Business Need :

Our client is an automobile marketing company based in the US. They receive vast amounts of data daily from various vendors, relating to vehicle sales and service. They required a way to process this data and apply a variety of business rules to generate meaningful insights. Initially, they received data from a couple of vendors, but expected this to grow rapidly. Thus, they needed a solution that could not only process their current data but also cater to their future data processing needs. The transformed data is essential for the client's email and physical mail campaigns, for both B2B and B2C marketing promotions. Furthermore, internal business users require reports to design content for lead generation and marketing promotions.

Solution :

• Set up two on premise server machines which will work as our FTP server for different vendors. R sync is setup between those machines and data is always read from one specific machine. As soon files arrives on FTP server, it is being validated and moved to a specific location in HDFS.

• Our input data arrives in different formats such as csv, json, xml etc. All these input files are transformed to parquet.

• These parquet files acts as input to our Spark job which runs everyday at a specific time and applies all the transformation to input data.

• We also use sqoop to get configurations and business rules data from RDBMS.

• After, all the processing has been done, output data is written back to HDFS.

• Transformed data us being used by Sendgrid and Tableau for various reporting purposes.

Benefits :

• Better tracking of performance of marketing campaigns across different channels (website, social media, email, etc.)

• Analyze website traffic and user behavior to identify potential customers who are most likely to convert into paying customers

• Use customer data and behavior to personalize marketing messages and landing pages for increased engagement and conversion rates.

• Track effectiveness of email campaigns and other lead nurturing tactics to improve conversion rates and shorten sales cycles.

Data-Driven Marketing in the Automobile Industry with Spark and Hadoop

Introduction

The surge of digital transformation has led to an explosion of data, particularly in industries like automobile marketing, where understanding consumer behavior is vital for success. An automobile marketing company in the US faced the challenge of processing vast, multi-format data streams from various vendors to drive insights for targeted marketing campaigns. With the anticipation of data sources proliferating, they needed a robust, scalable solution to harness this information for both B2B and B2C marketing strategies effectively.

Business Challenge

The client's main hurdles were multi-dimensional:

• Volume and Variety: Managing and processing large volumes of data in various formats such as CSV, JSON, and XML.

• Real-Time Processing: Immediate processing of data as it arrives to facilitate timely marketing campaigns.

• Scalability: The solution had to handle the current data flow and scale up as the number of data sources grew.

• Insight Generation: Transforming raw data into actionable insights for email and physical mail campaigns was crucial.

• Reporting: Internal business users needed access to reports to design content for lead generation and marketing promotions.

Solution Overview

To meet these challenges, a comprehensive data processing solution was architected with the following components:

1. On-Premise FTP Servers

Two on-premise server machines were set up as FTP servers to receive data from different vendors. Rsync was used to synchronize the servers, ensuring data availability and consistency.

2. Data Transformation to Parquet

Incoming data in diverse formats was standardized by transforming it into Parquet files, which offer efficient compression and enhanced query performance.

3. Spark Processing

A scheduled Spark job was established to run daily, applying necessary transformations to the input data according to predefined business rules.

4. RDBMS Integration with Sqoop

A scheduled Spark job was established to run daily, applying necessary transformations to the input data according to predefined business rules.

5. Integration with SendGrid and Tableau

A scheduled Spark job was established to run daily, applying necessary transformations to the input data according to predefined business rules.

Key Benefits

This robust solution enabled the client to reap several benefits:

• Marketing Performance Tracking: Enhanced ability to track and measure the performance of marketing campaigns across various channels, leading to more effective allocation of marketing resources.

• Behavioral Analysis for Conversion: Insights into website traffic and user behavior were used to pinpoint potential customers, significantly boosting conversion potential.

• Personalized Marketing: Leveraging customer data to tailor marketing messages resulted in higher engagement and conversion rates.

• Email Campaign Optimization: Detailed tracking of email campaigns informed strategies to improve conversion rates and shorten the sales cycle.

Conclusion

The deployment of an analytical platform leveraging Apache Spark and HDFS transformed the client's ability to process and analyze data for marketing purposes. The scalable architecture catered to immediate needs and was well-equipped to handle future expansion. As a result, the client experienced improved marketing campaign performance, personalized customer engagement, and ultimately, a notable increase in conversion rates. This case stands as a testament to the power of data analytics in refining marketing strategies in the highly competitive automobile industry.