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jerryking : legacy_players   3

Three Hard Lessons the Internet Is Teaching Traditional Stores
April 23, 2017 | WSJ | By Christopher Mims.
Legacy retailers have to put their mountains of purchasing data to work to create the kind of personalization and automation shoppers are getting online
(1) Data Is King
When I asked Target, Walgreens and grocery chain Giant Food about loyalty programs and the fate of customers’ purchasing data—which is the in-store equivalent of your web browsing history—they all declined to comment. ...Data has been a vital part of Amazon’s retail revolution, just as it was with Netflix ’s media revolution and Google and Facebook ’s advertising revolution. For brick-and-mortar retailers, purchasing data doesn’t just help them compete with online adversaries; it has also become an alternate revenue source when profit margins are razor-thin. ....Physical retailers must catch up to online retailers in collecting rich data without making it feel so intrusive. Why, exactly, does my grocery store need my phone number?

(2) Personalization + Automation = Profits
Personalization and Automation = Profits
There’s a debate in the auto industry: Can Tesla get good at making cars faster than Ford, General Motors and Toyota can get good at making self-driving electric vehicles? The same applies to retail: Can physical retailers build intimate digital relationships with their customers—and use that data to update their stores—faster than online-first retailers can learn how to lease property, handle inventory and manage retail workers? [the great game ]

Online retailers know what’s popular, and how customers who like one item tend to like certain others. So Amazon’s physical bookstores can put out fewer books with more prominently displayed covers. Bonobos doesn’t even sell clothes in its stores, which it calls “guideshops.” Instead, customers go there to try clothes on, and their selections are delivered through the company’s existing e-commerce system.

Amazon’s upcoming Go convenience stores, selling groceries and meal kits, don’t require cashiers. That’s the sort of automation that could position Amazon to reap margins—or slash prices—to a degree unprecedented for retailers in traditionally low-margin categories like food and packaged goods.

While online retailers are accustomed to updating inventory and prices by the hour, physical retailers simply don’t have the data or the systems to keep up, and tend to buy and stock on cycles as long as a year, says George Faigen, a retail consultant at Oliver Wyman. Some legacy retailers are getting around this by teaming up with online players.

Target stocks men’s shaving supplies from not one but two online upstarts, Harry’s and Bevel. Target has said that, as a result, more customers are coming in to buy razors, increasing the sales of every brand on that aisle—even good old Gillette. Retailers have long relied on manufacturers to drive customers to stores by marketing their goods and even managing in-store displays. The difference is this: In the past, new brands had to persuade store buyers to dole out precious shelf space; now the brands can prove themselves online first.

(3) Legacy Tech Won’t Cut It

Perhaps the biggest challenge for existing retailers, says Euromonitor’s Ms. Grant, is finding the money to transition to this hybrid online-offline model. While Target has announced it will spend $7 billion over the next three years to revamp its stores, investors fled the stock in February after Target reported 2017 profits might be 25% less than expected.

When Warby Parker, the online eyeglasses retailer, set out to launch stores across the U.S., the company looked for in-store sales software that could integrate with its existing e-commerce systems. It couldn’t find a system up to the task, so it built one from scratch.

These kinds of systems allow salespeople to know what customers have bought both online and off, and what they might be nudged toward on that day. “We call it the ‘point of everything’ system,” says David Gilboa, co-founder and co-chief executive.

Having this much customer knowledge available instantly is critical, but it’s precisely what existing retailers struggle with, Mr. Faigen says.

Even Amazon is experiencing brick-and-mortar difficulties. In March, The Wall Street Journal reported that the Go stores would be delayed because of kinks in the point-of-sale software system.

Andy Katz-Mayfield, co-founder and co-chief executive of Harry’s, is skeptical that traditional retailers like Wal-Mart can make the leap, even if they invest heavily in technology.

The problem, he says, is that selling online isn’t just about taking orders through a website. Companies that succeed are good at selling direct to consumers—building technology from the ground up, integrating teams skilled at navigating online marketing’s ever-shifting terrain and managing the experience through fulfillment and delivery, Mr. Katz-Mayfield says.

