Shopify Plus and wholesale built around how your buyers work.

Shopify's core B2B tools are no longer limited to Shopify Plus. Companies, locations, buyer permissions, catalogs, net payment terms, self-service ordering, quantity rules, and Shopify Flow automation can be available on other Shopify plans, subject to current plan and Markets requirements.

Shopify Plus becomes relevant when the business needs Plus-only depth. Current examples include unlimited B2B market catalogs, catalogs assigned directly to specific companies or company locations, and advanced payment capabilities such as deposits and partial payments. Plus may also be justified by broader checkout, organization, automation, support, or commercial needs outside the wholesale scope.

We document each requirement, map it to the current Shopify plan matrix, and compare platform cost with the operational value. Features and eligibility can change, so final plan advice is verified against Shopify's current documentation before implementation.

• Requirement-to-plan comparison
• Plus-only feature and dependency review
• Total operating model and application costs
• Clear upgrade triggers for future growth

The storefront and the operating model must agree. We map how company accounts, contacts, locations, catalogs, permissions, pricing, payments, tax status, inventory, fulfillment, returns, and reporting are owned across Shopify and connected systems.

Every integration receives a clear source of truth, field mapping, trigger, exception path, and support owner. That matters when an ERP controls credit or price, a PIM controls product data, a warehouse controls availability, or a CRM controls the account relationship.

• Company, location, contact, and permission governance
• Catalog and price ownership across systems
• ERP, PIM, CRM, warehouse, and fulfillment workflows
• Order, payment, tax, and reporting reconciliation

A wholesale migration must preserve the rules behind each account. We identify companies, locations, contacts, permissions, tax status, catalogs, customer-specific prices, volume breaks, quantity rules, payment terms, addresses, order history, credit information, and identifiers used by connected systems.

Source data rarely matches Shopify's model without transformation. We profile representative records, define mappings and exclusions, run repeatable test migrations, reconcile results, and plan how late changes will be captured before launch. Sensitive data and unsupported history are handled according to an agreed scope and retention policy.

If the program includes a broader replatform, see our Shopify migration services for storefront, content, application, SEO, and launch planning.

• Company, contact, location, and address mapping
• Catalog, price, terms, tax, and permission transformation
• Test migration, reconciliation, and exception handling
• Cutover, final-delta, and post-launch validation

We start with buyers and operations: who buys, who approves, how prices are agreed, how orders enter the business, and which teams resolve exceptions. From there, we define the Shopify model, integration boundaries, storefront journeys, migration scope, security needs, reporting, and acceptance criteria.

Build and testing use representative companies, catalogs, prices, products, terms, and order scenarios. The launch plan covers data cutover, integration sequencing, buyer invitations, staff training, support ownership, and a stabilization period. This prevents a technically complete storefront from failing at adoption.

1. Discovery, buyer research, and requirements
2. Solution architecture and operating-model decisions
3. Experience design, configuration, and development
4. Integration, migration, and end-to-end testing
5. Launch readiness, training, and buyer onboarding
6. Stabilization, measurement, and ongoing improvement

B2B storefronts often combine public marketing and product information with account-only catalogs, prices, and purchasing tools. We define which content search engines may crawl and which experiences require authentication. Public pages use semantic HTML, descriptive headings, crawlable links, useful metadata, and supported structured data based on visible content.

For answer engines and AI discovery, we organize public content around clear buyer questions, service definitions, platform comparisons, implementation details, and direct answers. Company-specific prices, terms, customer data, and private documents remain outside public indexation.

During migrations or redesigns, we review public URLs, canonicals, robots directives, sitemaps, redirects, internal links, and structured data before and after launch. These practices improve clarity and technical eligibility; they do not guarantee rankings, citations, or inclusion in AI-generated answers.

• Public-versus-private content and crawl rules
• Semantic templates, metadata, and internal linking
• Answer-focused service and product information
• Redirect, sitemap, canonical, and structured-data checks