AI Advantage

Gamelight’s heart is a sophisticated AI algorithm designed to maximize ROAS, ARPU, and user retention. Unlike old-school methods that depend on manual review and slow progress, Gamelight’s AI checks campaign results instantly, always tweaking to boost conversion rates.

This approach transcends the classic display of ads to the highest bidder. Instead, the algorithm creates user profiles, identifying overlaps between engaged users of the game and potential new users and recommending the games to the most suitable users.

The AI’s ability to analyze the match between a user and an ad creative even before installation allows for precision in determining user fit, optimal ad display timing, and game-user matching.

Data Analysis Revolution

Gamelight’s AI targeting outperforms traditional manual methods. While old approaches use basic factors like gender, iOS version, and demographics, Gamelight’s system examines a wider range of data, including app usage and behavior patterns.

This information fuels an algorithm aimed at boosting ROAS, ARPU, and retention for advertisers. By processing data in such detail, Gamelight delivers much better results than its rivals.

Gamelight partnered with Korean app publisher JOYCITY to promote and scale their titles, Gunship Battle: Total Warfare and World War: Machine Conquest, in the United Kingdom, South Korea, and Japan.

For Gunship Battle: Total Warfare, Gamelight’s AI platform delivered impressive results:

• In Japan, the Return on Ad Spend (ROAS) at Day 30 (D30) reached 38.71%, exceeding the D30 ROAS goal by 48%. Additionally, there was a 213% growth in ROAS from Day 7 (D7) to D30.

• In the UK, the ROAS D30 was 35.37%, surpassing the goal by 35.78%, with a 143% growth in ROAS from D7 to D30.

For World War: Machine Conquest, the campaign also achieved remarkable results:

• In Japan and South Korea, there was a 257.61% growth in ROAS from D7 to D30. ● In the UK, the growth in ROAS from D7 to D30 was 230.20%.

These case studies demonstrate the efficacy of Gamelight’s AI-driven approach in significantly enhancing mobile user acquisition and engagement across multiple regions.

The Power of Personalization

Unlike traditional algorithms that operate on simple “if-else” rule bases, Gamelight’s AI-driven methodology is far more sophisticated. It doesn’t rely on predefined rules. Instead, it independently determines the most suitable user for each game, the optimal time to recommend a game and the most effective presentation method.

This approach considers factors such as how long a user has been engaged with the platform, ensuring that recommendations are always appropriate.

This knowledge allows for delivering highly relevant recommendations that resonate with individual players. Two users never receive the same game suggestions unless their data is identical, with the system constantly optimizing recommendations, timing,

Performance and Cost-Effectiveness

Gamelight’s platform stands out for its ability to skip expensive learning phases often seen in traditional targeting methods. From day one, the AI pinpoints ideal users, boosting overall revenue by focusing on those with the highest potential average revenue per user (ARPU).

Game publishers and user acquisition (UA) teams benefit from Gamelight’s blend of advanced technology and user-friendly design.

“Campaign setup takes just 2-3 minutes, doing away with complex processes that can eat up 30 minutes or more on other platforms”, – said Günay Aliyeva, Gamelight co-founder.

This efficient approach frees UA managers to concentrate on campaign strategy, while the AI handles the nitty-gritty of optimization. The system’s speed and accuracy lead to better results and smarter resource allocation.

Rewarded Marketing Advantage

In traditional models, advertising revenues are typically shared with publishers. Users end up just seeing ads, with no direct benefit. In contrast, Gamelight shares these revenues with users.

By sharing data, users play a part in a system where they can earn rewards, making it a win-win situation for all involved.

The process is straightforward. Playing a publisher’s game earns users points based on gameplay duration, fostering progression. Points can be exchanged for gift cards and

vouchers, rewarding loyalty. This Loyalty Program maximizes retention and engagement, fostering a dedicated fan base for immersive experiences. Users who reach their first reward milestone are also more likely to stick to their second reward.

With 7 self-published game recommendation apps on iOS and Android, and more than 10 million users in Tier 1 regions, Gamelight gave 2 million gift card counts and paid out $20 million in rewards in Q1 2024 only. Each mobile user in the US has seen apps’ ads 3 times on average.

AI-Powered UA: Reshaping Mobile Game Marketing

As mobile gaming grows, smart AI-driven user acquisition becomes vital. Gamelight leads this shift, not just keeping up. By blending advanced tech with deep gamer insights, Gamelight is building a system where finding new games is as fun and rewarding as playing them. This approach is setting new standards for how players discover and engage with mobile games.

