For those that have eCommerce stores where sales data is flowing so well that it is becoming a bit challenging to keep up with, then the way to make life easier is through better data management. Shopify API is mature and enables all kinds of systems to connect to it. These Shopify Connectors are also called Shopify Integrations, where the APIs of two systems are integrated and data can flow between 2 accounts (one in each system).
Type of API Implementations
The ultimate API Implementation is where you have a 2-way connection that can update and synchronize fields. An example of this could be a 3rd Party Logistic (3PL) Connector, where once an order is placed, it is synchronized and the order is sent to the 3PL system via the API, and once the order is processed, the 3PL system updates the order in Shopify as “shipped” with the tracking number and any other notes associated with the order. The synchronization can be triggered by synchronization every hour, triggered by a new order or manually requested. Usually, consideration to efficiency and use of the API looks to deliver a best practice approach on how to connect and synchronize the data.
One-way Connectors API’s that “Get” data from one system to another, such as QuickBooks for financial reporting, is another key Shopify Integration that saves the shopkeeper’s time in entering sales data into QuickBooks by having the data flow in the direction from Shopify to the QuickBooks system.
Application Programming Interface (API) Data
For those that are curious about the details, systems that have an API, where it gives account users a way to interface with their accounts using programming requests via this portal. Much like a Web-portal, the API interface uses a set of secure commands to requests or supply data to records and copying these data records from one place to another. Fields such as the Client’s name, address, order items, price of each item, tax, shipping cost, discounts, order details/summary, and instructions are some of the key items related to one order. When processing hundreds of orders a day, taking this data from one system to another can be daunting – the API allows this access to have your financial system, 3PL system, or can be the likes of MailChimp to Mass Mail an offer – just get the data and process it.
Data Correction and Field matching
Shopify Integrations are not as straightforward as people think – not all fields match up directly such as a Shopify Order will fit into a 3PL’s order structure. The Connector has to process the data to structure its fields and elements so that the other system that receives it accepts it. Things like “quantity of items” – this is logically an integer and if it is on the order, it would be greater than 1. Simple enough, the 3PL or Financial System would have this formatted the same for this field – but others such a product description which is “text” can have issues with the field length (one side is more restricted than the other), Asian Languages that are double-byte characters (DBCS), or might require a process to define a product before it can be sent.
Data Correction, or manipulating the data for the business to reach its operational goal in transfer, reporting or allowing it to be used as a record takes place in this Connector, and the rules of matching the fields from one system to another can be tricky. The maturity of the connector is important to understand its abilities as the more data is pushed through it, the variation of information will test its logic, and ensure that transfers are reliable.
Support and Diagnostics
When doing large data transfers where two systems are under heavy usage (with constant records being generated), one could say that a very methodical and structured Shopify Integration is going to be required, since if there is anything that interrupts the dataflow there will be needing someone to look at what might interrupt it, and have it resume so as to complete its synchronization. A lot of times the strain of the connector is on its initial synchronization where the Shopify Store provides its full history to the other system.
A Connector with feedback will provide a certain level of diagnostics, such as the stages of transfers. Sometimes the Synch of a new store takes a different “queue” so as not to interrupt other client’s small synchronizations, and the data is processed in batches such as Customer Data, then Order Data, etc. Progress bars, diagnostic reports such as failed records that could not be transferred and the reason it failed are key to obtain to ensure a full transfer. The report can be used by the supporting programmer to ensure the connector is adapted to your dataset, and the diagnostic report to be resolved.
Shopify Integrations via the API are commonplace, but not all have the level of support, diagnostic and logical approach for a good customer experience. The best approach is to use a sample store with order data to test out an “integration” to the targeted system and ensure that the variation of what is commonplace in your live store is included. With a test account on the other end, give the transfer a try, and see how well it performs. Considering peak times, doing the initial synch during off-hours and low-traffic times would make more sense, just to ensure that less chance of data transfer interruptions occurs.
At TheGenieLab where we build API Connections and run Shopify Integrations with our clients, we have built and own our own ERP Integrations, we have a keen eye on how the tools work and need to deliver for the business owner. If you have any questions, feel free to reach out to us at firstname.lastname@example.org