We discuss here of what are the best data models for your Marketing Automation projects and how you can improve your Marketing Automation success both immediately, and also gradually while you are improving your data and omnichannel setup.

We address first

• what are the available data (section 1 : Understand the data),

• then highlight the way they can be accessed and used (section 2: How to use the data)
  and we finish on what are the business goals, data availability, and metrics and KPIs to consider for your projects (section 3: How to set Marketing Automation Objectives & Goals)

Open

1. Understand the data

We separate here two types of data: the Core Data (the data which are loaded in ourGoogle BigQuery Data Warehouse) and the Analytics & Lab data, which are generated on the basis of the Core data (see more details in Open Data Warehouse (CODW) )

The Core Data

We consider here a base situation Boxalino Winning Interactions clients typically reach early on in their Setup (here-after the Base Core Data) as well as Additional Core Data which we recommend integrating into your data set-up to improve the impact of marketing automation projects.

We also then explain the added value of the Analytics and Lab Data (which are generated on the basis of the core data).

The Base Core Data

The base Data consists of the following aspects:

• E-shop Product Data (typically updated many times per day in the format doc_product )

• E-shop Purchase History Data (typically updated once per day in the format doc_order )

• E-shop Customer Data (typically updated once per day in the format doc_user )

• Google Analytics 4 Data (typically updated once per day with How to transfer your Google Analytics 4 Data to BigQuery )

• Google Ads Data (typically updated once per day with How to transfer your Google Ads Data to BigQuery )

• Boxalino Tracking and API Requests / Responses (typically updated once per day)

Additional Core Data

In addition, we recommend our clients to integrate the following data (by order of priority)

1. ERP Purchase History Data (typically updated once per day in the format doc_order )

2. Newsletter statistics (typically updated once per day in the format communication_history )

3. Headless CMS content (typically updated many times per day in the format doc_content )

4. Newsletter trigger mails automation* (typically send trigger mails in the format communication_planning )

5. Newsletter automation* (typically send newsletters in the format communication_planning )

* This is a feed to use from the BigQuery environment, so it’s an export, not an import

The Analytics & Lab Data

Boxalino generates many reporting and automation tables in Google BigQuery which are processed daily (and sometimes weekly on Mondays).

Find here more information:

• Analytics, Insights, Reports (CAIR)

• Open Data Science Lab (B/C DSL)

2. How to use the data

We provide this section in form of a FAQ.

What data is needed to achieve our goals?

All the Base Core Data are typically needed as a minimum.

Additional Core Data

In addition, the following data are needed in order to:

1. ERP Purchase History Data → get offline purchases, returns, and cancelations

2. Newsletter statistics → monitor, analyze and optimize marketing automation initiatives

3. Headless CMS content → dynamic automation of not only products but also any other type of content

4. Newsletter trigger mails automation* → generate triggers emails based on the data

5. Newsletter automation* → change the content of newsletter based on the data

Is the data available?

Yes, the data are available at any time, in different ways:

• directly by connecting to Google BigQuery (with their SDK)

• through custom data feeds configured in the Boxalino Platform

• through Product & Content recommendations (available through API and link/image http service)

• through standard feeds like communication_planning

How long will it be available?

Forever as long as no deletion policies are requested.

How is the data collected?

This depends on the type of data:

• E-shop/ERP Product Data, Customer Data and Purchase History Data are sent typically by the E-shop or the ERP to the Boxalino Data Integration API (see more details here: https://boxalino.atlassian.net/wiki/spaces/BPKB/pages/252149803 )

• Google Analytics & Google Ads are collected with the standard BigQuery Data Transfer Services

• Boxalino Tracking and API Request / Response are tracked directly within the Boxalino Platform, they are collected upon each request to the API or by the browser tracker (similar to Google Analytics)

Where are they stored?

All the data are stored in Google BigQuery

Backups and source files are kept (for a period up to 1 year depending on the types of data) in Google Cloud Storage

How often and when are the data updated?

The Core Data a mainly every day (except for products and content which are updated many times per day).

The Analytics and Lab Data are updated partially every day (and fully every week on Mondays).

What triggers changes in the data?

All changes are triggered by either a push of the data to the Boxalino Data Integration or a scheduled daily (or weekly) processing.

Some processing can be scheduled more than once per day based on crontab configuration if required.

Who manages the data?

The data in the Data Warehouse (BigQuery) are managed by Boxalino.

The data which are provided to the Boxalino Data Integration API are managed by the managers of the exporting systems (e.g.: E-shop data are managed by the E-shop agencies)

What is the format of the data?

The format of the data are all provided in the links above.

How is the data linked?

• The Order Data are Linked to the Customer Data and the Product Data (typically by the product idand the customer account id we call the persona_id)

• The Google Analytics Data are linked to the Google Ads Data primarly by the gclid, but also by the traffic source campaign name and other utm parameters

• The Google Analytics Data are linked to the Boxalino Tracking data by the google analytics cookie id (they also link to the product data with the ‘items’ structure and the purchase data by the ‘ecommerce’ structure)

• The Boxalino Tracking & API Requests / Response data are linked by customer account id, the product id and the transaction id with the order, product and customer data)

• The communication history and planning data are linked by the e-mail address to the customer data as well as to the product and content data through their id when applicable

• The ERP data are linked to the E-shop data through the product id, order id and customer account id (sometimes also e-mail address)

How will we use it?

The data can be used in the following ways:

• Analysis in standard reports

• Analysis in custom reports

• Set-up of custom data feeds for trigger mails

• Personalization of content for newsletters

• Personalization of products for newsletters

• …

3. How to set Marketing Automation Objectives & Goals

We recommend following a customer life-cycle approach with the following steps:

Awareness

• Lead Generation (newsletter subscription, push notification activation, …)

Consideration

• Time on site

• Page views (esp. Product and Campaign / Content Pages)

Purchase

• Newsletter traffic source revenue share

Growth

• 1st → 2nd Purchase rate

• Customer Retention Rate

• Purchase Frequency

Promote & Preserve

• NPS score