How Data powers a $71.3 billion business To Make Better Decisions

For one of the biggest home improvement retailers in the U.S. and Canada, Lowe’s, data is the biggest business enabler.

Big Data Engineering Team at Lowe’s India

Imagine the amount of data we generate: We have 18 million customers walking in to our stores each week. Customers who work on home improvement projects as either ‘do-it-yourself’ or ‘do-it-for-me’. Their shopping experience with Lowe’s is through online channels or through the mobile apps on Android and iOS. A big part of our professional “pro” customers also shops online through similar channels. Apart from this, our internal store associate apps for product info, orders and inventory planning generate data from 2200+ stores!

Are you getting the picture of the scale of data?

It translates to a whopping ~500 GBs of click event data being generated every day!

So how does Lowe’s use this mammoth amount of data to its advantage? That’s a task for the big data engineering team!

The big data engineering team processes multiple channels of raw click event data, every hour in our Petabytes scale Hadoop infrastructure and build insights that help in understanding customer needs and behaviors. This multistage asynchronous data pipeline is built on Apache Crunch, Apache Spark, Hive and Oozie to enable massive data processing and it is sustainable, auto-scaled and lazy monitored.

How does this create an impact?

Various teams such as digital analytics, online category merchants, and data sciences utilize this information to enable unique and unified shopping experience across channels.

• The online merchandising team analyzes the performance of a category, product, brand or a vendor and optimizes assortments across the online business.
• Analytics and Insights team analyzes the data to measure and optimize both commercial metrics such as revenue, orders, conversion rate, revenue per visit, per click, etc. and non-commercial metrics on visitor pathing and navigation, geographical visitor analysis, product views, dwell time, sessionization, exit and bounce rate, and in minimizing page errors, app crashes, etc.
• This data helps in optimizing online search relevance and recommendation effectiveness which leads to better conversions.
• The digital marketing teams use this data for measurement and conversion of digital ads – clicks and impressions.
• Click data from associate apps helps to improve the experience of store associates and empower them to serve customers better.

To that effect, the foundation for how various teams use data to derive meaningful insights and enable our businesses is built on data infrastructure developed by the big data engineering team. The tools, technologies, processes, and human intelligence all work in perfect symphony to make the data speak!

Here, the big data engineering team contributes to:
• Harnessing the power of massively parallel data processing frameworks to deal with large volumes and complexity of data
• Building a data lake that represents the data created by all business processes and systems for integrated analytics and data mining
• Institutionalizing advanced analytics in operational processes by embedding data intelligence in partnership with data science and analytics teams

Data is the most critical asset to an organization. The data engineering team is proud to help Lowe’s scale to make data-informed business decisions using cutting edge big data technologies, to ensure that the customer who shops with us has the best shopping experience while at any Lowe’s store!

If you want to work in an environment where what you do matters to a $71.3 billion organization, visit our careers page to know more about job openings in the big data engineering team at Lowe’s India.