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2023 Facebook Algorithm Guide: Overview & Best Practices

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2023 Facebook Algorithm Guide: Overview & Best Practices

Every month, 2.7 billion people use Facebook, Meta’s globe-dominating social network. For marketers, this is an un-ignorable audience. However, reaching that audience isn’t always easy – to get content in front of a relevant user, they need to make the Facebook algorithm work in their favor.

Unfortunately, the algorithm can feel very mysterious. Why do some posts go viral with engagement while others wither and disappear without so much as a few courtesy likes?

The good news is that while the technical rules governing Facebook’s algorithm may be in a black box, there are plenty of guidelines and common-sense tips that can help ensure your content gets prioritized and seen. Facebook has published many explainers and tutorials over the past few years to break down how its algorithm ranks and distributes content to users’ Feeds.

Here’s how Facebook’s algorithm works in 2023 with ten expert tips on increasing the impact, performance and lifecycle of your Facebook content.
 

Table of Contents

 

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  • What is the Facebook Algorithm?
  • A Recent History of the Facebook Algorithm 
  • How the Facebook Algorithm Works in 2023
  • 10 Best Practices for Working with Facebook’s Algorithm
  • Final Takeaway

 

What is the Facebook Algorithm?

 
The Facebook algorithm is the set of rules and formulas that determine what content users see in their Feeds. Its goal is to make the posts that “matter most to the user” highly visible to that user. To do this, it analyzes each piece of content eligible to be displayed and ranks them according to a set of criteria.

As Facebook explains, the algorithm is actually “not just one single algorithm; it’s multiple layers of [machine learning] models and rankings that we apply to predict the most relevant and meaningful content for each user.”

If that sounds complex, that’s because of the sheer volume of content on the Facebook platform. There are over 2 billion Facebook users and trillions of posts they can see; the algorithm needs to be sophisticated to sort through all that content in an instant between launching the Facebook application and the population of each user’s Feed. 

 

A Recent History of the Facebook Algorithm

 

Since 2017, Facebook has been increasingly transparent about significant changes in how it ranks and distributes content. That also means the algorithm is constantly evolving. In general, those updates have favored user input, posts friends and family over publishers, and content personalized to a user’s interests… all geared toward generating more “meaningful interactions.”  These updates include:

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  • Meaningful Interactions Update (2018) – This update signaled that the algorithm would predict which posts a user might want to interact with their friends about and show these posts higher in Feed. These posts inspire discussion in the comments and posts that users might want to share and react to. 
  • Updates to Video Rankings (2019) – This update boosted the rankings of video posts that users sought out and returned to, watched for more than one minute at a time, and were original creations and not repurposed content. 
  • Addressing Sensational Health Claims (2019) – This update applied some of the existing “clickbait” rules specifically to posts making medical or health claims in an effort to reduce misinformation. Exaggerated or sensational claims were deprioritized, as were posts promoting products that advertised “miracle” cures.

 

The past three years have seen additional updates, and since they’re more recent, they deserve closer examination.

 

2020: Key takeaway from 2020

 

In 2020, Facebook modified its algorithm again to give more weight to original, credible news sources and create more personalized advertising encounters for users based on their interactions. Additional updates this year included changes designed to comply with Apple’s iOS 14’s privacy guidelines. 

 

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  • Prioritizing Original Sources: In response to users continually reporting a preference for “news stories that are credible and informative,” Facebook announced that it would make ongoing updates that “prioritize articles in News Feed that we identify as original reporting on a developing story or topic.”
  • Personalized Ads: The Facebook algorithm serves advertisements to a user’s Feed based on the posts and pages they have engaged with previously. Businesses are also given the option to share information about the actions that users take on their websites and apps so they can show the most relevant content in users’ Facebook Feeds. To balance this process of information gathering and sharing, which also lays the foundation for personalized advertising on the platform, Facebook instituted the “Why am I seeing this ad” feature and the “Ad Preferences” dashboard for users (and to address privacy concerns).
  • Retargeting Limitations: Even with expanded personalization, Facebook had to respond to the significant privacy and permissioning guidelines i=within the Apple iOS 14 update released in 2020 (Tinuiti’s Liz Emery takes a more detailed look at this topic here). When Apple users install or update to iOS 14, they will be prompted to opt-in or opt out of data sharing. While Facebook has other variables that can be used to identify devices, such as the associated email address and phone number, targeting that depends on users sharing their data at the device level is restricted based on this update.

 

2021: Machine Learning and User Control

 

In 2021, Facebook released new details about how the algorithm governing users’ Feeds works and increased the amount of control users have over what they see. 

