Turning the Tide: How PrestaShop Regained Trust in Data
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Since 2007, PrestaShop has helped companies unlock the power of e-commerce through its open-source platform. Over 300,000 merchants worldwide use the PrestaShop platform to grow their business and serve online shoppers.
“Our open-source strategy to ecommerce enablement sets us apart,” says Rémi Paulin, Ph.D., Data Architect at PrestaShop. “Customization is becoming more crucial to retailers, and our open-source platform allows companies to continually evolve their sites and services to stand out from competitors.”
As PrestaShop grew, it wished to derive more value from its data, but the company ran into issues caused by a legacy, siloed architecture that negatively impacted data consistency and accessibility.
Let’s look at how PrestaShop works with Google Cloud and partners Fivetran and Hightouch to gain more control over data, enable a beyond-BI data strategy, and increase employee engagement from less than 10% to more than 40%.
Improving trust in data
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.
“Not long ago, less than 10% of the company regularly relied on data, so we were missing opportunities to make more data-driven decisions,” says Paulin. “Data was underutilized, and people were rapidly losing trust in data.”
PrestaShop set out to design a new architecture to address past challenges, such as lack of data consistency, and improve data accessibility.
“Google Cloud, along with Hightouch and Fivetran, allowed us to build a modern stack to solve these challenges and support our beyond-BI data strategy.”
Building a modern data stack
The first step was to build a robust data ingestion pipeline. After considering several vendors, PrestaShop chose to work with Fivetran to extract data from SaaS applications, including Zendesk, HubSpot, and GitHub, to load into BigQuery. They also use Datastream to stream Change Data Capture (CDC) data from transactional databases into BigQuery in real-time.
“Fivetran and Datastream are no-ops, efficient and highly reliable, and relieve our Data Engineers of management tasks. This brings us a high degree of confidence to build the rest of the stack atop these services,” says Paulin.
PrestaShop relies on several Google Cloud solutions, including Dataflow, and a managed Spark service by Ascend.io, for data transformation. It also uses Looker for its semantic modeling capacities and as a self-serve data platform.
As the company continued on its journey to transform how it manages and benefits from data, it engaged Hightouch to enable data accessibility through activation. Sitting on top of Looker, Hightouch unlocks all data models for operational intelligence. For example, in just a few days, the team built a customer knowledge model combining data from multiple sources and used 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%.
“Hightouch feels like a natural extension of Looker and reinforces the position of the semantic data model as the single source of truth,” says Paulin. “It powers a variety of Data Activation use cases, supporting our beyond-BI strategy by providing teams with access to data when and where they need it to improve everyday operations. This has a big impact on the company, bolstering employee trust in available data.”
Becoming data-driven
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.
“Data is now accessible to every stakeholder within the company, regardless of their technical abilities,” says Paulin.
PrestaShop has already seen much progress in its shift to a more data-driven company and is excited to roll out more self-service intelligence capabilities in the future.
“Google Cloud drives home a culture of simplicity around our data stack, which is essential for us, especially given the small size of our engineering team,” says Paulin. “Fivetran and Hightouch share this culture of simplicity. Together, they offer strong foundations to support our data needs.”
Dashboards, which the company had always had an appetite for, are seamlessly created today. Before moving to Looker, a full-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.
Furthermore, data usage goes beyond dashboards. Thanks to Looker’s self-service exploration capabilities, many stakeholders can now glean insights surrounding product issues and business opportunities. Thanks to Hightouch, teams can activate their data to make better and smarter operational decisions.
“This is a big leap forward and one of many to come as we continue to add new models, activate our data, and onboard more users,” says Paulin. “Given our global reach and unique approach to e-commerce enablement, we know this is just the start of the great things we can accomplish with Google Cloud, Fivetran, and Hightouch.”
Check out Fivetran on Google Cloud Marketplace, or sign up for a free Hightouch workspace to learn more about what partners can do for your business.
Linking the Middle East with Southern Europe and Asia: Google’s New Subsea Cables to Be Ready by 2024!
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Today, we’re announcing that we are collaborating with Sparkle and others to build and operate two submarine cable systems linking the Middle East with southern Europe and Asia: the Blue Submarine Cable System connecting Italy, France, Greece, and Israel; and the Raman Submarine Cable System connecting Jordan, Saudi Arabia, Djibouti, Oman and India.
