Grow Your Playerbase with User Acquisition Segmentation

Introduction

In a post-App Tracking Transparency (ATT) world advertising has become all the more challenging. Advertising networks have become more opaque and provide fewer knobs for user acquisition teams to leverage for their advertising campaigns. This leads to lower yields from your advertising dollars. While you can spend more money to keep your player base growing, analytics and AI can also help.

There are three core areas in which analytics can help in this space:

1. Ad network spend optimization
2. Look-a-like lists
3. Ads creative-based segmentation

User Acquisition Foundations

Traditionally, user acquisition (UA) campaigns focus on influencers, SEM, app store optimization, social media, brand collaboration, word of mouth and brand awareness performance marketing. In decades past, these strategies were effective and got the job done. Today, however, games companies have exhausted these methods only to see return on ad spend (ROAS) shrink as a result of there being several dominant games in the market. 

To stand out amongst the crowd, game companies must leverage a variety of analytic, ML and AI methodologies. Player telemetry and behavioral data are assets that can help maximize each marketing dollar spent. Using this data, game companies can maximize performance marketing strategies by targeting desired audiences with messaging that appeals to their specific interests. This shows players that the games company values the time and financial commitment players make. If done correctly, the goal of obtaining new players and highlighting the original and innovative experience the game provides will be achieved.

A high-value, yet underutilized capability, of performance marketing today is the creation and usage of look-a-like audiences. Ad networks use lists of existing audience members to identify and advertise to people who share similar traits, behaviors, or interests, creating what's known in the industry as look-a-like audiences or lists. 

As networks become more opaque this can be, at times, the primary mechanism by which you can influence who sees your advertisements. These lists are often quite simple: a list of the ad network’s user ID. When creating your player databases this is a datapoint you’ll need to keep track of and maintain a lookup table aligned with your internal PlayerID. A novel approach to audience targeting is the creation of ads creative aligned with specific player segments, see targeted advertising creative below.The first step for either approach is truly knowing your player.

Know your player: Critical to success.

It’s no surprise that the most critical first step is understanding your players: their tastes, behavior and how they engage with your title. Just as an advertiser will charge you more for ads when they have a solid understanding of the audience found in their network, you can achieve higher returns when you understand your players. We discuss a few different lenses to consider as a part of these efforts but the most critical is to understand that you have to go beyond binary, heuristic and self-reported (survey) based segmentation to be truly effective.

To understand your players consider:

• How players play your game
• Timing and localization
• Player value and demographics

Once we understand players across these different perspectives we can bring it all together to improve your user acquisition outcomes.

How players play your game

Categorize your players into groups to name your player, as you would with the persona model, by leveraging game telemetry data, entitlements, social cues, etc. This starts by clustering your players into a manageable number of groups based on these datasets. Make sure that you include insight about how your players engage with your core game loop. What activities do they participate in, their event engagement, PvE/PvP engagement and contest results? Clustering projects can be time-consuming and hard to complete. Consider leveraging an LLM as we proposed here to help shorten that timeline. 

Once clusters are defined, name them. Having a name is useful when communicating with others. Within games, it’s typical to see names similar to what you would have found in Bartle’s taxonomy but do not limit yourself to them as they were made with a very specific genre in mind. With these defined you have some idea on how to engage with them. A completionist might be interested in knowing about a recent addition to NG+, a killer might want to see statistics on PvP battles, a socializer might be interested in the community aspects of your title. 

Don’t be overly myopic when you consider playstyle. For example, how your player engages with aspirational content, free items, user-generated content, custom levels, or even microtransaction preferences can be included in this dimension. Knowing that a player always completes the free battlepass, or completes content that rewards them with a specific type of consumable or item can help you with your targeting efforts. Similarly, understanding their purchase behavior will help you to target them, particularly when determining what ads creative to use with a specific campaign.

Once you have these clusters defined it is important to understand where your players play.

