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Retail IT Consulting

Boost margin and customer experience with retail technology. Upturn builds demand forecasting, omnichannel platforms, and AI personalization for modern retailers.

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18%
Margin improvement
32%
Waste reduction
2.4×
Personalization conversion

Industry challenges

The problems Retail teams face

Inventory imbalance — too much and too little

Overstocks tie up capital while stockouts drive customers to competitors. Demand forecasting solves both.

Fragmented customer data

Online, in-store, and loyalty data in separate systems makes it impossible to understand or target customers effectively.

Disconnected e-commerce and in-store

Customers expect a seamless experience across channels — but most retailers operate them as independent silos.

Personalization at scale

Relevant recommendations dramatically increase conversion — but most retailers can't implement them without specialist ML.

Our capabilities

Services we deliver for Retail

Machine Learning

Predictive models for forecasting, scoring, and recommendations — built and maintained.

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Data Analytics & BI

Unify your data and turn it into dashboards and forecasts leaders actually use.

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Application Development

Web, mobile, and platform builds shipped iteratively with modern engineering practices.

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Gen AI, ML & Chatbots

Custom LLM copilots, RAG assistants, and ML models that automate decisions and delight customers.

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Business Process Automation

Map, streamline, and automate workflows to reclaim hours and cut error rates.

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Measured impact

Results we deliver for Retail

18%
Margin improvement
Demand forecasting and inventory optimization deliver significant margin gains.
32%
Waste reduction
Better demand signals reduce perishable waste and markdown depth.
2.4×
Personalization conversion lift
Recommendation engines increase conversion rates by more than double.
45%
Support ticket deflection
AI-assisted customer service handles nearly half of inbound queries automatically.

Featured case study

RetailAnalytics

Demand forecasting lifts gross margin by 18%

A 22-location specialty retailer was managing inventory across 3,400 SKUs using manual buying decisions informed by last year's sales. Seasonal peaks created chronic stockouts on bestsellers while end-of-season markdowns on slow movers eroded margins. The buying team had no visibility into demand signals beyond sales history.

18%
Margin lift
32%
Less waste
12 wks
To value
"The ROI was obvious in a quarter. We went from gut-feel buying to data-backed decisions that our whole leadership team now trusts."
Marcus Lee
VP Operations, Marketly

FAQ

Common questions about Retail

We're a mid-size retailer — is ML affordable for us?
Yes. We right-size engagements for your volume and budget. A focused demand forecasting project for 100 SKUs is very different in cost from an enterprise-wide platform — we'll scope what's realistic for your situation.
How do demand forecasting models handle promotions and seasonality?
Our models incorporate promotional calendars, seasonal patterns, and external signals (weather, events, trends) as features. We calibrate on your historical data so the model understands your specific demand drivers.