Bringing the retail revolution to a wider audience

Creating richer experiences for shoppers across channels by employing state-of-the-art AI and ML methodologies

At MAG, we take the power of big data and digitization beyond current applications in e-commerce creating new dynamics between consumers, producers, wholesalers, and retailers in the physical commerce space. This plays out across several dimensions including distribution logistics and supply chain, integrated shopping experiences for consumers and value-added services for retailers and producers.

New Retail

Building an integrated retail delivery model

Companies have been relentlessly working on moving from single to multi-channel and now omni-channel business models to provide more avenues for transactions. At MAG, we build solutions that provide customers with a fully integrated shopping experience by converging digital and offline experiences and everything in between.

Bridging New Frontiers

Realign with the latest in retail technology

Implementing New Retail, the right way

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Customer Churn Management

Industry Problem:
In retail, unless customers have had a particularly bad experience with your product or customer service, they don’t tend to tell you they’re leaving. Many retail customers just drift away gradually, rather than making a conscious decision to leave.

Instead of a swift chop, retail churn therefore presents as a slow slide out. Typically, our clients will see a gradual decline in the level or frequency of sales, showing that customers are either spending less on their product or moving to competitors.

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Demand Forecasting

Industry Problem:
Heraclitus couldn't have been more right when he said change is the only constant, especially when it comes to demand forecasting in retail. Today’s customer expectation and preferences are more complex than ever. Fulfilment preferences, purchasing channels and methods, and customer segments are multidimensional and very different from classical models.

That makes it very hard for retailers to make accurate and more reliable forecasts to get the right inventory to the right location.

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Client Profitability Management

Industry Problem:
CLTV represents the total amount of money a customer is expected to spend in a business during their lifetime and is an important metric to monitor because it helps to make decisions about how much money to invest in retaining existing customers and acquiring new ones.

Businesses are often in the dark when it comes to analysing customer behaviour and their cost of acquisition vis-à-vis their total spends over a given period. Knowing CLTV helps them build effective marketing strategies with a positive Return on Investment (ROI).

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Next Best Offer (NBO)

Industry Problem:
Historically, retail experiences have been built around personal bonds with the consumers. Salespeople knew each other as well as the customers they were catering to. However, today’s retail stores lack this personal touch and the only way to build a loyal customer base is through data analytics and technology.

The NBO is a way of providing better and more precise marketing to inspire a purchase, drive loyalty or both. They are usually derived from data mining, statistical analysis, segmentation, and predictive modelling, and then executed based on business rules.

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Employee Churn Prediction and Anticipated Turnover

Industry Problem:
Companies must often deal with high attrition rates in retail. A reliable workforce is the backbone of any business so naturally, businesses struggle when employees leave. To ensure smooth day-to-day functioning, companies must be aware of overall employee morale and seek to address any issues they may be facing.

At MAG, we build solutions that help companies stay ahead of any potential situations that may lead to employee attrition and investigate numerical and categorical data to keep attrition rates in check.

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Other Solutions

Apart from Data Consultation, MAG provides solutions across two other business critical verticals

In need of smarter ways forward? Get in touch.