Summary 

• In a world of information overload, retailers need access to the best insights quickly to make accurate business decisions.  
• Using AI summary within a retail intelligence platform, retailers can access the main takeaways from data. 
• This process saves retailers ample time, allowing them to focus on taking action. 
• Uncover how AI summaries can impact your retail decision-making now. 

Introduction 

Retailers have been drowning in data for as long as data has been available. 

With the rise in access to data, there has been a secondary rise in tools automating the process of analyzing said data to provide insights. 

This information is crucial to understanding your business’s performance, but now there is a new challenge… Retailers are drowning in insights.  

Better, Quicker Retail Decisions With Advanced AI

Retail moves fast, and if you don’t make decisions quickly, your business will fall behind. However, speed is not the only factor at play — you also must be accurate. 

Data overload and insight fatigue can prohibit retailers from identifying the most important information upfront and achieving tasks quickly.   

Imagine confidently walking into your Monday morning meeting without having to spend hours digging through data and insights ahead of time. 

What Are AI-Generated Summaries?

AI summaries within a retail intelligence platform are high-level synopses and key takeaways of the data in a retail dashboard. AI generates the most pertinent insights so users can quickly get answers to their most relevant questions, spending less time hunting down insights and more time taking action. 

The data science component of this functionality requires leveraging generative LLM (large language model) and creating a process that can automatically take the data behind a dashboard and convert it into this summary statement.

The end product highlights important points, gives supporting data as evidence, and refrains from making opinionated comments.

How Can These AI-Based Summaries Optimize Your Day-to-Day?

These LLMs allow you to: 

Simplify and Summarize Data:

• Generate concise summaries of complex data, highlighting the most critical insights.
• Access visual summaries, such as charts and graphs, making data more digestible.

Prioritize Key Metrics:

• Monitor metrics with ease. 
• Focus on the most critical KPIs that align with business objectives and spend your time on strategy rather than analysis. 

Using a retail intelligence dashboard with AI summaries gives you immediate access to the main takeaways from market data, enabling you to get insights as quickly as possible. 

Within this function, you and your team can set up monitoring and alerts to inform you about crucial insights into pre-season strategy, pre-season planning, in-season planning, and in-season trade adjustments.   

Use Case – Black Friday

With Black Friday 2024 preparations in full swing, an AI summary can help you quickly get up to speed on what competitors are doing and what has historically performed well vs what hasn’t. 

Here’s how you can use an AI summary to prepare for Black Friday:

1. Compare Retailers or Categories: Utilize the comparison function to look at specific retailers or categories and access immediate insights. This information can help you identify opportunities to target specific customer segments or product categories.
2. Inform Your Marketing Strategy: Use the insights from the AI summary to inform your marketing strategy for Black Friday. This information can help you create targeted campaigns and reach the right customers with the right message.

Conclusion

Utilizing an LLM for AI summaries can significantly improve your workflow. EDITED’s AI Summary within the myEDITED™ dashboard is designed to provide customers with thorough, yet succinct, takeaways from the underlying data that they can then use to guide better business decisions.

Want to learn more about the future of prompt engineering and where our LLMs are heading? Check out this article featuring EDITED here.