Why programmatic advertising is a must-have in 2024
In the previous material, we outlined the challenges advertisers face in the mobile traffic market and proposed our alternatives for solving them. Now, we are ready to back it up with action and demonstrate through specific examples why programmatic platforms should be considered as primary traffic sources in 2024.
1. Low fraud percentage
Undoubtedly, the fraud percentage in programmatic platforms is much lower than in other sources. In our experience, the peak value within an advertising campaign did not exceed 7%.
For example, here are the statistics of an advertising campaign for one of our FinTech clients in traditional traffic sources (CPI/CPA networks). The average fraud percentage across all sources was 39.4%.
Below is the statistics for a similar time period, but only for launches in programmatic platforms. The average fraud percentage here is 0.7%. The difference is not just significant, it’s enormous.
Another example is a client from the Entertainment category and their statistics from programmatic sources:
The average fraud percentage is 1.87%.
One of the indicators of quality traffic is the click-to-install conversion rate (CR). Let’s compare this metric in CPI/CPA and programmatic sources.
If in CPI/CPA traffic sources, the click-to-install conversion rate varies from 0.05% to 0.15%, in programmatic platforms, this metric is in the range of 0.38% to 1.31%:
The results of advertising campaigns prove that with proper attention at the launch stage of programmatic sources and the completeness of the provided data, we have quality traffic with a high CR and a low percentage of fraud.
2. Achieving KPIs
Before launching ads in programmatic sources, it is necessary to consider all technical nuances and set up campaigns correctly: starting from providing first-party data and ending with budgets, which are usually higher than in traditional sources. We provided more details about the setup features here.
In addition, it’s important to monitor the entire pool of sources you launch because click spamming sources can steal not only organic traffic but also the traffic from other high-quality sources.
Unfortunately, in reality, it is hardly possible to comply with all the requirements for the correct launch of programmatic advertising. However, even in these conditions, programmatic platforms deliver much higher quality results. Therefore, in our work with clients, we always strive to build transparent and trustworthy relationships – much of the success depends on it.
Client 1 — Online Retail
The goal: to increase the number of orders in the iOS app
Target CPA (in-app order): $10
This is one of the few clients who was open to experiments and entrusted us with launching programmatic sources. We gained access to first-party data, checked the technical settings of trackers, and agreed on the necessary budget for the launch. The only drawback was the absence of suppression lists, which ultimately affected the results.
Nevertheless, as seen in the chart below, after a month (exactly the time required for campaign learning), we were able to achieve the target CPA.
Unfortunately, we cannot disclose the campaign’s profitability data, but we can confidently say that the quality and LTV of users were close to the characteristics of organic traffic.
Client 2 — FinTech
The goal: to improve the quality of traffic for Android and iOS
Target CPA (subscription on service in the app): $10
Next, we provide a table with the results of advertising campaign launches in programmatic sources, comparing them in September and October. It is evident that after the learning period, the results are significantly better.
It’s worth noting that throughout this campaign, the client also had click spamming sources connected, which could have influenced the final result. However, even with this consideration, the trend of reducing CPA while maintaining traffic quality is evident.
Client 3 — YOU
To understand how well programmatic traffic sources can perform, we created a simple model. It will help forecast the launch results.
As an example, let’s take a client whose campaigns become profitable at a CPA of $1,000. The CAP on events for all sources is set at 400 events per month.
The client launches CPA/CPI networks where fraud via Protect 360 is not paid for. The client tracks orders in CRM and does not pay for traffic if more than half of the orders are canceled. We do not consider data reconciliation in the model, but we assume that only those orders that passed it by the end of the month were paid for. Let’s assume that the client’s average ARPPU (Average Revenue Per Paying User) is $6,000.
On average, post-fraud, namely empty users, bots, and users with abnormally low checkouts, make up about 35% of the traffic, but ‘catching’ them at the reconciliation stage is practically impossible. Therefore, for CPI/CPA networks, we will reduce the average ARPPU received by the same 35%.
In parallel, we launch test campaigns in programmatic sources. We allow optimization for the target CPA only in the third month. According to the model, the traffic, taking into account the learning period, will fully pay off and turn into a solid profit after 4-5 months from the launch.
3. Audience selection
Programmatic platforms allow you to reach the desired audience faster. We recommend launching 5-6 programmatic sources to fully test various types of machine learning optimization. Here are some of the targeting options within the platforms:
Conclusion
In the market, there is a problem with the quality of traffic. The overall capacity of the market remains the same; only the methods of working with traffic change. Anti-fraud systems are becoming more and more sophisticated, making it increasingly challenging to meet the criteria of ‘quality traffic.’ This pushes many agencies to work in a conservative mode and search for new sources that will pass the verification.
On the other hand, clients’ unwillingness to reconsider ways to achieve KPIs does not give a chance to test sources that could replace bot traffic. It might seem that this imposes additional risks on agencies and clients themselves. However, in reality, it is not the case.
We see an obvious solution – programmatic platforms. However, here we also encounter clients’ reluctance to share their data. This wasn’t required before. Unfortunately, there is no other option. Only working in an environment of complete trust, readiness for experiments can bring a quality result and push the entire market towards positive changes.
