Global programmatic spend is projected to continue showing tremendous growth, with an expected surge from $557.56B in 2023 to $724.84B by 2026. This is according to Statista. Furthermore, even though the pandemic is over, it has left a noticeable and persistent mark on consumer behavior. People are spending more time on their mobile devices. According to Data.ai’s ‘State of Mobile 2023’ report, in the Top 10 front-runner regions, the average time spent on mobile increased by 9% between 2020 and 2022 to an average of 5 hours and 2 minutes.
With this in mind, is it time to level up your mobile marketing? Incorporating mobile programmatic into your marketing plan will help you reach your targets anytime, anywhere, all at once.
Help marketers reach the desired audience
Programmatic is a powerful media buying tool, the fundamental nature of it being the ability to target the right audience. To do this, segmentation is needed.
User segmentation is a common marketing strategy where marketers group audiences based on certain criteria. It provides a filter for your campaign, and it not only helps you save money, but it also helps improve performance.
Segmentation varies depending on your marketing objective. For a successful outcome, it is important to clearly define your marketing objectives. Also, feeding your first-party user data into machine learning models will help you reach your desired audience and improve the accuracy of your targeting.
4 types of user segmentation models for mobile app marketing
Launching an ad campaign to promote a hardcore shooting app to people seeking casual entertainment, or promoting an RPG game to a crossword lover would not make sense. Right? Delivering the right message to the right user is at the core of acquiring high lifetime-value users. Making sure each message is relevant to their interests. Simply put - relevance is the key to ensuring that your message resonates with your target audience.
To start the segmentation process, you need to understand your user’s persona, as well as define the primary goal for your campaign.
Pro Tip: It’s essential to give the ML model enough time to train and accomplish a specific goal and not to change your campaign goals frequently. This will help you to achieve optimal results.
Let’s dive into the 4 most common segmentation types when it comes to mobile marketing campaigns.
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Geographic
Geography is the most commonly used model. It includes country/region, city as well as language. By identifying filters based on geo-location and device language, you can break down the cultural barriers to deliver the right message to your audience.
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Demographic
Demographics look at the characteristics of your target audience. How old are they? How much do they earn? And what is their social status? By analyzing your first-party data, DSP partners can help to expand your user base and find audiences with similar features.
Pro Tip: A smart way to infer their income level could be their device type.
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Psychographic
Psychographics look at your audience’s attitudes and aspirations. Whether your app is aggregated with social features or not, it is important to try to understand your users’ motives. Are they competing against friends, or just staying connected? Understanding what drives them to keep coming back to your app could be the lever to your creative development and drive new concepts for your next campaign!
Ideally, the concepts should resonate with your target audience, and in-app activities should not only be smart but also provide value. When the ad fulfills the users’ mental needs, they are likely to promote your app on their platforms.
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Behavioral
Does your gaming app cater to quick play, or does your app aim to resolve daily pain points such as shopping or food delivery?
It is crucial that you understand your product’s core mechanism and combine it with the habits of your user base. And then promote your campaign during the users' most active hours! Seasonal promotions are welcomed, but it is important that you start preparing these promotions well in advance - at least one month in advance - so your stakeholders have enough time to leverage them.
Pro Tip: It’s also possible to identify whether your app users are at home or at work (connected to Wi-Fi or not).
User segmentation could provide great insights for mobile app campaigns. Especially when your apps have a global presence. Be sure to customize your chart and target the unique characteristics of your users to win them over.
Help marketers reach the desired audience
Now that you understand the theory of segmentation, you might be wondering which segments to target. How do you choose? Well, we're here to help with a few practical tips for your next retargeting campaign!
The more your DSP partner knows about your users, the better. So, sharing as many segments as possible with them will make it easier for them to analyze audience segments accurately. This, in turn, will help their models target the best users.
At Aarki, we use the data provided and our deep expertise in different verticals to make suggestions on which segments are most effective for a specific category. By leveraging our team's knowledge and experience, you can be confident that your campaign is optimized for success.
Need an example? Let’s say you have a shopping app. Well, you can segment your users using a behavioral approach based on the following events:
- Install
- Open
- Add to Cart
- Purchase
The Aarki team can suggest segmentation strategies based on this list of events and will identify groups to target in each segment. For example, if the advertiser shares two segments—days lapsed and spend level - they can create the following targeting groups:
- 7 Day Lapsed [A]
- Spender
- $20 - $49.99 Purchases [B]
- $50 - $99.99 Purchases [C]
- Non-spender
- $0 lifetime IAP [D]
Furthermore, the team can look at intersecting these segments to reach different kinds of users:
- Spender
- A + B – Inactive, low engaged users
- A + C – Inactive, medium engaged users
- Non-spender
- A + D – Inactive, not engaged users
The result of intersecting segments [A] and [C], is a segment of inactive, medium-engaged users (as illustrated in the first Venn diagram). If a third segment is added - add to cart - it is possible to target more relevant users - inactive and highly engaged users. These users will more likely spend more and stay in the app longer to complete the purchase in the cart. Thus, having more segments leads to the generation of superior campaign performance with a higher return on ad spend.
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Bottom Line
Segmentation is critical in in-app marketing and cannot be ignored. By understanding your audience's interests and behavior, you can tailor your message to resonate with them and increase engagement, retention, and revenue. With the help of advanced DSPs like Aarki, you can leverage the power of machine learning to analyze and utilize audience segments effectively. This can significantly impact the success of your campaign.
So, if you're looking to optimize your app marketing strategy and achieve better results, it's time to focus on segmentation. Shoot us a message for more insights.
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