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The Predict.X Platform enables data driven decision making across your organisation, background in advanced analytics not required!

Retail 10th March 2018 - 3 min read

The Science of Choice- a Brand New Product for Retailers

By Joni Lindes

PredictX, in partnership with Influence at Work,  launched a brand new product that optimises menus to influence customer purchase behaviour. Data, reliable as it is, does not always hold the answers. One key ingredient was missing- behavioural science.

“Influencing the purchase behaviour of a customer is not a purely analytical process. We need to understand how a consumer makes a choice,” said PredictX Senior Product Manager Shobana Balasundaram.

Understanding the choices people make is integral to success as a retail business. Attracting customers and persuading them to buy products, preferably those with a high profit margin, is the end goal for any hospitality chain.

Front-of-house staff make many snap decisions when approaching a customer. They know who is going to buy more, tip more and the more experienced staff know how to utilise subtle, social cues to achieve higher sales. This is all subjective knowledge gained from experience and therefore may not be statistically accurate. It is certainly not available to every member of staff and not available for every customer that walks through the door.

The Data

What if there was a way to mould this subjective experience into one dynamic system? PredictX and Influence at Work have done just that. PredictX combines historical data from your menu and past sales, identifying Key Performance Indicators (KPIs). These include:

  • Impact of vouchers and promotions on sales and margins
  • Historic product volume and sales before and after menu prices change
  • Impact menu price increases or decreases have on customer buying patterns.
  • Impact product type has on buying patterns. For example, chicken dippers and chicken nuggets are similar products, yet have different customer appeal.

Combining Data Analytics with Behaviour Science

In September 2017, a well-known fast-food chain approached PredictX for insights on how well their menu sells their products. PredictX pulled historical data from their menus and Point of Sale (POS) systems. Aiming to develop a more dynamic product, PredictX approached Influence at Work.

Headed by two of the world’s most recognised names in the psychology of persuasion- Steve Martin and Professor of Psychology and Marketing Dr Robert Cialdini– Influence at Work aims to use behavioural science to train businesses to create more profit.

“There are now seven decades of social or behavioural science research that shows there are fundamental rules to how people are influenced and persuaded. In exactly the same way that you might learn economics or engineering, it’s entirely possible to learn about persuasion,” said Steve Martin.

“Predictx and Influence at Work therefore help retailers to identify both the data and behaviour levers so we can influence that choice, “ said Balasundaram.

Evaluating the menu is the first step. Retailers can use this tool to receive an M-score. This is a brand new industry benchmark used to evaluate the level a menu is optimised to persuade buying decisions.

The Solution

Using the data and behavioural science we will make suggestions to improve your menu. PredictX will assist in rolling these measures out across the entire chain. Staff will be trained and results will be measured.

PredictX aims to take this a step further. We will tap into each FOH staff member’s handheld ordering device where they can create a profile of a table based on the number of people, their genders, ages and whether they are family, friends or business colleagues. PredictX will send real-time suggestions to the device based on what the retailer aims to sell and the type of products this group has been drawn to in the past. The waiter can make quality product suggestions while simultaneously ensuring they are in line with the retailers’ brand values and business goals.

Joni Lindes
By Joni Lindes
3 min read

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