Business Optimization with AI Reporting: Insights Based on a Real Project

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Olha Kanishcheva ML/NLP Engineer, Researcher

Data is the secret ingredient in the business success recipe, and 97% of decision-makers would only cook with it. By looking closely at data, you can find new ways to grow and manage risks.

But the more information we have, the harder it gets to keep up with it all. In fact, 70% of business leaders are so overwhelmed by collecting and understanding data that they would instead let machines make their decisions. 

While robots may not be ready to take on all business strategy tasks, the evolution of artificial intelligence offers an extensive set of tools that improves how we collect, process, and report data.

In 2024, intelligent reporting can be essential for unlocking higher business efficiency and wiser decisions. Let us dive into how AI reporting tools can improve data management and deliver insights from a real-world case.

AI Reporting Assistant for Retail: Real-Life Case Learnings

Let us start with our own experience in the retail sector. This industry is a huge fan of data, and some typical applications involve:

• gaining insights into shopper behavior,
• setting prices effectively,
• optimizing store layout,
• better managing a supply chain,
• demand forecasting,
• planning and analyzing marketing activities.

Numerous reports are generated every day, all relying on numbers. The sheer amount of data and the speed at which decisions must be made call for automation.

Project Background

Our client, a major North American retailer, needed faster reporting for quick decisions and ad-hoc information requests. Their analysts were spending too much time getting data ready for reports, so our engineers proposed to set up an intelligent assistant simplifying the process.

Ready-Made or Custom AI Solutions For Retail? Pros & Cons Read more

The CHI Software team handled the whole project, from the first discovery stage steps to the final solution rollout.

An Inside Look at Our AI-Powered Reporting and Analytics Solution

The product we crafted not only expedites the analysis process but also delivers precise data and trend insights in no time. Offered as a web app and a Slack chatbot, it simplifies data requests for all users. 

Managers can input a request like “Provide a comparison of electronics sales figures from Black Friday through Christmas Eve in Los Angeles branches,” and the bot instantly generates a detailed dashboard with comparative charts and critical metrics.

Here is a functionality breakdown of this innovative and intuitive AI analytics assistant:

1. Voice-to-data conversion: Analysts can message the chatbot to get updates on specific metrics, using everyday language just like they are talking to a human;
2. Natural language understanding: The chatbot translates the request into an SQL query and picks out key terms to ensure the data is pulled from the right databases;
3. Data visualization: After gathering the numbers, the tool employs Python to create visual displays, such as a web dashboard filled with charts and graphs, bringing the data to life.
4. Code optimization: To ensure Python code is efficient and error-free, we use advanced language models like GPT. They help polish the code to guarantee the dashboard is functional and well-designed.

This seamless flow from a question to visualization provides real-time data analysis and, with that, allows our client to make informed decisions very fast.

What AI features would YOU like to add to your business operations? Let's discuss it!

AI for Reporting: How Our Client Benefits From Innovations

The introduction of the new smart assistant brought several benefits:

• Boosted productivity: Managers and analysts are spending way less time making reports, which means they can make decisions much faster now;
• Improved accuracy: Using AI for analytics has made reports more precise, cutting down on human errors and leading to sharper business strategies;
• Simplified reporting: Requesting detailed reports with the chatbot interface is as simple as sending a quick message, which creates the most user-friendly workflow;
• Decision-making support: Managers armed with timely and accurate data visualization are better equipped to make strategic decisions that contribute to the company’s success.

How to use indoor positioning in retail and othere industries? Click here to find out

Top 6 AI Technologies that Take Your Reporting to the Next Level

Consider our case just a single illustration of what artificial intelligence can do  in reporting and analytics. Yet, the tech capabilities extend far beyond this, with AI ready to assist with various tasks that improve data management. As every company faces unique challenges, a set of tech tools can be tailored to meet individual needs.

Final Thoughts

Intelligent tech is reshaping business reporting at this very moment. From NLP to machine learning and interactive visuals to chatbots, AI turns data into insights and simplifies complex analysis. 

Imagine how close you are to informed business decisions with every step you make. Implementing AI reporting is a sure way to earn extra points for your business when the competition grows more fierce.

Your next move is to find the team that turns technologies into results. Gladly, you have just reached the right spot.

As an NLP consulting company, we at CHI Software are the AI experts who make things happen. With dozens of unique cases in our portfolio, we know how to help you out. And these are not just words. Do you want to discuss rough time & budget estimation?  Just leave your request, and let’s embark on this innovation journey together.

About the author

Olha Kanishcheva ML/NLP Engineer, Researcher

Olha boasts a decade-long journey in NLP, currently serving as a researcher at Jena University and a Consulting ML/NLP Engineer at CHI Software. Her expertise extends to various realms of NLP, including text summarization, named entity recognition, and keyword extraction. Olha's Ph.D. thesis explored knowledge representations and information retrieval in librarian systems.