In the world of User Acquisition campaigns, ‘creative hits’ lead to further reach and ultimately an improvement in overall campaign performance. However, it’s very rare a campaign is a hit from the outset. In fact, most hits result from incremental creative testing that pinpoints successful elements that can iterated upon, and then relaunched by the Performance Marketer with confidence.

Getting started with this creative testing can be difficult, especially when the creatives are entirely new. When putting new campaign creatives live, Performance Marketers should have a clear idea of how much budget to allocate, and know what milestones a new campaign should be reaching in order to be considered a successful test. This can be easier said than done. Of course you need to spend some testing budget on your creatives to garner impressions, and ultimately assess the efficiency of your campaign, but how much?

At Phiture, we’ve developed a simple creative testing framework that can be applied as a starting point for every new round of creative testing, and is seen here in the form of a flowchart. The aim is to guide the optimization of creative testing and show at which points you should make interventions and adjustments to bids.

Understanding your Performance Marketing campaign flow

The flow chart below outlines how to monitor a Performance Marketing campaign’s trajectory over a period of time. A Performance Marketing campaign is a dynamic and oftentimes intuitive undertaking, but there are rules of thumb and touch points that marketers can use to stay on track.

For example, upon launch, it’s important you have no more than five ads at a time running on social media. The crucial moment when you can start to assess the performance of a campaign is when an ad set has received an average of 50 install events or ~300 in spend, or 5-10k impressions.

Points to consider with the flow chart

1. This flowchart doesn’t taking into account testing on weekends, as this is usually considered downtime for most employees. That’s why we recommend proceeding with caution if deciding to make substantial bid increases on Thursdays or Fridays.
2. If you’re running a separate campaign for testing (as opposed to Evergreen), make sure you move your successful tests to Evergreen.
3. If your bid proves successful and it’s generating a creative hit, make sure you spend a significant amount of the total ad spend (+20%) on it. You can find out more about creative hits, and a systematic approach to creative reporting here.
4. For paid social campaigns, its advisable to limit the number of creative assets being tested at the same time in a single ad set. Budget is an important factor here, as the budget per asset will be limited if the number of assets is higher. For effective creative testing, it’s well worth concentrating on a lower number of assets and making sure they reach significance.

Before you go

• Need advice on your creative testing for user acquisition campaigns? Reach out to our team here. 
• We recently ran test automations with Apple Search Ads after hypothesizing that automation would help with supporting daily check-ins, controlling performance, and reducing the time spent on optimizations tasks. The test was a resounding success and you can find out more here.
• The Performance Marketing Creative Playbook. Scoring creative hits is a crucial aspect of Performance Marketing campaigns. At Phiture we don’t leave this to chance. We rely on conceptual frameworks to channel our creativity, and systematic testing to ensure incremental results that can then be scaled up.

In the realm of subscription apps, the freemium model promises continuous user insights, a competitive price structure, and scope for app optimization at pace.

A familiar question for mobile marketers is what features should be free, what should lie behind a paywall, and how to determine pricing. This article explores how user surveys and pricing models can help freemium apps identify mobile app value drivers and willingness-to-pay of their users in order  to optimize subscription plan packages and pricing. 

Listen along to the article with an AI-generated narrator. 

Challenges of the subscription model

With freemium apps, users have the opportunity to explore and experience a product by accessing features for free without financial commitment. However, to benefit from advanced functionalities, users need to pay for a subscription.

The freemium model serves as a powerful marketing and user acquisition strategy, providing potential subscribers with a sample of what the product offers. Users are subsequently encouraged to upgrade to a premium version to unlock additional features or enhanced benefits. When unlocking key features and functionalities within the app, users must feel that the paid experience delivers substantial added value that contributes to an enriched user experience overall. The price required to access the premium experience is the measurement of that added value. On the developer side, there are opportunities to foster user retention and drive continued revenue.

Despite its advantages, the freemium model also presents challenges, such as determining which app functionalities should be made available for free and which ones should be reserved for paid access. How then should freemium apps make this distinction, and how can they find a balance between staying competitive and without giving too much away? 

We witnessed this challenge when the New York Times switched to a $15 monthly subscription in 2011. The paper continued to offer free access to 20 articles, which ultimately diminished the attractiveness of the paid plan. Finding the right balance for a subscription-based app becomes crucial, as it entails creating a free experience that attracts new users while offering an attractive premium experience. 

Once you know how to package your subscription, it’s crucial that you set a competitive price for potential users. Finding the right price point requires sensitivity toward a variety of personas, but also an understanding of their willingness to pay for access to certain features. The subscription price must be reasonable as you risk either alienating potential subscribers or sabotaging future revenues.

When it comes to understanding how to package your subscription plan, which features to incorporate, and what pricing models to implement, there are tools that can inform your decision: market research and competitor analysis, A/B testing, analytics, and User Feedback and Surveys. A combination of these tools will provide you with accurate solutions. With all of this taken into consideration, the following section will focus on mapping value drivers and capturing willingness to pay through user surveys. 

Identifying your app value drivers using a MaxDiff questionnaire

The MaxDiff survey approach aims to identify the product features or benefits that are most valued by users, and to pinpoint the value proposition that best aligns with their specific use cases. These insights are essential for structuring your various subscription tiers and offering an appealing package.

From an analysis standpoint, this scale enables you to create a comprehensive report that considers each feature individually. It aggregates the relative preference magnitude on a scale ranging from -1 to 1. The aim is to create a scale of value for different features. 

Example of MaxDiff question

In the question above, users are asked: “Which features do you value the most and the least?” Other formulations are conceivable, as long as they allow a clear differentiation in terms of values. For each of the features #1, #2, and #3, users have the choice between two opposite options. 

To analyze the results, the calculation is quite simple. You calculate the number of times a feature was selected as ‘most important,’ minus the number of times the feature was set as ‘less important,’ divided by the number of times the same feature appeared in the responses.

Average Feature Value Perception graphic.

The closer the value is to -1, the less importance users attach to the feature. The closer the value is to +1, the more important the feature appears to be to users. 

Once this data is available, it becomes possible to determine the features that should constitute a premium plan. Exclude features that don’t add sufficient value, while not necessarily including all of the most valued features. The freemium plan must remain attractive to retain users. 

Identifying user willingness to pay with Van Westendorp’s model

The Van Westendorp pricing model is a survey technique that identifies the user’s sensitivity to price in order to understand their willingness to pay to access particular features. 

Using a set of four questions, this technique plots a graph that gives a price range that seems acceptable for paid access to the product. For a freemium app, the four questions can be as follows: 

• Too Expensive: At what price would you consider the premium subscription to be too expensive and you wouldn’t buy it? 
• Expensive/High Side: At what price would you consider the premium subscription to be getting expensive but you would still consider buying it?
• Cheap/Good/Bargain Value: At what price would you consider the premium subscription to be a bargain and you would definitely buy it?
• Too Cheap: At what price would you consider the premium subscription to be too cheap and you wouldn’t trust it?

Price information can be left to the discretion of users or a range of prices can be suggested. It may be also interesting for an app to ask which price sensitivities it should be evaluated against, and whether this is a potential monthly or yearly subscription price. Different parameters can be taken into account: LTV, popularity, acquisition, etc. 

