# Other people also bought - Wootomation

Tags: woocommerce,ecommerce,automation,ai,ml

Requires at least: 4.9

Tested up to: 5.8

Requires PHP: 7.2

License: GPLv2 or later

License URI: https://www.gnu.org/licenses/gpl-2.0.html

Wootomation allows to add \"Other people also bought...\" feature to your WooCommerce site.
Powered by Machine Learning Artificial Intelligence, the famous feature, used by eCommerce moguls such as Amazon, now on WooCommerce.

## Description

Imagine you run an e-commerce grocery store. Wootomation's AI will analyze all the past and future orders and realizes that a lot of people buy milk, bread, and butter together. This means that even for brand new customers, when they add bread to their basket, they will be recommended milk and butter.

Wootomation uses Machine Learning Artificial Intelligence to recommend the best products to your customers, based on their cart items.

This very light plugin adds a section, similar to up-sells/cross-sales, in the cart before totals, which suggests what other people have also bought. It silently analyses all sales of your store and processes it in order to train the AI. It only works in the background, when new data is being added, so it is not disruptive to the customers' journey.

Using the same concept, Amazon have increased their sales by 35%.

## Installation

Before installing, make sure you have WooCommerce installed and active, and use PHP version of minimum 7.2.

Simply install and activate the plugin, then go to the settings page (WooCommerce -> Wootomation) to setup the various options.

## Frequently Asked Questions

### How does it work?

The machine-learning artificial intelligence analyses all the sales in a smart way, it learns from them, and then is able to predict the most relevant products to your customers, thus increasing sales. With each purchase going forward, it keeps learning and gets better and better.

### Does it analyse previous orders?

Yes, on activation it will analyse all previous orders, then each month it will update the suggestions. We decided to go for montly retraining in order to keep the suggestions fresh and relevant, such as seasonal items or general user preferences.

### Does it work on large websites with 1000s of orders?

The more data it has to learn from, the better it gets at suggesting products. The predictions are saved in the database and are reused in a lightweight way.