For mobile marketers, UA managers, and advertisers, leveraging UGC is no longer a mere option; it’s a necessity. But what makes UGC such a powerful tool for mobile user acquisition? And how can mobile marketers incorporate UGC into their campaigns effectively? This blog dives deep into the world of UGC and its applications in mobile advertising, offering you actionable insights and strategies.

This article explores in-depth how AI solutions are transforming mobile app marketing strategies, detailing practical implementations, technical methodologies, and actionable insights to ensure scalable, sustainable growth.

This blog dives into how AI is revolutionizing mobile app marketing, shedding light on practical applications for improved creative testing, data analytics, and streamlined content production. Here’s how you can harness AI’s power to maximize campaign performance and dominate the mobile ecosystem.

Mobile advertising has undergone a seismic shift in recent years, largely driven by advancements in artificial intelligence (AI) and machine learning (ML). Among these technologies, neural networks have emerged as a revolutionary force, transforming how mobile app marketers and advertisers manage user acquisition, retargeting, and campaign optimization.

This blog dives deep into the top 10 benefits of using neural networks in mobile advertising and explains why every forward-thinking marketer should leverage this cutting-edge technology.

If you’re a mobile app marketer or developer, understanding how deep neural networks work—and the profound effects they’re having on mobile advertising—is crucial. This article will explore how DNNs are delivering scale, precision, and unmatched efficiency to mobile app campaigns.

We’ve compiled a comprehensive list of the top mobile game and app conferences in 2025 that you can’t afford to miss. From global gatherings to niche-focused forums, these events are perfect opportunities to gain insights, showcase your work, and connect with industry leaders.

This blog dives into the latest user acquisition strategies and highlights how innovative tools such as AI, machine learning, and demand-side platforms are transforming the way apps attract and engage their audience. If you’re a mobile app marketer looking to refine your approach to UA, here’s everything you need to know.

This blog will explore the top mobile programmatic advertising trends for 2025 to help you refine your app marketing strategies and maximize ROI.

For mobile app developers, marketers, and advertisers, understanding the dynamics of targeting and personalization in mobile programmatic advertising can significantly enhance campaigns by improving user acquisition and driving higher lifetime value (LTV). This blog explores the strategies, technologies, and platforms shaping the future of mobile advertising.

In the bustling world of mobile apps, getting noticed can feel like an uphill battle. Whether you’re an app developer or a marketer, your first major milestone is reaching 1,000 installs. This number not only represents initial success but also serves as a stepping stone toward gaining more users and establishing credibility in the app market. Here’s how you can achieve this crucial milestone for both iOS and Android platforms, leverage AI, minimize churn, and utilize demand-side platforms effectively.

In the fast-paced realm of mobile advertising, standing out is crucial. With countless apps competing for users’ attention, app marketers and advertisers must employ cutting-edge strategies to ensure their campaigns are seen and remembered. One such strategy gaining momentum is the use of mid-roll ads in mobile advertising. Whether you’re new to the concept or looking to refine your approach, this comprehensive guide will provide everything you need to know about mid-roll ads.

This blog post will explore the latest trends and best practices in mobile app A/B testing for ads in 2024, helping you refine your strategies and achieve better results. We’ll also examine the role of artificial intelligence (AI) in enhancing A/B testing efforts and how demand-side platforms can support your growth.

The world of mobile gaming ads is experiencing a quiet revolution. While the overall growth in ad spend has been modest, innovative strategies are gaining momentum among advertisers. Key among these is the rise of playable ads and the extension of campaign durations—a trend reshaping the landscape of mobile gaming advertising.

By harnessing the potential of in-app messaging, businesses can optimize user acquisition efforts, bolster their retargeting campaigns, and ultimately cultivate a more substantial and loyal user base.

Let’s delve deeper into the top 10 trends shaping the mobile gaming industry, influencing user engagement, technological advancements, and marketing strategies. By understanding and leveraging these trends, mobile app marketers can strategically position themselves for success and innovation in the evolving realm of mobile gaming.

