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How Bluecore and Google Cloud SQL Drive Online Shopping?

Note: The world situation in 2020 has boosted online shopping habits, martech provider Bluecore has been at the forefront. One of Google's Cloud Technology Partners of the Year in Retail, Bluecore powers a marketing platform for more than 400 retail brands, combining data and predictive intelligence for targeted campaigns. Here, we look at how Google Cloud SQL managed services free up Bluecore's valuable time and energy so they can continue to innovate. Let's see how Bluecore and Google Cloud promote online shopping?

At Bluecore, we help large-scale retail brands convert their shoppers into lifelong customers. We have developed a fully automated, technology-enabled multi-channel personalized marketing platform machine learning and artificial intelligence to power campaigns through predictive data models. Our suite of email, website, advertising and data solutions are at the heart of everything we do, helping our retailers deliver personalized experiences to their customers. their goods.

Because our market of retail customers needed real-time data access and processing in their user interfaces — without downtime or performance degradation — we needed a solution new database. Our engineering team has spent time upgrading our own relational database management, which means we'll need less time building marketing products. We realized we needed a fully managed service, which fit within our existing architecture so we could focus on what we do best. Google Cloud SQL can do that.

How Bluecore and Google Cloud SQL promote online shopping (1)

Bluecore and Google Cloud personalize the online shopping experience

Our retail partners can create highly accurate campaigns within the Bluecore app by tailoring their marketing messages and campaigns to their target customers based on factors such as traffic source, time, and location. space on page, scroll bar depth, browsed products, and cart status. Based on those rules, our product intelligently decides which information should be shown to which customers. Highly personalized campaigns can be created easily with drag-and-drop features and widgets like campaign-specific images or emails.

Our request for the database was full campaign creation functionality using metadata, including campaign type (pop-up, full-page, etc.), time-based campaigns (Christmas, Black Friday, etc.) and targeted customer segments. This Metadata campaign needs to be connected and available in real-time within the user interface itself without slowing down the retail partner's site. For example, a partner's customers who are highly engaged with discounts may be shown highly discounted products while browsing products.

Once the campaign is live, we can measure who participated in the campaign, what products they browsed, and whether they made a purchase. Those analytics are available to e-commerce houses and our own data science team, so we can measure which campaigns are most effective. We can then use that information to optimize our features and the future campaigns of retail brands.

Using the same underlying data set and feed, we can tie email functionality to the website. For example, if a customer hasn't opened an email in a certain amount of time and they visit a website, we can show them a campaign. Or if they've read a brand's email, we can show them another offer. Email and website channels can be used independently or together, depending on the marketer.

Need a real-time solution

The first use case with Cloud SQL is about storing campaign information. We have a multi-tenant architecture. Our raw data like user activity (clicks, views) is stored in raw tables in BigQuery. At first, our campaign information was stored in a Data Warehouse, which can scale easily, but we discovered very quickly that our data was better suited to a relational model much and we started using Cloud SQL..

If a marketing partner makes a change to one campaign, it can affect many other campaigns, so we needed a solution that could pull and apply that data immediately without breaking the bank. reduced performance or downtime. This is an important feature for Bluecore.

How Bluecore and Google Cloud SQL promote online shopping (2)

Choose Google Cloud SQL with Bluecore to optimize online shopping

When evaluating a relational database, we looked at a number of options and even initially tried setting up our own MySQL using Google Kubernetes Engine (GKE). But we quickly realized that switching to our existing partner, Google, could deliver the results we needed while freeing up time for our engineers. Google Cloud SQL provides a fully managed database service for high availability while handling common time-consuming tasks like backups, maintenance, and replication. With Google ensuring a reliable, secure, and scalable database, our engineers can focus on what we do best, enhancing the performance and features of the platform our marketing.

Specifically, one feature we have developed is to allow our retail brand customers the ability to deliver custom messaging in real time. For example, we might send a personalized message offering a coupon code in exchange for a customer's email subscription to a customer who has viewed five web pages but hasn't added anything to their cart. .

Cloud SQL pairs well with the Google Cloud suite of products

In addition to BigQuery and Cloud SQL services, we rely on many Google managed services across our infrastructure. Events are being sent from websites to Google App Engine, from there they are queued into Pub/Sub and processed by Kubernetes/GKE. Our user interface is also hosted on App Engine. Interfacing with Cloud SQL from both App Engine and GKE is extremely easy. Google continues to work with us to realize the full capabilities of the services we use and determine which services can best advance our growth plans.

To learn more about their marketing technology platform, visit Bluecore. Are you ready to get started with a fully managed relational database solution? Explore Cloud SQL now.

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