Developing additional network capacity and routes is critical to Google users and customers around the globe, who depend on robust connectivity to power their online lives, and communicate with friends, family and business partners. Google users and Google Cloud customers will benefit from increased capacity and decreased latency to regions in the area.
Each equipped with 16 fiber optic pairs, the Blue and Raman Submarine Cable Systems are expected to be ready for service in 2024. In time, consortium members hope to make additional landings and connect the two systems through terrestrial network assets.
Like with other infrastructure projects, building a subsea cable is an opportunity to pay tribute to a regional luminary who has advanced human understanding. The Raman cable is named for Sir Chandrasekhara Venkata Raman, an Indian physicist who won the 1930 Nobel Prize in Physics—the first Asian to receive that honor in science. C.V. Raman’s work centered on light scattering, which finds that when light traverses a transparent material, some of the deflected light changes wavelength and amplitude. This so-called Raman effect is a foundational principle in the field of optics that enables any underwater network cable. A trip across the Mediterranean also prompted him to ask why the sea is blue, when water itself is clear? Thanks to C.V. Raman, we now know that the sea isn’t simply reflecting the sky, but because the water itself causes blue light to scatter.
With Blue and Raman, we now have 18 investments in subsea cables around the world, including Google-funded cables like Curie, Dunant, Equiano, Firmina and Grace Hopper, and consortium cables like Echo, JGA, INDIGO and Havfrue. You can learn more about Google Cloud’s network and infrastructure here.
Learning Should be Your Resolution for 2022: Register for Google Cloud Skills Boost
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Start your 2022 New Year’s resolutions by learning at no cost how to use Google Cloud with the following training opportunities:
30 day access to Google Cloud Skills Boost
Register by January 31, 2022 and claim 30 days free access to Google Cloud Skills Boost to complete the Getting Started with Google Cloud learning path.
Google Cloud Skills Boost is the definitive destination for skills development where you can personalize learning paths, track progress, and validate your newly-earned expertise with skill badges.
The Getting Started with Google Cloud learning path will give you the opportunity to earn three skill badges after you complete hands-on labs and courses designed for aspiring cloud engineers and architects. It covers the fundamentals of Google Cloud including core infrastructure, big data and ML, writing gcloud commands, using Cloud Shell, deploying virtual machines, and running containerized applications on GKE.
Cloud OnBoard: half day training on getting started with Google Cloud fundamentals
Attend the Getting Started Cloud OnBoard on January 20 for a comprehensive Google Cloud orientation. Google Cloud experts will show you how to execute your compute, available storage options, how to secure your data, and available Google Cloud managed services.
Cloud Study Jam: expert-guided hands-on lab
Google Cloud experts will walk you through a hands-on lab included in Google Cloud Skill Boost’s Getting Started with Google Cloud learning path when you join our Cloud Study Jam on January 27. Google Cloud experts will also answer questions live via chat during this event.
APAC’s Retail Digital Pulse by Google Cloud and IDC Retail Index
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In the post COVID-19 pandemic world, some retail businesses have aced digital transformation while others are still lagging behind. The Google Cloud commissioned IDC Retail Insights analyzed over 1, 108 retailers across seven nations in the Asia Pacific region and across eight different segments (online, drugstores, speciality shops, convenience stores, department stores, restaurants, supermarkets and hypermarkets/big box stores) to develop Google Cloud Retail Digital Index. The digital maturity was reviewed in five dimensions that define the digital pulse like strategy, people, data, technology and process.
Apart from empowering retail brands to live up to customer expectations, technology is the backbone to back-office operations and still ranks low in the digital pulse. Download the Google-ODC InfoBrief to catch up on the latest, detailed insights on Asia Pacific’s Retail Digital Index along with essential guidance on driving digital transformation, use cases and more!
IT Team Figures Out Easiest Way to Build Data Pipelines and Create ML Models
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Building a strong brand in today’s hyper-competitive business environment takes vision. It also requires a flexible, easily managed approach to digital asset management (DAM), so marketing professionals and other stakeholders can easily share, store, track, and manipulate assets to build the brand.
