Automated Asset Generation Workflow

Visual asset creation begins by building a reusable template in Bannerbear, defining the fixed design elements — logo placement, color scheme, and layout structure — alongside the variable fields that will change per asset, such as a product name or price. Connect a data set, such as a spreadsheet of variable values, and Bannerbear will automatically generate one finished asset per row without requiring manual design work for each variant.

For any campaign requiring custom imagery or background elements the template needs as source material, use Recraft to generate that visual content ahead of time. Recraft's vector-native output and style-locking controls hold up better than raster-only generation once Bannerbear resizes the same source image across dozens of variant formats, so prompt it with a detailed description of the mood, composition, and brand style guide reference required, then import the generated asset into the Bannerbear template as a background or supporting element.

For supporting visual assets across multiple formats — such as accompanying social graphics for the same campaign — use Simplified to batch-produce these from the same saved brand kit, keeping visual consistency between the Bannerbear-generated primary assets and any supporting pieces.

Where a specific asset requires manual adjustment beyond what automated template generation supports, use Canva to finish that individual piece by hand, importing the same brand elements used across Bannerbear, Recraft, and Simplified. A sample Bannerbear template data row might look like:

{
  'template_id': 'example_template',
  'variable_fields': {'product_name': 'Example Product', 'price': '29.99'}
}

Review the full generated batch against the source data set before moving to distribution, confirming every row produced a correctly rendered asset.

Document generation applies the same template-and-data-merge principle from Stage 1, but routes through Docupilot rather than an image-oriented generator, since Docupilot's conditional field logic and native PDF handling are purpose-built for multi-page, text-heavy documents. Build a document template in Docupilot, defining fixed layout elements alongside variable text fields that will populate per document, such as a recipient name, date, or specific data point pulled from a source spreadsheet.

Connect a structured data set to the template, and Docupilot will merge each row automatically, producing a finished batch of personalized documents — certificates, reports, or similar repeatable formats — while its conditional logic can automatically include or exclude entire sections per document based on the data, something a purely image-based template merge cannot handle cleanly.

For any document requiring a layout too complex or non-repeating for a template merge to handle, use Canva to design that specific document manually, maintaining the same brand fonts and colors used in the Docupilot template so the manually designed piece still feels consistent with the automated batch.

A sample document template configuration might follow this structure:

{
  'template_id': 'example_doc_template',
  'variable_fields': {'recipient_name': 'Example Name', 'date': '2026-07-01'},
  'conditional_section': 'include_if_field_present'
}

Spot-check a handful of generated documents against their source data rows before finalizing the full batch, confirming variable fields populated correctly and conditional sections triggered as expected.

Scaling automates the distribution of the finished asset and document batches from Stages 1 and 2, using Make as the orchestration layer in place of a more limited automation tool, since Make's visual data-mapping makes it easier to bridge the image generator's output and the document generator's output into a single distribution flow without extensive custom configuration. Configure a Make scenario to trigger automatically whenever a new batch completes generation in either source generator, removing the need for a team member to manually check generation status before starting distribution. A minimal scenario configuration might look like:

{
  'trigger': 'batch_complete_webhook',
  'action_1': 'route_to_posteverywhere',
  'action_2': 'notify_team_channel'
}

Once triggered, PostEverywhere receives the finished batch and distributes it across configured destination channels, whether that means publishing visual assets to social platforms or delivering generated documents to their intended recipients through connected integrations.

For any distribution requiring a specific scheduled publish time rather than immediate release — such as a social campaign timed to a product launch — use Publer to schedule the finished assets instead of relying on PostEverywhere's default immediate distribution behavior.

Confirm the Make scenario completed successfully for the full batch by checking its execution history, and build a second scenario branch that flags any individual asset or document in the batch that failed to distribute correctly, so distribution failures don't go unnoticed until the whole campaign is expected to be live.