OfferFit by Braze

Get started with OfferFit by Braze to make 1:1 AI decisions that maximize your business metrics!

What’s OfferFit by Braze?

OfferFit replaces A/B testing with AI decisioning that personalizes everything, and maximizes any metric: drive dollars, not clicks—with OfferFit, you can optimize any business KPI.

OfferFit’s AI decisioning agents automatically discover the optimal action for every customer. Using your first-party data, OfferFit can maximize any business KPI for a wide range of use cases, including cross-sell, upsell, repurchase, retention, renewal, referral, winback, and more.

The AI Expert Services team will tailor OfferFit to the specific needs of your business. While OfferFit works best with Braze, a variety of other platforms are already supported. To learn more, book a call with OfferFit.

Key features

• Keep your tech stack, but add a brain: OfferFit plugs in as a decisioning layer between your data systems and your marketing automation platform.
• Pick winners for people, not segments: Use all your first-party data to make the optimal 1:1 decision for each individual.
• Personalize everything: AI decisioning agents find the best message, product, incentive, channel, timing, and frequency for each individual customer
• Maximize any metric: Clicks aren’t dollars. Use OfferFit to pick the offers or incentives that maximize revenue, profit, CLV, or any other business KPI.
• Open the black box: See how AI decisioning agents personalize for deep insights into the drivers of customer behavior

About use cases

How it works

A use case is a custom configuration for OfferFit’s AI decisioning engine that’s tailor-made to meet a specific business goal.

For example, you could build a repeat purchase use case to increase follow-up conversions after an initial sale. You define the audience and message in Braze, while OfferFit runs daily experiments, automatically testing different combinations of product offers, message timing, and frequency for each customer. Over time, OfferFit learns what works best and orchestrates personalized sends through Braze to maximize repurchase rates.

Building a good use case consists of:

• Choosing a success metric for OfferFit to optimize for, such as revenue, conversions, or ARPU.
• Defining which dimensions to test, such as offer, subject line, creative, channel, or send time.
• Selecting the options for each dimension, such as email versus SMS, or daily versus weekly frequency.

Sample use cases

Here are some examples of use cases that you can build with OfferFit. Your AI decisioning agents will learn from every customer interaction and apply those insights to the next day’s actions.

Use case	Business goal	Using typical methods	Using OfferFit by Braze
Cross-Sell or Upsell	Maximize average revenue per user (ARPU) from internet subscriptions.	Run annual campaigns offering every customer the next-highest tier plan.	Empirically discover the best message, sending time, discount, and plan to offer for each customer, learning which customers are susceptible to leapfrog offers and which customers require discounts or other incentives to upgrade.
Renewal & Retention	Secure contract renewals, maximizing both contract length and net present value (NPV).	A/B test manually, and offer significant discounts to secure renewals.	Use automated experimentation to find the best renewal offer for each customer, and identify customers who are less price sensitive and need less significant discounts to renew.
Repeat Purchase	Maximize purchase and repurchase rates.	All customers receive the same journey after making a website account (such as the same email sequence with the same cadence).	Automate experimentation to find the best menu item to offer each customer, as well as the most effective subject line, sending time, and frequency of communication.
Winback	Increase reactivation by encouraging past subscribers to resubscribe.	Sophisticated A/B testing and segmentation.	Leverage automated experimentation to test thousands of variables at once, discovering the best creative, message, channel and cadence for each individual.
Referral	Maximize new accounts opened through business credit card referrals from existing customers.	Fixed email sequence for all customers, with extensive A/B testing to determine the best sending times, cadence, etc. for the customer population.	Automate experimentation to determine ideal email, creative, sending time, and credit card to offer specific customers.
Lead Nurturing & Conversion	Drive incremental revenue and pay the right amount for each customer.	As privacy policies change at Facebook and other platforms, prior approaches to personalized paid ads become last effective.	Leverage robust first-party data to automatically experiment on customer segments, biding methodology, bid levels, and creative.
Loyalty & Engagement	Maximize purchases by new enrollees in a customer loyalty program.	Customers received a fixed sequence of emails in response to their actions. For example, all new enrollees in the loyalty program receive the same journey.	Experiment automatically with different email offers, sending times, and frequencies to maximize purchase and repurchase for each customer.

About API key permissions

During your OfferFit integration, you’ll create a Braze API key with specific permissions that will define your integration’s capabilities. Refer to the following table to learn more about each permission.

Permission	Purpose	Required?
/users/track	Updates custom attributes on user profiles, in addition to creating temporary user profiles when using test sends.	✓
/users/delete	Deletes temporary user profiles that were created while using test sends.	Only for test sends
/users/export/segment	Updates the available audience communications every morning by exporting the list of users from each selected segment.	✓
/users/export/ids	Retrieves a list of identifiers when targeting users using an external_id instead of a segment. Since OfferFit doesn’t accept Personally Identifiable Information (PII), you’ll need to ensure your fields_to_export parameter returns only non-PII fields.
Only if using external_ids
/messages/send	Sends recommended variants at the recommended time using API Campaigns that are configured for OfferFit’s experimenter.	✓
/campaigns/list	Retrieves the list of active campaigns and extracts available email content for experimentation.	✓
/campaigns/data_series	Exports aggregated campaign data to enable reporting, validation, and troubleshooting in OfferFit, so you can compare reporting values and analyze baseline performance. While not required, this permission is recommended.
/campaigns/details	Retrieves HTML content, subject line, and image resources from existing Campaigns for experimentation.	✓
/canvas/list	Retrieves the list of active Canvases to extract available email content for experimentation.	✓
/canvas/data_series	Exports aggregated canvas data for reporting and validation, especially when BAU is orchestrated via Canvas. While not required, this permission is recommended.
/canvas/details	Retrieves HTML content, subject line, and image resources from existing Canvases for experimentation.	✓
/segments/list	Retrieves all existing segments as potential target audiences for the OfferFit experimenter.	✓
/segments/data_series	Exports segment size information, which is shown in OfferFit when selecting an audience.	✓
/segments/details	Retrieves segment details such as entry and exit criteria to help understand changes in audience size or performance.
/templates/email/create	Creates copies of selected base HTML templates with dynamic placeholders (Braze liquid tags) for experimentation, avoiding changes to the originals.	✓
/templates/email/update	Pushes updates to OfferFit-created template copies when experimentation criteria change, such as call-to-actions.	✓
/templates/email/info	Retrieves information about OfferFit-created templates in your Braze instance.	✓
/templates/email/list	Validates that templates were successfully copied over to your Braze instance.	✓

Next steps

Now that you know more about OfferFit by Braze, you’re ready for the next steps:

1. Integrating OfferFit
2. Building a use case