Do we Need Data to Understand the Modern Consumer?

IN Artificial Intelligence — 26 February, 2018

Shoppers have fundamentally changed their consumer habits in recent years. Today, a typical buyer journey can involve any number of channels and devices; online and offline, physical and digital, mobile and desktop.

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What’s more, the modern consumer has unparalleled expectations around buyer experience, product diversity, competitive pricing and ethical sourcing. They are highly influenced by brand identity, online influencers and peers’ opinions.

Consumers drive the decisions in the modern retail world. They are quick to share their experiences, are far more opinionated yet retailers find it increasingly hard to understand them. But is the modern customer entirely unpredictable?

What do retailers need to know?

Getting under the skin of shoppers has always been essential for retailers to stock the right level of products for their customers, across the right locations. In the grocery retail industry, this stock replenishment process is a delicate balancing act; perishable, easily damaged produce is harder to transport and has an incredibly short shelf life.

Yesterday’s shopper was relatively predictable. Shopping cycles were seasonal, replenishment was standardized and pricing was easier to manage. Today, consumers have much more choice; they are shopping across borders more frequently, expecting much more competitive pricing. Retailers need to understand where their shoppers are spending their money, and why.

Are consumers less predictable?

97% of organizations are trying to achieve a complete view of the consumer, but 81% of marketers have challenges achieving a single customer view.[1]

According to research firm RSR’s benchmark report on omnichannel order profitability, unpredictable consumer demand is the top business challenge among retailers.

Yes, consumers are less predictable. That’s because there are far more variables on the table. At the same time, failure to identify consumer preferences and buying patterns is not purely down to consumer unpredictability; it’s a case of uninsightful data.

Granular data detail is necessary to drill into the endless channel complexities and stock assortments to make accurate predictions, but it is possible.

Stock forecasting and replenishment services, like that from Blue Yonder, deliver accurate decisions that are entirely automated and optimized based on based on hundreds of different data variables.

A unique digital data footprint

Ubiquitous modern technology and social networking has meant consumers are talking back to their retailers, sharing candid opinions with each other, and presenting themselves as self-appointed brand ambassadors. Retailers are now dealing with knowledgeable customers who have researched what they want to buy before they arrive in-store.

Each consumer movement, web visit, conversation, and opinion forms a 360 degree digital footprint of data. This consumer data, when unlocked with artificial intelligence, offers the high level insight that gives retailers a competitive edge.

Personalized experiences

Data does more than offer stock suggestions, it can improve customer experiences. By analyzing and exploiting data effectively, and using micro-location-based beacon technology, retailers can share personalized deals or suggestions to their customers.

Retailers that dedicate resources to either an in-house or third party data science specialist will discover the secret behind modern customers’ predictability and enhanced user experiences; the cornerstones to successful modern retailing.

Combining insightful consumer information with existing circumstantial data, product information and seasonal trends, meanwhile, gives retailers enhanced replenishment decisions and a more loyal consumer base. It can significantly boost a merchant’s profit too; Blue Yonder’s demand forecast & replenishment service can reduce out of stock rates by 80%.

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We enable retailers, consumer products and other companies to take a transformative approach to their core processes, automating complex decisions that deliver higher profits and customer value using artificial intelligence (AI).