Many of today’s leading companies, including JetBlue, Slack, TripAdvisor, Lyft, and HealthONE, rely on Brandfolder to deliver consistent, organized, and efficient brand experiences. Brandfolder provides an easy-to-use platform that can scale across an entire company with little end-user training, empowering customers to distribute digital assets wherever they are needed. Customers also gain much greater insight into how those assets are used, and how to use them more effectively in marketing campaigns and brand messaging.
“Google Cloud made it easy to build an ML platform to quickly iterate through different brand intelligence use cases and release data-driven product features into the Brandfolder platform.”
—Ajay Rajasekharan, Head of Data Science, Brandfolder
Brandfolder is constantly advancing its development efforts to introduce new data-driven features without complicating the user experience. Big data, artificial intelligence (AI), and machine learning (ML) are key to meeting customers’ unique business needs, and essential for Brandfolder to compete in the fast-moving DAM industry. To enhance these capabilities, Brandfolder sought a public cloud provider that could help it scale its data pipeline cost effectively while providing access to advanced AI technologies.
After graduating from the Techstars startup accelerator program in 2013, Brandfolder tried two other cloud providers before standardizing on Google Cloud Platform (GCP).
“We saw a difference with Google Cloud from the very beginning because the interactions felt like a strategic relationship,” says Jim Hanifen, Head of Product at Brandfolder. “Google gave us startup credits and a lot of face-to-face support, which we hadn’t experienced with other cloud providers. We decided to move our entire infrastructure to Google Cloud Platform.”
Building an ML platform for brand intelligence
After performing an initial lift-and-shift migration of virtual machines (VMs) onto Compute Engine, Brandfolder built an ML platform using GCP managed services to seamlessly deliver its data products. The platform leverages Cloud SQL, Cloud Storage as the data lake, Cloud Dataproc for cloud-native Apache Spark computing clusters, Cloud Composer as the batch job scheduler, Cloud Pub/Sub as the backbone data pipeline, Container Registry to store Docker images, and Google Kubernetes Engine (GKE) as the application orchestrator. Cloud Dataflow brings data into the data lake and into BigQuery for analysis.
“Google Cloud made it easy to build an ML platform to quickly iterate through different brand intelligence use cases and release data-driven product features into the Brandfolder platform,” says Ajay Rajasekharan, Head of Data Science at Brandfolder, who describes the architecture in a detailed blog. “We simply ingest raw application and event data on one end and output an ML service on the other.”
“Moving to Google Cloud Platform allows us to complete more sophisticated data analysis and ML models much faster, and at a much lower cost. We can create brand-specific ML models 12x faster and get them into production quickly to address our customers’ unique business needs.”
—Brett Nekolny, Head of Engineering, Brandfolder
For many general use cases, Brandfolder does not need to build custom ML models, and instead relies on pre-trained API models from GCP. For example, it uses Vision API and Video Intelligence API to auto-tag creative assets on import to enable fast, intuitive searches across images and videos. When more product- and brand-specific modeling is required to address unique customer use cases, Brandfolder builds and trains custom ML models using its GCP pipeline or Cloud AutoML, a suite of products built on Google transfer learning and neural architecture search technology. For example, if a Brandfolder customer makes different types of grills, Brandfolder can use AutoML Vision to train a model to recognize the different grills.
“Moving to Google Cloud Platform allows us to complete more sophisticated data analysis and ML models much faster, and at a much lower cost,” explains Brett Nekolny, Head of Engineering at Brandfolder. “We can create brand-specific ML models 12x faster and get them into production quickly to address our customers’ unique business needs.”
Industry-leading security and performance
Google Cloud’s security model helps Brandfolder give existing and prospective customers peace of mind that their data will be protected. Cloud Identity & Access Management (Cloud IAM) provides enterprise-grade access control, while Cloud Identity-Aware Proxy (Cloud IAP) enables remote users to work more securely without the hassles of a VPN client. GCP also isolates cloud resources into projects, making it easy to assign permissions and keep data and VMs organized and segregated.
“With Google Cloud, everything begins and ends with security, which makes things very easy for us,” says Jim. “If we’re under a security review, we can submit a Google security white paper. If a potential customer has security concerns, we tell them we are hosted on GCP, and those concerns go away.”
To give customers even better application performance for accessing their brand assets, Brandfolder uses Cloud Memorystore, an in-memory data store service for Redis, to cache data and provide sub-millisecond data access for production applications.
