Retail 4.0: The Next Step in the Evolution of Brick-n-Mortar Experiences

January 17, 2019

MONTHLY ANALYSIS

In the UK alone, an estimated 1,267 shops have been closed or earmarked for closure since January 2018 – potentially putting 25,159 jobs at risk. The situation is no better in the US – after shutting down more than 5,000 stores in 2017, nearly 5,000 more store closures were announced in 2018. According to CNBC, more than 70 million sq. ft. of retail space closed in 2018, largely attributable to the fact that retailers with massive floor plans are the ones shuttering stores.

Massive closures by the largest retailers are not necessarily indicative of the death of brick-and-mortar experiences as we know them. While an increasing emphasis on e-commerce could translate into greater convenience for customers and bring down the costs for retailers, all while opening revenue-generating opportunities, it’s not enough to stay competitive anymore. Retailers have to take a step beyond simple digitization to truly compete with Amazon, Alibaba, Tencent, eBay, and the likes.

The future of brick-and-mortar retail is in hyperconnectivity between former competitors. And there are two important illustrative examples for the retail industry to look at to be able to evolve beyond physical changes in remaining stores and even beyond competing online – one from leading e-commerce platforms and one from FinTech.

A lesson from the Amazons of the world: Embrace competition for the benefit of the end user

Have you noticed how many options of the same type of product there are on Amazon? For example, there are 4,000 results for over-ear headphones. Retailers like Bose, Sony, Bits, Skullcandy, etc., only represent a fraction of those selling over-ear headphones on Amazon. Amazon embraces competition between online merchants for the benefit of the end user and, ultimately, to guarantee a sale of at least one of the options. The beauty of the e-commerce giant is in the choice provided to the end user by bringing together as much variety and competition as possible into the world of Amazon – even if that means serving as a distribution platform where other brands compete with its own products.

Best Buy appreciated this idea of turning into a platform (no matter physical or virtual) back in 2014 when the company doubled-down on the idea of a store-within-a-store. At the time, it had announced that Sony was opening stores in 350 Best Buy locations and Samsung would be adding 500 new stores to its presence within Best Buy – and Best Buy had its own suite of private-label gadgets to sell. Best Buy manufactures hundreds of unique products – from cell phone cases to smart TVs – under its five private-label brands: Insignia, Rocketfish, Platinum, Modal, and Dynex. These brands turn 16 years old this April.

More recently, in April 2018, in an unlikely matchup, Best Buy teamed up with its (now former) competitor Amazon to sell Amazon’s Fire TV Edition smart TVs. In the summer of 2017, Best Buy said it will launch more than 10 4K and HD Fire TV Edition models from Toshiba and Insignia, one of Best Buy’s private-label brands. The TVs will be sold in Best Buy stores as well as online – and for the first time, Best Buy will be a third-party seller on Amazon.com, giving the retailer access to Amazon’s vast customer network.

Best Buy is a unique case in all senses and I think one of the rare examples of a retailer that can really pivot and survive. A number of retailers that are closing down their stores today are the ones that failed to expand their brand universes faster than attention spans of modern consumers shrank. Basically, a large number of retailers remained either single-branded islands or simply added inadequate choices.

The winners of 2019 and beyond will be able to not only coexist on the same distribution platform with other strong brands but will also be able to incentivize consumers to remain in their newly-built universes even if it means supporting the sales of competing brands. And I will cover a potential case of how retailers could step up their collaboration model to enter the era of Retail 4.0.

A lesson from FinTech: Collaborate to compete

Lesson learned from most successful e-commerce platforms is very close to the one FinTech can teach the rapidly transforming retail industry. There are two important trends shaping the FinTech industry today:

1. The evolution of bank-FinTech narrative from competition to collaboration (and, subsequently, acquisitions). Collaborate to compete is the new motto of the financial services industry.

Startup-institution relationships (whether its Carrier-InsurTech or Bank-FinTech cases) have evolved from competition to a beautiful friendship, bringing out the best and accelerating innovation adoption. Significant capital allocations into strategic acquisitions are followed by the stage of active learning, and institutional players rapidly turning competition into the way to reinvent own operations and leadership.

Estimates suggest that ~50% of the world’s financial services firms are planning to acquire FinTech startups in the next several years. Moreover, 8 out of 10 institutions foresee making strategic partnerships with P2P lenders, digital money transfer platforms, and myriad other firms that are reshaping the business of money.

In fact, in 2018, we have seen 21 acquisition deals by major banks and FIs. The total acquisition deal value was more than $1.4 billion (not including deals with undisclosed values). In the 21 acquisition deals, we saw 10 banks acquiring 13 FinTechs; 2 asset management companies acquiring 2 FinTechs; and 5 insurance companies acquiring 5 FinTechs. The highest disclosed funding round was $1.06 billion when Intermediate Capital Group, an asset management company, acquired IRIS software, which specializes in accounting software.

