Streamline your Back in Stock Alert system with the Batch Data Platform

To achieve system reliability when implementing a Back in Stock alert system, it is crucial to carefully integrate it with the stock management system to ensure real-time updates on product availability.

The Batch Data Platform enables its e-merchant customers to achieve this by automating the sending of personalised alerts while handling a large volume of requests without compromising performance, scalability, and data management reliability.

This is crucial for user confidence, maximising sales opportunities, and conducting in-depth data analysis to assess the effectiveness of alerts.

How does the Batch Data Platform enable its e-merchant customers to achieve system reliability?

This post addresses the scenario of a user interested in an item that is currently out of stock.

Detecting user interest in an out-of-stock item

From a technical perspective, this use case starts in the customer's back-end.

The initial step is to collect user interest in each product.

This can be accomplished in various ways, such as:

• adding the item to their wishlist and receiving an email when it is back in stock;
• subscribing to an alert via a dedicated module on the website or app.

To initiate this scenario, the Batch clients map and store in their back-end the identifiers of the users who are interested in specific items.

Activating Batch’s personalised Trigger Automation

After an item is restocked, Batch clients use our Profile API to retrieve information for all users associated with the item.

The Batch Data Platform then receives an event, usually called 'back_in_stock', which triggers the Trigger Automation that was previously set up on the Batch dashboard.

Typically, our customers prefer an immediate message to inform the user as soon as possible. Thanks to the Batch Data Plaform real-time differentiator, they can easily trigger their emails in a highly responsive manner.

The API call’s payload contains the user's Custom User ID and information about the product, in the form of custom attributes. This enables message personalisation, including an image of the product, a link to the item or the user's wishlist, or even an option to add the item directly to the shopping cart. This approach aims to personalise and simplify the user experience, making it easier to purchase items of interest when they become available again.

Feedback loop to optimise use case performance

Batch has implemented a feedback system to track user interaction with emails. This is crucial for evaluating message effectiveness and making informed decisions to optimise future strategies.

Users open emails and click on links, providing Batch with feedback to record and analyse interaction data and calculate statistics such as click rate, open rate, spam rate, bounce rate, and details of links clicked.

How the Batch platform optimises the Back in Stock alert personalisation

To improve back-end message management, it is crucial to identify users' interests in each item.

For the Batch user, this involves creating a mapping table that specifies which users are interested in which products. The product table must include all necessary fields for each item, such as description, name, and links to images. Once established, the mapping table is used for each call to the Profile API, allowing Batch to compose highly personalised messages.

For back in stock Email alerts, the Batch customers can use the following features:

• The Email Composer on the Batch Dashboard to create personalised messages using the data provided via the Profile API. This feature provides great flexibility, allowing customers to personalise messages according to their preferences and test different approaches directly from the Batch Email Composer. This strategy aims to make communication with users more relevant, personalised, and effective based on their specific product interests.

• The Email Preview feature is also a powerful tool for marketers using Batch, as it allows them to see the email as it will appear to a specific user. This is particularly useful once the data flow has been established. Marketers can access past events and run tests to see how an email appears for an item that has come back into stock. This feature offers a practical perspective, allowing them to see how the data will translate into the final message for a specific item. It brings an important level of personalisation and precision to the creation of marketing campaigns.