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Dramatic Performance Improvements Enable More Retail Artificial Intelligence Analytics

Dramatic Performance Improvements Enable More Retail Artificial Intelligence Analytics

AI analytics

Leading provider of Artificial Intelligence-based decision platforms, solutions, and customer-centric insights achieves 3-10x performance, enhances management, and consolidates cloud and on-premises platforms onto a single, easy-to-manage Yellowbrick Data system.

Case Study Category
  • Retail Industry
  • Artificial Intelligence Analytics
Snapshot of Customer Benefits
  • 3 to 10x performance for faster insights
  • Consolidated cloud and on-premises platforms into a single system
  • Seamless adoption with standards-based technology
  • Enhanced management capabilities with detailed query visibility
  • Improved predictive insight through additional AI analytics
Overview of Retail Industry

The global retail industry is segmented into multiple categories, including:

  • Products (apparel, furniture, food and beverages, personal and household care, electronics and household appliances, and other products).
  • Distribution channel (department stores, online and ecommerce, department stores, convenience stores, supermarkets and hypermarkets, specialty stores, and other distribution channels).
  • Geography (North America, Europe, Asia-Pacific, Latin America, and Middle-East and Africa).

Deloitte points out that while the retail industry has experienced significant challenges over the last few years due to the pandemic, it has also yielded the opportunity for transformation that could help many retailers shift into a more stable and profitable position in the longer term. And one of the biggest drivers of growth and evolution is AI in the retail industry.

Artificial Intelligence Analytics & Its Importance

Among the biggest challenges that retailers face is that they have an excessive and overwhelming amount of data in their ecosystem. They must efficiently and effectively transform this into reliable and actionable intelligence that drives richer insights and faster decision-making. That is where artificial intelligence analytics enters the story and makes a game-changing difference.

In essence, artificial intelligence analytics is a collection of technologies that extra insights and patterns from massive sets of data. This helps organizations get a better understanding of what has happened in the past, what is happening now, and what is likely to happen in the future.

Transform Your Data Analytics with AI

The fundamental limitation of traditional software is that it requires continuous human input when, for example, a function needs to be modified or a process must be added. In all cases, a software engineer (or more practically a team of engineers) need to modify the code.   

Conversely, artificial intelligence analytics does not require constant human input and intervention. It uses machine learning (ML) algorithms to constantly learn and improve the capacity to identify, analyze, and visualize patterns. What more, AI data analytics is not limited to a single data source. It can gather data from multiple data sources (e.g. inventory data, pricing data, customer trends, product popularity, e-commerce data, etc.) to generate penetrating insights that go beyond an analysis of quantitative data, and deliver qualitative insights into the past, present, and future.  

AI (Artificial Intelligence) in the Retail Industry

Artificial intelligence in retail is not just altering the landscape: it is re-imagining it in a variety of powerful ways. For example, retailers around the world are leveraging AI to:

  • Help brick-and-mortar customers skip checkout lines.
  • Enhance security and loss prevention.
  • Improve virtual shopper profitability, customer experience, and satisfaction.
  • Improve inventory management.
  • Empower customers to “try on” virtual outfits from their home.

Overall, the AI market in the retail sector is projected to grow $29.57 billion USD between 2021-2026, which represents a CAGR of 35.69 percent.  

The Case Study
artificial intelligence analytics

Symphony RetailAI is the leading global provider of Artificial Intelligence-enabled decision platforms, solutions and customer-centric insights that drive validated growth for retailers and CPG (Consumer Packaged Goods) manufacturers, from customer intelligence to personalized marketing, merchandising and category management, to supply chain and retail operations.

Nigel Pratt, SVP Technology described his team’s challenge: “We have a ton of data that comes from the retailers, including all transactional point of sale information as well as information about their promotions and pricing. We collect all that information and synthesize that down into actual insights a retailer or supplier can then use to understand their customer and provide understanding of their promotions, personalized marketing, pricing, and assortment.”

Challenges with Retail Artificial Intelligence Solutions

The existing Symphony RetailAI solution required managing data across multiple locations for cloud, data center, and on-premises platforms. Nigel said, “we were looking for a solution where we could reduce the number of platforms we had and provide a faster response time to user queries.”

Enter Yellowbrick Data to elevate Symphony RetailAI’s retail AI analytics solution, and deliver dramatic performance improvements.

The Simplicity of a Single System

Yellowbrick Data gave Nigel’s team a single solution to manage that consolidated their three platforms into a single system. Nigel told us: “We’ll be able to consolidate a number of different platforms onto the Yellowbrick Data system—a system that’s so small, the team couldn’t believe it had 150TB of storage.”

Symphony RetailAI

Figure 1: Yellowbrick Data consolidates multiple platforms into a single system.

Yellowbrick Data uses standards-based technologies, which made it easy for Nigel’s team to jump in and start using it immediately. Nigel told us: “Yellowbrick Data gave us very good support, but the system was easy to use to begin with because there was a lot of commonality with the systems we already had. We had six engineers touch the system and all of them found the system very easy to use.”

AIdata analytics

The Yellowbrick Data interface also gave Nigel’s team capabilities they did not have before: “the administration interface was very easy and informative for all of our users,” Nigel said. “We could see how the queries were forming and get insights into the execution plans that were being done on the system.”

AI in retail

Figure 2: Yellowbrick Data enables administrators to view and track query details.

3-10x Faster Performance

Yellowbrick Data dramatically improved the performance over their existing system, enabling Nigel’s team to enhance the customer experience and accelerate time to insight.  Nigel told us: “Our standard processes saw a 3x to 10x performance improvement, without any performance tuning—running them ‘as is.’” In contrast, Nigel said the eight to 10 other cloud and on-premises solutions his team tested delivered just “marginal improvements.”

A Growth Platform for the Future

In addition to accelerating customer queries, Nigel’s team plans to use the performance capabilities of Yellowbrick Data to foster new innovation. Nigel says: “We’ll be able to add more AI analytics onto the platform and turn our focus to providing more predictive insights into our data.”

A Clear Path Forward

The opportunities Yellowbrick Data creates for Symphony RetailAI excites Nigel, who states: “We’re expanding Yellowbrick Data out to multiple customers across the globe. We’re also trying to get other applications auto-running on Yellowbrick Data because we think we can consolidate even more solutions onto the Yellowbrick Data platform.”

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