Beyond the Hype: Discover how Mobio redefines AI in digital marketing

In the latest Apptica Talks episode, Apptica was hosting Sergey Konovalov, CEO and founder of Mobio Group, who shared insights into the transformative role of AI in digital marketing. Sergey spoke about Mobio’s innovative approach to adopting AI tools, their focus on talent development, and the practical ways AI enhances marketing processes – from creative production to fraud detection.

The discussion touched on the challenges and opportunities of AI integration, upcoming features at Mobio, and what the future holds for mobile marketing. Sergey’s expertise shed light on how AI is not just a trend but a powerful tool reshaping the industry. Let’s dive into the key takeaways!

To watch or listen to the full interview, follow the links below:
YouTube
Apple Podcast
Spotify

Sergey, could you please give our listeners a snapshot of Mobio Group – your mission and what sets you apart in the competitive world of mobile marketing?
Mobio Group is a reliable mobile app marketing agency headquartered in the UK, with offices in the USA, offering high-quality mobile app promotion. Our team of over 80 experienced marketers and app promotion specialists helps clients achieve maximum results for their advertising budgets. We prioritize transparency in our client relationships and provide top-notch services.

Our mission is to identify talent, foster growth and help individuals become industry-leading experts. Over the past 11 years, we’ve supported over 300 young professionals in starting their careers and excelling in the mobile industry.

The uniqueness of Mobio lies in our relentless drive for innovation and our constant striving to learn and provide cutting-edge solutions for our clients and partners. Every 2-3 years we discover new traffic sources and test 100+ hypotheses to launch something groundbreaking.

Mobio works with top-tier app developers and global brands, delivering measurable results. Given how AI has been marketed as a game-changer for digital campaigns, I’m curious: why do you think it’s often perceived as overhyped in marketing?

Many people don’t realize they’re already living in the AI era. Companies like Facebook, Google, and TikTok are already operating at the forefront of AI technology. Yet these innovations are so seamlessly integrated into our everyday lives that they often go unnoticed.

This creates a paradox: while people underestimate the impact of current AI technologies, they hold inflated expectations for future breakthroughs. They’re looking for something radically new, even as transformative changes are happening around us every day—especially in fields like marketing, where AI is already reshaping the landscape.

Speaking of the beginning of this AI era: from your experience, were the initial promises of AI realistic, for overall digital marketing, or for some particular areas?

We considered this in areas like user acquisition or creative performance. When we talk about the acquisition, it’s important to say: while AI is developing rapidly, it can never keep pace with the constantly changing behavior of users. I believe that even if AI technology influences user behavior, humans will adapt and learn to understand other human beings faster and better than AI. That’s why, in the realm of user acquisition, and especially in creative production, we will always need human beings to set trends and connect on a deeper level.

Are there any other factors that have shaped this reassessment of AI’s potential?

When it comes to AI’s potential, I don’t believe it’s overestimated—in fact, I’d argue it’s quite the opposite: it’s underestimated. Over the next five years, we’ll likely see content production increase by 10, 100, or even 1,000 times. This will push us into uncharted territory, where we’ll face entirely new questions about how advertising operates and how users behave in this rapidly changing landscape. AI holds immense potential, much of which remains invisible and unexplored today.

Mobio is one of the greatest examples of wise AI usage – you even created a specific section with AI-driven tools on your website. Could you tell us more about this “collection” of useful AI services in one place?

We decided to create a specialized AI department within our company to ensure a structured approach to working with AI tools. This department was designed to test and validate AI tools and integrate them into our daily operations. We brought together experts from various departments — analytics, creative, performance, marketing, and sales — ensuring a comprehensive approach to identifying and leveraging the best AI solutions.

Besides this framework, how does AI fit into your operational activities? Maybe you could share a specific tool where AI has transformed the working process and outcomes?

I’d like to highlight a critical application with two examples from our experience:

1. Fraud Detection Bot: we developed a bot to work with affiliate networks and teams, addressing the significant issue of fraud. Our bot uses fraud scoring to analyze data from AppsFlyer, detecting hidden and sometimes unknown fraud patterns. This automated approach enhances our ability to stay ahead of evolving threats.
2. Traffic Anomaly Detection Bot. Another bot we built monitors traffic for critical deviations. It sends real-time notifications to our team in Slack about anomalous activity in traffic, allowing us to act quickly.

These tools have saved thousands of dollars during user acquisition campaigns by identifying and addressing issues early, ensuring clean, fraud-free traffic.

