"With Locoia we created a data pipeline (ETL) between our ad server (SSP) Xandr and Google BigQuery in 2 days. It used to take us 4-6 weeks of manual programming. Locoia is an absolute accelerator for sales ops and data pipelines."
Opinary - The publisher that generates interactions via opinions
With 120 million unique users, Opinary gives people new ways to express their opinions online. Leading brands and agencies use Opinary to build direct relationships with their audiences. Opinary acts as a marketer on the most well-known Europe-wide websites.
Media / Advertising
Deals from the CRM Pipedrive are to be created directly in the Xandr ad server and the corresponding performance data is to be transferred back to Pipedrive for sales.
Basic data for billing is prepared manually based on the CRM data in Google Sheets and then manually entered into an invoicing tool.
- Static and performance data must be exported and processed manually from the ad server
- Sales and Ad Ops create campaigns by copy & paste and find out about delivery results
- Many manual steps to create monthly invoices
- Using Locoia’s Google BigQuery data pipeline template
- Creation of own workflows for Sales Ops processes with Locoia
- Optimizing workflows with Locoia Solutions Consulting team
With the help of the Locoia Flow Builder and workflow templates, Opinary was able to activate a data pipeline according to Big Query with just a few clicks and then adapt it to their specific use cases.
The Locoia Solutions consulting team was able to support the further optimizations with their experience from hundreds of customer workflows regarding the optimal procedure.
3. Result of the automation
Engineering department: Opinary was able to create a fully automated data pipeline within 2 days (a few hours net).
Sales Ops department: The Ad Ops team no longer has to create manual campaigns: the key data is created fully automatically from the CRM in the ad server.
Finance department: Invoices are created automatically from the CRM in sevDesk.
- Engineering: All master and performance data in Big Query fully automatically every day: Implementation in just 2 days instead of 3-4 weeks of in-house development of a data pipeline
- Sales Ops: Manual data transfer workload reduced by 80%
- 1-2 days savings per month for Finance with regular invoicing