This survey technique should only be used on free users. You can understand the willingness to pay or to renew subscribers by analyzing their behavior. 

Van Westendorp Price Sensitivity Report. Source: Survey King

Once the data has been collected, it’s possible to create a line graph representing the price on the x-axis and the number of respondents as a percentage for each of the prices on the y-axis. A line is drawn to represent the responses to each of the questions from  Van Westendorp’s model. 

Key points of intersection of these lines can then be identified, and are as follows:  

• The Point of Marginal Cheapness (PMC) is the intersection of the number of people who think that the product is “too cheap” and “a bargain.” The price of your subscription shouldn’t go lower, otherwise you risk users questioning the quality of the product because the price is so cheap. 
• The Point of Marginal Expensiveness (PME) is the intersection of the “too expensive” and “not expensive” lines. It’s the price point where users believe the subscription cost has become  unaffordable or unreasonable, compared to how much value they’ll get. 
• The Indifference Price Point (IPP) is the intersection of the “too expensive” and “a bargain” lines – whereby users feel the subscription is neither cheap nor expensive. Their indifference to the price doesn’t influence their decision to purchase or not.
• The Optimum Price Point (OPP) is the intersection of the “too cheap” and “too expensive” lines. It’s the sweet spot at which the maximum conversion will happen, where users will have less resistance. This is the most favorable price for maximizing revenues.

The range of acceptable prices that users might consider paying for subscriptions lies between Marginal Cheapness and Marginal Expensiveness. It’s here that you’ll get an indication of how a subscription could be priced. 

Consider which features should be behind a paywall

The Van Westendorp pricing model is valuable for understanding the overall willingness to pay for a product. However, to create the desired final matrix for subscription optimization, you need to delve into users’ willingness to pay for individual features.

To accomplish this, you can include a targeted question in the survey, such as: “How do you feel about paying for that specific feature?” The respondents would be presented with answers that require them to make choices, ranging from being entirely willing to pay to completely unwilling to pay for access to a particular feature. Unlike Van Westendorp’s sensitivity model, this type of question can be asked to both free and premium users.

This approach is optional. It could be enough to identify value drivers and then the overall product willingness to pay. But by having more granularity in the willingness to pay, you can construct a comprehensive feature value matrix, which will be instrumental in better optimizing subscription models.

General survey considerations

There are some important prerequisites for creating effective, unbiased surveys that all surveyors must take into account. Online resources such as Qualtrics, Survey King, or Reforge are valuable sources of information but below is a list of things we have considered:  

Determine the focus of your research 

Carefully identify the critical aspects of your product and consider which specific features you’ll inquire about. To ensure the surveys are intelligible and the responses focused, avoid designing lengthy surveys. If you’ve already questioned your users, you can get an idea of their past level of engagement and build your survey accordingly. Stay within the scope of the research and do not mix the value driver and willingness to pay questions with another questionnaire. 

Consider your audience and segmentation parameters 

This step is critical for several reasons. Depending on factors such as the demographics of your users, their specific use cases, their stage in the customer lifecycle, and their level of engagement, the insights obtained can vary significantly. By adopting a segmentation approach, you can understand how different user segments perceive the value of features. It’s important to avoid mixing too many different demographics together, as this can lead to counterproductive and potentially misleading insights. The minimum segmentation should be your paid and free users, as their level of engagement and commitment already differs and the survey structure will vary. 

Include screening questions

Including screening questions in your survey is advised. They can help ensure the accuracy and consistency of respondent samples by identifying any potential errors or false answers. They also serve as a preliminary filter to verify that respondents meet specific criteria, or have a certain level of understanding or experience related to the survey’s objectives. By incorporating such screening questions, you can mitigate the risk of collecting unreliable or irrelevant data. This ensures that the insights derived from the survey are more robust and meaningful. For example, you can start the survey with questions with basic demographic questions, but also how long they use the app, how frequently, etc. When it comes to the features, it’s better to screen between users who don’t know about the feature in question or use it very rarely versus users who use it on a regular basis, daily, or weekly.  

Other considerations

Of course, avoid formulating difficult or guided questions. Keep the survey free of bias (more here). Spend time testing and reviewing the survey. The survey flow may vary from one respondent to another, for example, if a respondent doesn’t know a feature exists, you might decide to skip the value questions about that feature and go directly to the next section. 

Conclusion

How to cultivate a proposition that feels relevant and impossible for potential customers to overlook?

It’s a fine balance between gathering user insights from your apps and products and encouraging engagement through subscription models that generate revenue and promotion for your brand(s) and product(s). As every app developer knows, subscription models present frequent but navigable challenges. 

The key takeaways from this blog post tell us to: 

Quantify app value drivers with a MaxDiff Questionnaire 

As a means of evaluating price differentials, this method leverages users’ most valued elements against value propositions of their needs. Use this survey to structure your subscription tiers. 

Determine pressure points for user payments with Van Westendorp’s model

 How much are users willing to pay for freemium-meet-subscription apps? This technique plots user sensitivity to price implementations and indicates the point at which your target audiences are willing to pay for a range of included services.

Evaluate paywall features

A simpler, classic survey technique that shouldn’t be overlooked – implement a deep-dive into paywalled features. Find out what features should sit firmly behind the paywall, and which features are out in front attracting target users.

Useful Resources 

• Kumeer, Harvest Business Review, ‘Making “Freemium” Work’
• SurveyKing, ‘MaxDiff Analysis Explained: Survey Template + Examples’ 

Before you go 

• The Reach Audit Framework is for Growth Marketers wanting to understand their reach to ensure they’re connecting with more users and generating a bigger impact. This resource will help you understand your opt-in rates and benchmark them against industry standards, in order to identify possible drop-offs and opportunities to win-back users.
• Both surveys and interviews are great tools to understand what people perceive as important. It is important to make a distinction between a user’s perceptions and their actions. In this article we show how user research can inform on why people are – or aren’t – converting into installs.
• Dynamic pricing is the practice of having multiple price points based on a few critical factors. In this article we run you through the do’s and don’ts of such pricing strategies, and show how to set one up using Braze

The app analysis framework is used by Phiture’s Growth Team to foster collaboration and creativity, and can be explored and downloaded here. 

This framework provides a structure for systematic and granular analysis of an app to reach a clear and precise understanding of its UX, CRM strategy, value proposition, and core functionality. The insights gathered from an app analysis session can help your Growth or CRM teams quickly identify low hanging fruit in need of attention which can be used to optimize your growth strategy. App analyses at Phiture are an interactive team learning event, and they improve collaboration and spark creativity within our Growth Team. The inspiration for this activity comes from the well known practice of Product Teardowns, which we have adapted for our own purposes, with a clear format. 

This format of running an app analysis session is important, as it influences what insights can be generated. In this guide, we share our own best practices, taking in the value of these sessions, a framework to setup and run analysis, and a  short guide to turning insights into scalable ideas for experimentation and new tactics. In the video below, Sameer Ginotra takes us over the key elements of an app analysis. 

