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IoT and data science will boost foodtech in the post-pandemic era
Sunny Dhillon is an early-stage investor at Signia Ventures in San Francisco where he invests in retail tech, e-commerce infrastructure and logistics, alongside consumer and enterprise software startups.
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Even as e-grocery usage has skyrocketed in our coronavirus-catalyzed world, brick-and-mortar grocery stores have soldiered on. While strict in-store safety guidelines may gradually ease up, the shopping experience will still be low-touch and socially distanced for the foreseeable future.
This begs the question: With even greater challenges than pre-pandemic, how can grocers ensure their stores continue to operate profitably?
Just as micro-fulfillment centers (MFCs), dark stores and other fulfillment solutions have been helping e-grocers optimize profitability, a variety of old and new technologies can help brick-and-mortar stores remain relevant and continue churning out cash.
Today, we present three “must-dos” for post-pandemic retail grocers: rely on the data, rely on the biology and rely on the hardware.
Rely on the data
Image Credits: Pixabay/Pexels (opens in a new window)
The hallmark of shopping in a store is the consistent availability and wide selection of fresh items — often more so than online. But as the number of in-store customers continues to fluctuate, planning inventory and minimizing waste has become ever more so a challenge for grocery store managers. Grocers on average throw out more than 12% of their on-shelf produce, which eats into already razor-thin margins.
While e-grocers are automating and optimizing their fulfillment operations, brick-and-mortar grocers can automate and optimize their inventory planning mechanisms. To do this, they must leverage their existing troves of customer, business and external data to glean valuable insights for store managers.
Eden Technologies of Walmart is a pioneering example. Spun out of a company hackathon project, the internal tool has been deployed at over 43 distribution centers nationwide and promises to save Walmart over $2 billion in the coming years. For instance, if a batch of produce intended for a store hundreds of miles away is deemed soon-to-ripen, the tool can help divert it to the nearest store instead, using FDA standards and over 1 million images to drive its analysis.
Similarly, ventures such as Afresh Technologies and Shelf Engine have built platforms to leverage years of historical customer and sales data, as well as seasonality and other external factors, to help store managers determine how much to order and when. The results have been nothing but positive — Shelf Engine customers have increased gross margins by over 25% and Afresh customers have reduced food waste by up to 45%.
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Conversational analytics are about to change customer experiences forever
A digital marketing and customer experience leader, Evan Kohn is chief business officer at Pypestream, where he created PypePro, an AI onboarding methodology used by Fortune 500 firms.
Companies have long relied on web analytics data like click rates, page views and session lengths to gain customer behavior insights.This method looks at how customers react to what is presented to them, reactions driven by design and copy. But traditional web analytics fail to capture customers’ desires accurately. While marketers are pushing into predictive analytics, what about the way companies foster broader customer experience (CX)?
Leaders are increasingly adopting conversational analytics, a new paradigm for CX data. No longer will the emphasis be on how users react to what is presented to them, but rather what “intent” they convey through natural language. Companies able to capture intent data through conversational interfaces can be proactive in customer interactions, deliver hyper-personalized experiences, and position themselves more optimally in the marketplace.
Direct customer experiences based on customer disposition
Conversational AI, which powers these interfaces and automation systems and feeds data into conversational analytics engines, is a market predicted to grow from $4.2 billion in 2019 to $15.7 billion in 2024. As companies “conversationalize” their brands and open up new interfaces to customers, AI can inform CX decisions not only in how customer journeys are architected–such as curated buying experiences and paths to purchase–but also how to evolve overall product and service offerings. This insights edge could become a game-changer and competitive advantage for early adopters.
Today, there is wide variation in the degree of sophistication between conversational solutions from elementary, single-task chatbots to secure, user-centric, scalable AI. To unlock meaningful conversational analytics, companies need to ensure that they have deployed a few critical ingredients beyond the basics of parsing customer intent with natural language understanding (NLU).
While intent data is valuable, companies will up-level their engagements by collecting sentiment and tone data, including via emoji analysis. Such data can enable automation to adapt to a customer’s disposition, so if anger is detected regarding a bill that is overdue, a fast path to resolution can be provided. If a customer expresses joy after a product purchase, AI can respond with an upsell offer and collect more acute and actionable feedback for future customer journeys.
