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Nick Elias

Jeenga Delivers Cross-Channel One-to-One Customer Experiences with DataStax Enterprise

By Nick EliasSeptember 29, 2015

This post is one in a series of quick-hit interviews with companies using Apache Cassandra™ and/or DataStax Enterprise (DSE) for key parts of their business.  For this interview, we talked with Luiz Filipe Couto from Jeenga.

DataStax: Tell us about Jeenga and your role there?

Luiz: I’m the founder and CEO of Jeenga. Jeenga is a Real-time Customer Journey Platform that combines an unique B2C CRM and Marketing Automation engines to understand and execute one-to-one marketing across site, app and offline channels.

DataStax: What kind of data will people share in the exchange and how do others access it? What sets you apart from other solutions?

Luiz: Our solution captures customer and behavior data across different sources and channels in real time, including historical purchase, marketing campaign and customer support data.

Based on this information we build the customer timeline that maps all the customer lifecycle, including LTV (Life Time Value), ROI (Return On Investment)  and risk of churn. What differs Jeenga from other vendors is our focus on Customer Data and B2C CRM strategy. Another particularity is our “Actionable” concept, we do not send emails, text or push message, we delegate this job to best companies in the globe like SendGrid, Mandrill, Twilio and others. This way, we can put all the team effort, time and money on the data.

DataStax: Did you use a different technology before Apache Cassandra™?

Luiz: We researched all the NoSQL solutions for a few months before we decided to use Apache Cassandra™ and DataStax.

Apache Cassandra™ is the best fit for us because we are building a global company based on customer data, multi-datacenter and multi-region that can handle billions of customer interactions across different touch points and channels.

DataStax: Why did you pick Apache Cassandra™ and DataStax Enterprise? What kind of data is stored there?

Luiz: Compared with others solutions, Apache Cassandra™ was designed to be multi-region, multi-datacenter, with no point of failure, multi-master and very very fast in both writes and reads.

But we also needed the commercial support around our choice of Apache Cassandra™ and that’s how DataStax is a great resource ans support for us. Furthermore, DataStax EcoSystem and Tools have native Apache Solr™ and Apache Spark™ integration with Apache Cassandra™, and these are unique features for those who would like to work with big data and NoSQL database.

The DataStax customers list just confirmed our choice. Plus we learned a lot from DataStax’s documentation.

DataStax: What features from the DataStax Enterprise stack are you using at the moment? What business use case do they fulfill?

Luiz: Apache Cassandra™ handles all the writes and some reads in our platform. We are using DSE Search with Apache Solr™ for reads and more complex queries and Apache Spark™ for our Real-time Analytics and DashBoard. Our use case is B2C CRM and Marketing Automation platform.

DataStax: What advice would you give to other startups that are thinking about using Apache Cassandra™ for the first time in their solutions?

Luiz: Before we founded Jeenga, our team started with the database and backend solution that could support our platform, operations and or goal to have thousands of B2B customers with their thousands or millions of clients.

Additionally we don’t like to be dependent on PaaS Providers, since they have their own big data, search solutions. It was an easy option for us but on the other hand you will get stuck and obligated to follow the future rules, changes, policies and so one.

I would highly recommend to follow the Apache Cassandra™ and DataStax documentation, recommendations and best practices, including: OS and Apache Cassandra™ Tuning, VM types and configurations, especially the data model and to understand how Apache Cassandra™ works, for us this was the “secret sauce”.



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