In the fast-paced world of mobile app marketing, understanding cutting-edge technology can make all the difference in achieving successful advertising campaigns. One such area that is gaining traction is the use of neural networks and deep neural networks in mobile advertising. But what exactly are these technologies, and how do they differ? More importantly, how can they impact your advertising strategies?

Numerous industries are harnessing the immense potential of deep learning to fuel innovation. As computing power and datasets have significantly expanded, deep learning has transitioned from theory to practical applications. Whether enhancing manufacturing processes or refining mobile advertising strategies, deep learning offers opportunities to boost efficiencies and foster growth in various business sectors. Below, we unveil how neural networks with deep learning algorithms are poised to drive groundbreaking machine learning innovations for mobile advertising in 2024.

Tracking essential metrics for mobile app performance is crucial to guarantee a favorable user experience, boost engagement and retention, optimize revenue generation, and remain competitive in the constantly changing mobile app environment.

The rapid expansion of artificial intelligence (AI) has revolutionized diverse industries, notably mobile marketing. Through AI advancements, machine learning is now integral to data analysis and implementation in mobile marketing. This evolution is reshaping online advertising, prompting mobile marketers to adopt innovative strategies and technologies. Understanding AI’s significance in the marketing evolution is crucial for competitiveness in the mobile app industry.

Artificial Intelligence (AI) is at the forefront of transforming the landscape of mobile advertising, playing a pivotal role in driving significant change within the industry. Its influence extends across various critical areas such as campaign optimization, audience targeting, fraud prevention, and enhancing creative components, showcasing the multifaceted impact AI has on mobile advertising strategies.

Crafting a compelling ad for your mobile game can forge a strong bond with users, a pivotal factor for triumph in the mobile game industry. A captivating ad not only attracts the right audience but also enhances organic user acquisition, leading to optimal ROI. Furthermore, monitoring the performance of mobile game ad creatives can unlock the full potential of your game.

For years, focusing on user acquisition (UA) has been a key strategy for mobile game publishers to attract valuable players. This approach thrived on the abundant user data that powered their successful marketing efforts. However, recent privacy changes by Apple, and now Google have limited access to this data, prompting marketers to adapt their tactics to meet performance goals and rethink the role of AI in achieving success.

Want to grow your app’s user community? You’ll want to employ a user acquisition funnel—a strategic setup designed to captivate and convert newcomers to your app. It all starts with raising awareness about your app, nurturing potential users’ interest, stirring their consideration, and finally prompting them to act and install your app.

There are numerous strategies employed in the acquisition of users. Some of the most popular methods include influencer marketing, paid advertisements, social media campaigns, and search engine optimization (SEO). These strategies require a detailed understanding of your target audience to effectively reach and engage with them.

The technique known as cross-device targeting involves the identification and subsequent delivery of advertisements to individuals across this array of devices and platforms. Statista forecasts that by the start of the next decade, an average person worldwide will have close to 7 devices connected to the network. This projection presents advertisers with the formidable task of engaging with consumers in a consistent and impactful way across every device they use.

In today’s economy, increasing costs and inflation are not only impacting mobile purchasing trends but also tightening advertising budgets. Brands can no longer solely focus on growth as app abandonment and user churn continue to rise. Nearly half of all apps are uninstalled within 30 days. This is where paid media retargeting campaigns come into play. These campaigns help keep your brand at the forefront of users’ minds who have previously engaged with your app, generating considerable value.

Remarketing and retargeting are similar in many ways, but they do have some subtle differences. While they are often used interchangeably, remarketing generally refers to reconnecting with users through email. It involves targeting individuals who have previously engaged with a website or social media account, using personalized messaging. Remarketing emails nurture leads, encourage repeat purchases, or re-engage inactive customers.