Major banking players in the acquisition spree in 2018 were Goldman Sachs, Banco Sabadell Group, and Societe Generale, which acquired more than two FinTech startups. In the insurance field, Munich Re acquired Relayr in a 300-million-dollar deal to create new industrial business models using IoT.

All of this for one important point – the rebirth of banking will happen from the ashes of FinTechs. Both parties have realized the immense value of merging efforts and today, some of the most progressive institutions are the ones very actively involved in the FinTech ecosystem.

2. FinTech startups are increasingly utilizing one of the business models of how modern networks operate. More particularly, they are forming *regional + vertical + strategic *alliances.

Networks are a deliberate evolution of the corporate world across industries from an alluring island of proprietary solutions to an overwhelmingly invisible cloud of highly detailed solutions, encompassing every conscious and unconscious action, decision, and preference of any given individual, whether those solutions are proprietary or acquired.

But let’s get down to particular examples and details to illustrate the formation of modern networks. The case study of a cooperation network, named House of the Future, carried out in the framework of a project with significant participation of the University of Aveiro in Portugal, described a visionary framework of networks based on combinations of the following hallmarks:

By duration:

  1. Project teams and virtual corporations – gathering for a short-term goal

  2. Strategic alliances, joint ventures, and business association – implying longer run collaboration

By actors involved:

  1. Vertical: Connecting actors along a supply chain

  2. Horizontal: Connecting actors from similar functional areas or sectors

  3. Diagonal: Connecting actors from complementary functional areas or sectors

Geo-scope:

  1. Local

  2. Regional or national

  3. International or global

If we were to build a three-dimensional map, zooming in on various combinations of hallmarks constituting every type of a network, there would be a handful of real-world embodiments across industries representing one or another combination.

This time, I’d like to focus on a particular type that should serve a lesson to the retail industry: let’s talk about regional + vertical + strategic alliances.

The financial services industry, gig economy services, logistics, insurance – all good examples of industries where this particular network model is a good approach for scaling a business.

Discover – the network of networks – is one of the most vivid examples from the financial services industry of why this model is so interesting and is tailored for scale in a respective industry. Discover Network is a comprehensive, payments network accepted at millions of merchant locations in the US, Canada, Mexico, Central America, and the Caribbean. Discover’s power is magnified by the two core networks it is built on:

  • Diners Club International introduced the first multi-purpose charge card to the world in 1950. Diners Club International has over 26 million merchant acceptance locations and 1.9 million ATM and cash access locations across 185 countries/territories.

  • PULSE is one of the nation’s leading debit/ATM networks. PULSE provides cardholders with access to 1.8 million ATMs worldwide.

Discover is also accepted by three major mobile wallets – Apple Pay, Samsung Pay (>5 million monthly customers), and Android Pay (>5 million monthly users). Discover covers a network of 80+ acquirers covering the needs of businesses around the world. Being a network and an issuer, Discover is able to offer unique benefits to Discover cardholders that are rooted in operational efficiency and network reach.

An important hallmark of the Discover Network is its approach to acceptance expansion. The Discover Network itself is strategically picking global partner networks to ensure the backing of the leading institutions across pan-regional markets – the ones that have the most scale and reach. More importantly, the potential of this growth is fueled by the partnerships that Discover acceptance members create themselves.

In industries other than financial services, there are examples like Uber + Grab, Amazon + Whole Foods.

The Enterprise Ethereum Alliance is also an interesting case: the alliance brings together a diverse and powerful bunch, but that bunch has only one niche interest with this alliance – the application of blockchain technology and exploration of opportunities in the crypto space. BNY Mellon, BBVA, JPMorgan, ING, Santander, Credit Suisse, and many more came together to form their own network of interested parties. Where will this alliance lead? Hard to say. But one is evident: it falls into one of the combinations – international + vertical (if we look at it from the connective tissue perspective) + strategic alliance.

Alternative lending as a vertical and a concept will likely perish in the years ahead because there is no alternative financing behind alternative lending in the vast majority of cases, which means technically, there is nothing alternative about alternative lending. Banks are using the national + vertical + strategic alliance model to remain a dominating financial force in the lending space. A multitude of strategic partnerships plays a transformative role in the lending space, especially for underserved groups of the population.

Partnerships such as Avant & Regions Bank, OnDeck & JPMorgan Chase, Kabbage & Santander, Kabbage & ING, Prosper & Radius Bank, LendingClub & Union Bank, and other industry examples represent a mindset transformation and strategic work in place to learn and find avenues for expansion of business in the lending space.