Tap into a multitude of conversational data points
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As the world stays home, edtech’s Q2 venture totals rose sharply
My friend and colleague Natasha Mascarenhas has been reporting on the edtech beat quite a lot in 2020. So far reading her coverage, I’ve discovered that not only is edtech less dull than I anticipated, it’s actually somewhat interesting on a regular basis.
This week, for example, India’s Byju bought WhiteHat Jr., another Indian edtech company, for $300 million. So what, you’re thinking, that’s just another startup deal? Yes, but it was an all-cash transaction, and White Hat Jr. was only 18 months old.
That’s enough to tell you that edtech is hot at the moment. Which makes sense: much of the world is sheltering at home with school and offices shuttered.
The Exchange explores startups, markets and money. You can read it every morning on Extra Crunch, or get The Exchange newsletter every Saturday.
The COVID-19 era has provided an enormous boon to many software startups, though some more than others. Luckily for its boosters, edtech, after being neglected by VCs due to an expectation of small exits and long sales cycles thanks to red tape, is one of the sectors enjoying renewed interest from private investors and customers alike.
According to a Silicon Valley Bank (SVB) markets-focused report, edtech venture funding reached a local-maxima in Q2 2020, jumping more than 60% from the first quarter of this year to the second. On a year-over-year basis, Q2’s VC edtech results were even more impressive.
But, there’s some nuance to the data that should temper declamations that private edtech funding is forever changed.
This morning let’s peel apart the SVB data and parse through edtech funding rounds themselves from the second quarter to see what we can learn. COVID-19 is remaking the global economy as we speak, so it’s up to us to understand its evolving form.
An edtech boom?
From the top-line numbers, you’d be forgiven for thinking that edtech’s Q2 venture capital results were across-the-board impressive.
Before we dig into the results themselves, here’s the chart you need:
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Can learning pods scale, or are they widening edtech’s digital divide?
Lucia, a six-year old, hides from Zoom calls and has rejected every edtech tool from Seesaw to Khan Academy. She will spend all of first grade in quarantine.
Her mother, Claire Díaz-Ortiz, says her daughter fits squarely into the “distance learning death zone.” The idea is that younger children are too young to do distance learning solo, even with tools meant to make it easier. Here’s one kindergartner’s remote fall class schedule:
Just got this schedule for my kindergartner’s “distance learning” in the fall and would just like to say LOL FOREVER TIMES A THOUSAND pic.twitter.com/CXXzdbwUWa
— Aubrey Hirsch (@aubreyhirsch) July 31, 2020
“And unfortunately for my daughter, I’m a VC, not a Zoom mom,” Díaz-Ortiz said.
The impact of the distance learning death zone, as Díaz-Ortiz calls it, is one of the reasons why many wealthy families with young children are considering a new solution: learning pods.
Learning pods are small clusters of children within the same age range who are paired with a private instructor. Depending on a parent’s preferences, learning pods could be an in-home or virtual experience and be either a full-time school replacement or supplemental learning.
In recent weeks, the concept has taken off all across the country, from suburbs to cities. There’s a Facebook group for Boulder, Colorado school districts; organizers launched Pandemic Pod San Diego to “connect families looking for in-home, teacher-led learning groups.” Some households are offering teachers a retainer. Among working mom groupchats, pods are taking off as a sanity lifesaver, especially as childcare responsibilities fall disproportionately on women.
Looking for the best 4-6th grade teacher in Bay Area who wants a 1-year contract, that will beat whatever they are getting paid, to teach 2-7 students in my back yard#microschool
If you know this teacher, refer them & we hire them, I will give you a $2k UberEats gift card
— jason@calacanis.com (@Jason) August 2, 2020
Startups are pivoting to keep up with the demand for private teachers. But because of high costs, only affluent families are able to form or join learning pods, which may limit the model’s ability to reach scale while extending the existing digital divide.