That e-commerce startups are so confident about their own future doesn’t mean they are right about the fate of traditional retailers, however.

A report from Merrill Lynch argues Wal-Mart is embarking on a period of 20% to 30% growth for its e-commerce business. A spokesman for the company said that in addition to acquisitions, the company is focused on growing its e-commerce business organically.

It isn’t hard to picture today’s e-commerce companies becoming brick-and-mortar retailers. It’s harder to bet on traditional retailers becoming as tech savvy as their e-competition.[the great game]
lessons_learned  bricks-and-mortar  retailers  curation  personalization  e-commerce  shopping_malls  automation  privacy  Warby_Parker  Amazon_Go  data  data_driven  think_threes  Bonobos  Amazon  legacy_tech  omnichannel  Harry’s  Bevel  loyalty_management  low-margin  legacy_players  digital_first  Tesla  Ford  GM  Toyota  automobile  electric_cars  point-of-sale  physical_world  contra-Amazon  brands  shelf_space  the_great_game  cyberphysical  cashierless  Christopher_Mims  in-store  digital_savvy 
april 2017 by jerryking
The Evolving Automotive Ecosystem - The CIO Report - WSJ
April 6, 2015| WSJ | By IRVING WLADAWSKY-BERGER.

An issue in many other industries. Will the legacy industry leaders be able to embrace the new digital technologies, processes and culture, or will they inevitably fall behind their faster moving, more culturally adept digital-native competitors? [the great game]

(1) Find new partners and dance: “The structure of the automotive industry will likely change rapidly. Designing and producing new vehicles have become far too complex and expensive for any likely one company to manage all on its own.
(2) Become data masters: “Know your customers better than they know themselves. Use that data to curate every aspect of the customer experience from when they first learn about the car to the dealership experience and throughout the customer life cycle. Having data scientists on staff will likely be the rule, not the exception.
(3) Update your economic models: “Predicting demand was hard enough in the old days, when you did a major new product launch approximately every five years. Now, with the intensity of competition, the rapid cadence of new launches, and the mashup of consumer and automotive technology, you may need new economic models for predicting demand, capital expenditures, and vehicle profitability.
(4)Tame complexity: “It’s all about the center stack, the seamless connectivity with nomadic devices, the elegance of the Human Machine Interface.
(5) Create adaptable organizations: “It will take a combination of new hard and soft skills to build the cars and the companies of the future. For many older, established companies, that means culture change, bringing in new talent, and rethinking every aspect of process and people management.
Apple  automotive_industry  autonomous_vehicles  ecosystems  Google  know_your_customer  adaptability  CIOs  layer_mastery  competitive_landscape  competitive_strategy  connected_devices  telematics  data  data_driven  data_scientists  customer_experience  curation  structural_change  accelerated_lifecycles  UX  complexity  legacy_players  business_development  modelling  Irving_Wladawsky-Berger  SMAC_stack  cultural_change  digitalization  connected_cars  the_great_game 
april 2015 by jerryking
Push to exploit an ocean of information
Richard Waters Source: The Financial Times. (Dec. 10, 2012): News: p19

Like anticipating film demand and judging the effectiveness of window displays, much of the effort in the field of big data analytics is aimed at making existing companies more effective. Designing products, setting optimal prices and reaching the best prospects among potential customers are turning into data-driven exercises.

But it is also throwing up disruptive new businesses. Companies set up from scratch have the chance to draw on public streams of digital data to enter markets that were once closed to incumbents with long-established customer relationships and proprietary information. And such businesses come without the legacy technology platforms, entrenched business processes and cultural norms that make it hard for big groups to change.

"Even if you're not a bank or a healthcare company, you can play in banking or healthcare," says James Manyika, director at McKinsey's research arm.
massive_data_sets  Quantifind  Hollywood  Climate_Corporation  sensors  Euclid_Analytics  Kabbage  Factual  disruption  start_ups  McKinsey  data_driven  new_businesses  large_companies  open_data  legacy_players  digital_disruption  customer_relationships  legacy_tech  cultural_norms  Richard_Waters 
february 2013 by jerryking

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