Behind the Scenes
How do I trust Sortment AI's output?
An in-depth explainer on how Sortment builds trust-by-design
An in-depth explainer on how Sortment builds trust-by-design
It’s one of the most honest questions we hear from marketers and it doesn’t come from abstract fear. It comes from experience.
Maybe you’ve seen a demo that looked promising, only to find the real thing couldn’t deliver even a fraction of what was shown. Or maybe you’ve watched a campaign go sideways because the AI misunderstood the brief.
Even a single mistake can hurt. Imagine sending:
That kind of misstep damages brand trust and also puts the marketer on the hook.
One of our customers put it perfectly: “With great access comes great responsibility. How do I trust the data?”
Previously, there was comfort in knowing a data expert had reviewed everything. Now, with direct access, marketers can move faster, but they also wonder, what happens if there’s a mistake in the data and I’m the one accountable?
That’s why we built Sortment to earn your trust, by giving you visibility and control at every step.
Most AI tools act behind the scenes. Sortment is built to show you how it works, every time.
Whether it’s building a segment or defining an attribute, Sortment surfaces the logic in a drag-and-drop format you can inspect, adjust, and verify.
This is what we mean by human-in-the-loop design. Here’s how it works:
During onboarding, Sortment gets read-only access to the 20–30 most relevant data warehouse (your company’s source-of-truth) tables. Then we run a schema/data mapping workshop with marketing and data stakeholders to align on which tables are live and fresh.
The result: the AI starts from context you’ve confirmed, not assumptions.
Once access is in place, Sortment builds a semantic layer. It’s a data dictionary that acts like a translation layer between raw warehouse tables and how marketers actually think.
This includes:
• Human-readable labels for each table and column
• Descriptions based on metadata and naming conventions
• Relationships between tables, like how orders connect to users or sessions to events
And the best part? You don’t need to dig into dashboards or documentation to find this.
You can talk to the AI directly, and see its interpretation of your data in plain English.
For Security & Privacy: Sortment provides an option to mask columns which might contain sensitive information.
When you ask Sortment to build an audience or define an attribute, you get more than a chat response. You see the logic in a visual builder.
You can edit filters or definitions directly in the visual builder.
For complex use cases, Sortment AI might create a SQL output which can be verified through an approval workflow by a data colleague, discussed in the later sections.
Before publishing, Sortment provides a Customer 360 view. This is a required step before publishing, nothing goes live without a final check.
Sortment gives you role-based access control (RBAC) to manage who can:
• View only access
• Create access
You can also introduce approval workflows, so one person creates an attribute, and another (like a team lead or data partner) reviews and approves it.
These guardrails help teams:
• Avoid duplicates or conflicting definitions
• Catch subtle logic issues before data is live
• Maintain accountability without bottlenecking speed
Even when everything looks right, things can still go wrong after publishing, especially when something upstream quietly breaks.
Tables may change. Data may stop updating. Pipelines may fail. And without visibility, broken segments can keep running unnoticed.
Sortment monitors pipeline health in real-time. If something breaks, it:
• Detects the issue: stale data, missing tables, or sync failures
• Notifies the right people: via Slack, email, or in-app
• Pauses the pipeline: until it’s fixed
So you don’t send emails off outdated data or push broken segments downstream. Because even great AI needs a system that keeps it safe, stable, and up to date.
Here’s what Drew Price, Director of Lifecycle Marketing @ BryteBridge, had to say:
AI is everywhere in the marketing stack, but most tools push the marketer out of the loop. They either automate decisions without explanation or respond to prompts without understanding your data. Either way, you’re left hoping the output is right, with rarely any potential for fixing mistakes.
Sortment takes a different approach: it’s built to work with you, visibly and verifiably. Here's what sets it apart:
• Visual logic, not hidden rules
• You see exactly how an audience or attribute is constructed and can change it.
• Understands your data, not just your prompt
• Sortment maps your schema upfront, so responses are grounded in your actual setup.
• Controlled publishing, not blind automation
• Nothing goes live without your review and approval.
Sortment gives you speed without sacrificing clarity. It’s not a black box — it’s a co-pilot that works the way marketers actually do.
Sortment was built on a simple idea: marketers should be able to use AI without losing control.
You should be able to see how something was built, edit it confidently, and publish only when you’re sure.
That’s what Sortment makes possible. It turns AI from a black box into a transparent assistant — one that works at your speed, speaks your language, and shows its work.
Still wondering if the AI gets it right?
Try Sortment’s interactive demo. See exactly how it reads your data, builds logic, and gives you full control.
