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In today’s mobile-first world, loyalty apps are more than a nice-to-have – they’re a critical tool for building stronger customer connections, driving in-store visits, and delivering personalized experiences and offers that keep people coming back.
Research shows that 72% of U.S. consumers shopping online and 63% shopping in-store prefer engaging with loyalty programs through mobile apps rather than physical cards. This preference, coupled with the rise of mobile payments, location-based promotions, and reward programs, shows that loyalty apps have become essential for meeting consumer expectations and staying competitive.
For gas stations and convenience stores, loyalty apps offer a unique opportunity to retain high-value customers in an increasingly price-sensitive market. With 42% of U.S. consumers reporting that they opt for generic products, providing seamless, personalized app experiences can help brands retain loyalty and combat price-driven churn — and beyond retention, loyalty apps allow brands to collect valuable customer data, which in turn drives more informed marketing strategies and business decisions.
Despite their potential, loyalty apps often rely heavily on advertising within walled gardens like Google and Meta, which limits their ability to reach and grow their audience. This creates a significant gap: while 66% of mobile users spend time outside these platforms, many app marketers overlook the opportunity to connect with these users through the open internet.
Programmatic advertising fills this gap by leveraging machine learning and in-app ad placements to reach audiences in the apps they already know and love. By tapping into these less saturated and more cost-effective environments, loyalty app marketers can scale user acquisition, and improve engagement and retention, for a lower cost.
In the sections below, we’ll share some actionable strategies for using programmatic channels to fuel the growth of loyalty apps and achieve measurable success, along with some practical tips to help gas station and convenience store marketers get the most out of this approach.
Moloco’s advanced machine learning models unlock the potential of programmatic advertising for loyalty apps. Built by the engineers behind YouTube’s monetization algorithms, our technology evaluates billions of ad placements in real-time to deliver unmatched precision and efficiency. Here’s how:
By applying walled garden-level machine learning to the open internet, Moloco allows loyalty app marketers to acquire high-value users while minimizing costs.
Loyalty apps have become foundational for customer engagement because of the personalized experiences they deliver, which drive repeat visits and brand loyalty. To unlock the full potential of these apps, marketers must implement strategies that go beyond traditional advertising approaches. The following recommendations will help loyalty app marketers optimize their campaigns to achieve meaningful results. From increasing app installs to driving in-store purchases, these strategies will set your loyalty app up for success in an increasingly competitive landscape.
To maximize the impact of programmatic advertising and achieve consistent growth, it’s essential to follow best practices. This includes setting clear goals, optimizing ad placements, regularly reviewing campaign performance, and making data-driven adjustments. Moloco integrates with leading MMPs to track essential metrics like installs, purchases, and reward redemptions, and offers real-time troubleshooting and optimizations to ensure campaigns stay on track and deliver optimal results.
Brand safety is essential, particularly for loyalty apps aiming to protect their brand’s reputation and maintain trust. To ensure your ads appear in environments that reflect your brand’s values, and to avoid any associations that could harm your reputation, you should partner with a brand-safe programmatic partner like Moloco. With certifications from the Interactive Advertising Bureau (IAB) and Trustworthy Accountability Group (TAG), Moloco is equipped to ensure that ads are placed only in secure, appropriate contexts. Be sure to research whether your programmatic partner takes measures to protect both brand integrity and the user experience.
Success in programmatic advertising requires an approach that addresses all stages of the customer journey. By combining user acquisition campaigns with re-engagement efforts, loyalty apps can drive both installs and meaningful actions with cost-per-action (CPA) metrics, like registrations, purchases, or repeat visits. Taking a layered approach ensures your campaigns are optimized for lifetime value rather than just installs, creating sustainable growth.
Outcome-based pricing models, like oCPM, are critical for getting the most ROI out of programmatic advertising campaigns. Instead of bidding solely for impressions, oCPM campaigns optimize bids based on predicted outcomes to achieve specific campaign goals, like app installs or in-app purchases. For example, if a loyalty app marketer’s primary goal is to drive registrations, using oCPM pricing ensures their bids prioritize the users most likely to register, rather than wasting spend on impressions that won’t convert. This approach improves cost efficiency and helps deliver higher-quality users
While cohort-based targeting can be a shortcut to precision, it can also limit a marketer’s ability to reach untapped, high-value audiences. By keeping targeting broader, loyalty app marketers allow machine learning algorithms to analyze vast data sets and find high-value user segments that may otherwise have been overlooked. For loyalty apps, this approach is incredibly effective for connecting with users who are likely to engage with your app but don’t fit traditional demographics or behavioral categories.
Loyalty apps often serve local markets, making geo-gargeting an important tool for driving app engagement and in-store visits. By using lat-long radius targeting, loyalty app marketers can reach users near physical store locations with highly relevant offers. For instance, a gas station loyalty app can target drivers within a specific radius, promoting discounts on fuel or convenience store purchases. Geo-targeting ensures that ads are seen by the users who are most likely to act, increasing immediate foot traffic and app downloads.
Effective programmatic advertising goes beyond basic targeting, using real-time insights and granular data to optimize a campaign’s creative. For example, gas station app marketers can analyze performance metrics and device data, like timestamps showing when users typically engage with the app, to fine-tune their creative strategies. This allows marketers to customize creatives to resonate with different audiences, like morning or afternoon commuters, ensuring the right message reaches users at the right time. For example, for loyalty apps, full-screen video ads are perfect for showcasing rewards programs or highlighting limited-time offers, while eye-catching display ads can build awareness. Dynamic creatives that adjust messaging based on user behavior or location can also drive better engagement.
Fast-food chains face fierce competition when it comes to engaging customers and driving app usage. Burger King needed to attract high-value users to its app while promoting its “King Order” omnichannel feature and turned to Moloco for help meeting this challenge.
Using advanced machine learning and precision targeting, Burger King:
Moloco’s solutions helped Burger King focus on high-LTV users, optimize performance, and outperform benchmarks, ensuring sustained success in a competitive market.
As loyalty apps continue transforming how brands engage with their customers, Moloco is here to help marketers seize growth opportunities through cutting-edge machine learning and programmatic advertising solutions. With our fully managed, machine learning-powered solution, Moloco Ads ensures your ads reach high-value users at the right time, helping to maximize performance without adding operational overhead. Marketers can focus on refining strategies using rich, granular campaign and user behavior data rather than spending time on manual adjustments.
For additional insights on optimizing your programmatic campaigns, check out our blog on Decoding the Open Internet: Supply Path Optimization.
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