Documenting lifecycle testing
We're looking to enhance our documentation process for lifecycle testing and would love to hear what’s working for others! Do you have any templates or strategies that help effectively track experiments and build on learnings? Our goal is to make it easier to: Keep track of live, completed, paused, and inconclusive tests—including test descriptions, hypotheses, start/end dates, audiences, and key metrics. Summarize metrics, key insights, and recommendations to inform future campaigns and decision-making. Would appreciate any tips, templates, or frameworks anyone has found valuable! Thanks in advance.Canvas Frequency Capping.
Hello community! After designing a referral strategy composed of various campaigns and canvases, I’m setting up frequency capping to prevent users from receiving multiple campaigns on the same topic simultaneously. However, while implementing the frequency capping strategy, I encountered several doubts. My main objective is that if a user enters a canvas with the referral tag during a week, they should not be able to access any other canvas with that tag. However, I believe that the current rules do not achieve the desired effect. Does anyone know if there’s a way to meet this condition? Thank you very much!Referral Strategy
Hello Braze Community! I’m currently working on creating a referral strategy to drive new user acquisition through our most engaged users. I’d like to start a thread with all of you to gather inspiration and discuss different flows we could implement. So far, I’ve identified the following key moments: After a user gives a high rating in our review After a purchase Targeting our most engaged users After a user completes an “aha moment” in our app What do you think? Which strategies have you implemented to carry out a referral strategy. Best regards, Sergio
Liquid arrays personalization
Hello everyone I'm trying to implement this liquid code in one of my templates: {% assign combinedResults = canvas_entry_properties.${data}.results | concat: canvas_entry_properties.${data}.featuredResults %} {% assign results = combinedResults | sort: 'totalEstimatedCost.amount' | reverse %} The arrays canvas_entry_properties.${data}.results and canvas_entry_properties.${data}.featuredResults are two arrays that contain a list of offers, with each offer having a name, an ID, and a totalEstimatedCost.amount Using this Liquid code, I want to first create a third array called combinedResults that merges the offers from both canvas_entry_properties.${data}.results and canvas_entry_properties.${data}.featuredResults. Then, I want to sort this combined array so that the offers are displayed in descending order based on totalEstimatedCost.amount, from the highest to the lowest price However, the issue is that the displayed list first shows the two offers from the featuredResults array sorted in ascending order (from the smallest to the largest price), followed by the five offers from the results array sorted in descending order (from the largest to the smallest price). Do any of you know why this could happen? the structure of the original arrays is the same. Thank you in advance!
System-led QA with Braze
Hi there! Our team has had a few incidents where emails have been sent to the wrong audience (i.e. filtering didn't save, filtering never added, duplicate tabs open, etc). We've implemented a number of human-led QA processes (see below) but we want to implement system-level guardrails as well. Does anyone know of a) Braze features that would let us do this or b) hacky ways that involve our engineering team? Any/all help would be GREATLY appreciated! What we plan to implement: formal QA process (including live QA) Braze approval process Audience and rate limits Datadog alerts for post launch if anything sends to audience >10K
Transactional Push Notification ideas?
Hi - We hope to launch some basic transactional push notifications which we were told were high performers! I was wondering if anyone has done something similar and if they had any ideas of some of the 'lower hanging fruit' of transactional push's that were high performing... Some examples that we are starting with are: 1. Order Confirmed 2. Order Shipped 3. Order Delivered Are there any other 'transactional' messages such as the above that you have seen success with?Forge Canvas Template: Product repurchase reminder (with timing and channel testing)
Hello fellow Braze orchestrators, I didn't make it to Forge in person this year, but it was great tuning in to the keynotes and catching up on all the latest Braze innovations. 🔥 Here is a quick Canvas that we are about to launch to drive repurchase of two of our products that customers need to by on a regular basis. Entry criteria: purchase of a certain SKU Experimentation (both set up as Personalized Path): Message timing (30 days vs 45 days after the purchase) Message channel (email vs SMS, in this case) Message sequence: A user gets a reminder to repurchase the product she might be running low on; If a user engages with the message from step 1, but does not purchase, he receives a reminder 3 days later with a special offer, to incentivize the purchase. Let me know if you see any opportunities for improvement. I imagine, soon we will be able to simplify this flow by leveraging all the upcoming Braze AI tools. Cheers, Olga Baker Charlie Banana / P&GForge Canvas Template: Frequency/Channel mix Experiment Setup”
This Canvas serves as a starting point for setting up an experiment aimed at sending specific sub-groups of a user population down the engagement journey that has the highest likelihood of converting them. The criteria that differentiate the journey in this Canvas are tied to two variables: 1. Frequency: n times over n periods depending on the use case, industry, and type of product. For example, n times per week for n weeks. Both the 'times' and 'periods' should be customized according to the use case. 2. Channel mix: combinations of at least 2 channels based on the use case, industry, and type of product. For example, a push notification followed by an email or an IAM followed by an email. The channels to test should be customized based on the use case. The goal here is to leverage Braze's personalization systems to take experiments to the next level: no more simple A/B tests where all users are sent down the engagement journey that converts the most overall. Instead, specific sub-groups of the population will be sent down different, specific paths based on their unique characteristics/preferences. This allows us to avoid a 'one size fits all' approach and instead create multiple journeys that users can experience based on what they prefer (and what tends to convert users like them better 😉 )." I’ve been using this setup for a while, and the uplift compared to a single experience for the entire population (chosen after multiple iterations of a classic A/B test) is significant. Let me know what you think and if you have any ideas for improving this setup!Conversion Rate over 100%?
Hi, I'm struggling to understand the performance of one of our Canvases. I have both the conversion event and exit criteria as "any purchase", and users cannot re-enter the canvas. When I analyze the variants, I see more conversions than entries, leading to a conversion rate over 100%, which shouldn't be possible. Does anybody know what could be going wrong here? thanks!