With a wide range of options, from DSP to social media, navigating the landscape of mobile app marketing and connecting with your target audience can be difficult. Here are some top app distribution channels to help you identify the best marketing platforms for promoting a mobile app:

Game developers nowadays are discovering innovative ways to monetize their titles, acquire users, and improve development efficiency using a model called Play and Own (P&O).

In June 2023, Apple held its WWDC event and shared some updates on its latest plans to increase user privacy. Naturally, these announcements will significantly impact mobile advertising and the entire ad-tech ecosystem. At Bigabid we follow these updates and constantly analyze their impact on our customers and the service we provide.

Mobile app feedback is essential for delving into user experience. As an app developer, you are likely familiar with the significance of contextual user feedback. When combined with behavioral data, it can provide more insights into user experience and app performance compared to traditional techniques.

The usage of AI in mobile app development is widespread. It serves to resolve common user queries and improve their daily routine. By collecting and analyzing information from mobile devices such as contacts, location, and activities, AI can aid in enhancing user satisfaction. AI-based apps have the capability to accumulate and examine the data from customer interactions to facilitate human requirements.

Seasonal creatives have been shown to be highly effective in improving return on advertising spend (ROAS). Successful holiday creatives, such as those for single-day events like Easter, see peak performance over everyday creatives. Even more impressively, successful seasonal creatives can stay at the top for an average of 5 weeks.

In this article, we’ve provided a recipe for selecting the right technology or vendor for your business. By carefully mapping out your needs, resources, and constraints, and exploring potential solutions, you can make an informed decision that aligns with your goals. It’s important to keep in mind that there may not be a perfect solution, but rather a solution that fits your specific context and needs

Where should you publish first? What store will give your app the best chances for success? Understanding the differences between these two major app stores is essential for app developers and marketers. This article will outline the important difference to help you grow your app.

Despite challenges, 2023 will be a time for greater ideas, more comprehensive solutions, and harnessing technological opportunities in mobile app marketing. In this article, we will discuss the future of mobile gaming and non-gaming app marketing and share some key predictions for the upcoming months.

In this blog, I’ll teach you how to avoid dumb SQL syntax errors automatically. We will check the validity of each of our queries before we merge the code into production. The code for this article can be found on GitHub.

In this post, I will present why it is difficult to build trust in machine learning projects. To gain the most business value from the model, we want stakeholders to trust it. We want to provide defensive mechanisms to avoid problems impacting stakeholders and to build developers’ trust in the product.

This brief article will define the difference between all three and help illuminate best practices when utilizing these metrics.

App developers depend on a steady stream of ad revenue to be in business. Besides working with ad networks and partners to deliver the highest eCPM, publishers need to achieve the highest possible ad fill rates to maximize their ad revenue.

This brief article will define hyper-casual games, where they came from, and most importantly, how they can be monetized.

2022 has seen a challenging market hampered by the economic downturn, rising inflation, a war in Ukraine, a post-covid slump, and the remaining aftershocks of Apple’s privacy changes. But as they say, “when the going gets tough, the tough get going”.

Most Mobile marketers work tirelessly to increase their app’s conversation rate. The conversation rates they’re chasing could apply to app store installs, in-app purchases, subscriptions, etc., but the idea is the same… get your prospect to complete an action that converts them to a paying customer.

This article will outline what ads.txt is, how it works, its use in the mobile space, and uncover the app-ads.txt solution.

Mobile ad mediation is a mobile app monetization solution that allows app developers (publishers) to set, manage, and optimize multiple mobile ad networks with only one SDK (software development kit) integration.

In recent years, programmatic advertising has gone through rapid changes. With the onset of RTB and Header-Bidding technologies, auctions have grown more complex. If Publishers and buyers haven’t opted for fixed or pre-auction deals, the auction will be dynamic, where buyers bid for advertising inventory at different rates. This article will expose the benefits and pitfalls of both.

