User acquisition and app marketing optimization are crucial steps if you want to monetize your app. To achieve them, you need to have a DSP (Demand-Side Platform) that understands your needs and helps you with the more technical aspects of your campaign.
Here at Mapendo we believe to be a very reliable partner that can assist you in this long and hard process, and we will explain to you why by telling you our best features.
An enormous volume of impressions for every need
Our A.I. receives tons of billions of impressions each day, generated all around the globe and from both iOS and Android users.
Such quantity of impressions secures a large audience pool with no risk to exhaust it and can surely be of much help in times of decreasing profit.
We developed our own machine learning technology and it never turns off
Our machine learning technology has been developed entirely in-house and, for this reason, we hold a wide range of proprietary features that can really help app marketing optimization and user acquisition.
- One of them is the Logistic Regression model, which enables us to predict future clicks and conversions based on historical data. To have this large quantity of data trained to assess the likelihood of a specific event occurring, we can place bids on the most promising offers.
- Moreover, our machine learning technology and in particular our OpenRTB bidder is responsible for creating different dynamic creatives and keeping a balanced rotation of them so the better performing ones will be shown with more regularity.
We use Machine Learning to optimize towards IAPs
Within instants from the beginning of the user acquisition campaign and the app marketing optimization, our machine learning technology immediately starts to work, learn, and improve. It will only need a few weeks for its improvement to be considered complete.
When optimizing towards in-app purchases, Machine Learning stands out as an essential tool.
- It can analyze user patterns and behavior within the app. That allows us to create personalized recommendations and increase the likelihood of conversions.
- In a similar way, ML can help make predictions by using user behavior, in order to maximize engagement and time in-app purchase prompts.
- By detecting unusual patterns of in-app purchases, it can also pose a safeguard against possible fraudulent activities and protect the app’s revenue stream.
This is an example of how we managed to decrease CPA with our algorithm of Machine Learning.
This process of self-optimization is powered by what is called a Reinforcement Learning algorithm. We also own our AI powered CPA optimizer, called Jenga, which collects tens of thousands of data to predict the possible outcome of a mobile user acquisition campaign and find the audience most likely to convert.
A perfected bid optimizer
Mapendo is, for all intents and purposes, a fully managed DSP: we own our proprietary tech platform, managed by a great team of people, and that goes for our bid optimizer as well.
Every day, we take part in millions and millions of auctions in real-time bidding and our bid optimizer can make decisions in less than 60 milliseconds.
We have developed a great deal of experience with our powerful proprietary technology and that has enabled us to deliver global campaigns since 2013, the year of our launch.
Our machine learning tech allows our bid optimizer to constantly learn and improve, and to keep on acquiring advertising space at always better prices.
We deal with your budget with a multi-faceted approach
Being able to optimize your budget and make wise investments goes hand to hand with the outcomes of a user acquisition and app marketing optimization campaign.
Mapendo’s policy as a DSP involves three different and simultaneously applicable ways of budget optimization:
· First, we target high-quality users, those users who we think will generate the most revenue through post-install events. In this way, we prevent you from wasting budget on those who, on the contrary, after downloading your app, will proceed to uninstall it.
· We always make decisions and plan our strategies based on actual data, to learn what users like or do not like about your app and predict which areas can be improved or which areas can be monetized even more.
· Machine learning cannot be left out when talking about app marketing optimization, as it provides us with many useful information we can use to analyze users’ behavior and focus our efforts on high-conversion users.
We strongly believe in full transparency
Transparency has to be considered key when talking about results, but with all sorts of data as well. This aspect is crucial and, make no mistake, must go in both directions, from advertisers to DSPs and vice versa.
It's imperative to emphasize that Mapendo never requests any form of personal data. All data shared is exclusively pertinent to app optimization.
At Mapendo we have a well-established practice of continuous data exchange, focusing on engagement metrics, conversion rates, and revenue generated, so that we can tune our strategies and make decisions based solely on data-driven factors. One of the elements we always take into account is ROI (Return on Investment), which we consider to be one of the most indicative in terms of app marketing optimization.
Furthermore, we strongly encourage our partners to integrate our systems with their internal Business Intelligence (BI) so as to have a better understanding of the app’s performance in real time. Having access to metrics such as LTV, ARPU and predicted ROI helps us with the optimization process when targeting high-quality users.
Creative support is a strength of ours
When it comes to making user acquisition and app marketing optimization successful, creatives play a fundamental role, equal in importance to everything we have talked about so far.
Mapendo provides creative support and expertise through the employment of various ad formats and A/B testing, which enables us to assess the efficiency of every single creative employed, from video and playable ads to banners.
Something that makes us proud is the success of our own dynamic ad units, which consist in the combination of video and playable ads with the addition of an end card that can be static or dynamic.
This kind of approach has proved to be very effective and has always made ROI optimization possible and ROI goals easily traceable and achievable, which has always been our intent.
SKAdNetwork is well within our compass
SKAdNetwork was released by Apple in 2018, along with the launch of iOS 14.5, and, according to the company itself, represents the only method that guarantees deterministic attribution of conversions in app install campaigns.
Having SKAdNetwork always been a certainty in terms of quality traffic without any chance of fraud, it has been one of our priorities from the beginning. This is why Mapendo is well-integrated with the SKAdNetwork technology to receive conversions from both install and post-install events and has launched many UA campaigns in the US in this way.
We also take advantage of the recent implementation of SKOverlay, another tool developed and provided directly by Apple itself, with which we have been able to increase our conversion rates.
We target successfully, even without IDFAs
With the release of iOS 14, Apple has made a significant impact on the world of user acquisition by introducing the App Transparency Tracking (ATT), which places stringent privacy safeguards to protect users. In plain English, if before iOS 14, advertising could work with unique identifiers referring to individual mobile devices (IDFA), that has not been the case anymore since then.
This means that, along with what is called behavioral targeting, the world of app mobile marketing has seen the comeback of contextual targeting, and we at Mapendo have been more than able to adapt to this new market.
Our bidding and app marketing optimization technology can segment users into what we technically refer to as 'pockets,' representing groups of users with similar characteristics. This segmentation allows us to precisely target users who are most likely to generate revenue.
Such characteristics are not behavioural data based on individual interests but, instead, are the app itself, the current session and the type of mobile device on which the app is installed. Through a thorough analysis of these factors, Mapendo's algorithm excels in identifying high-performing areas and optimizing cost-effective strategies.