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Robinhood’s Q2 soars
Robinhood’s huge, two-part Series F round came partially in Q2 and partially in Q3. The app-based trading platform announced the first $280 million in early May, valuing the company at around $8.3 billion, up from a prior price tag of around $7.6 billion.
Then in July, Robinhood tacked on $320 million more at the same price, raising its valuation to around $8.6 billion.
While it has long been known that savings and investing apps and services are seeing a boom in 2020, precisely what caused investors to pour $600 million more into this already-wealthy company was less immediately evident. Recent data released by Robinhood concerning one of its revenue sources may help explain the rapid-fire capital events.
The Exchange explores startups, markets and money. You can read it every morning on Extra Crunch, or get The Exchange newsletter every Saturday.
Filings from Robinhood covering the April through June period, Q2 2020, indicate that the company’s revenue from payment for order flow, a method by which a broker is paid to route customer orders through a particular group, or party rose during the period. As TechCrunch has covered, Robinhood generates a sizable portion of its revenue from such activities.
The company is hardly alone in doing so. As a new report from The Block, shared with The Exchange ahead of publication notes, Robinhood’s Q2 payment for order flow haul was impressive, but not singularly so; trading houses like E*Trade and Charles Schwab also grew their incomes from order flow routing in the period.
But Robinhood’s gains come in the wake of the firm’s promise to shake up its options trading setup after a customer took their own life. As we’ve written, there is a tension between Robinhood’s desire to limit who can access options trading, its need to grow and the incomes options-related order flow can drive for the budding fintech giant.
This morning, however, we are focusing on revenue growth over other issues (more to come on those later). Let’s dig into Robinhood’s Q2 order flow revenue numbers and see what we can learn about its run rate and current valuation.
A big Q2
According to The Block’s own calculations, Robinhood saw saw its total payment for order flow revenue roughly double, rising from $90.9 million in Q1 2020 to $183.3 million in Q2 2020, a 102% increase.
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Eight trends accelerating the age of commercial-ready quantum computing
Ethan Batraski is a partner at Venrock, where he invests across sectors with a particular focus on hard engineering problems such as developer infrastructure, advanced computing and space.
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Every major technology breakthrough of our era has gone through a similar cycle in pursuit of turning fiction to reality.
It starts in the stages of scientific discovery, a pursuit of principle against a theory, a recursive process of hypothesis-experiment. Success of the proof of principle stage graduates to becoming a tractable engineering problem, where the path to getting to a systemized, reproducible, predictable system is generally known and de-risked. Lastly, once successfully engineered to the performance requirements, focus shifts to repeatable manufacturing and scale, simplifying designs for production.
Since theorized by Richard Feynman and Yuri Manin, quantum computing has been thought to be in a perpetual state of scientific discovery. Occasionally reaching proof of principle on a particular architecture or approach, but never able to overcome the engineering challenges to move forward.
That’s until now. In the last 12 months, we have seen several meaningful breakthroughs from academia, venture-backed companies, and industry that looks to have broken through the remaining challenges along the scientific discovery curve. Moving quantum computing from science fiction that has always been “five to seven years away,” to a tractable engineering problem, ready to solve meaningful problems in the real world.
Companies such as Atom Computing* leveraging neutral atoms for wireless qubit control, Honeywell’s trapped ions approach, and Google’s superconducting metals, have demonstrated first-ever results, setting the stage for the first commercial generation of working quantum computers.
While early and noisy, these systems, even at just 40-80 error-corrected qubit range, may be able to deliver capabilities that surpass those of classical computers. Accelerating our ability to perform better in areas such as thermodynamic predictions, chemical reactions, resource optimizations and financial predictions.
As a number of key technology and ecosystem breakthroughs begin to converge, the next 12-18 months will be nothing short of a watershed moment for quantum computing.
Here are eight emerging trends and predictions that will accelerate quantum computing readiness for the commercial market in 2021 and beyond:
1. Dark horses of QC emerge: 2020 will be the year of dark horses in the QC race. These new entrants will demonstrate dominant architectures with 100-200 individually controlled and maintained qubits, at 99.9% fidelities, with millisecond to seconds coherence times that represent 2x -3x improved qubit power, fidelity and coherence times. These dark horses, many venture-backed, will finally prove that resources and capital are not sole catalysts for a technological breakthrough in quantum computing.
