Data handling & security
Years of working with customer-provided business datasets have led us toward a simple security principle: the safest customer information is information Salesbroom does not need to receive.
Context matters
The business information Salesbroom typically cleans is public information: company names, business addresses, executive names, titles, business email addresses and phone numbers. The sensitivity comes from the dataset itself—who assembled it, which records they selected, how those records are grouped, and what they intend to do with them. That context can reveal valuable business strategy even when every individual data point is publicly available.
Anonymous project datasets
Customers provide Salesbroom working datasets without ownership information or information that creates an association between the data and a particular customer, user or business purpose. Salesbroom needs the records and the project rules. We do not need the customer’s identity embedded in the working dataset.
Minimum-context principle
Before a dataset is transferred, unnecessary customer-identifying and project-identifying information should be removed. If a field is not required to deduplicate or standardize the data, it generally does not need to be included. The goal is simple: give Salesbroom what is required to perform the work—and no more.
Anonymous project IDs
Every Salesbroom project is assigned a randomly generated project ID. That project ID is the bridge between two separate systems: the customer relationship, project management and billing records on one side; and the anonymous working dataset used to perform the data work on the other.
Project management, scope, billing record and delivery instructions.
The records and project rules required to perform the work—without customer ownership embedded in the file.
A working file can simply be identified as “Project 847261.” The project-management system knows which customer Project 847261 belongs to. The working dataset does not need to.
This separation lets Salesbroom connect the work to the correct project manager, scope, billing record and delivery instructions without embedding customer ownership information inside the dataset itself.
Encrypted at rest
Customer datasets are encrypted at rest throughout the period in which Salesbroom is working on the project. Encryption protects stored project data while Salesbroom needs access to perform the work.
No customer-data repository
Project files exist only for the period required to perform the work, complete quality control, deliver the project and address agreed project closeout requirements. When the work is complete, the completed dataset is returned to the customer and the Salesbroom working copy is destroyed. Ordinary project-management and billing records may remain; the customer dataset does not.
Customer provides an anonymous working dataset.
Salesbroom performs the defined work.
The dataset remains encrypted at rest during the project.
The completed dataset is returned to the customer.
Salesbroom’s working copy is destroyed.
A clear boundary
Salesbroom is designed primarily around spreadsheets, CSV files and other exported datasets. For most Dedupe and Standardize projects, Salesbroom does not need direct access to the customer’s CRM, marketing platform or other production system. The customer exports the required data. Salesbroom performs the work on the project file. The completed file is returned. This creates a clear boundary between Salesbroom and the customer’s production environment.
Human project management
Every Salesbroom project has a human project manager. The project manager works with the customer to define project scope, dedupe or standardization rules, required fields, exceptions, output format, delivery and customer-specific security requirements.
Software, automation and AI
Salesbroom may use software, automation and AI-assisted workflows to perform data work efficiently and consistently. These tools support the work. They do not replace project-level accountability. If a customer has restrictions involving particular software, external systems, AI use or data-processing methods, those requirements should be defined before the project begins.
Enterprise requirements
Enterprise customers may have additional requirements involving confidentiality, file transfer, encryption, access, approved systems, AI use, retention, deletion or vendor-security procedures. These requirements can be addressed during project scoping. The important point is to define them before the production dataset is transferred.
The Salesbroom security model
The working dataset does not need to identify the customer or explain the business purpose behind the records.
Provide only the fields required to perform the work.
Project data is encrypted at rest during the project.
When the work is complete, the data is returned and the working copy is destroyed.
Talk with a Salesbroom project manager before sending a production dataset. We can define the appropriate workflow, transfer method and project requirements first.