 

  • Favorites: A new tool where users can control and prioritize posts in their Feeds from the friends and Pages they choose. By selecting up to 30 friends and Pages to include in Favorites, their posts will appear higher in ranked and can also be viewed as a separate filter.
  • Revealing the algorithm’s machine learning mechanics: In 2021, Facebook published an in-depth post explaining how the Feed predicts what users want to see. For the first time, it detailed the machine learning processes behind predicting what users see in their Feeds based on various factors, including what and whom they’ve followed, liked, or engaged with recently. These mechanics are largely still in place today.

 

Source: Facebook

 

2022: From ML to AI

 

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Last year, the Facebook algorithm evolved further in the direction of user control and augmented its use of machine learning tools with more sophisticated artificial intelligence systems. These two updates went hand-in-hand. Users were given a new function on each post they saw, the “Show More/Show Less” feature. Selecting “Show More” would increase the ranking score for that post, increasing the likelihood of a similar post or a similar user appearing in the user’s Feed. The inverse would happen when “Show Less” is selected.

These per-post user inputs are simultaneously helping the AI system generalize how relevant future content will be for that user. Or as Facebook puts it, “by offering more ways to incorporate direct feedback into Feed ranking, we’re making our artificial intelligence systems smarter and more responsive.”

Facebook’s AI model generates what the company calls user and content embeddings, which help predict the types of content a person wants to see more of or less of in their Feed. Another Facebook blog post from 2022 explains that a “user embedding captures a person’s tastes, while the content embedding captures the essence of what a post is about.” 

One last update from 2022 – what was once called the Facebook News Feed is now just the “Feed.” That’s how we refer to it throughout this article, except where relevant due to historical discussion.

 

How the Facebook Algorithm Works in 2023

 
That’s the state of the Facebook algorithm in 2023 – it has evolved to become an AI-powered, user-centric model designed to present users with relevant, welcome content in their Feeds. Even though Meta will admit that the algorithm isn’t perfect (and may never be), Facebook has demonstrated a willingness to modify its processes to give users what they want.

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Despite the Facebook algorithm’s complexity and integration of new technologies like AI and machine learning, understanding its core functionality boils down to four ranking factors.

The Four Ranking Factors Fueling the Facebook Feed Algorithm

 
Prioritizing what “matters” to users has been one of the most consistent purposes of the Feed and all of its previous iterations. The goal of Facebook’s algorithm is to “show stories that matter to users,” according to Adam Mosseri, VP of Facebook’s News Feed Management. That aim is reflected across the platform’s many updates and tweaks to its algorithm, from more user control to increased personalization on advertisements. 

With that in mind, you should know how Facebook’s different algorithm factors work together to determine which stories “matter” to a user. And Facebook made these factors easy to understand in its published help center post.  
 

1. Inventory

 
Inventory represents the stock of all content that can display to a user on Facebook’s News Feed, which fluctuates based on user activity once scrolling has begun. This includes everything posted by friends and publishers.
 

2. Signals

 
Signals represent the information that Facebook can gather about a piece of content. Signals are the single factor that you have control over.

These are your inputs that Facebook interprets; type of content, the publisher, its age, purpose, and more.

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You want your content to signal to Facebook that it’s meaningful and relevant to your target audience.
 

3. Predictions

 
Predictions represent a user’s behavior and how likely they are to engage with a content piece. Will a user watch a video to completion? Will they select the “Show More” feature on the post?

Predictions take authentic engagement like comments, likes, and shares from real profiles into account.
 

4. Relevancy Score

 
Relevancy Score is the final number assigned to a piece of content based on the likelihood that the user will respond positively to it. It also accounts for whether a post is “clickbait,” whether it links to a low-quality webpage, or if it’s misinformative in some way.
 

10 Best Practices for Working with Facebook’s Algorithm

 
So how can you tailor your content to ensure a high Relevancy Score and a strong enough ranking to appear in your target audience’s Feeds? Most of the following tips will be common sense if you currently produce content for social audiences, but many are specific to the sophisticated Facebook algorithm. 

Here are some guidelines and best practices for keeping your content meaningful in Facebook’s eyes, based on our research, Facebook’s recommendations, and Matt Navara and Paul Armstrong’s coverage of Facebook’s News Feed webinar
 

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1. Keep posts relevant to your audience

 
Your content should always be relevant to your core audience — the people you want to build a community around. If your content is relevant to a user, the Facebook algorithm is likely to interpret that content as “meaningful,” a key consideration in ranking. 