“It was much easier for us to use Cloud Memorystore versus running Redis on our compute instances,” says Brett. “The high availability, replication across zones, and automatic failover with no data loss are big for us.”
Global private network interconnects between Google Cloud and the Fastly content delivery network (CDN) dramatically reduce latency, allowing Brandfolder’s customers to deliver and update even very large creative assets quickly around the world.
“What’s beautiful about the relationship between Google and Fastly is that if one of our customers uploads a new version of an asset, we can propagate that out to Fastly, and the new version will automatically show up in all the places where it’s referenced,” says Brett.
“The ability to quickly solve problems with AI has a substantial impact on our revenue, and that’s more apparent every quarter. Few of our competitors are doing product- or brand-specific modeling because it takes a lot of time and resources. We overcame those hurdles with Google Cloud.”
—Jim Hanifen, Head of Product, Brandfolder
Improving employee and customer productivity
Brandfolder also uses Google solutions for real-time collaboration and productivity, using G Suite to connect employees with intuitive, cloud-based apps. Teams use Gmail, Calendar, Docs, Drive, Sheets, Slides, and Hangouts Meet every day to move the business forward. Many of Brandfolder’s customers are also G Suite users, and Brandfolder offers a plug-in that allows them to view their creative assets inside of Docs and pull images in as needed. Customers can also log into Brandfolder with their G Suite credentials, making the solution even easier to use.
“We’ve been using G Suite since the beginning, and it’s helped us collaborate efficiently to build a successful, growing company,” says Jim. “Our teams expect to have that kind of close collaboration, and everyone here enjoys the G Suite experience.”
Driving 99 percent annual business growth
With automated tagging and other innovative AI-based features, Brandfolder is helping customers locate and distribute assets faster. As a result, Brandfolder is building customer loyalty and increasing sales, growing its business by 99 percent year-over-year. Since moving to GCP, Brandfolder has been able to scale its analytics and data pipeline 50x without a corresponding increase in costs and has not had to expand its development team.
“The ability to quickly solve problems with AI has a substantial impact on our revenue, and that’s more apparent every quarter,” says Jim. “Few of our competitors are doing product- or brand-specific modeling because it takes a lot of time and resources. We overcame those hurdles with Google Cloud.”
Macy’s Uses Google Cloud to Streamline Retail Operations
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As retailers strive to meet the growing expectations of shoppers, they are turning to Google Cloud to transform their businesses and tackle opportunities in an increasingly challenging industry. From optimizing inventory management to increasing collaboration between employees across locations and roles, to helping build omnichannel experiences for their customers, we are working together with retailers to help make the shopping experience as seamless and personalized as possible.
A standout Google Cloud customer is Macy’s, one of the world’s largest retailers. Founded in 1858, Macy’s operates approximately 680 Macy’s and Bloomingdale’s, and 190 specialty stores including Bloomingdale’s The Outlet, Bluemercury and Macy’s Backstage. And through macys.com, bloomingdales.com, and bluemercury.com, it also serves millions of customers across more than 100 countries.
By moving its infrastructure to the cloud, and taking advantage of Google Cloud data warehousing and analytics solutions, Macy’s is streamlining retail operational functions across its network.
With the opening of its new approximately 675,000 square-foot distribution center in Columbus, Ohio, Macy’s is leveraging the scalability of Google Cloud to ensure that merchandise is accurately and efficiently received, sorted, ticketed, picked, packed and shipped from the distribution center to the stores—even during peak retail seasons like back to school and the holidays.
“Powered by software developed at Macy’s technology, this new distribution center is a fantastic first step in our cloud journey. Working with Google Cloud allows us to be more nimble, efficient and flexible in how we utilize our warehouses,”
Naveen Krishna, CTO, Macy’s
Leveraging Google Cloud’s data management and analytics solutions, Macy’s new warehouse management system will initially service 200+ Macy’s Backstage off-price stores at launch. Macy’s will begin rolling out this software solution to additional distribution centers that service its nationwide fleet of Macy’s and Bloomingdale’s department stores, as well as Macys.com and Bloomingdales.com direct-to-customer orders.
Our continued work with Macy’s reflects their investment in technology to improve digital and mobile experiences, site stability, store technology, fulfillment, and logistics, and integrate its front line and back office to reinvent retail. I look forward to deepening our partnership with Naveen and his team to help them achieve these goals.
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