From that it creates and generates automated pieces to publish on the site (Banners, Carrousels, Emails)

b) It connects to the business rule engine and triggers actions

a) It´s easy to install, a Script is added in Google Tag Manager

Based on 4 Pillars

1. Metrics Analytics

4. Location

3. Rules

2. Templates

HOW BRAINDW WORKS

From that it creates and generates

the site (Banners,Carrousels,Email)

automated pieces to publish on

b) It connects to the business rules

engine and triggers actions

a) It´s easy to install, a Script is

added in Google Tag Manager

Based on 4 Pillars

1. Metrics Analytics

4. Location

3. Rules

2. Templates

HOW BRAINDW WORKS

Based on cookies, Braindw collects data and monitors each of the activities that users perform on the site.

THE 4 PILLARS ON WHICH BRAINDW SUPPORTS

ANALYTICS

t is essential to work on metrics and have the ability to measure what end users are doing, what buyers are doing, both with banners and gondolas on the site and with emails, both on desktop and on mobile devices. important to measure, analyze and improve.

RULES

  • Best offers of a category or collection
  • Most viewed products of the site
  • Latest products browsed by the user
  • Most added products to the cart all over the site
  • Most viewed products in a category
  • Most added products to the cart in a category
  • Offers in the last category navigated
  • Products Recovery of failed search terms
  • Latest searches Terms
UBICACIÓN

  • HOME
  • GENERAL CATEGORÍES
  • PRODUCT CATALOG CATEGORY
  • PRODUCT URL
  • SEARCH RESULTS
  • CHECKOUT

Our real-time online intelligence engine captures and persists data by tracking each of the activities that users perform on a site, which products they look at, which they add to the car, which they end up buying, which searches perform, the last ones products that they visit, and what their favorite categories are.

This allows the customer to identify the user’s profile and create audiences based on it, giving it a HIGH RELEVANCE content, all this allows to build and enriches profiles of the navigator which are the basis of the recommendations of products that are presented.

Braindw works with 3 APIs or services that interacts among them through the process and deliver the contents.

1. The rules engine API, which processes user behavior, evaluates and decides what action to take on the web in real time.

2. The API that processes, evaluates and delivers the products that integrate the parts generated by Braindw. The requirements are asynchronous and depend on the need for the action and the characteristics of the website. The response of this API is in JSON format and the origin of the content can be generated from the consumption of an API (integration with a platform such as Vtex) or through a Scrapping on the client’s website.

3. The persistence API is responsible for obtaining specific information on the web for a particular session / user and save it in a historical / statistical format

The ability to respond in real time allows us to recognize, among other things, what search a user is doing and based on the term used to show a dynamic banner with offers from highest to lowest or most viewed in the last 48 hours. You can also identify which is the geographical location or the device from which the navigator is connecting.

By linking the cookie with the user’s email that he leaves in the registration box, Braindw sends smart email campaigns in real time, based on User activity on the site, whether it returns after a while and starts a new session or if it accesses a certain category or leaves a car abandoned for some time.

With the incorporation of the Persistence concept into the Braindw suite of solutions, we were able to strengthen the circuit that feeds the rules and actions in real time that our AI platform provides. In this way, it adds to the hot data of the present moment of the user’s navigation, the historical data that enriches and multiplies the possibilities of understanding more precisely what products you need to acquire. Braindw consolidates and organizes customer data sets in an Amazon (AWS) environment.

We can incorporate multiple information channels, which are integrated into the data with which our model operates. Based on the discovery of navigation patterns we check whether these coincide and work with the actions generated (Banners, gondolas and email) once we publish them on the website.