Stories should be compelling enough for a user to want to share with family and friends. Content should be informative and interesting… and, of course, accurate. 

Products, education and lifestyle imagery, should reinforce your post’s meaningful and informative nature and build on your identity as a brand answering to a specific audience.

 

2. Engage readers and encourage interaction

 
Facebook’s News Feed algorithm favors content that fosters positive interactions between your followers and others.

Any piece of content, from products to education to entertainment — should provoke conversation. Remember that conversations can’t be one-sided; you want your audience to respond, but you must also respond to them when possible. 

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You want your content to prompt people to stop their scroll, interact, and share. Interaction is a crucial weighting factor for the Facebook algorithm, so all your content should be tailored to maximize engagement.
 

3. But don’t use clickbait or engagement bait

 
 
Remember all those “like if…” and “share if you are…” posts?

This is considered engagement baiting; it doesn’t add value or interaction for users. It may not entirely be clickbait, but the Facebook algorithm will penalize it as though it were. 

Avoid asking people to “please comment, like, and share.” Your content should inspire them to engage without having to ask.

Facebook penalizes brands that encourage comments, likes, and shares on organic and ad posts. Keep this in mind when developing content for Instagram and Facebook.

 

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4. Expand your post reach with employees and brand advocates

 

Because the Facebook algorithm gives preference to posts from users’ friends, families and the pages they interact with, your company’s Facebook page will have naturally limited reach. This is where enlisting employees and brand advocates can have a real impact. 

Facebook represents your widest audience, but to reach them, you need to engage the audience closest to home. Encouraging your work team to share your brand’s content with their networks broadens the reach of the post or piece of content and your brand. Directly engaging with Facebook users who are already devotees of your brand and asking them to share content with their friends and family can have a similar effect.,
 

5. Or put ad dollars behind content with organic momentum

 
 
The new Facebook algorithm values content that performs well organically, and you can build off that momentum by boosting or promoting that content with ad dollars.

Content that already has strong organic traction means lower CPCs which, combined with ad dollars, can act as a snowball effect for your content.

Identify opportunities for ads based on organic post engagement and tap into Facebook Ads Manager tools by leveraging these posts in ads.

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Conversely, don’t waste ad dollars on poor-performing organic content. It will have higher CPCs and cost you more while offering less in return.

“If a post performs well with engagement, likes, and shares, there’s an opportunity to place additional ad dollars to drive that performance even further.”

— Nii Ahene, Chief Strategy Officer at Tinuiti
 
Portrait of Nii Ahene
 

6. Create compelling, original video content

 
 
2019 was the year that Facebook began leaning into its video offering in earnest, and it hasn’t stopped since. Today, the video formats available on Facebook have expanded to include Reels and Stories (shorter clips), Video on Demand and Live video. Reels, in particular, is Facebook’s fastest-growing content format “by far.” s video continues to be the top-performing content type across all social media networks, focusing on video should be a central part of your Facebook marketing strategy.

For your video content to perform best in the Feed, Facebook recommends that it be original, capture the audience’s attention, spark engagement, and inspire users to seek additional video content from the same source. 

To create original and authentic Reels, Stories and full-length videos, make sure they capture your brand’s voice and avoid duplicating content. To retain attention, ensure your creative and copy is optimized towards mobile viewing (i.e., shortened copy, readable overlays, shortened headlines). And to generate engagement, encourage discussion and genuine interactions (but like always, avoid engagement bait).

 

7. Inspire audiences and evoke emotion with storytelling

 

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Just as videos should be original, engaging and attention-grabbing, so should any content you post on Facebook. Understand the kinds of stories that resonate with your audience and craft your posts to tell those stories in an exciting way.

You can create connections with your audience through authenticity, interactivity and accuracy. But the surest way is by listening. Ask for feedback. Learn their interests. Take cues from their activity on other platforms. When you know what your audience cares about, you have a better chance of inspiring them… and a better chance of rising to the top of their Feeds.

 

8. Post authentic and truthful content

 

Facebook says that “authentic stories are the ones that resonate most” and that users want to see accurate information. After the controversies surrounding “fake news” and the spread of dis- and misinformation on the platform in recent years, the company has made promoting truthful content central to the Facebook algorithm’s function. 

To signal that your content is genuine and accurate, write clear headlines free from exaggeration or sensationalism. Use well-sourced, reliable information, and avoid sharing content from sources you need clarification on. And above all, don’t lie or try to mislead with your content.

