AI & RPA Solutions For
Retail & Marketing
Adapt To Expectations Of The New Generation Of Shoppers
The millenials’ expectations keep growing. They want the retailer to know them as well as their close ones. They do not want to be overwhelmed with hundreds of mismatched products. They look for seamless shopping experience, personalized product recommendations, short wait times, and simplicity.
We can help you adapt to this new reality. Many of our engineers are young yet experienced talents, who are not only great developers but can help you build the whole process from the ground up – they are often part of the generation themselves.
Just A Portion Of Problems We Can Help You Solve
Product Recommendations
Leverage AI-based product recommendations to increase CCR, NPS, and increase the revenue per customer.
Demand Prediction & Management
Maintain products with respect to demand and understand the seasonal trends. Hence, avoid stock-outs.
Customer Service
Utilize AI to meet consumers’ growing demand to improve customer experience, lower employment costs, and decrease reliance on contact centers.
Enhance Your Sales
Create personalized messages and offers with machine learning. Retarget your customers, find new target groups, and fix the sales funnel.
Lawrence Burns
Partner
Baillie Gifford
“The Sigmoidal team demonstrated their deep knowledge in applying AI to assist investment analysis. Their solution provided us with additional signals and thus a further perspective to company analysis to aid decision-making.”
Jonas Lee
EVP & Partner
Verus Analytics
“Sigmoidal demonstrated a strong degree of proactivity, taking time to thoroughly understand the problem and continuously suggesting performance and usability enhancements.”
Other Case Studies In Retail & Marketing
Insights
Take The Next Step
Send us your inquiry or schedule a free consultation to:
See if our proprietary solutions can help you right away.
Build a roadmap, choose the right KPIs and deliverables.
Estimate the time and budget needed to automate your process.
