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Covid 19

4 views on the future of retail and the shopping experience

The global spread of COVID-19 and resulting orders to shelter in place have hit retailers hard.

As the pandemic drags on, temporary halts are becoming permanent closures, whether it’s the coffee shop next door, an historic bar, or a well-known lifestyle brand.

But while the present is largely bleak, preparing for the future has retailers adopting technologies faster than ever. Their resilience and innovation means retail will look and fee different when the world reopens.

We gathered four views on the future of retail from the TechCrunch team:

  • Natasha Mascarenhas says retailers will need to find new ways to sell aspirational products — and what was once cringe might now be considered innovative.
  • Devin Coldewey sees businesses adopting a slew of creative digital services to prepare for the future and empower them without Amazon’s platform.
  • Greg Kumparak thinks the delivery and curbside pickup trends will move from pandemic-essentials to everyday occurrences. He thinks that retailers will need to find new ways to appeal to consumers in a “shopping-by-proxy” world.
  • Lucas Matney views a revitalized interest in technology around the checkout process, as retailers look for ways to make the purchasing experience more seamless (and less high-touch).

Alexa, how do I look?

Natasha Mascarenhas

The best investment every digital brand can make during the COVID-19 pandemic

Intuitively, stores that sell online should be making a killing during the COVID-19 pandemic. After all, everyone is stuck at home — and understandably more willing to shop online instead of at a traditional retailer to avoid putting themselves and others at medical risk. But the truth is, most smaller online stores have seen better days.

The primary challenge is that smaller shops often don’t have the logistics networks that companies like Amazon do. Consequently, they’re seeing substantially delayed delivery timelines, especially if they ship internationally. Customers obviously aren’t thrilled about that reality. And in many cases, they’re requesting refunds at a staggering rate.

I saw this play out firsthand in April. At that point, my stores were down 20% or in some cases even 30% in revenue. Needless to say, my team was freaking out. But there’s one thing we did that helped us increase our revenue over 200% since the pandemic, decrease refund requests and even strengthen our existing customer relationships.

We implemented a 24-hour live chat in all of our stores. Here’s why it worked for us and why every digital brand should be doing it too.

Avoid the common ‘unreachability’ frustration

When I started my first online store in 2006, challenges that bogged my team down often meant that my team’s first priority became resolving those challenges so that we could serve our customers faster. But admittedly, when these challenges came up, it became more difficult to balance communicating with our customers and resolving the issues that prevented us from fulfilling their orders quickly.

TinyML is giving hardware new life

Aluminum and iconography are no longer enough for a product to get noticed in the marketplace. Today, great products need to be useful and deliver an almost magical experience, something that becomes an extension of life. Tiny Machine Learning (TinyML) is the latest embedded software technology that moves hardware into that almost magical realm, where machines can automatically learn and grow through use, like a primitive human brain.

Until now building machine learning (ML) algorithms for hardware meant complex mathematical modes based on sample data, known as “training data,” in order to make predictions or decisions without being explicitly programmed to do so. And if this sounds complex and expensive to build, it is. On top of that, traditionally ML-related tasks were translated to the cloud, creating latency, consuming scarce power and putting machines at the mercy of connection speeds. Combined, these constraints made computing at the edge slower, more expensive and less predictable.

But thanks to recent advances, companies are turning to TinyML as the latest trend in building product intelligence. Arduino, the company best known for open-source hardware is making TinyML available for millions of developers. Together with Edge Impulse, they are turning the ubiquitous Arduino board into a powerful embedded ML platform, like the Arduino Nano 33 BLE Sense and other 32-bit boards. With this partnership you can run powerful learning models based on artificial neural networks (ANN) reaching and sampling tiny sensors along with low-powered microcontrollers.

Over the past year great strides were made in making deep learning models smaller, faster and runnable on embedded hardware through projects like TensorFlow Lite for Microcontrollers, uTensor and Arm’s CMSIS-NN. But building a quality dataset, extracting the right features, training and deploying these models is still complicated. TinyML was the missing link between edge hardware and device intelligence now coming to fruition.

Tiny devices with not-so-tiny brains