Achieving Greater Insights into Sales Performance with AWS Redshift in Retail Industry

Achieving Greater Insights into Sales Performance with AWS Redshift in Retail Industry

Regardless of whether you are a small local business or a national corporation, tracking your retail sales is incredibly important. The valuable activity lets you identify potential sales patterns, close more deals in much less time, and make better and informed sales forecasts. However, it is seen that most retail sales managers struggle to keep a tap on their sales performance. This, in turn, impacts their retail productivity. 

 

The amount of data gathered by retail businesses keeps growing at an alarmingly high rate. Sales managers are unable to ensure the adequate utilization and analysis of data, contributing to the issue of data silos. Besides, it results in the most common challenges for retailers: a lack of consistency in the implementation of the sales process, limited line-of-sight for managers, and reps spending too much time not selling. 

 

It is crucial to find a technology solution that can effectively handle all the generated data and use it to unlock meaningful insights into sales performance for the retail industry. This is where AWS Redshift comes into the picture. In today’s blog, we will understand how using Amazon Redshift can help to significantly improve sales performance and tracking. 

 

How AWS Redshift Can Improve Sales Performance in the Retail Industry

Amazon Redshift or AWS Redshift is a fully-managed data warehouse solution from Amazon. The efficient solution lets you manage enormous volumes of data and effectively process both structured and unstructured data on an exabytes scale. This facilitates retail organizations to utilize their data and gain new insights to streamline processes such as sales tracking and performance. 

 

Below we look at the top features and capabilities of Amazon Redshift that can benefit retailers:

  • It allows for Partner Console integration

Amazon Redshift integrates with Partner solutions in the AWS Redshift console to accelerate the process of data onboarding and using it to generate valuable insights. This means that retailers can collect data from varied sources such as Facebook Ads, Google Analytics, Slack, etc. into the Redshift data warehouse and analyze them to produce actionable insights into the sales performance.

 

  • It allows for data sharing

Redshift allows its users to turn single clusters into multi-cluster deployments and promote efficient data sharing. With this, the retailers can gain instant and quick access to data across the Redshift clusters without the need to move or copy any data. This also ensures live access to the most updated information. 

 

  • It provides Redshift ML

Amazon Redshift ML is an excellent functionality that enables data analysts and BI professionals to create and use Amazon SageMaker models using SQL. Thus, retailers can leverage Redshift ML to use SQL statements to create Amazon SageMaker models on the data present in the AWS Redshift warehouse and make notable sales predictions.

 

Implementing AWS Redshift in Your Retail Business

Amazon Redshift is a fully-managed and scalable data warehouse that lets you analyze all your retail data and achieve performance insights at scale with predictable costs. The basic tier version of the platform is suitable for beginners to set up, query, and play with the fully-functional data warehouse on Redshift for free. One of the best aspects of implementing AWS Redshift is that it is highly scalable. You can go from gigabyte to petabyte scale without any hassle at all. 

 

To migrate your data warehouse to Amazon Redshift, you must consider several factors such as the total size of the warehouse, data transformation complexity, data change rate, etc. Additionally, your choice of ETL tools can also impact the speed and difficulty level of the migration process. Keep these factors in mind to develop a suitable migration strategy and implement Amazon Redshift to improve sales performance and tracking. 

 

Case Study

Analysis of Legacy Customer Data for Russia’s Largest Retail Chain

In today’s data-driven world, retail companies can no longer solely rely on traditional sources of decision-making, such as sales history or executive instinct. However, striving to become more data-driven is sought with common challenges such as data accessibility issues, integration with legacy systems, and more. These were the challenges our client was facing. 

 

improve_sales_performance_aws_redshift

 

A thorough analysis of their operations and data management practices enabled us to uncover a massive amount of unstructured and unorganized data that was held in silos. This vital customer data was seldom leveraged to unlock business insights which hampered their decision-making process. 

 

The experts at Algoscale helped the client analyze their legacy customer data and derive meaningful insights on performance (sales, new customer acquisition, customer retention, etc.). We deployed effective data cleaning to clean and format all of the client’s fragmented data and structure it into a consistent format. This data was finally used to generate a range of reports, promote strategic decision-making, and facilitate business expansion.

 

The analysis also helped the client to determine the most feasible geographical location for new stores to be opened. This was based on data gathered about customer demands and competition. 

 

 

Conclusion

Data is growing in size and complexity faster than ever. But unfortunately, only a small fraction of this vital asset is being used for analysis. Traditional on-premise data warehouses that most retail businesses are using don’t scale for present-day big data analytics use cases. Also, these traditional data warehouses involve huge upfront payments to set up and operate. 

 

Leveraging AWS Redshift in retail, on the other hand, is the most viable option. AWS enables retailers to build a next-gen intelligence and insights engine that facilitates seamless sales data analysis and helps to improve sales performance. It can also help to improve IT efficiency, automate supply chains, augment store productivity, and drive ongoing innovation with technologies powered by ML. 

 

At Algoscale, we can help you modernize your retail data warehouse with AWS Redshift. With a proven track record, our specialists can support you through every stage of data warehouse implementation and use it to derive meaningful insights for your business. 

Recent Posts

Subscribe to Newsletter

Stay updated with the blogs by subscribing to the newsletter