A programmatic waterfall (aka daisy-chaining) starts with a chain of ad networks/exchanges arranged in order of their performance for any given publisher from top to bottom. The network/exchange performance is typically rated based on CPM, fill rate, latency, etc.. Ad impressions are passed from network to network, from top-rated to bottom-rated ones until they’re sold.

Israel Mobile Summit is the ultimate event for everyone in the apps/games/adtech ecosystem. Whether you’re a publisher, developer, app marketer, startup, or VC, the summit features sessions on how to grow and monetize your apps using advertising and in-app purchases, how to analyze your data, as well as how to acquire and maintain more users.

If you’re looking to enhance your mobile app marketing campaign ROAS and deliver the best possible experience to your users, then understanding user segmentation is key.

As we depend more and more on ML (machine learning) in big business, we are beginning to see the effect of some big business ML failures. 9-figure ML-induced losses are becoming a trend like the recent Unity 110 M loss, Zillow’s recent ML failures, and many more. Considering this disturbing trend, we thought it pertinent to share how Bigabid approaches ML data quality, real-time and near-real-time monitoring, and performance by segment.

Many DSPs (Demand-Side Platforms) specialize in either UA (User Acquisition) or RT (Retargeting) technologies but not both. Running UA and RT campaigns in isolation can lead to misattribution, redundancies, and therefore a wasted spend. Bigabid advocates running UA+RT in harmony, and here are five reasons why!

Mobile gaming has taken over the world. Today, 9/10 gamers are mobile gamers, about 70% of all app store revenue is gaming, and by next year there will be roughly 3.07 billion mobile gamers worldwide.

From exploration to execution, high-scale campaigns demand the symbiotic coordination of an experienced team and revolutionary AI. Bigabid’s RTB team has refined its methodologies and technologies to scale campaigns with confidence by baking in all the essential ingredients that our high-scale campaigns depend on.

Recent mergers and acquisitions involving gaming companies like Microsoft and Activision Blizzard and advertising companies like AppLoving, IronSource, and Zynga have furthered the shift towards the use of first-party data.

Benchmarks can be CPI, ROI, or any other KPI that is important to the client. Sharing what ROI other vendors are reaching does not disclose any sensitive information such as budget or even strategy and is completely anonymous.

With proprietary tools like Deep Categories, which uniquely categorizes apps into thousands of categories instead of the 50 or so that the app stores use; Real-Time Data Analysis, which analyzes terabytes of data in real-time; and Creative Personalization, which creates thousands of ad variations to find the perfect fit…

App Tracking Transparency (ATT) is here to stay. Whether or not Apple is an altruistic champion of user privacy, playing war games with Facebook, or creating an unfair home-field advertising advantage is moot.

Bigabid has built an A/B testing system that is able to run hundreds of experiments simultaneously to provide answers about the effect size and statistical significance of creatives and treatments to any sub-group.

With recent advancements in creative optimization and personalization, along with modern AI-powered retargeting technologies, Bigabid can execute retargeting ads at high resolution and accuracy. 

In the past 3 years, we’ve collaborated with game app developers, designers, analysts, and monetization experts to give our proprietary ML (machine learning) technologies the edge in the social casino app industry

In the past 3 years, we’ve collaborated with game app developers, designers, analysts, and monetization experts to give our proprietary ML (machine learning) technologies the edge in the social casino app industry

We often hear from advertisers around the globe the term “cannibalism” relating to working with multiple advertising channels on either user acquisition or retargeting campaigns at the same time.

Today, Bigabid is hyper-focused on spearheading the use of ML to create a new generation of DSPs to target high LTV users in a more effective way than anyone else in the market.

App tracking transparency (ATT) is a new privacy protection framework for Apple devices. In practice, it means that when one downloads or opens an app, a notification pops up asking if the user wants to be tracked…

Retargeting activities are crucial for app growth. From owned media to working with DSPs, retargeting should be constantly evaluated and tailored per app. Now go find your retargeting partner or partner(s).