As the industry watches and competitors scramble to keep up, one thing is clear: with the advent and development of AI the game of user acquisition will never be the same.

The post Gamelight    redefines    Mobile    Game    User   Acquisition    with    Advanced   AI Targeting. appeared first on Mobile Marketing Watch.

The following is a guest contributed post by Blis President Harry Dewhirst.

Current AI systems use training algorithms and brute-force computational strength, as opposed to real intelligence. If an alteration is made to a situation involving AI, it will currently not adapt as it has no ‘understanding’ and therefore cannot recognize new strategic patterns. There’s no doubt that future technologies such as AI and the Internet of Things (IoT) will be put to work properly by marketers, but the questions remain as to when and what it will take.

The limitations of algorithms

Algorithms are limited in their learning to a set of defined tasks, so if a self-driving car approaches a zebra crossing with some pedestrians standing nearby, it will stop and wait for them to cross, even if they have no intention of crossing, and won’t respond to their uniquely human gestures.

The limit to machine learning is data; with new streams constantly feeding in from all directions, there is an opportunity to learn and discover, but also a major technical challenge.  As the volume of new devices like hearables and wearables feeding into the IoT rapidly expands, they provide a treasure trove of data which needs to be speedily and accurately analysed to allow the IoT to live up to its potential. However, the manipulation of Microsoft’s Tay chatbot, which learned to be racist and rude in less than a day, reflecting the information it was fed and the behavior that it mirrored, shows us the importance of being able to logically sift good and bad data inputs.

Extracting meaningful insights

Machine learning can help companies take the billions of data points they have from IoT devices and boil them down to what’s really meaningful, so that better decisions can be made. This is essential to find patterns, correlations and anomalies, since current human approaches of data analytics don’t scale to IoT volumes.

Although location data from connected TVs (CTVs) and other IoT devices that rarely move currently has limited value, smaller mobile devices provide one of the largest location data sets as they are incredibly dynamic by nature, with mobile apps in particular proving very useful input data tools, feeding CTV advertising optimization.

The importance of context

As advertisers build in-depth profiles of users based on data from IoT devices, the importance of context to advertising is increasing. There needs to be a good reason to reach a consumer in their home and, while artistry and storylines are important in engaging audiences, the context in which ads are delivered is today equally as important to engagement as the uniqueness of the ad storyline and copy itself. Based on data insights, personalized ads can now be delivered to the right person, at the right place and time to ensure the message engages and resonates, creating a return on investment. Intelligent analysis of location data is critical because the “where” can significantly influence the choice of campaign served to a particular user at a given time.

Although the volume of data and the challenges and insights presented by our increasingly digital, mobile-centric world have made the job of advertising to consumers more difficult and multi-layered in some ways, if the correct infrastructure is in place, it is extremely helpful. Depending on how these advances are implemented, ads will either cause concern as they become invasive and affect overall privacy or, if they work smoothly, consumers will come to expect them more and more as they seamlessly fit in their lives.

While machine learning is enhancing the capabilities of the industry, real AI is expected to bring further advances; precisely how it will achieve this is hard to predict, but it is likely to generate surprising insights into customers’ requirements.

The post The Future May Be AI Powered – But We’re Not There Yet appeared first on Mobile Marketing Watch.

We’re told that 5HD will utilize Adbrain’s Identity AI to offer its clients a single, consolidated, cross-platform view of their customers.

Adbrain’s Identity AI approach utilizes machine learning technology to create cohorts of identities across three dimensions of data: People, Places and Devices. The multi-dimensional identity methodology affords 5HD a comprehensive view of identity beyond a single-device context.

According to an emailed statement, 5HD also selected Adbrain due to the ability to get raw-level data and because Adbrain can provide a cross-platform view across all 5HD’s advertising partners. These capabilities allow 5HD to present clients with a complete conversion path, taking all media channels into account to enable insights like how mobile page views result in desktop conversions.

“Cross-device is essential to understanding the full path to conversion. Through our partnership with Adbrain, we can bring all the pieces together and aggregate performance and conversion data like never before,” said Andrew Bauer, Director of Software Development at 5HD. “We can now give truly actionable insights, combining cross-platform marketing reporting with a 360-degree customer view. We’re able to show our clients in-depth insights on how simultaneous campaigns affect one another. That same reporting then helps us continually improve our campaigns to deliver more prospects and improved cost-efficiency.”

The post First Look: 5HD Boosts Analytics Platform with Adbrain’s Identity AI appeared first on Mobile Marketing Watch.

