Offering easy integration and support for Android and iOS along with a suite of basic features and a generous free tier, Firebase Cloud Messaging is an incredibly popular option for apps who are looking to establish basic customer engagement.
However, as apps grow and the need for more sophisticated customer engagement strategies arise, Firebase Cloud Messaging may start to show its limitations, leaving teams in a tough spot.
Here are just a few of the challenges teams report with Firebase Cloud Messaging as they scale:
Finite user segmentation and targeting
The basic user segmentation capabilities and targeting Firebase Cloud Messaging offers are typically sufficient for smaller apps, but as audiences and capabilities grow, apps often find themselves wanting to reach a more granular audience.
Limited testing capabilities
Testing is a cornerstone of CRM and growth, but teams often report that A/B testing in Firebase Cloud Messaging is cumbersome and time consuming which makes it less feasible for teams to run more than a small number of tests simultaneously.
No multi-channel orchestration
While Firebase Cloud Messaging supports several basic messaging channels independently, teams often find themselves wanting to engage customers in a more cohesive multichannel or omnichannel capacity than what’s possible in FCM.
Insufficient capabilities for customer journey building
Real user journeys are incredibly complex and require multiple touchpoints that adapt based on user behavior. As they’re looking to scale their customer engagement and experience, apps often feel limited by the lack of user journey orchestration that Firebase Cloud Messaging offers.
No true personalization or dynamic content
While Firebase Cloud Messaging offers very basic personalization features, this is far more limited than what standard customer engagement platforms can offer.
According to Salesforce research, 66% of consumers expect companies to understand their unique needs and expectations, and 52% expect all offers to be personalized. Smart Insights even found that 63% of consumers actually won’t buy from brands that have poor personalization. The majority of marketers rate personalization as their #1 priority for 2023 and on its own, Firebase Cloud Messaging does not offer the solution.
Limited analytics and reporting
Firebase Cloud Messaging provides basic analytics on message delivery, opens, and clickthrough rates, but doesn’t have the capability to report more advanced capabilities which could allow deeper insights into user behavior and campaign performance.
Few integrations with third-party services
If an app requires seamless integration with a wide range of third-party services for marketing automation, CRM, analytics, and more, a dedicated marketing platform may be a better fit.
Reliance on developer support
Firebase Cloud Messaging is very streamlined and efficient, but lacks a user-friendly UI that would allow more traditional CRM teams to get the most benefit from its features.
Do I have to start over on a new customer engagement platform?
What should team do when they outgrow Firebase’s limited capabilities?
Do they really need to spend the money, tear everything down, and rebuild their experience from scratch on one of the big customer engagement platforms.
What if there is a better option?
There is. It’s Aampe.
Aampe is an AI-native infrastructure that offers teams a workflow that overcomes the limitations marketing and CRM teams experience with Firebase, and it easily connects via the Firebase Cloud Messaging API.
[It’s actually so good, that many customers actually move away from larger customer experience platforms (like Braze, CleverTap, MoEngage, and others) to use a combination of Firebase and Aampe.]
As opposed to manual segmentation, which requires you to identify key groups and continuously refresh key segments, Aampe runs a clustering algorithm to automatically discover thousands or even hundreds of thousands of unique and specific segments.
Instead of being based on general criteria, such as user activity level, the segments Aampe creates are based on patterns observed between the complex interactions each of your individual users has with each one of your app events, combined with their reactions to specific elements within your messaging.
Aampe also maintains a continuously adaptive synthetic control group, which allows teams to run tens or hundreds of thousands of continuous tests without interference.
Aampe continuously refreshes all of these clusters based on your users’ individual responses and changing behaviors.
User-Level User Journeys
Aside from being an unexpectedly laborious source of incredible complexity, one-size-fits-all user journeys just don’t make sense.
Aampe automatically navigates this incredible complexity at an individual user level, finally turning that dream of CRM being a one-to-one conversation into a reality.
Active users who are receptive to messaging continue to get messaging that supports and maintains their activity level:
While, for users who are at risk of churn, Aampe’s model switches back to explore mode, automatically reducing messaging volume and trying different offerings and motivations, and then optimizing messaging patterns that lead to each individual user’s sustained activity and conversions:
Not only does Aampe’s model learn and understand which specific timing and messaging will encourage a user to take action, Aampe also navigates the complexity of omni-channel marketing by learning each user’s individual preferences and tolerances for each messaging channel (SMS, push notifications, web push, in-app messaging and even email) and then deploys a full omni-channel strategy on a per-user basis to keep them engaged.
Testing as a Function (not just an event)
Aampe’s model learns from every single interaction with a user, making every single message a multivariate test.
With each message send, Aampe monitors every user interaction as a matrix, not just looking at what they click, but also when they click and what they do after the click, and comparing this to details contained in the content within the message (e.g. do they view the content referenced in the message or something else entirely?).
After individual user data from these interactions is observed, the model’s scoring of that user is modified based on the observed behavior and the next test or optimization for that user is scheduled.
How do CRM Teams Work With Aampe?
If Aampe is building the segments and journeys and is running testing, what do I do?
As Aampe actually allows you to achieve true, hyper personalization (meaning: unique messages tailored to the specific needs, desires, and motivations of each individual user), CRM teams at companies who use Aampe focus on growing a deeper understanding of their customers at an individual level and ensuring they have the appropriate content to support it.
It means…Actually, we’re not going to tell you what it means. We’re going to let some of our customers — who came from a customer engagement platform like Firebase — tell you how they feel using Aampe:
Should you use Firebase without Aampe?
Many teams do, and they admit that their growth is limited because if it.
Alternatively, companies who use Aampe + Firebase note incredible results such as:
- 11x increase in CRM team efficiency
- 329% increase in conversions
- 1,128% increase in app visits
- 112% increase in engagement rate while sending 75% fewer SMS messages
- 32% increase in new-user retention
Could Aampe help you get all of the features you need out of Firebase without needing to by a new customer engagement platform?
We’re at the forefront of AI CRM marketing automation. Want to join us?