The inspiration for the Phiture app analysis framework

Phiture is a remote-first company organized into dynamic and agile teams that are dedicated to different client accounts. This is an effective way of channeling our diverse skill sets to deliver impact, however we missed a shared space for creativity, exploration, and the exchange of fresh ideas. 

We wanted a systematic process for bringing the team together and exploring, compiling, and shortlisting new ideas for optimizing growth strategies. Ideally, this would be a chance to think outside of the box and beyond established industry best practices – but also deepen knowledge across our team. 

The spark of inspiration came from Growth Marketing’s other half: Product Teams.

Product Teardowns are a well known industry practice, and typically involve a variety of Product Team stakeholders, from Product Managers, UX Designers, and Leadership, to even Customers. In brief, the process of a Product Teardown entails carefully disassembling a product to understand its components, design, functionality, and structure. 

This method struck us as an ideal example of what we wanted to achieve and inspired us to apply the same systematic and analytical approach to digital products. We decided upon our own, unique framework, which could be applied to apps our Growth Team would analyze for the very first time as a team-building creative exploration. As a result of this, the framework would concentrate on analyzing an app in the initial stages of user experience, that is, onboarding, first time user experience, and CRM communication. Of course, if your concern is later stages of user experience, (engagement or churn prevention, for instance), the framework can easily be adapted! 

To put our fledgling framework to the test, we scoped out an ideal app candidate to systematically dissect, and for which we could make observations that could contribute to a  common goal. In the case of our initial chosen candidate, it was a photo-editing app, with a goal to enhance user activation in the first week of downloading the app by 15%. 

Benefits of using the app analysis framework

A structured approach to gathering insights will ensure a strong basis for taking later strategic actions. For this end, we’ve defined our process for app ‘teardown’ or analysis sessions – from the preparation stage right through to follow-up and prioritization.

The benefits of using this structure is that it focuses discussion towards a clear objective, whether that’s about improving activation and engagement, or reducing churn.

The framework not only facilitates a core understanding of important app components which impact upon growth and retention, but also provides a context for innovation and creativity within the team. Eventually, by analyzing competitors’ apps, your team should feel confident and empowered to highlight industry best practices at play and be inspired to produce scalable ideas for new tactics and experimentation.

The framework can be found here, and our recommendations for applying the framework can be found below.

Setting up and running an app analysis exercise

Participation

Although the session should be voluntary, encourage participation on the basis that the exercise will facilitate collaboration and learning across your team – as well as spark creativity.

Depending upon your team’s location and availability, the session can be organized either online or offline. At Phiture, our team is located remotely across Europe, (as well as further afield too!), so remote makes most sense, however it might be that bringing your team together in a room filled with whiteboards, sticky notes and the scent of fresh coffee is the better option!

At this point, it’s advisable to elect a moderator who will guide and manage the session.

Analysis kickoff

The moderator should kick off the analysis by introducing the agenda with the participants Ideally, we recommend breaking down the session in two parts (see below), and which can also be found in the framework. At this point, the team should be aligned on an overarching common goal for the session. For example, it could be to highlight opportunities to improve activation by 10-15% by the end of the month.

The moderator should also introduce the app to be broken down, and of course the team will all need to download it. If you’re analyzing a competitor’s app, highlight the key platform, the USP or key functionalities, and other important information such as the monetization model. Introducing these details will allow participants to build up recommendations more precisely, in light of the agreed common goal.

Key details of the app ready to be further explored. 

Group Work: Exploration

Once aligned, you can split the team into smaller groups of three to four people. If working remotely, set up break out rooms for everyone to recreate the environment of working groups. 

These small groups should establish a collaborative environment where the barriers of conventional thinking can be broken. Different roles can be assigned to different team members, whether that’s monetization, onboarding, Apple or Android. 

How to structure your observations of the app under study

The first part of the group work should be reserved to explore the app, go through onboarding, activation, paywalls, and anything else you can look at within the time. Add screenshots of the user journey for visualization and use stickies that explain the good and bad of each product. 

In case you find yourself going off-piste, we provided within the framework document some guiding questions that can steer the group discussion and keep them on target. 

Collected thoughts and observations following a successful exploration.

Group Work: Analysis

The second part of this session should focus on discussing the most important observations. Each group should narrow down their list to an agreed top three-five observations, which should in turn be introduced to the broader team, inviting questions and further discussion. 

The broader team can also hypothesize suggestions, recommendations, and solutions at this point – a great opportunity to encourage ownership and enhance the wider team’s CRM expertise and knowhow. 

The top observations from each team, with the suggestions coming from the wider team.

Formulating Your Next Steps 

The observations gathered from the session should be handed over to Growth Managers and CRM Leads, to inform their product strategy. 

In general, the takeaways of an app analysis session should give Growth and CRM managers a heads up in terms of new trends and potential areas and components they should be looking into. From here, it’s a short jump to hypothesizing the potential impact of what each observation could achieve, with a testing plan based on the resources at hand.

The Brain Framework 

For this end, we recommend using the BRAIN framework that allows you to drill down on specific user behavior that you want to optimize for your app. Using this framework effectively will give you a launchpad from which you can learn and experiment, with clearly defined goals towards accountable growth. 

For instance, if the short-term goal is to increase communication reach in the app, it would make sense to look at newsletter subscription rates and experiment accordingly. 

We’d further advise tearing down other benchmark/direct competitors apps to be completely equipped and running the BRAIN sessions with even more knowledge/ideas. Once you have the ideas defined and set in place, use RFFCK framework to set your CRM direction for business impact. The end goal should have 5 action items to be accomplished in a defined time period with defined tasks outlined, responsibilities assigned, deadlines defined.  

Conclusion

The app analysis process is a meticulous and well-structured method of dissecting an app to garner valuable insights into its user experience, CRM strategy, core functionality, and overall value proposition. 

Rooted in the traditional engineering and product design approach of product teardowns, this method is designed to foster a culture of creativity, collaborative learning, and strategic thinking within teams. By creating a shared space for innovation, teams can pinpoint opportunities for growth, refine CRM strategies, and understand the underlying nuances that drive user behavior. 

Furthermore, with tools like the BRAIN and RFFCK frameworks, teams are equipped to translate their insights into actionable growth strategies, ensuring that every observation culminates in tangible results. In essence, regular app analysis sessions not only empower teams with the knowledge they need to succeed but also cultivate a proactive approach to product enhancement and innovation.

Before you go: 

• Curious to learn more about how we craft great user journeys for our clients at Phiture? Find out how we optimized SoundCloud’s onboarding with help of motivational theory. 
• The BRAIN Framework is designed to help CRM teams focus their problem solving and inspire particular user behaviors.
• The Key Reach Relevancy Framework Complexity (KRRFC) Framework takes Phiture’s Reach Relevancy Framework provides independence to your CRM team by deciding which campaigns to send next

Phiture’s award-winning Design Team delivers creative motion design for category-leading apps operating in numerous markets and locales. This makes effective localization crucial. In this article Michał Gryga shows how we at Phiture rely upon robust internal processes to facilitate the delivery of localized motion design, and suggest best practice to inspire your own workflows.

