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Artificial Intelligence Helps to Better Predict Consumer Demand of the 2018 Shopping Season in South Africa

TechInAfrica – Shopping season—including Black Friday and a few weeks before Christmas Day—always brings profits to many retailers in Africa as consumer demand is at its peak. From Black Friday to days before Christmas, there are at least more than three weeks in total.

The high demand on the shopping season causes many retailers to prepare everything, unexceptionally this year. Many of them have considered making prediction methods on customer demand to prevent risks of out of stock products, understaffed, and unprepared when the days come.

Artificial Intelligence to Predict Consumer Demand on Shopping Season
Artificial Intelligence to Predict Consumer Demand on Shopping Season via

The CEO of Xineoh, Vian Chinner stated how this year’s shopping season will be totally different from the previous shopping seasons. Xineoh is a Canadian company that provides machine learning to out-predict competition, optimize efficiency, and improves customer satisfaction.

According to Chinner’s remarks: “With 1 November falling on a Thursday, Black Friday will be taking place before pay-day for most people. The last weekend before Christmas, which marks the official ‘end’ of the shopping season, will then drag the season out over a period of four weeks and two days.”

Chinner moreover also says, “With our experience in the e-commerce sector, we know that the structure of this year’s festive shopping season will see consumers spending more in the run-up to Christmas rather than spending the same amount, spread out over the longer period. This presents retailers with an opportunity to boost sales – and profits – even further than they normally would at this time of year, but only if they are prepared.”

Despite the prediction and solution he offers, Chinner says that most of the South African retailers often use the calendar dates-based prediction, like the Autoregressive Integrated Moving Average (ARIMA) model developed in the 1970s by George Box and Gwilym Jenkins. Commenting on this, Chinner says, “Basing predictions on dates would normally be relatively adequate, but not when we look at an outlier season like the one approaching.”

Chinner then adds, “For example, the 23rd of November is normally a really poor day for retail sales. This year, however, with Black Friday falling on this date we will probably see about four times the average number of sales for this day. Those using calendar-based prediction methods may not have the staff or inventory in place to cope with, and optimize, demand,”

Chinner offers a better solution for making more accurate predictions through the use of Artificial Intelligence that his company provides. Artificial Intelligence in his company, Xineoh helps to make quick predictions with more affordable cost.

Chinner states: “Going far beyond estimating demand relative to calendar dates, Xineoh’s algorithm considers all variables specific to the current situation.”

To conclude his statement, Chinner says: “Matching people with products, inventory with opportunity, price with spending propensity and people with usage patterns, adopting a modern AI solution ahead of the surge in year-end shopping can help retailers make informed decisions and provide their customers with the service, products, and experience they expect – no matter how the shopping season is structured.”

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