The tool, called Winston, is designed to increase engagement with the company’s video content. Winston breaks down a multitude of attributes for each video including metrics on audience viewership, audience retention and drop-off, shares, views, likes, comments, and benchmarking against prior videos created.

The tool provides a ranking of the video and offers suggestions on how and where improvements can be made. The bot combines these data points with a deep understanding of the algorithms populating social media feeds to help propel virality of content. Brands can utilize Winston’s capabilities when working in partnership with Keli to produce engaging, sharable videos for marketing purposes.

“AI tools like Winston are essential to our creators as they look for deeper insights and a better understanding of valuable content,” says Michael Philippe, Keli’s CEO and co-founder. “Winston’s judgments are fascinating, often quite unexpected but always of genuine value.”

To learn more about the technology at hand, click here.

The post The Keli Network Launches AI-Powered Video Analysis Tool appeared first on Mobile Marketing Watch.

The report, a survey of more than 100 marketing leaders including CMOs from prominent retail brands headquartered in the U.S. and U.K., explores plans and priorities for marketing investment this year.

The findings indicate that 86% of retail marketing leadership have planned to invest in AI/machine learning solutions in 2017.

The majority of respondents (47%) are looking to spend up to $50 million on AI, but a quarter are budgeting as much as $100 million. For marketing leaders surveyed, effective customer engagement is expected to be the primary benefit of implementing AI, where “engagement” is considered foremost as a driver of revenue (37%) and to a much lesser extent, brand awareness (13%).

Retail marketers look to improve engagement by providing more relevant experiences but continue to struggle with personalization. On a scale of 0 to 4, with 0 as least effective and 4 as most effective, marketers find that they could do a better job with personalization techniques: tailoring product recommendations (2.85); segmentation (2.53); offer personalization (2.49); and personalizing content (2.13).

“Most major retailers have more data than they know what to do with or have the capacity to process. AI and machine learning allow marketers to generate insights for sure, but the key is to leverage the machine towards a particular purpose, and to one that actually drives results,” said Ryan Deutsch, SVP of Global Customer Success at Persado.

The post Retail CMOs to Invest Record Sum in AI This Year appeared first on Mobile Marketing Watch.

In partnership with BrandGarage, this study highlights the “overwhelming emphasis retail executives are placing on automated platforms” to improve customer communication.

All told, 87% of the 100 retailers surveyed planning an increase in the use of AI to service their customers moving forward.

In 2016, 82% of customers stopped doing business with a company after a bad experience, according to the Internet Trends 2017 Report by Mary Meeker of Kleiner Perkins. At the same time, customer service costs are rising dramatically. As a result, retailers are increasingly turning to customer service and engagement automation technologies that leverage AI, including chat on Facebook Messenger and voice through voice assistants such as Google Home and Amazon Alexa, to unlock new revenue, reduce costs and boost customer loyalty, satisfaction and lifetime value.

This study explores the increased value retailers are placing on AI to alleviate points of friction and improve margins and revenue through their customer service and engagement.

To learn more, check out the report online here.

The post Most Retailers to Ramp Up Use of AI in Customer Engagement appeared first on Mobile Marketing Watch.

PulsePoint is a leading global programmatic advertising platform and it’s out with something new. MME has learned that the next generation of its content marketing platform has been launched.

“Story by PulsePoint” provides unified distribution across top social media channels, native and content discovery platforms, and premium websites — at global scale — according to the company.

The benefit? It greatly consolidates workflow as well as simplifying execution for content marketing.

“Content marketing continues to grow in importance as advertisers look for ways to differentiate themselves and connect with their core audiences in an increasingly complex media landscape,” reads the official word. “Branded content has proven successful. Consumers welcome useful or entertaining information and spend significant time with advertiser-produced media, which in turn produces higher conversion rates than traditional marketing, increases brand recognition and drives sales lift.”

What does Story by PulsePoint do? In sum, it helps marketers optimize for post-click behavior. The platform provides creative, audience, and page-level engagement metrics across channel and format and enables marketers to achieve maximum results through optimization tools that adjust campaign configurations in real time.

The addition of AI and machine learning to update algorithms and continuously improve performance is a major plus.

“Story by PulsePoint is built to help brands make meaningful connections with consumers,” said Andrew Stark, SVP of Content Solutions at PulsePoint. “Our technology focuses on engagement with content and provides actionable page-level behavior metrics to drive results and deliver successful campaigns.”

Want to see a Story by PulsePoint demo? Click here.

The post New PulsePoint Platform Offers Enhanced AI and Machine Learning appeared first on Mobile Marketing Watch.