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An Insider’s View of Retail: Part One

It has been a while since I’ve written an article and my goal is to change that over the next few months. I was inspired to write this series while on a plane coming back from an investor road show. It hit me that the world of retail, which we live in, is misunderstood by the market.

Is offline retail dying in North America? Do we still need department stores? Do smaller retailers have a chance at survival? Will Amazon be the one retailer to rule them all? It turns out the answer isn’t that simple. I am writing this three part series because the public doesn’t get to hear a true insider’s view of retail. We are too quick to conclude on flashy news titles and oversimplified statistics. This three-part series is meant to bring you into the world of the retailer, specifically from the vantage point of the retail operators and executives.

So here is the trillion dollar question:

“Why are current omni-channel retailers struggling and what can we possibly do to address the challenges?” Want the TL:DR version? They need to stop playing defense and start playing offense with their secret weapon – their customer base.

The series will break down into three categories:

  1. What are the existential threats to retailers and why do these threats make it difficult to get ahead in today’s retail market?
  2. What is the role of loyalty providers and specialized retail consulting firms. Are they actually helping?
  3. How do elastic cloud computing and advanced machine learning to accelerate the bottom line for retailers and increase their customer loyalty?

 

A final note – None of the stats or stories used here will be from existing clients. We are under strict confidentiality from all our clients. Any stats used in this series will be from publicly available sources, and any stories will be from anonymous non-client experiences.

It’s been a particularly bad two years for retailers. Taking a look at twelve random large omni-channel retailers in North America, the story looks bleak. All of them show either flat or decreasing revenues from Q1 2015 to Q1 2016 and annual revenue from 2014 to 2015. (See the graph below)

ChangeInRevenue

Source: Google Finance
It’s easy to blame this problem on traditional retail issues like increased competition, poor inventory management, weaker consumer demand, and other reasons that are commonly stated by analysts.

We would like to present three different perspectives.

Threat # 1: The Inability to Influence End Customer Behaviour

RetailProblem-facebookCurrently, the demographic with the largest purchasing power is characterized by their hyper-connectivity with the world through their individual relationships with consumer technologies including Facebook, Netflix, Spotify, LinkedIn, and Twitter. These technologies are increasingly being driven by several layers of machine intelligence with built-in learning mechanisms that have revolutionized the consumer’s relationship with technology. Consumers are open to the idea of a machine learning their behavior and tailoring the experience to their individual needs (i.e. with the Facebook Newsfeed or the Netflix recommendation engine), and they have grown to expect this level of machine intuition in their human interactions. However, 97% of loyalty programs offer nothing more than basic product recommendations on past purchases or mass promotions. Therefore, it is no wonder that 90% of consumers have a negative opinion of loyalty programs.

 

Threat # 2: The Amazon Effect

RetailProblem-amazon

We need to call out the impact of Amazon. Traditional retailers’ single biggest competitor is a technology company with 230,000 employees, $107 billion in revenue, 200 million products, and 54 million US households registered in a paid loyalty program (Prime). Amazon has become the largest and most active loyalty program in the US, the fastest growing fashion and apparel retailer, and the single most disruptive market force to traditional retail sectors like books, electronics, mass merchandise, and soon, grocery.

Retailers must compete with Amazon’s technology ecosystem designed to reinforce the three demands of a hyper-connected consumer base: immediacy (machine calculated shipping predictions and site load experiences), transparency (product and customer reviews tailored to your search needs), and convenience (one-hour shipping, one click check-out, free refunds, and personalized product recommendations through every channel).

Additionally, Amazon is now one of the largest private label brands in North America. Close this all off with one of the world’s largest big data, engineering, and machine learning staff and you have one hell of a company to compete against.

Threat # 3: Legacy Technology Systems and Cost Commitments

Over the past 15 years, traditional retailers have been one of the largest purchasers of information technology. This technical debt, combined with expensive system integration makes it difficult for them to take advantage of this new wave of big data, machine learning, and AI technology. Meanwhile, this new technology is being rapidly adopted in new retail start-ups such as Bonobos and Warby Parker. New database frameworks and open source developments in data architecture now enable businesses to rapidly standardize and process petabytes of data in a fraction of the time. Publicly available and infinitely scalable cloud technology has made global on-demand computing power available to anyone with a laptop and internet connection. Finally, advanced machine learning and AI research have finally gone beyond academic research phases and into commercialization. Unfortunately, given the legacy infrastructure and reliance on system integrators, retailers cannot take advantage of these developments fast enough to impact their bottom or top line.

At Rubikloud, we are bullish on omni-channel retailers. We see the true brand power of these businesses and are encouraged at the size and adoption of loyalty programs across North America. Stay tuned for our next article: Are loyalty providers and retail consultants actually helping? TL:DR: Sort of.



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Data-driven decisions in retail need to rely on more than legacy analytics.

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