At first glance,  localization for design seems  a straightforward task. The creatives are briefed for several locales, then prepared for the client. It might be required that some aspects of the creative design are tailored to fit specific regions, and any copy and assets translated into different languages.  

However, as the asset count increases, so does the potential for confusion and mistakes, especially  so when the scope of a creative brief and localization requirements are not initially clear or change over time. For this reason, it’s worth investing time in planning your approach to localizing creatives and how you organize your files. The benefit? Designers won’t find themselves mired in files, assets, and translated texts later. Instead robust processes will mean Designers and Design Teams can concentrate on delivering great assets. In this article, we introduce our own best practices for managing this process, and discuss the relative merits of different approaches to file storage.  

Initial localization considerations for motion designers

Central to the localization process is knowing how many variants there are to prepare. Note we don’t say languages, as each further variant requires its own place within work files – even with just a single difference between two videos in the same language.

If there is just one or two locales, this is easy enough to handle without thinking too far ahead. If there’s up to ten locales, it’s worth anticipating the next steps by preparing the source files specifically for the process of localization prior to localizing any asset. If there’s more than ten, there may be potential to save some time by automating the process.

Differences between locales

With the number of locales locked down, the next topic for the motion designer to consider is the differences between locales. It’s also worth adjusting creatives to better fit new markets, if any, too. These differences might amount to simple cases where only a few lines of copy are translated, or it could be the complete localization of UI elements, images, stock footage, and even preparing a new ‘hyper-localized’ variant that differs from the original.

Bear in mind the more changes we expect for each locale, the better our plans for organizing our files should be at the outset.

Number of deliverables

Just like the number of locales, the number of deliverables and formats will also influence the workload. If you need to prepare many ad groups and formats, there are a few localization shortcuts you can try. One shortcut is to reuse assets between formats and ad groups, so you only need to replace them once.

However it’s certainly worth doing more planning and source files cleanup for the video you need to create before doing any localization work.

Project cooperation

A separate topic worth discussing is how the project and cooperation will take shape across timelines, and especially if you anticipate making global changes to creatives after localization. Of course, the best-case scenario is that the client approves the localization process beforehand. This is because defined project stages are crucial for clean workflows.

However, there might be reasons why you need to make changes to the video after localization, for instance if seasonal iterations of the video are required. Making changes later will be much easier if you organize the source files within a single Ae project as you can share a single pre-composition between all language versions and means you will only need to change once instead of individually for each locale.

The importance of hardware

It’s easy to forget about the limitations of hardware. When planning file structure, consider how big your source files might get, and specifically, what is the limit of what Adobe After Effects can handle on your hardware? Working with big .aep files – especially ones with a lot of expressions, linked assets, and so on – can slow down your hardware. From this standpoint, the fewer project files you create, the better, however this is something you need to reconcile with your workflow.

Timelines

Timelines are also important for the selection of solutions of motion designers. The work can be sped up by dividing the localization between many people. If you take this route (or even if there’s a chance you do so later in the process), it will limit how the source files can be handled, simply because it’s not possible to have more than one person working on a single .aep file at the same time.

Solutions

Based on these initial considerations, we can now ensure the implementation of tailored organization solutions for our motion design localization tasks. 

For this end, there are a few ways to organize files;

• separate packages (project file and linked assets) for each locale, 
• separate project files for each locale but with a shared footage folder, 
• or keeping all locales in a single project file.

There’s no perfect solution; each brings their own benefits and drawbacks, depending on your client work. The flow chart below outlines good rules of thumb to follow when plotting your organization, with further explanations of these practices’ relative merits below. 

A flow chart to help motion designers decide which storage solution works in practice, depending on the project. 

Solution 1: Separate packages

The default approach to file organization is to keep the first locale separate and to create a copy of the content (.aep file and all the linked assets) for each additional locale. In effect, this treats each locale as a separate, standalone project. There are many benefits to this approach.

Separate packages in practice, with standalone projects for each locale. 

Separate packages – benefits

• Simplicity of process: For every new locale required, simply copy an entire folder and you’re ready to go. Any asset can be replaced without problems surfacing, such as inadvertently replacing the asset for another locale.
• Content clarity: When every deliverable and locale is stored separately, they are easily found. There’s no need to open .aep files to look for a particular composition to render.
• Easy file management: There are no shared footage elements between folders, eliminating the risk of accidentally overwriting something as each deliverable has its own set of files. Ease of sharing: Whenever there’s a need to share the source files, there is a folder ready to send.
• Fast replacement: Theoretically, assets can be replaced from the file manager level directly. So once After Effects is opened, all the assets are already replaced. It’s worth noting, though, that this fast replacement can be a double-edged sword. It is sometimes safer to replace the assets one by one to see how they behave in After Effects and catch any errors.
• Software performance: By working on a single locale at once, the project file won’t grow too much. As a result, problems common for big source files are unlikely to happen.

Separate packages – drawbacks

• Disk space: Each folder created by copying the original will contain a lot of video footage.
• Rendering process: As there are separate .aep files, each would need to be opened to start the render. It’s a tedious process, even if an external renderer (like Media Encoder) is used, and  even longer again when the file is  rendered from After Effects directly. Unfortunately, this can’t be set up in advance and left  overnight  as each .aep file needs to be opened separately, and the render started from there.
• No easy way to apply global changes: If there’s a request to change something globally, it will need to be done  many times over in every separate .aep file. The same principle applies to any global footage change – the files will need to be replaced  in each instance.

When separate packages are the best solution

• Low number  of deliverables: The drawbacks won’t be a concern if the  localization process only creates two or three separate deliverables (ie. locales, formats).
• Big differences between locales: If the videos for each locale are very different from others, there’s no need to force any process improvements as there will be few associated benefits.
• Multiple designers: As files aren’t shared across different deliverables, many people can work on localization at the same time.
• Clear project timeline: If it’s certain that there won’t be any global changes after approval of the first locale, then this is a safe solution.

Solution 2: Separate project files with a common footage folder

To cut down on some of the obstacles from the previous solution, create a single Footage folder where all the project files will link. That means, for each new instance,the .aep file is copied and the Footage folder will contain files for all the locales. This can be approached in two ways. . 

1. All files are dropped there, which works if there aren’t too many locale-specific assets variants,  or
2. have a single folder that will hold all the localized assets.

A common footage folder in practice, with linking project files. 

Separate project files with a common footage folder – benefits

• Saving disk space: All the major files shared throughout the locales exist only once, as a single file. This also means that if an asset needs to be replaced globally, it only needs to be done once.
• Neat file organization: This approach forces clean file management. It’s obvious  which files require localization by checking the content of the Footage folder, even if the designer is seeing the files for the first time.
• Software performance: Since the designer is working on a single locale at once, the project file won’t grow too much with none of the problems common for big source files.
• Simple loc process: Store all assets requiring localization separately and sort them by locale. After that, it’s easy to create another instance, while if another designer is taking over the task, this solution enables them to check which assets need localization.