Real-time data analysis adds an exciting performance-enhancing element to user acquisition. Targeting in real-time based on session features and Deep Categories greatly improves our pricing, and therefore, your ROAS.

Bigabid upholds transparency as a core value in all of our relationships from clients to users, employees, and investors. It is the basis of our workflow, and therefore, it flows throughout our technology.

An app retargeting campaign is targeted toward users of an app who previously installed the app, were active for some time, and have churned. Because the audience is accurate and relevant, these campaigns can be highly effective and profitable.

The fact that Bigabid has been effectively using Deep Categories for a few years now, gives us a major advantage. We can spearhead this new era with our compliant, contextual-based technologies and help our clients have a smooth transition and ongoing success.

This is why Bigabid has developed such a unique approach. We create, produce, and run a massive collection of ad creatives. We integrate different concepts, wording, web-psychology insights, design patterns, and many more elements.

Bigabid is among the pioneers bringing order to this segment that was once called the “wild west of advertising,” helping advertisers reach users who are outside the “safe zones” of the Google and Facebook duopoly.

Incrementality is the measure of the lift that advertising spend provides to the conversion rate. Incrementality allows the advertiser to measure the effect of paid advertising for users from being idle/churned to coming back to the app on top of the organic return.

Whether a data scientist is just beginning her professional career, or she is already a seasoned professional, working at a startup offers a number of advantages. Most startups are more hands-on, and usually most employees are involved in many aspects of the company.

Companies know what buzzwords prospective clients want to hear, and they’ll use them regardless of whether they truly relate to their offering. This not only damages the client’s trust; it also harms the entire ecosystem’s push towards a safer and more efficient industry.

At Bigabid, ensemble learning methods are the weapons of choice when it comes to our machine learning (ML) architecture. As ensemble learning methods combine multiple base models, together they have a greater ability to produce a much more accurate ML model.

When you implement the Data QA process we’ve outlined here, you’ll be amazed by the number of bugs that exist in the data writing process that you’ve never even noticed.

One in five users forgets about an app after using it for the first time. They’re originally drawn to the app from an offer they’ve received or for a specific use, but after their first time using it, there’s a good chance the app will fall completely off the user’s radar.

The most obvious issues are related to computational efficiency, and the inability to visualize high-dimensional data. In this article, we’ll dive into the technicalities of PCA to help you better understand the model and its uses, benefits, and limitations. We’ll also explore some extensions to PCA. 

AI is now mature and widespread enough to encounter criticism. Since most AI systems today aren’t quite software, the difference in their business model renders them less attractive for venture capitalists.

Although feature stores play a vital role in data strategy, it’s still difficult to find information about them online. But understanding what feature stores are and why they’re important is crucial, especially in today’s world of increasing data governance, and business problems being increasingly solved by machine learning models.

A Game-Plan to Scaling in a Responsible Way. Scaling up your platform is a necessary part of the evolution of your company. Moreover, scaling should be something that’s always on your mind.

How to deal with scaling on a day-to-day basis. You’re now managing a scaled system. Congratulations! But wait—don’t throw your feet up just yet.

Are you interested in getting into the field of data science? We don’t blame you. Data science is an exciting field that’s constantly changing and developing, which gives data scientists’ work endless potential.

Imbalanced classes are a common problem in machine learning classification, where there’s a disproportionate ratio of observations in each class. In this article, we offer guidelines for working with imbalanced datasets.

A/B testing is usually the first choice for people aiming to optimize an ad campaign setup. Instead of relying on guesswork, with A/B testing you can make choices based on more scientific data. 

While heatmaps are hardly a new concept in digital advertising, their advantages are often forgotten and they’re rarely used for in-app user acquisition. In this article, we survey some of the ways in which heatmaps can be beneficial to your performance strategy.

In order to ensure that the work of data scientists is well-managed and delivers impactful results, our approach focuses on defining a set of possible outcomes for each data science task.