Break Into New Retail Markets With the Power of Automated Machine Learning
When the retail division of one of the world’s leading manufacturing companies wanted to win over another one billion consumers by improving its sales operations in a key emerging market—it realized that traditional analytical tools like Power BI and Excel didn’t cut it.
With more than 30 brands—and an immense amount of data—it was already quite challenging for their retail sales operations team to keep up with all of the company’s strategic initiatives for 2023. They needed some breakthroughs—particularly in the Turkish market—via innovation and process optimization.
But, Breaking in Is Hard To Do
The manufacturer wanted to leverage their own substantial investments in data acquisition and overcome the drag that the traditional analytical approach was having on the team—leading to internal tension in cross-department communication, increasing operational burden, and even possible employee churn.
They finally decided that machine learning was the solution and tapped Aigoritma to build a business case for the digital transformation of their Retail division in Turkey. Aigoritma offered to work on a business case for their Data & CRM Manager—who was driving the Digital Transformation initiative.
Overcoming the Endlessly Emerging Challenges in the Retail Industry
After researching their as-is process, reviewing all the context/data provided, and creating a business case, Aigoritma proved that—by using ML Studio End-to-End AI platform—the manufacturer’s Data Team would 10x their KPIs at a fraction of the time and cost.
By building predictive models in just a few minutes—instead of weeks—their sales operations team was able to learn from their own data at a faster pace. This empowered the company to:
- Attract new customers
- Deepen existing relationships
- Improve customer satisfaction
- Never miss out on new sales opportunities by smoothing out operational excellence
This strategy not only helped them break into Turkey—it aligned with the global company strategy for the entire year and the foreseeable future.
Identify Retail Patterns, Make Decisions, and Generate Predictions Based on Historical Data
So, how exactly does machine learning help retailers? Machine learning models can forecast efficient and scalable sales predictions by training the data drawn from sales systems, company databases, local archive files, and external variables.
Aigoritma also offers solutions on pricing suggestions by conducting widespread and detailed market research due to its access to a broader database than traditional manual recording of sales and market prices.
Aigoritma also understands that not everyone has a background in coding or programming. That's why we've created a user-friendly drag & drop canvas for both technical and non-technical people, enabling you to perform complex data operations with ease.
ML Studio democratizes AI by making it accessible for your organization to solve real-world retail problems—such as sales prediction and price optimization—with a robust and ready-to-use End-to-End AI platform that doesn’t go off budget.
Take control of your data without needing to learn complex programming languages or syntax—and expand your retail endeavors with automated machine learning.
Get in touch for a personal demo.
