough data. 

By strengthening the algorithm, you will have to accept some uncertainty, a black box you cannot control 100%. Therefore, you must always consider what is most important: optimal performance or maximum control? When you rely on the power of the algorithms, you must keep at least two principles in mind: make sure the algorithm has sufficient (clean) data at its disposal and always maintain the correct (business) objective.

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Privacy measures like GDPR, the launch of iOS14, and the disappearance of cookies by 2023 are making marketers' lives increasingly difficult. Indeed, it will become more and more challenging to track and target consumers across different devices and channels. These changes mean that topics such as measurement and attribution that are already complicated now will become even more so in the future. 

Concretely, for marketers, this will have an impact on digital strategies as we will start to see a decline in ad performance over time as conversions will be underreported.

In this area of change, all publishers are investing in finding alternatives and developing their own methods to respond to it. In this article, you will find more explanations on the solution proposed by Google called Enhanced Conversion. This solution allows the use of first-party consumer data to track performance and try to limit the decline of your campaigns.

What are Enhanced Conversions?

As explained above, enhanced Conversions is a new Google Ads feature. It will allow you to improve the accuracy of your conversion measurement when cookies are not available using first-party data. This is made possible by using first-party data that has been securely hashed. Effectively, hashing the data before sending it to Google Ads ensures user privacy.

This way, advertisers can send hashed (de-identified) customer data from their conversion page (e.g. email addresses), which will then be matched to Google's logged-in data. Enhanced conversions are not intended to replace standard conversion tracking, but instead, complement it with more data.

As a result, enhanced conversions can help advertisers more effectively measure campaign results across multiple devices, even when users are not logged into the same email address on each device.

What are the benefits?

• Provide more robust conversion tracking
• Increase the accuracy of conversion attribution
• Improve modeling accuracy and reporting
• Provide more data-driven optimization

Requirements before you start

If you are convinced and now want to start implementing enhanced conversions, here are the elements you should take into account before starting:

• You need to know your site's code and when and how a conversion is triggered
• You need to make sure that first-party data is available and stored on the page where the conversion happens
• You must read and accept Google’s enhanced conversions data policy that you can find here.

Once these three elements are completed, you need to go to your Google Ads account in Tools > Measurement > Conversions and click on the conversion where you want to set up enhanced conversions. At the bottom of the ‘enhanced conversions’ section, click ‘Turn on enhanced conversions.’ You will then need to read the compliance statement, agree to it, and then click on ‘Check URL’ to check your website for a Google tag.

What about the implementation?

Enhanced conversion tracking will require some minor changes to your tagging configuration, depending on whether you use Google Tag Manager (GTM) or Google Ads Global Site tag (gtag). You can find more information about these setups in the Google guides here for GTM and here for Global Site tag. 

In my next article, you will find a concrete case on how to do the implementation via GTM. In the meantime, I can already tell you that it can take up to 5 days to see the new options appear in GTM after the activation in Google Ads.

Conclusion

In conclusion, Enhanced Conversion is a new feature developed by Google to help businesses measure and improve their advertising effectiveness. Moreover, it allows us to realize that first-party data is more valuable than ever in this area of change. 

As you can probably guess, I recommend to all marketers to plan the implementation of enhanced conversions in your Google Ads account and I will explain a concrete case in my next article.

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At the end of 2020, we launched the first video campaign on TikTok with VOO. This was a first test to adapt our approach to the new way of living during the pandemic: people were much more connected and tiktok boomed as one of the most downloaded app in Belgium. Also, it started to be much more used by older users with 22% of the users being between 25 and 34 years old and 12% between 35 and 44 years old. 

This shift in behavior made us curious about tiktok advertising and that’s how we launched the first campaign as one of the first brands to have visibility on this platform. Today, TikTok has become a must in all media plans and is going to grow much bigger in 2022. 

Let’s go back to the end of 2020, we couldn’t redirect users to our website. It was pure awareness that we could do through reservation with no control on the audience, the budget optimization, and more. At the beginning of 2021, we could finally direct users to our website and analyse the quality of the traffic coming from this platform. Results were encouraging with a quality in trafic. Afterwards, a much bigger improvement came with the arrival of TikTok Ads manager. This was the opportunity to have immediate controle on our campaigns and have a day to day optimisation. In the evolution of this trend, we could also add conversion tracking in the platform to know the impact of our advertising. We see through this evolution that 2021 was the year of tiktok and that the evolution was tremendous during this year. 

And this is not finished, they have already announced many improvements for 2022. In the continuity of the conversion tracking, the shoppable ads will arrive soon becoming a must in the different phases of the acquisition funnel.

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