Geography and timing

The most straightforward of the different segmentation models, but one that will help you better target and deploy your user acquisition and remarketing funds. Seek to define your player session engagement details. When do they log in, how long do they play, how many sessions per day, week, month, etc? This will be useful in many ways, such as deciding when advertising should be active. Localization is similarly important. What language does your playerbase speak and in what geographies are they located? From here you can determine what localization efforts are most impactful and with which local influencers you might partner.

From here we seek to define player value across several dimensions.

Player value

When you saw this title you likely thought “Yeah, LTV matters,” but player value shouldn’t be defined so narrowly. Player value includes several forms of impact—monetary, social and play experience. Value need not always be considered as a positive integer. Take social, for example, a player who frequently engages with the chat system, who has people respond often, and who brings positivity to your title could be a high value of 1.0 vs a toxic player who seems to end conversations, has been reported for language, or disruptive play behaviors might be a -1.0.  Within social there are other cues such as engagement via forums, social media, influencer value and player feedback. 

Monetary value is, at its surface, more straightforward: Who has the highest observed LTV? This works for large titles that have been around for a long time and have a solid labeled dataset to be relied upon, but what if you have a newer title or frequent changes to your title that skew those numbers? In that case, you would want to rely on pLTV (predicted LTV) and spend time creating an ML model to make that prediction for all of your players. While not as precise as using the observed number, it may yield better long-term impact for your game.

Play experience, from a player value perspective, is an attempt to understand the value that the player brings to the game from a content perspective. How often does this player play, how do they add to the core game loop of other players (e.g. are they a challenging opponent for others to play with) or do they play at a time when players need an opponent? Straddling between social and play experience, you might consider whether they help new players into the game, produce content and/or guides for other players to leverage and how welcoming to the community they are.

Taking action and making this useful

Empowered with this understanding of your playerbase you’re ready to make a change. You will leverage this knowledge across your performance marketing, brand marketing and re-marketing channels. Specifically, you’re going to create better look-a-like lists, re-align ad network spend, modify ad campaigns and make your Ads Creative target different segments. Step one is still defining your target outcome. You may have a campaign focused on bringing in high spenders and another to boost player count within a specific region. How you leverage your newfound insight on your players will vary based on these goals. The following frames how you might apply different goals to your marketing approach.

With an impact statement in mind, consider the following example actions:

• Campaign messaging optimization: If a goal of UA marketing is to show potential players why they should play your game consider optimizing your campaigns with personalized ads that have player-type specific messaging. Our partner, .Monks, adds “Look-a-like based campaigns can be further optimized by aligning ads creative messaging with the main interests of each player type cohort therefore showing the potential player that the game being advertised appeals to the reasons why they play games. Player cohort segmentation campaigns increase the efficiency of each marketing dollar spent by ensuring the campaign brings in the highest quality new players.”
• Ad network mix: With an impact statement in mind consider which players fit that goal, based on the above data points, and consider which ad networks have been most successful bringing in that audience. Lean in more deeply with this ad network and provide look-a-like lists for the players that embody your target audience. While audience members are relatively consistent over time you should align some percentage of your spend to other networks with their look-a-likes and revisit your spend over time.  As our partner, .Monks, calls out “If you're trying to identify the best marketing mix, the harmonization of campaign attribution data across all ad networks and channels will reveal which ad networks and channels are producing the most conversions per marketing dollar spent. This kind of analysis guides marketers into allocating budget into the ad networks and channels that will increase the efficiency of each marketing dollar and produce the highest ROI.”
• Named player personas: Our partner, Amperity, shared “Your persona model should include all facets of a user. The in-game behavior matched to LTV allows you to assign a general weight/value of a given persona. A common strategy is to target marketing toward moving people from a lower-value category into a higher-value category. If you comprehensively understand each category, you can focus and refine your strategy around a user journey and transitioning between categories. For example, turning casual players into free battle pass players, then turning them into paid battle pass players. In addition, when building your persona groups for different types of players, consider the media channels they will be used in. Look-a-like features in paid media will often be stronger when the data used to create the targeted persona models reflects the channel they will be used in. For example, Meta ads will let advertisers target people based on demographics, hobbies, and groups they participate in. If your persona models leverage similar logic your targeting in the marketing channels will be more accurate.”
• Player segment-focused campaigns: When starting a campaign, seek to name that campaign: “Grow PvP players in Regions A, B, C.” Leveraging your player insight you add Campaign ID to understand which campaign is bringing in the players you’re targeting. Once again you provide look-a-likes to the network and adjust over time.   
• Targeted advertising creative: When you have no dials to turn or look-a-likes to provide, your ad creative becomes your segmentation. Imagine you're running a campaign where you want to attract high monetary value players, have determined they engage more with elder game content, PvP, are mostly located in Singapore (buying pet cats), China (buying pet horses) and the US (buying hats), are night owls. You may run a campaign where all ads feature someone playing in the dark, getting a pentakill achievement and in SE Asia feature cats, China players riding their horses and in the US putting special attention on a high-value hat. While you will bring in people outside of the desired segment this way, you will improve your odds to get the people that are most interesting to you.
• Building actionable player profiles: Our partner, Snowplow, highlights “the importance of building a complete view of each player by capturing granular behavioral data across every touchpoint, whether that’s gameplay sessions, web visits, forums, or mobile interactions. By modeling these cross-platform behaviors in Databricks, studios can go beyond isolated metrics to create unified player profiles that inform audience segmentation and predictive LTV models. This holistic foundation not only improves look-a-like audience quality but also makes attribution more transparent and actionable, connecting upstream ad engagement to downstream in-game behavior, purchases, and retention outcomes. With real-time data stitched together and governed in one place, marketing and UA teams can iterate faster and with greater confidence.”
• Advertising creative optimization: As our partner, .Monks, calls out “Future look-a-like based campaign optimization should be driven by previous UA data. Identification of the creative formats, placement types, and ad creative attributes (like tone of voice and topic of messaging) that led to high-value conversions is achieved through an analysis of combined historical campaigns, player behavior, and 1st-party data. By ensuring these past learnings are leveraged, future campaigns are set up for success, and an actionable feedback loop is established.”
• Owned channel analysis: Our partner, Braze, calls out: “Analyzing player engagement data from owned channels (e.g., email, SMS, push, and in-app messages) can enable cross-channel measurement to accurately attribute ad campaign effectiveness in acquiring high-engagement players. By correlating ad campaign performance with subsequent owned channel engagement, marketers can more effectively determine which acquisition strategies yield long-term engaged players, which would refine look-a-like audiences for more precise targeting of similar high-value cohorts. This could also be integrated into the predictive LTV models mentioned, improving their accuracy by incorporating owned channel engagement as an indicator of future player value.”

Leveraging a Data Intelligence Platform

User acquisition is often one of the largest cost centers and value creators for a game studio. Small improvements can have a huge impact on the overarching revenue for a title and the long-term viability of a studio. Growing your playerbase, along with creating an amazing game, personalizing your player’s experience and aligning the value your game provides to players is necessary to ensure your success.

It isn’t easy to do, unfortunately, but the Databricks Data Intelligence Platform can help make it easier.

• Near real-time matters: Changes often have to happen in near real-time so getting data in, processed and insight created in seconds or minutes is important. 
• Data governance matters: The data needed to do this right is often personally identifiable and subject to regulatory scrutiny.
• Empower UA analysts: This team understands the data, needs to understand the “why” behind a metric and can’t wait weeks for central data to produce another report for them. Empowering analysts with tooling that enables them to converse with their data and uncover actionable insights will further their success
• Flexible and operationalizable: Trends change frequently, what worked yesterday won’t necessarily work tomorrow. The model you used may be junk in a week, and the technique used may evolve. Using a platform will enable you to react quickly to change.

Databricks helps game companies, of all sizes, across the globe to solve challenging data, analytics and AI problems. Our team of experts and thought leaders are here to support your success. If you haven’t seen our ebook, check it out. If you’d like to talk more, please reach out to your account executive.  We look forward to helping you bring more play to the world.