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9. Schedule content when readers are likely to engage

 

The Facebook Feed is no longer chronological, but timing can still impact post performance within the algorithm. You want to post content when your audience is likely to engage with it, which is likely in the evening or overnight, but it can vary widely by the user. There is some research exploring the objectively ideal time for posting, but the ultimate best practice is understanding your audience and when they are most likely to be on the platform. 

 

10. Learn what works by tracking content performance

 

After you’ve published your content, remember to use Facebook Insights to track the performance of your content. This will help you understand how your different content pieces are performing in terms of engagement, which is the key ranking metric. 

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Facebook also offers a variety of tools designed to help you measure both organic content and paid ads. Choose the best tools for your brand, and track performance regularly. Learn from your own Insights data and the tools you use, and optimize your content from there.

Final Takeaway

 
The Facebook algorithm is sophisticated and constantly evolving. There are few shortcuts and no way to “hack” it. But the steps outlined in this article can help make the algorithm work for you and help you get your content in front of the Facebook users who need to see it.

Want to work with our team of Facebook experts? Reach out today!

Editor’s Note: This post was originally published by Greg Swan in April 2020 and has been updated for freshness, accuracy, and comprehensiveness.

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YouTube Ad Specs, Sizes, and Examples [2024 Update]

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YouTube Ad Specs, Sizes, and Examples

Introduction

With billions of users each month, YouTube is the world’s second largest search engine and top website for video content. This makes it a great place for advertising. To succeed, advertisers need to follow the correct YouTube ad specifications. These rules help your ad reach more viewers, increasing the chance of gaining new customers and boosting brand awareness.

Types of YouTube Ads

Video Ads

  • Description: These play before, during, or after a YouTube video on computers or mobile devices.
  • Types:
    • In-stream ads: Can be skippable or non-skippable.
    • Bumper ads: Non-skippable, short ads that play before, during, or after a video.

Display Ads

  • Description: These appear in different spots on YouTube and usually use text or static images.
  • Note: YouTube does not support display image ads directly on its app, but these can be targeted to YouTube.com through Google Display Network (GDN).

Companion Banners

  • Description: Appears to the right of the YouTube player on desktop.
  • Requirement: Must be purchased alongside In-stream ads, Bumper ads, or In-feed ads.

In-feed Ads

  • Description: Resemble videos with images, headlines, and text. They link to a public or unlisted YouTube video.

Outstream Ads

  • Description: Mobile-only video ads that play outside of YouTube, on websites and apps within the Google video partner network.

Masthead Ads

  • Description: Premium, high-visibility banner ads displayed at the top of the YouTube homepage for both desktop and mobile users.

YouTube Ad Specs by Type

Skippable In-stream Video Ads

  • Placement: Before, during, or after a YouTube video.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
    • Action: 15-20 seconds

Non-skippable In-stream Video Ads

  • Description: Must be watched completely before the main video.
  • Length: 15 seconds (or 20 seconds in certain markets).
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1

Bumper Ads

  • Length: Maximum 6 seconds.
  • File Format: MP4, Quicktime, AVI, ASF, Windows Media, or MPEG.
  • Resolution:
    • Horizontal: 640 x 360px
    • Vertical: 480 x 360px

In-feed Ads

  • Description: Show alongside YouTube content, like search results or the Home feed.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
  • Headline/Description:
    • Headline: Up to 2 lines, 40 characters per line
    • Description: Up to 2 lines, 35 characters per line

Display Ads

  • Description: Static images or animated media that appear on YouTube next to video suggestions, in search results, or on the homepage.
  • Image Size: 300×60 pixels.
  • File Type: GIF, JPG, PNG.
  • File Size: Max 150KB.
  • Max Animation Length: 30 seconds.

Outstream Ads

  • Description: Mobile-only video ads that appear on websites and apps within the Google video partner network, not on YouTube itself.
  • Logo Specs:
    • Square: 1:1 (200 x 200px).
    • File Type: JPG, GIF, PNG.
    • Max Size: 200KB.

Masthead Ads

  • Description: High-visibility ads at the top of the YouTube homepage.
  • Resolution: 1920 x 1080 or higher.
  • File Type: JPG or PNG (without transparency).

Conclusion

YouTube offers a variety of ad formats to reach audiences effectively in 2024. Whether you want to build brand awareness, drive conversions, or target specific demographics, YouTube provides a dynamic platform for your advertising needs. Always follow Google’s advertising policies and the technical ad specs to ensure your ads perform their best. Ready to start using YouTube ads? Contact us today to get started!

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Why We Are Always ‘Clicking to Buy’, According to Psychologists

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Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.