Separate project files with a common footage folder – drawbacks

• File management: To prevent changing an asset across all locales or linking a file meant for a different locale, you can control what’s happening in the Footage folder. Here, having a separate folder with shared and localized assets helps. At the same time, pay attention to what’s linked in After Effects, and manage the files properly there, too.
• Rendering process: In this case, separate project files are also possible. The rendering process looks similar to what’s happening when source files are not organized together.
• No easy way to apply global changes: If there’s a need to change something globally, it will  need to be done multiple times in every separate .aep file.

When separate project files with common footage folder is the best solution

• Most versatile solution: If it’s unclear how many locales there will be to produce, it’s safer to split the project files by language from the beginning. This is because it’s easy to create a new copy of an .aep file.
• Multiple designers: Several designers can work on the localization at the same time, as long as they’re aware of how the file management functions. Designers can either work on a shared folder or on their private instance, which is then synced into a single place.
• A lot of deliverables: When there is a big number of locales, After Effects might not be able to handle a single file containing all of them inside.

Solution 3: Single project file

Once all the assets are kept together as a single (footage) folder which the .aep files are linking to, it’s time to declutter the Footage folder and have the common assets and localized ones stored in separate subfolders. It’s also tempting to replicate this approach inside After Effects too, and having all localized versions in a single .aep file to mirror the structure in the (Footage) folder.

Assets and compositions grouped by locale within a single project file.

Single project file – benefits

• All in one place: Having a single .aep file for all deliverables makes the whole process simpler. This is because there’s no need to make copies of project files or open several  files.
• Rendering simplicity: Whether rendering using Media Encoder or After Effects, including all output compositions in a single file is far simpler.
• Cleanest organization: This approach forces a clean structure, both in the (Footage) folder and also in the .aep file directly.
• Easier to make global changes later: If you need to change something globally, having everything in a single .aep file is helpful so it’s not necessary to change separate instances.

Single project file – drawbacks

• Software performance: The biggest problem when storing a lot of deliverables in a single file is that the .aep file size will grow fast. This influences the performance of After Effects, to the point of not even being able to open the project file on a slower machine. 
• Doesn’t enable cooperation: The work cannot be divided between multiple designers  because they would have to work on a single project file at the same time.

When this solution is the best

• Average amount of deliverables: If you’re not expecting a lot of locales (both now and in the future), it’s safe to go with a single file. The worsto- case scenario is that these  locales can be divided by groups or tiers in order to divide a bigger file into two separate ones.
• There is only one designer working on the project: If it’s certain there won’t be a situation where two designers  have to work on the same project.

Summary

In conclusion, there’s no single solution that’s perfect for every application. That’s also the reason why it’s sometimes hard to form a rigid motion design process to which all designers involved will have to stick to for every project. It’s important at the beginning of every project to take a step back and think about what you need to achieve and what would be the best approach to do so. Asking yourself questions about the scope and the environment you’re working with can help avoid stressful situations later.

Before you go:

• The Persuasion Emotion Trust (PET) Model is a framework used by Phiture to channel creativity into great design concepts for mobile. In this downloadable resource, Phiture’s Design Team shows how they use the PET Model to design for apps, whether that’s for the product itself, or for Retention, App Store Optimization, or Performance Marketing purposes.
• Curious to learn more about how we localize for our clients at Phiture? Find out how we helped Sololearn identify new markets and reduce cost per trial by 40%.
  

This is a bonus article for our blog series about the Subscription Stack, guest written by Jenny Kay Pollock, Lead Monetization Program Manager at Together Labs.

Here we introduce the key components of subscriber loyalty starting with its benefits and then digging into the tactics that create loyal users. Boosting loyalty among users of subscription apps will help drive engagement and reduce churn. You can read the full Subscription Stack here. 

Introduction: 

Churn prevention is a crucial component of the Subscription Stack, and the key to reducing subscriber churn is creating loyal users.

There are various ways to inspire loyalty among your user base, however only once you have a clear understanding of your subscriber’s journey should you layer on common tactics such as gamification, personalization, fostering community, and loyalty programs.

This article outlines the importance of user loyalty and its benefits for subscription optimization, from positive testimonials to referral programs and improved word of mouth, before drilling down into the tactics that will help you increase loyalty.

The wider benefits of boosting loyalty

Of course, the chief benefit of boosting loyalty is the long term revenue you’ll receive. However, making loyalty a priority for your business will have positive impacts across the Subscription Stack, aiding other initiatives such as user acquisition, conversion rate optimization, and user research.

User testimonials

Loyal subscribers can help gain new customers with social proof in the form of testimonials that can be used on your webpage, app advertisements, or promotional ads. Steve P. Young of App Masters, recommends including testimonials as part of longer paywalls, finding from paywall experiments that longer paywalls convert better.

Word of mouth and referral programs

Referral programs are mentioned in the User Acquisition section of the Subscription Stack, and are a simple way to capitalize on your happy users. Loyal users often refer their friends and family through word of mouth, even if you don’t give them an incentive to do so. However, incentive programs will help supercharge your referrals. This is typically done with an incentive given to users for referring their network to your app, such as a discount or coupon to both the referrer and the referee.

Positive reviews
We all know positive app reviews are gold, and it goes without saying that loyal users leave better app reviews. According to research by Apptentive, 50% of customers won’t download an app with a 3 star review. If the app has a 2 star review 85% of users won’t download it.

Examples of positive reviews from Duolingo and Calm. 

App ratings and reviews are highlighted in the app store and can be the difference between a download or a pass from a potential user.
Word of mouth marketing (mentioned above) leads to greater brand awareness, but it can be hard to measure if your efforts are paying off. A common way to measure user sentiment and potential word of mouth is the Net Promoter Score (NPS).

NPS is calculated by running a user survey with one question, “How likely would you be to recommend (i.e. promote) this app to other people on a 1 to 10 scale?”

Source: Netigate

Improvement in word of mouth can be measured by an increase in your NPS over time. NPS is calculated by the proportion of users who answered as a promoter minus the proportion of detractors. For more information on how to successfully leverage NPS, see here.

Understand the Subscriber Journey as a basis to boost loyalty

Having a detailed understanding of the subscriber journey will provide strategic opportunities to add value as you implement loyalty-driving tactics.

A good start pointing is looking at the data:

Where do your users spend most of their time?
Are there any underutilized features?
What is a user’s journey like in your app’s pre-subscription? Post subscription?

A user research best practice is to validate the learnings from your data with quantitative and qualitative user research. Ask questions like:

• What are the reasons users log out of your app?
• What are the reasons users sign in to your app?
• What do your users value most?
• What motivates users to spend more time in your app?

For more on user research, learn how to translate survey results into actionable insights here.

Tactics to increase User Loyalty

There are four main levers to increase user loyalty: gamification, personalization, fostering community, and loyalty programs.

Gamification: Introducing game-like behavior and features into non-game contexts creates the same loyalty that games have. The goal behind this is to give your users reasons to come back through game-like reward systems.

An example of this is the meditation app, Headspace, which notifies you of how many days in a row you have meditated and provides statistics like total amount of time meditated. These features provide game-like incentives that make people more likely to come back day after day to meditate.

Personalization: This includes providing personalized content to users and/or allowing them to personalize their experience. For example, the New York Times Cooking app allows you to create lists of your favorite recipes, while also providing personalized suggestions based on your other recipes.

