Shopify CRM / ERP Integrations
Shopify, talking to
the rest of the business.
ERP, CRM, warehouse, 3PL and POS connected with sync that is idempotent, monitored and honest about failure — because a feed nobody watches is a feed that eventually breaks.
What this is
A Shopify integration, plainly.
An integration keeps Shopify and another system in agreement about products, inventory, pricing, orders and customers, without anyone retyping data. The code is the easy part. The work is deciding which system owns each field, which direction each one syncs, and what happens when the two disagree — which they will, on day three, at 2am, during a sale.
ERP
The system of record for most of what the store sells. Usually the hardest integration and the one worth doing properly.
- Product and variant master data, one owner per field
- Inventory sync across locations and channels
- Pricing and B2B price lists driven from the ERP
- Order writeback with correct customer and terms mapping
- Returns, credits and adjustments reflected both ways
CRM
So the sales and support teams see the same customer the store does.
- Customer and company record sync
- Order history surfaced in the CRM
- Lead and account mapping for B2B buyers
- Marketing consent kept consistent across systems
- Sales-rep visibility into store activity
Warehouse, 3PL & fulfilment
Where inventory accuracy and customer trust are actually decided.
- Order routing and multi-location fulfilment logic
- Shipment, tracking and delivery status writeback
- Stock adjustments and cycle-count reconciliation
- Backorder and partial-shipment handling
- Carrier and rate integration
POS & retail
For brands whose inventory is shared with physical stores.
- Shopify POS and third-party POS systems
- Shared inventory across retail and online
- Customer and loyalty continuity across channels
- Buy-online-pick-up-in-store flows
- Reconciliation between store and channel reporting
Reliability engineering
The part that separates an integration from a script someone wrote once.
- Idempotent operations — a replay does not duplicate an order
- Retry with backoff and rate-limit awareness
- Dead-letter handling: failures parked, never silently dropped
- Reconciliation jobs that detect drift before a human does
- Alerting to the people who can act on it
Connector or custom
We will use an off-the-shelf connector when it is genuinely the right answer, and say so.
- Assessment of existing connectors against your data model
- Direct API integration where a connector cannot cope
- Middleware where several systems share the same data
- Cost of running it, stated before you commit
- Documentation so you are not locked to us
The honest version
Integrations fail in the gaps.
Nobody loses money on the happy path. They lose it on the cases that were never specified — and those cases are what discovery is for.
Questions we insist on answering first
- Which system owns price? Stock? The customer record?
- What happens when a product exists in one system and not the other?
- Does a Shopify refund create a credit note, and who issues it?
- How do you handle an order placed while stock was syncing?
- Who gets alerted at 2am, and what are they expected to do?
- What does “reconciled” mean, and how often do we prove it?
What we assume will go wrong
- The other system will be down or rate-limited
- Someone will edit a record by hand in the wrong place
- A malformed record will arrive and must not stop the queue
- A webhook will be delivered twice, or not at all
- The data model will change without anyone telling us
- A sale will multiply traffic on the worst possible day
Finding out about a broken feed from a customer complaint is a design failure, not bad luck.
How it runs
Map the data, then write the code.
Most integration overruns are not engineering overruns. They are the discovery that the two systems have disagreed quietly for three years and somebody has to decide which one is right.
Systems Discovery
What each system contains, what its API can actually do, where the data has drifted, and which fields are genuinely authoritative. Documented before anything is estimated.
Week 1–2Integration Design
Field-level mapping, sync direction and frequency, conflict rules, error handling, and the monitoring plan. This is the document the build is measured against.
Week 2–3Build & Test
Developed against sandbox or staging environments with realistic volumes, including deliberate failure testing. An integration that has never been broken on purpose has not been tested.
Week 3–8Reconcile & Cut Over
Historical data reconciled, discrepancies resolved with the business rather than guessed at, then a monitored cutover with a rollback path.
CutoverMonitor & Maintain
Dashboards, alerting, periodic reconciliation and capacity for the API changes that will arrive whether you planned for them or not.
OngoingOur thinking, published
Systems, in more depth.
Integration decisions are mostly build-versus-buy decisions. These are the frameworks we use to make them.
FAQ
Integration questions.
It is a connection that keeps Shopify and your ERP in agreement about products, inventory, pricing, orders and customers, without anyone retyping data. In practice it means deciding which system owns each field, syncing in the right direction, and handling the cases where the two disagree — which is most of the actual work.
ERP, CRM, warehouse and 3PL, POS, accounting, PIM and subscription platforms. Where a supported connector exists and is reliable, we use it rather than billing you to rebuild it. Where the connector does not exist, cannot handle your data model, or has failed before, we build and monitor a direct integration.
Direct when there are one or two systems and the mapping is stable. Middleware when several systems need the same data, when the mapping changes often, or when the business needs somewhere to see and replay failures. Middleware costs more to run, so it is a decision we justify rather than default to.
It will — APIs rate-limit, systems go down, records arrive malformed. The integrations we build are idempotent, retry with backoff, park records they cannot process instead of dropping them, and alert a human. Finding out about a broken feed from a customer complaint is a design failure, not bad luck.
A single well-documented connector is usually weeks. A multi-system integration where the data model has drifted for years is months, and most of that time goes on reconciling what the systems actually contain rather than on writing code. Discovery tells you which one you have before you commit.
Related services
B2B Shopify Development
Company accounts, price lists, net terms and gated catalogues on Shopify B2B.
ExploreShopify Migration
Outdated POS, inventory and commerce systems migrated into one Shopify ecosystem in under 90 days.
ExploreApp Development
SaaS platforms, mobile apps, APIs — built by engineers, not freelancers.
ExploreWhat has to
stop being manual?
Tell us which two systems disagree and what your team is retyping between them. We’ll map the integration, state what it costs to build and to run, and be honest if a connector already does it.