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A deeper dive into data, personalization and Copilots

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A deeper dive into data, personalization and Copilots

Salesforce launched a collection of new, generative AI-related products at Connections in Chicago this week. They included new Einstein Copilots for marketers and merchants and Einstein Personalization.

To better understand, not only the potential impact of the new products, but the evolving Salesforce architecture, we sat down with Bobby Jania, CMO, Marketing Cloud.

Dig deeper: Salesforce piles on the Einstein Copilots

Salesforce’s evolving architecture

It’s hard to deny that Salesforce likes coming up with new names for platforms and products (what happened to Customer 360?) and this can sometimes make the observer wonder if something is brand new, or old but with a brand new name. In particular, what exactly is Einstein 1 and how is it related to Salesforce Data Cloud?

“Data Cloud is built on the Einstein 1 platform,” Jania explained. “The Einstein 1 platform is our entire Salesforce platform and that includes products like Sales Cloud, Service Cloud — that it includes the original idea of Salesforce not just being in the cloud, but being multi-tenancy.”

Data Cloud — not an acquisition, of course — was built natively on that platform. It was the first product built on Hyperforce, Salesforce’s new cloud infrastructure architecture. “Since Data Cloud was on what we now call the Einstein 1 platform from Day One, it has always natively connected to, and been able to read anything in Sales Cloud, Service Cloud [and so on]. On top of that, we can now bring in, not only structured but unstructured data.”

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That’s a significant progression from the position, several years ago, when Salesforce had stitched together a platform around various acquisitions (ExactTarget, for example) that didn’t necessarily talk to each other.

“At times, what we would do is have a kind of behind-the-scenes flow where data from one product could be moved into another product,” said Jania, “but in many of those cases the data would then be in both, whereas now the data is in Data Cloud. Tableau will run natively off Data Cloud; Commerce Cloud, Service Cloud, Marketing Cloud — they’re all going to the same operational customer profile.” They’re not copying the data from Data Cloud, Jania confirmed.

Another thing to know is tit’s possible for Salesforce customers to import their own datasets into Data Cloud. “We wanted to create a federated data model,” said Jania. “If you’re using Snowflake, for example, we more or less virtually sit on your data lake. The value we add is that we will look at all your data and help you form these operational customer profiles.”

Let’s learn more about Einstein Copilot

“Copilot means that I have an assistant with me in the tool where I need to be working that contextually knows what I am trying to do and helps me at every step of the process,” Jania said.

For marketers, this might begin with a campaign brief developed with Copilot’s assistance, the identification of an audience based on the brief, and then the development of email or other content. “What’s really cool is the idea of Einstein Studio where our customers will create actions [for Copilot] that we hadn’t even thought about.”

Here’s a key insight (back to nomenclature). We reported on Copilot for markets, Copilot for merchants, Copilot for shoppers. It turns out, however, that there is just one Copilot, Einstein Copilot, and these are use cases. “There’s just one Copilot, we just add these for a little clarity; we’re going to talk about marketing use cases, about shoppers’ use cases. These are actions for the marketing use cases we built out of the box; you can build your own.”

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It’s surely going to take a little time for marketers to learn to work easily with Copilot. “There’s always time for adoption,” Jania agreed. “What is directly connected with this is, this is my ninth Connections and this one has the most hands-on training that I’ve seen since 2014 — and a lot of that is getting people using Data Cloud, using these tools rather than just being given a demo.”

What’s new about Einstein Personalization

Salesforce Einstein has been around since 2016 and many of the use cases seem to have involved personalization in various forms. What’s new?

“Einstein Personalization is a real-time decision engine and it’s going to choose next-best-action, next-best-offer. What is new is that it’s a service now that runs natively on top of Data Cloud.” A lot of real-time decision engines need their own set of data that might actually be a subset of data. “Einstein Personalization is going to look holistically at a customer and recommend a next-best-action that could be natively surfaced in Service Cloud, Sales Cloud or Marketing Cloud.”

Finally, trust

One feature of the presentations at Connections was the reassurance that, although public LLMs like ChatGPT could be selected for application to customer data, none of that data would be retained by the LLMs. Is this just a matter of written agreements? No, not just that, said Jania.

“In the Einstein Trust Layer, all of the data, when it connects to an LLM, runs through our gateway. If there was a prompt that had personally identifiable information — a credit card number, an email address — at a mimum, all that is stripped out. The LLMs do not store the output; we store the output for auditing back in Salesforce. Any output that comes back through our gateway is logged in our system; it runs through a toxicity model; and only at the end do we put PII data back into the answer. There are real pieces beyond a handshake that this data is safe.”

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