Personalization is a powerful tool that helps users enjoy a specific experience in-app or express themselves to others. Spotify’s year end recap playlists are a textbook example of the success of personalization.

Foster Community: Creating a space for users to connect with each other. This can be in your app or separately with community building tools like Reddit and Discord. Even the free version of Slack can be used to create these communities. These communities are great at providing value to your users outside of your app while also reminding them why they want to return to your app. These communities are especially great for games, where community members can share achievements and strategies. Getting the support of the community helps further encourage success in the game while strategizing helps players have success.

Loyalty Program: A great way to boost loyalty is to design a loyalty program, reducing churn by giving customers a reason to engage and stay, and increasing customer engagement by giving users something to strive for. When customers know that they can earn rewards for using your app, they are more likely to use it more often.

An example of this is Fortnite’s season rewards. By offering players the ability to unlock greater rewards by subscribing to the current season, it incentivises players to come back throughout the season to move up that season’s reward ladder.

Image from Fortnite Season 7 Battle Pass Rewards, IGN

If you are looking for a way to improve your app revenue then a loyalty program is a great option. Loyalty programs can help you reduce churn through increasing customer engagement and improving customer satisfaction.

Conclusion

Loyalty is a key piece of the Subscription Stack, fostering loyalty will allow you to retain and grow your user base. Loyalty driving tactics like gamification, personalization, fostering community or setting up loyalty programs can help you mint more loyal users.

More loyal users will ramp up benefits like reduced subscriber churn, improved testimonials and word of mouth, and exponential growth from referral programs. Once you have loyal users, do everything you can to keep them.

BEFORE YOU GO:

• For the full overview of the Subscription Stack by Alice Muir, you can download the pdf here.
• NPS is a metric, used by many organizations, that calculates overall user satisfaction by asking users to rate the product between a score of zero to ten. Learn how to implement an NPS here.
• The first in Alice Muir’s Subscription Stack blog series handles User Acquisition and is a must read as it preempts Conversion Rate Optimization.
  

When automated rules are used with the search results placement of Apple Search Ads (ASA), marketers can expect a number of benefits, not least improved performance. 

This has been our own experience at Phiture, after we decided to test automations with Apple Search Ads after hypothesizing that automation would help with supporting daily check-ins, controlling performance, and reducing the time spent on optimizations tasks. This experimentation was enabled by the tools SearchAds.com and SplitMetrics.

After implementing rules, we have observed several benefits, some related to the performance, others to work distribution and practices. Here we outline the main gains we experienced as well as some best practices on how to set automated rules up and optimize them.

Why use automated rules in the first place?

Using rules for a tailored approach 

Rules are especially useful in creating a tailored approach when targeting multiple markets where users typically behave differently. A best practice here at Phiture is to create distinct and separate campaigns for each targeted market within the same app. This is because a keyword might perform differently within different countries and because costs vary based on location. Having separate campaigns allows us to gather more localized learnings and also helps with potentially having different targets and KPIs at a market level, instead of an app level. For example, the cost to acquire users is likely going to be higher in the US than in Spain due to a variety of factors, such as the level of competition, search volumes, the tier they fall into, and the macro economics in the market. Based on historical data and industry benchmarks, setting up specific KPIs for the different markets is the advised approach.

From an optimization point of view, this would influence the steps that consultants need to take. Instead of looking at the global level, we need to check and take action market-by-market, which can be time consuming and repetitive. As an alternative, we could check at a global level by looking at average global metrics, but this still wouldn’t be enough to decide on how to optimize the bids, as some metrics could be within target for some markets but not for others. 

Applying automated rules in order to optimize accounts with multiple markets and different KPIs allows us to be on top of each metric without giving up on accuracy and customization.

Time spent on optimization

It sounds obvious, but using automated rules will really help you save a lot of time on manual optimization. Generally speaking, manual optimization can get very complicated, very quickly, especially with a higher volume of keywords, differences in keyword behavior, a higher number of targeted markets, and resulting KPIs.

In addition, the tools that can be used to optimize ASA campaigns have some limitations and make the process even lengthier.

For example, some tools don’t allow bulk actions and if they do, there is a maximum of keywords, ad groups, and campaigns that can be selected at once. Most tools allow you to select 50 to 5000 keywords at once, but when accounts have thousands of keywords, working with those numbers can quickly become a burden.

This doesn’t mean to say that once rules are created and launched, consultants won’t need to take any action. Instead of taking actions on the actual campaigns, ad groups or keywords, they are taken at the rule level. This has several advantages. It helps create an understanding of what works best between manual optimization and rules. It also supports the creation of a process through which rules can be updated and tested against previous ones. 

Rules as ‘controllers’

Rules play a relevant role as controllers. In fact, they oversee the performance and take actions no matter the time, the day, or the event. Thanks to this, when rules are active, a change in performance never goes unnoticed. Have you ever experienced  a keyword CPA increasing above target over the weekend, but you only found out on Monday? Well, to avoid such occurrences, a rule that checks CPAs at keyword level is very useful. Has it ever happened to you that a campaign reached its daily budget but you didn’t notice and performance was affected? A rule to notify you via email or to directly take action could remove this hiccup. 

In general, rules become key elements that help with the monitoring of an account and its activity based on the frequency they run. Of course, the outcome is heavily dependent on how conditions are set and which actions are chosen. This is why a consultant that oversees the performance and carefully plans a rule strategy is key for the success of the implementation of automations. In the next section, we will deep dive into some rules examples and best practices.

Examples of automated rules and best practices 

When developing a keyword automation strategy, you should define your goals and consider which optimizations you would usually perform manually. By taking into account some of the best practices to optimize your keywords bids, you’ll easily be able to create rules set-up for success. 

Below are some examples of the three most common and useful types of rules we use on keyword level optimizations and some general best practices. 

Rules to increase/decrease keywords bids based on their performance

Example of a mid converter rule: 

Action: Increase bid by 10%

Conditions: If: CPA is 5.01$ <> $10 AND Goals > 0 AND Impression share < 90 in previous 3 days.

Frequency of the rule: Every day

Action taken by the rule: Once every 3 days 

This rule involves increasing or decreasing the bids based on performance targets. 

For example, if your target CPA is $10 and a keyword has a CPA above this, you would decrease the bid, and if it has a CPA below this, you would increase the bid. 

Some things to take into account: 

Different levels of optimization: when deciding on the percentage of the bid change, consider how far or close you are to your target goal. For instance if your target CPA is $10 and the current CPA is $20, a decrease of 15% may be necessary, whereas a decrease of 5% may be sufficient if the current CPA is $11. 

Set an acceptable range within your target CPA: while your target may be $10, it’s important to allow for small fluctuations over a short period of time, as over a longer time span the keyword may still fall within the targeted CPA, or may bring significant volume without impacting the overall CPA of the campaign. For that, we recommend setting a slightly higher threshold, such as $10.5 or even $11.

Limit increases by using impression share: If your keyword already has an impression share of 95%, it may not be necessary to increase the bid, as the current bid is already bringing the maximum available volume. 

