Empowering Mobile Marketers with AI: PGC London Report
PGC London, calling to the faraway towns — and bringing together the best of the mobile gaming industry, all for one fantastic event.
Last month, Pocket Gamer Connects London 2023 had its most impressive turnout in history. If you were there, you saw it for yourself.
After a knock-down, drag-out kind of year in 2022, it was inspiring to see so many intelligent and motivated people coming together again to share their thoughts and collaborate on strategy for 2023.
This was my first time attending PGC London, but it’s earned a position as one of my top conference experiences. I want to extend a special thank you to the entire team at Pocket Gamer Connects for facilitating such a wealth of meaningful conversations.
From the expert panels to the conference floor, and even next door at The Jugged Hare, there was one recurring theme: AIArtificial intelligence (AI) refers to the development of computerized systems that can carry out tasks and perform actions that augment or take the place of… More. More specifically, there was a lot of discussion about whether AI can help mobile game makers contend with the challenges they’re facing, especially in marketing their games.
Mobile game marketing today: uncertainty reigns
Like marketers in other industries, mobile game marketing teams face demands to do more with less. They have smaller teams, smaller marketing budgets, and tight KPIs. CPMs are falling. Their data on users and engagement is more constrained, providing less insight into user behavior and less detail for attributionThe process of identifying and assigning credit to the various marketing touchpoints that contributed to a conversion or another business outcome, such as a sale… More.
All those forces combine to generate a lot of uncertainty. Which campaigns will provide the greatest return — and which should be killed before they waste precious resources? Which channels should receive more investment — and which less? What is the ideal marketing budget right now — and what will be the ideal allocation next week or month, considering all the other influences on user behavior and the changing app ecosystem?
Marketing mix modeling can be a powerful tool for mobile app marketers.
Take a deep dive into MMM with our guide ➞
More than a hot topic: AI for mobile game marketing
PGC London offered attendees the chance to share their experiences with all those sources of uncertainty (sometimes over a pint or two or more). But they also shared potential solutions, including how data-savvy marketers can use artificial intelligence.
Marketing mix modelingA statistical approach used to quantify the impact of various elements of a company’s marketing strategy on sales and other key performance indicators (KPIs). MMM… More (MMM), for example, is a powerful machine learning-driven tool for game marketers. MMM provides comprehensive insights into your entire media stack. This technique lets you measure marketing performance across TV, CTV, print, performance, programmatic, and more. Every channel’s ROI can be calculated and compared.
Ideally, MMM solutions (including Pecan’s) provide optimizationBroadly speaking, optimization is a process used to either maximize or minimize an output value by selecting the right input values. In data science, this… More and simulation tools that let marketers experiment with different budget allocations that can help them achieve their KPIs, even within constraints.
AI is also playing a role as mobile marketers contend with SKAdNetworkA method created by Apple for measuring mobile app advertising effectiveness. SKAdNetwork is intended to offer a more private, secure way for developers and advertisers… More. When SKAN dramatically reduced the amount of data available to marketers, predictive modeling came to the rescue. Using the data on hand, AI-powered models can generate predictive signals that app developers can leverage alongside the best practices for SKAN 4.0 and MMPs’ recommendations.
And, of course, today’s effective user acquisitionUser acquisition (abbreviated as UA) is the process of obtaining new users for an app, software, service, or platform. User acquisition for apps and software… More campaigns basically require a predictive signal that reflects users’ predicted lifetime value (pLTVCustomer predicted lifetime value (pLTV) is the total amount of revenue a business can predict will be received from a specific customer over the entire… More). That’s true regardless of the specific ad channels or optimization metrics.
I was struck at PGC London by the consensus of all five panelists at the “Leveraging CPE Campaigns to Maximise ROASReturn on ad spend (ROAS) is a metric used to assess the performance of marketing efforts. It is equal to the amount of revenue generated… More, LTVLifetime value (LTV) is the total amount of revenue a business can expect to take in from a specific customer over the entire time period… More & Game Growth” session. They noted that the only way they can confidently spend on cost per engagement (CPE) campaigns is through implementing a reliable pLTV modelIn the context of machine learning, a model is a specific instance or example of an algorithm that has been created based on a particular… More. For these pros, AI is a powerful tool to reduce uncertainty — and bring better results.
Feel confident about your campaign investments by predicting pLTV and ROAS.
← Find out how predictive analytics makes it possible
Fast-tracking AI to solve marketing challenges in mobile gaming
AI has powerful potential to help address mobile game marketers’ most significant challenges today. But obstacles remain for many who want to adopt this approach. AI has traditionally been expensive and slow to implement fully. It’s usually required hiring and training entire teams of data scientists and data engineers and the enhancement of data infrastructure to handle these tasks. Waiting half a year or more to (maybe) see a single predictive model achieve deployment is way too long in the hypercompetitive, fast-changing mobile ecosystem.
Fortunately — though I may be biased here — Pecan offers a speedy, effective solution to bring AI into game publishers’ user acquisition efforts. With MMM, SKAN, and pLTV solutions, Pecan is ideally positioned to fulfill game marketers’ needs for marketing efficiency and maximum return on ad spend (ROAS).
We automate much of the predictive modeling process, including data preparationData preparation is a blanket term that can include everything from combining data from different sources, dealing with outliers and missing data, making statistical adjustments,… More, model building, and evaluation, and support easy model deployment and live monitoring. Even better, you don’t need an SDK to use Pecan, making implementation simple and seamless.
Pecan has deep expertise in the mobile gaming industry, working with major players like SciPlay, Beach Bum, Pixio, and others. Our predictive models are in use across both IAA- and IAP-driven titles.
So if you’re a mobile game marketer who’s hearing the power of AI calling to you, consider whether it’s time to move forward. I can’t wait to hear more AI success stories in London in 2024.
If you’re ready to learn more about how AI can support your mobile app marketing efforts, get in touch.