What is the lesson for retailers that want to survive? Form vertical alliances to keep customers in a locked ecosystem. I strongly believe that the most unintuitive alliances today are the strongest ones tomorrow. It’s logical for Ulta and Sephora to be rivals. What’s not logical, and, possibly, right is that if those retailers decided to team up on common rewards and loyalty program to cross-sell off one another, there is a chance they’d glue customers to the new Ulta-Sephora world tighter than each of them separately.

Let’s get down to more details of how would Retail 4.0 work.

What would Retail 4.0 look like in reality?

Let’s take a hypothetical example of Macy’s, which as of 11/2018 was operating 850+ stores in the US.

Macy’s, like Best Buy, Home Depot, Sephora, Ulta, Sears, and many other retailers, despite being selling private-label products and distributing third-party brands, do not operate brand-specific POS terminals. All payment terminals at Macy’s belong to Macy’s (which has its own problems, like the inability to return a third-party brand product from a standalone store to the booth of that brand at Macy’s), which has an important benefit to the retailer – a vast data on consumer behavior inside a store with a variety of brands.

Using that information, Macy’s could see correlations in brand affinity and use unique purchase patterns to force consumers to shop more.

Let’s look at Macy’s in my favorite city out of the five I have lived in – NYC – as a more particular example. Macy’s on 34th Street & 6th Avenue in Manhattan is a big mall with a large number of high-end brand stores and cafes inside. Let’s say our Jane Doe always goes to that store and there are two particular brands she goes there for – Louis Vuitton and Gucci, after which she always gets a coffee at the Herald Square Cafe.

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The transactional history of our Jane Doe over the years of her visiting those stores would demonstrate loyalty to those two stores, and, possibly, an indication that once a purchase happens at one of them, a purchase at another one follows in a certain period of time.

What’s more interesting is that Macy’s could force Jane Doe to buy coffee at Herald Square Cafe every time she makes a purchase at one of her two favorite brands instead of leaving it to chance. So every time Jane Doe performs a transaction at Gucci or Louis Vuitton, Macy’s app could trigger a discount code pop-up for 10% off coffee in Macy’s Herald Square Cafe, which can only be used in the next 30 minutes or expire. Those stores are all next to each other on the same level, making it a no-brainer choice for a person who already has this habit, but is not really a sure-shot sale for every visit.

How does this apply to competitors, you may ask? This model could work in the exact same way for Sears and Marshalls, for Best Buy and Home Depot, for Ulta and Sephora, and a lot more seemingly unrelated combinations. In the case of standalone branded stores, there is another party with even more power – the payments network – that could spice up the game.

Every major city has shopping districts with an intense concentration of stores. Let’s look at NYC’s SoHo. The map below is just a part of it.

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Areas such as SoHo are widely present at a different scale and offer a perfect opportunity to each of the stores in the area to leverage the motto ‘collaborate to compete’ literally.

Without pointing fingers at any particular network, let’s just say one of the biggest payments networks – X – analyzes purchasing patterns localized exclusively to SoHo and discovers that customers to visit and make a purchase at Adidas Originals Flagship Store, often make the following purchase at Arcteryx SoHo. Both of these stores are within one block.

Having that knowledge, the payments network could help shape mutually beneficial alliances among seemingly competing retailers. The payments network could use the transaction location and one of the stores in the often-met-combination to immediately send a timed discount code to the phone number of that customer for the other store in that combination.

What would the customer experience? The second Jane Doe makes a transaction at Adidas to buy running shoes and a message pops up on her phone with a discount code for compressor socks from Arcteryx with a 10% discount if they are bought in the next 30 minutes. The physical proximity of a variety of stores in shopping districts would ensure that the person can walk out of one store and quickly get into the next one where the discount works. The customer could actually receive a Google Maps link with directions to the store along with the discount countdown.

Using the exact location of the PoS where the triggering transaction happened, payments networks and participating retailers cannot just entice, but sort of force someone with an expiring in a short time discount to make another purchase in a very close distance in a place where people have been known to go next (either from generalized analytics or personal analytics). All of this can be automated.

If the payments processor creates an alliance with all the stores in a particular area and brings together transactional analytics to see the hottest combinations, the retailers would understand who see the best tie-up opportunities in each location.

It may seem counterintuitive for Adidas to be sending people to Arcteryx for compression socks when it has its own socks to sell. The issue here is that there is no guarantee of any of the following:

  1. The customer may not intend or may not indicate an intention to also throw in the socks while s/he is buying the running shoes there because there is no trigger like an immediate, very shortly timed discount. So the opportunity could be lost just there.

  2. Let’s say there is a trigger. However, there is no guarantee that this customer is a fan of Adidas’ compressor socks. Today, consumers are highly promiscuous in terms of loyalty to brands.

By cross-selling among the competition, the brands with the most frequent tie-ups almost certainly guarantee that there will be a sale – and they should be competing on quality. But more importantly, there is a chance that the customer will be returning consistently to each of the stores in this unique tie-up just to see what immediate discount a purchase would trigger.

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