Adding other conditions: Sometimes you have a secondary goal, for instance, keeping the CPI below $5. In that case, you can also create a condition to not increase the bid if the CPI is higher than a certain threshold. 

Rules to increase impressions 

An example of increasing an impressions rule runs as follows: 

Action: Increase bid by 10%

Conditions: If spend < $5 AND Impressions < 15 in previous 7 days

Frequency: Every 2 days

Action taken: Once every 24 hours 

When adding keywords, it can be difficult to determine the optimal bid that will generate impressions. To address this, one useful strategy is to create a rule to increase impressions for keywords that aren’t generating any yet. 

There are typically two reasons for a lack of impressions: 

• Irrelevant or low search volume keywords
• Low bid  

By increasing bids, we can discard the hypothesis of a low bid. 

This rule is best applied to newly added keywords or a list of keywords that haven’t performed poorly but haven’t generated volume over a longer time span. You can do this by, for instance, labeling these keywords. This way you’ll avoid increasing bids for historically poor performers that have already been targeted by decreasing rules. 

However, it’s important to monitor the keywords affected by decreasing rules. Analyze the keywords’ performance over a longer time span and look for patterns. If a loop emerges where the bid is increased by a rule to increase impressions, generates impressions but now has a CPA above the target, is decreased by the rules, and is then back to not having impressions, the keyword may need to be removed from the list to avoid wasting money on a low-performing keyword, that will only bring cost metrics up. 

We’re not suggesting pausing the keyword entirely, as there is a possibility it may pick up again with the current bid in a couple of weeks when competition is lower, and generate volume within the target goal. 

Delivering a highly personalized user experience is one way to stand out from the crowd for your users.  Phiture’s partner Braze – the leading customer engagement platform – relies on Liquid code to help their clients deliver this personalized experience. 

Originally developed by Shopify, and now an open source project on Github, Liquid is a versatile templating language written in Ruby that enables the dynamic rendering of content in different channels, such as emails, push notifications, and in-app messages. Due to its simplicity, flexibility, and ease of integration, Liquid has become a popular framework for developers to manipulate, format, and display data, allowing for the creation of tailored and customizable content.

This article explores the world of Liquid, its purpose, and use cases. We explain why decision-makers should consider incorporating Liquid into their CRM Strategies, and some common examples of its application with Braze.

The importance of personalization

We cannot underline enough how important personalization is. At a top level, 76% of consumers are more likely to consider purchasing from brands that personalize. This is also reflected in Braze’s experience of using personalization across different channels, where they recorded:

• 40% uplift in in-app message click rates
• 37% uplift in email click rates
• 48% uplift in mobile push open rates

So why doesn’t everyone embrace personalization given the uplifts? Well, if a CRM Team needs to implement individual variants for each campaign, it quickly becomes very time consuming, and CRM teams typically have limited resources. Indeed, it’s with this problem that Liquid is able to play a role. 

Beyond basic personalization

While personalization is key to engaging users, just adding the first name and sending in the preferred language of the user is not enough. Liquid can help your brand resonate with each individual customer by incorporating rules based on the user’s behavior in the app/website, and dynamically generating content based on custom data and preferences. For example, using connected content or Braze catalogs to provide product recommendations based on previous purchases. This helps maintain consistency across all customer interactions and strengthens brand affinity.

The importance of good taxonomy

Scoping your app’s or website taxonomy when creating your Lifecycle Communications Roadmap is of utmost importance, as it lays the foundation for effective personalization using Liquid Code in Braze. 

A well-defined taxonomy ensures clarity and consistency, allowing CRM Teams to know which custom attributes, event properties, and API-trigger properties are available to use for personalization purposes, as well as their format and type (string, array). This will enable them to know which tags and operators from Liquid Code are most useful and ensures seamless integration with data sources that will later feed all personalized campaigns. Ultimately, a good taxonomy serves as a guiding framework for CRM Managers and empowers them to create impactful campaigns.

Examples of How to Program Liquid for an App

Basic personalization: Name, Language

Liquid provides a vast number of objects, tags, filters, and operators that help you insert information into the message, even giving the right format.  This will give consistency and a professional look across all channels. One of the most used tags is the “if” statement”, which allows you to establish rules and conditions to display (or not display) content. For example:

First, we determine the languages we want to use. We want to display the copy in Spanish or a default language (English):

{% if {{${language}}} == "es" %}
      Gracias por tu compra 
{% else %}
      Thanks for your order.
{% endif %}

Then, we check if the user has a first name on their user profile. If there’s no first name, we make sure we don’t have any blank spaces:

{% if {{${language}}} == "es" %}
¡{% if ${first_name} != blank %}{{${first_name}}}, g{% else %}G{% endif %}racias por tu compra! 
{% else %}
{% if ${first_name} != blank %}{{${first_name}}}, t{% else %}T{% endif %}hanks for your order! 
{% endif %}

Finally, we want to make sure that we have the right format, so the name is in the correct case. 

{% if {{${language}}} == "es" %}
¡{% if ${first_name} != blank %}{{${first_name} | capitalize}}, g{% else %}G{% endif %}racias por tu compra! 
{% else %}
{% if ${first_name} != blank %}{{${first_name} | capitalize}}, t{% else %}T{% endif %}hanks for your order! 
{% endif %}

The result:

If there is a first name, for example, “Alexa” , and the language is Spanish, it’ll generate “¡Alexa, gracias por tu compra!”

If there’s no first name and the language is not Spanish, for example Dutch, it will generate, “Thanks for your order!”

Other things that can be edited in a similar fashion to this example include: 

• append
• capitalize
• downcase
• first
• last
• upcase
• split
• date format

Dynamic content using event properties

By leveraging event properties, as well as custom attributes, you can dynamically insert information based on a user’s action in the app. If you have a triggered campaign, you can insert Liquid tags with all the event properties included in the triggering event. This will enable real-time messages with specific information about user behavior. For example, if you wanted to trigger an abandoned cart nudge to users who added an item but didn’t complete the purchase.

{% if {{${language}}} == "es" %}
     ¿{% if ${first_name} != blank %}{{${first_name} | capitalize}}, a{% else %}A{% endif %}ún estás interesado en comprar {{event_property.${product_name} | capitalize}}?
{% else %}
     {% if ${first_name} != blank %}{{${first_name} | capitalize}}, a{% else %}A{% endif %}re you still interested in buying {{event_property.${product_name} | capitalize}}. 
{% endif %}

In this script we are: 

• Asking the user’s preferred language. If the user doesn’t speak Spanish, we show the default (English).
• We’re formatting the copy to display the first name of the user (if any) with the proper case.
• We’re adding the name of the product the user added to their cart but didn’t buy.

The result:
Alexa, are you still interested in buying Cool T-Shirt?

Highly personalized messages 

Liquid code’s power is truly evident when you utilize Control Flows, Iterations, Templates, and Variables tags.

• Control Flows, create conditions that decide whether blocks of Liquid code get executed. Here’s where we use “if” statements, the most commonly used and useful tag we will use.
• Iterations, repeatedly run blocks of code. One of the most common tags is “for,” which is commonly used to find objects inside an array. Check out the example below.
• Templates tell Liquid where to disable processing for comments or non-Liquid markup, and how to establish relations among template files. “comment” is the most used one: {% comment %} Your comment here {% endcomment %}
  Variables create new variables. For example, “assign” and “capture.”