Those are impressive applications! However, I’m sure that you faced some difficulties while incorporating AI into your work. In the case of Mobio, what were some of the biggest challenges you faced while adopting AI?

At the start of this process, we faced a lack of specific AI skills: while many team members had basic knowledge, like prompt engineering, no one had deep, specialized expertise in AI. Next, lack of ready-made solutions: it might seem like tools like Jasper or other marketing AI platforms can solve all problems, but in reality, these tools often don’t fit your specific tasks, clients, or requirements. So, most AI models need to be trained for your unique use case and that requires significant investment which takes time. And even after model training you need to remember that there will be no immediate perfect solution. The final is safety concerns. The potential risks, like data breaches, made us cautious about how we implemented AI tools.

These were the main challenges we encountered at the beginning of our AI integration journey.

You mentioned a lack of specific AI skills firstly, but your case of AI adoption is more than successful, so you’ve most likely built a strong in-house team to navigate this landscape and overcome this challenge. What competencies or roles have proven essential for using AI & neuronets effectively in performance marketing?

Several key skills are essential:

1. Generating prompts. We engage in work analysts with experience in crafting effective prompts and understanding how to interact with AI tools.
2. A foundational understanding of coding and familiarity with machine learning principles, that helps teams understand how AI models function and how to refine them for specific needs.
3. Understanding neural networks. A grasp of how neural networks operate is critical for optimizing AI tools and addressing complex challenges.
4. Knowledge of data protection principles and adherence to regulatory requirements is crucial for ensuring security and compliance.
5. The last but not the least: organizational skills. Coordinating experts from different departments—analytics, marketing, creative, performance, and sales—requires strong organizational abilities to synchronize efforts effectively.

These skills will help to effectively implement AI in a business.

Could you please share the main tools or platforms you rely on, and how do they complement your processes?

1. Gamma for creating presentations and visual storytelling
2. Pieces for organizing and managing creative assets efficiently
3. Perplexity for enhanced research and contextual AI assistance
4. Claude (Cloud) for advanced natural language processing and content generation.
5. Continuum for project management and task automation
6. Notetaker for capturing and organizing meeting notes seamlessly.
7. Dataline for analyzing and visualizing business data.

In addition, we rely on classic tools like Slack, Asana, and Data Studio for daily operations and team collaboration.

Given the volume of data Mobio handles across multiple campaigns and regions, how do you ensure secure use of AI? Are there specific frameworks or practices you’ve implemented?

We have defined several principles for safe data handling.

1. Anonymized Data. Ensure that all data used is anonymized.
2. Generalized Data. Work with aggregated or generalized data instead of specific numbers to reduce exposure of sensitive details.
3. Split Data. Distribute data processing between local and cloud neural networks to minimize risks associated with centralized storage.
   To prevent accidental data sharing we activate temporary or hidden chat modes. Additionally, it’s a good idea to consult with data analysts to implement robust data encryption protocols.

As Mobio has always been ahead of the curve, identifying trends before they go mainstream, I’m thrilled to ask: what’s next for AI awaits us at Mobio? Are there any specific innovations or tools in development that you can share with us?

We will focus on synthetic conversions and integrate AI into their creation, enabling more efficient ad system training and achieving better results while with reduced spending.
Also we plan to develop several tools for the App Store:

1. An optimization bot, which will serve as an analytics tool and provide actionable recommendations to improve app visibility and performance
2. A copywriting bot for generating optimized ad copy.
   Additionally, we will design a user segmentation system based on value metrics (recency, frequency, and monetary indicators) to enable more effective targeting. Lastly, we will implement an HR analyzer—a tool designed to streamline the recruitment process by analyzing resumes to identify the best candidates more efficiently.

Speaking of the broader industry, how do you see AI evolving in mobile digital marketing over the next few years? Are there any trends or challenges that marketers should be preparing for now?

I believe one of the most significant trends is the development of voice interfaces, which have the potential to be a game-changer for many industries. The combination of voice interaction with visual displays could revolutionize the way we access information, making interactions more natural, intuitive, and efficient. The way we engage with technology will undergo a fundamental transformation, opening up new possibilities that go far beyond what we experience today.

It’s been a fascinating discussion! To close, if you could give one piece of advice to marketers or businesses looking to integrate AI into their mobile strategies, what would it be?

I recommend giving young professionals more opportunities to prove themselves as they are more open to learning and practicing with new technologies. Our generation can greatly benefit from the fresh perspectives and adaptability of the youngers. They feel comfortable with new tools and trends, which can greatly help us bridge the gap and stay ahead in this rapidly evolving technological landscape.