PrestaShop improves time-to-resolution for support tickets by 33% with Fivetran, BigQuery, Looker and Hightouch

Results

• Increased employee engagement with data from 10% to more than 40%
• Reduced dashboard development time from six weeks to less than two days
• Shortened time-to-resolution for Zendesk support tickets by 33%
• Improved NPS score by 7 points
• Lowered Hubspot costs by 25%

The Challenge

As Prestashop grew, it wished to derive more value from its data, but the company ran into issues caused by legacy, siloed architecture that negatively impacted data consistency and accessibility.

Teams were constantly reinventing the wheel to manually scale and solve use cases, and less than 10% of the company actually trusted or used the data. Most data sources were only accessible to a handful of data people, and to make matters worse, the data was only ever available in a dashboard.

The Solution

To address these challenges, PrestaShop set out to design a new architecture built around a modern data platform to improve data accessibility and consistency. This meant adopting a composable architecture that could easily scale and meet PrestaShop’s growing needs.

Fivetran

Core systems at PrestaShop, including SQL and NoSQL databases, and SaaS Applications, were siloed; each presenting its own data, often captured from different sources such as support tickets, marketing engagement, purchase activity, and product usage. This setup made data overall inconsistent as no single system would contain a source of truth, resulting in many inefficiencies, poor collaboration across teams, and a reluctance to use data to support key decisions.

The first step in centralizing this data was building out a robust data ingestion pipeline. After considering several vendors and spending weeks and countless resources trying to debug integrations, Prestashop chose to work with Fivetran. Ingestion reliability is extremely important for PrestaShop, and Fivetran completely automates the entire process in the background extracting data from data sources like Zendesk, HubSpot, and GitHub and ingesting all of that data into Google BigQuery.

BigQuery And Looker

With fully automated data ingestion pipelines in place, Prestashop simply needed a centralized platform to consolidate all of the data from its numerous sources, so adopting Google BigQuery and Looker was a “no-brainer” for the data team.

Before BigQuery and Looker, the PrestaShop had no reliable source of truth, and building a fully-fledged dashboard would take an average of six weeks to develop. Now, it takes less than two days – and a simple dashboard can be created autonomously by business users in as little as 15 minutes.

BigQuery is extremely performant and scalable for PrestaShop’s many different workloads. Thanks to Looker’s self-service exploration capabilities, PrestaShop can go beyond dashboards and glean insights into surrounding product issues and business opportunities.

Hightouch

Sitting on top of Looker, Hightouch unlocks all the data models PrestaShop has built-in Looker for Operational Intelligence. For example, in just a few days, the team built a customer knowledge model combining data from multiple sources and uses Hightouch to sync data from the semantic layer to Zendesk via Reverse ETL. This allowed the care team to make more data-informed decisions speeding up the time to resolve support tickets submitted through Zendesk by 33% and increasing PrestaShop’s NPS score by 7 points.

Using Hightouch to sync data to Postgres, PrestaShop has been able to build an application for the sales team that recommends a list of add-ons for each merchant based on their site performance and other metrics. This application saves the SDR team hours every week, and they no longer have to do manual data collection.

Prestashop also uses Hightouch to enrich Hubspot with additional merchant and store-related data to provide the sales and marketing teams with more relevant data for personalization. Syncing enriched customer data into Hubspot also helps PrestaShop identify invalid contacts to improve data quality, and this has decreased Hubspot costs by 25%.

What’s Next?

In less than six months, PrestaShop managed to get the entire data stack up and running, build over 30 data models, and engage over 120 employees with a small team of only two data engineers. PrestaShop has already seen much progress in its shift to becoming a more data-driven company and is excited to roll out more self-service intelligence capabilities in the future.