Combining these with Braze’s features, such as connected content, promotional codes, and catalogs, you can build automated flows where users receive tailored recommendations, timely messages, and highly personalized content in real time with less effort on the part of the CRM Team. That’s because once set up, it’s continuously maintaining and monitoring performance.

For example, based on the user’s order, you can recommend more products, encouraging re-purchases. This could be a dynamic product carousel displayed as in-app messages.

{% connected_content https://yourAPIurl.com :save response %}
{% assign favoriteProducts = {{custom_attribute.${favorite_products}}} %}
{% assign productids = {{response.data.campaigns[0].content.productids}}%}
{% assign productbought ={{event_property.${product_name}}} %}

{% for favorite_product in {{favoriteProduct}} %}
  {% assign id = {{ids[favorite_product["id"]]}} %}
  {% if {{id}} != nil %}
   {% break %}
  {% endif %}
{% endfor %}
{% if id == nil %}
{% abort_message('No match found') %}
{% else %}
People that bought {{productbought}} also liked {{id.ProductName}}
{% endif %}

Here we’re using the %for% loop to find a match between the product ids in the catalog or connected content call, and the “ids” inside the array favoriteProducts. If it matches, you send the message.

The result: 

People that bought Cool T-Shirt also liked Awesome Sweatshirt. 

Another interesting use case is using Liquid Code for Dynamic pricing, the practice of having multiple price points based on a few critical factors, such as user behavior or characteristics. You can read more about this strategy and how to implement it in Braze here. 

Transactional messages using API-triggered campaigns

Transactional API-Triggered campaigns are set up with Braze where the CRM manager takes care of all the settings except the actual sending, as the IT Team or Developer usually performs this task. 

API-triggered campaigns are ideal for more advanced transactional use cases. These allow marketers to manage campaign copy, multivariate testing, and re-eligibility rules within the Braze dashboard while triggering the delivery of that content from their servers and systems. The API request to trigger the message can also include additional data to be templated into the message in real-time (similar to event properties).

To facilitate and make the code more readable, when using Liquid Code it’s better to assign tags to all the items from the API call at the beginning of the HTML and later just name them in the HTML body. 

For example, this is the information you’re receiving from the API call (payload)

"campaign_id": "YOUR-CAMPAIGN-ID",
        "recipients": [

           {
             "external_user_id": user_1234,
             "trigger_properties": {
               "first_name": "John",
               "language": "en",
               "order_number": "12345",
               "order_items": [
               {
                  "product_id": "product_1",
                  "product_name": "Product 1",
                  "quantity": "1",
                  "price": "32.99",
                  "price_formatted": "32,99 €",
                  "image_link": "image.png",
                  "product_link": "mywebsite.com/product-1"
               }
            ]
          }

Then, in the HTML, you can assign a tag to each item and make the content fully dynamic. 

{% assign fname = {{api_trigger_properties.${first_name}}} %}   
{% assign language = {{api_trigger_properties.${language}}}%}
{% assign order_id = {{api_trigger_properties.${order_number}}}%}
{% assign product_name = {{api_trigger_properties.${order_items.product_name}}}%}
{% assign price = {{api_trigger_properties.${order_items.price_formatted}}}%}
{% assign quantity = {{api_trigger_properties.${order_items.quantity}}}%}

<!DOCTYPE html>
<html>
<head>
      <meta charset="utf-8">
      <title>Order Confirmation - {{ order_ide }}</title>
</head>
<body>
      <div>
            <p>Dear {{ fname }},</p>
            <p>Thank you for your order!</p>

       <table>
           <thead>
                 <tr>
                     <th>Product Name</th>
                     <th>Quantity</th>
                     <th>Price</th>
                 </tr>
          </thead>
          <tbody>
                {% for order_item in {{api_trigger_properties.${order_items}}} %}
                 <tr>
                      <td>{{ product_name}}</td>
                      <td>{{ quantity }}</td>
                      <td>{{ price | money }}</td>
                 </tr>
                   {% endfor %}
         </tbody>
         <tfoot>
              <tr>
                    <td></td>
                    <td><strong>Total:</strong></td>
                    <td>{{ price | money }}</td>
              </tr>
         </tfoot>
       </table>
       <p>If you have any questions or concerns about your order, please don't hesitate to contact us.</p>
       <p>Thank you for shopping with us!</p>
     </div>
</body>
</html>

For order confirmation emails, consider using %for% statements to make the HTML dynamic and display all products purchased. For example:

{% assign order_items = {{api_trigger_properties.${order_items}}} %} 
{% for order_item in order_items %}
    {% assign product_id = {{order_item.product_id}} %}     
    {% assign img = {{order_item.image_link}} %} 
    {% assign url = {{order_item.product_url}} %}
    {% assign price = {{order_item.price}} %}
    {% assign quantity = {{order_item.quantity}} %}
    {% assign price_formatted = {{order_item.price_formatted}} %}
    {% assign voucher = {{order_item.used_voucher}} %}
    {% assign code = {{order_item.voucher_code}} %}
    {% assign alt = {{order_item.product_name}} %}
    {% assign product_name = {{order_item.product_name}} %}

     <tr>
     <!-- 1. Space Column left 10px -->
     <html info> 
     <!-- 2. Column Product image --> 

     <a href="{{url}}">

     <!-- 3. Column Product name -->
       <HTML info> {{product_name}}
     <!-- 4. Column Quantity -->
       <HTML info>{{quantity}}  
     
     <!-- 5. Column Price -->
       <HTML info>{{price_formatted}}
     <!-- 6. Space Column right 10px -->    
       <HTML info>

{% endfor %}

An example of an order confirmation message with Liquid

Conclusion

Incorporating Liquid into your CRM strategy is a game-changer for delivering a highly personalized and engaging customer experience. Using Liquid goes far beyond basic personalization, allowing you to create tailored messages with dynamic content based on the user’s behavior and characteristics. Liquid Code can empower your App to connect with your customers on a deeper level, driving increased engagement, conversion, and brand loyalty. As a Braze partner and heavy users of Liquid, we have witnessed the impact of Liquid in CRM Strategies, allowing teams to be more efficient when creating campaigns, unlocking Braze’s full potential, and rocketing your App to success. 

Before you go

• Need support to understand how to deploy Liquid Code to supercharge your CRM strategy? Reach out to us here. 
• Phiture’s Subscription Stack is designed to help growth marketers conceptualize their subscription optimization strategy and understand the essential components of running a mobile subscription business. CRM is vital across the stack, and you can check it out here. 
• Phiture’s Mobile Growth Stack Slack Community brings together professionals from around the world, who are engaging with technology like Liquid to supercharge their CRM strategy. Join today to stay on top of the latest industry updates and trends, pose questions (or answer them), and connect with fellow mobile growth marketers. 

Further Reading

Read Github’s guide to Liquid Code.

Braze’s guide to personalization using liquid tags. 

Read Braze’s guide to API campaigns.