UAMASTER digital agency

Development of connectors for integrating marketing data

We set up integration, automation, and the foundation for end-to-end analytics

Today, businesses use dozens of digital tools: advertising platforms, CRM systems, analytics, email marketing, and e-commerce platforms. However, data from these systems is usually stored separately, which makes it difficult to analyze marketing performance and make strategic decisions.

The connector development service allows you to automatically consolidate data from different sources into a single data repository. This creates the foundation for end-to-end analytics, accurate dashboards, and deeper analysis of business performance.

What are data connectors for data transfer

A connector is a software module or integration that enables the automatic transfer of data between different systems.

Connectors are typically used to collect data from:

  • advertising platforms
  • CRM systems
  • web analytics systems
  • e-commerce platforms
  • marketing tools
  • internal company databases

The data is regularly transferred to a centralized data warehouse, where it can be used for analytics, reporting, and building dashboards.

Tools used

Data warehouses

BigQuery

PostgreSQL

Snowflake

Cloud platforms

Google Cloud Platform

Cloud Functions

Cloud Scheduler

BI tools

Looker Studio

Tableau

Power BI

Programming languages

Python

Why businesses need connector development

Without data integration, companies often face the following problems:

  • data is stored in different systems and is not interconnected
  • reports are created manually
  • it is difficult to assess the true effectiveness of marketing
  • end-to-end analytics cannot be built
  • data may differ across various sources

Connector development allows for the creation of a centralized data system and automates work with analytics.

Connector development stages

Data source analysis

In the first stage, the following are determined:

  • which systems need to be integrated
  • which data is required for analytics
  • the frequency of data updates
  • API limitations

Data structure design

The structure of the future data warehouse is created:

  • table schemas are modeled
  • relationships between sources are defined
  • data processing rules are established

Connector development

The connector performs the following functions:

  • connects to the data source API
  • retrieves the required data
  • processes and cleans the information
  • prepares the data for loading
  • transfers the data to a centralized data warehouse

Setting up automatic execution

To ensure integration works without manual intervention, automatic execution of connectors is set up.

Scripts can run:

  • daily
  • hourly
  • on a custom schedule

Testing and data accuracy verification

Before launching the integration, the connectors are tested.

The following are checked:

  • accuracy of the retrieved data
  • compliance with the data structure
  • stability of data transfer
  • handling of potential errors

Integration launch and maintenance

After successful testing, the connectors are put into operation.

Ongoing activities may include:

  • monitoring data transfer
  • updating integrations when APIs change
  • connecting new data sources
  • optimizing system performance

Is data integration necessary for analytics?

We help consolidate data from advertising platforms, CRM systems, and other sources into a single data warehouse and create the foundation for effective analytics.

Request a free consultation, and we will find the optimal solution for integrating your data.

Contact with us

FAQ

Connectors can integrate various types of systems, including:

The specific list of integrations depends on the technical capabilities of the systems and the availability of APIs.

The service will be useful if:

  • you use multiple advertising platforms
  • CRM data is not combined with marketing channels
  • reports have to be created manually
  • you need end-to-end analytics
  • you plan to build a BI dashboard system

Data transfer is usually carried out through the source system’s API. A special script connects to the API, retrieves the required data, processes it, and sends it to a centralized data warehouse.

The process is automated and can run on a schedule, for example, daily or hourly.

The update frequency depends on business needs and the technical limitations of the systems.

Data is most often updated:

  • hourly
  • daily
  • several times a day

The update schedule is configured individually.

Collected data is usually sent to a centralized data warehouse, such as:

  • BigQuery
  • PostgreSQL
  • Snowflake

Yes, this is one of the most common use cases for connectors. Integrating CRM with advertising platforms allows you to combine marketing spend with lead and sales data and build end-to-end analytics.

The development duration depends on the number of data sources, the complexity of the APIs, and the volume of required information.

On average, developing a single connector takes anywhere from a few days to several weeks.

Yes, sometimes systems change their APIs or data formats. In such cases, connectors may need to be updated. Maintenance can also include connecting new data sources or optimizing data transfer.

Perfect digital experience

years
1
countries
1
clients
1
projects
1

Testimonials

Award-winning Digital Agency

Our expertise is backed by awards from advertising festivals.

The agency holds top positions in industry-specific rankings.

Our achievements

Do you want to create your own project that will win an award?

Contact with us
Contact
with us