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Go public now while software valuations make no sense
Software valuations are bonkers, which means it’s a great time to go public. Asana, Monday.com, Wrike and every other gosh darn software company that is putting it off, pay attention. Heck, even service-y Palantir could excel in this market.
Let me explain.
Over the past few weeks, TechCrunch has tracked the filing, first pricing, rejiggered pricing range, and, today, the first day of trading for BigCommerce, a Texas-based e-commerce company. You can think of it as a comp with Shopify to a degree.
Image Credits: IMGFlip (opens in a new window)
In the wake of the Canadian phenom’s blockbuster earnings report, BigCommerce boosted its IPO range. Yesterday the company did itself one better, pricing $1 per share above that raised range, selling 9,019,565 shares at $24 per share, of which 6,850,000 came from BigCommerce itself.
Before some additions, there are now 65,843,546 shares of BigCommerce in the world, giving the company an IPO valuation of around $1.58 billion.
Given that the company’s Q2 expected revenue range is “between $35.5 million and $35.8 million,” the company sported a run-rate multiple of 11.1x to 11x, depending on where its final revenue tally comes in. That felt somewhat reasonable, if perhaps a smidgen light.
Then the company opened at $68 per share today, currently trading for $82 per share. Hello, 1999 and other insane times. BigCommerce is now worth, using some rough math, around $5.4 billion, giving it a run-rate multiple of around 38x, using the midpoint of its Q2 revenue range.
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Software stocks set new records despite earnings, pandemic
You might have missed it, but amidst the current political-M&A-pandemic-election-disinformation news cycle we find ourselves in this week, SaaS and cloud companies reached new public market records.
Yesterday, the Bessemer-Nasdaq cloud index closed at 2,035.54, a new record finish for the basket of software companies. And, today, the index broached the 2,040 mark before ceding some ground.
The Exchange explores startups, markets and money. You can read it every morning on Extra Crunch, or get The Exchange newsletter every Saturday.
What matters for our purposes is that with a good chunk of the Q2 earnings cycle behind us, software companies are not only holding onto their gains from earlier in the year, they are managing to add to them, albeit modestly. Of course, valuation expansion during earnings season could still lead to gently falling multiples; as companies grow, if their shares gain value at a slower pace, their price/sales ratio can lose ground.
Regardless, for our purposes it’s notable that recent public market gains are not dissipating. Tech valuation boosts have helped major American indices regain ground lost early in the year, and Q2 earnings were a possible threat to prior progress. So far earnings-related dents are thin on the ground.
So, what’s going on? Why are SaaS and cloud stocks doing so well? Leaning on notes from two VCs — Jamin Ball from Redpoint and Mary D’Onofrio from Bessemer — we can unspool recent valuation highs.
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Even as cloud infrastructure growth slows, revenue rises over $30B for quarter
The cloud market is coming into its own during the pandemic as the novel coronavirus forced many companies to accelerate plans to move to the cloud, even while the market was beginning to mature on its own.
This week, the big three cloud infrastructure vendors — Amazon, Microsoft and Google — all reported their earnings, and while the numbers showed that growth was beginning to slow down, revenue continued to increase at an impressive rate, surpassing $30 billion for a quarter for the first time, according to Synergy Research Group numbers.
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Where is voice tech going?
Mark Persaud is digital product manager and practice lead at Moonshot by Pactera, a digital innovation company that leads global clients through the next era of digital products with a heavy emphasis on artificial intelligence, data and continuous software delivery.
2020 has been all but normal. For businesses and brands. For innovation. For people.
The trajectory of business growth strategies, travel plans and lives have been drastically altered due to the COVID-19 pandemic, a global economic downturn with supply chain and market issues, and a fight for equality in the Black Lives Matter movement — amongst all that complicated lives and businesses already.
One of the biggest stories in emerging technology is the growth of different types of voice assistants:
- Niche assistants such as Aider that provide back-office support.
- Branded in-house assistants such as those offered by BBC and Snapchat.
- White-label solutions such as Houndify that provide lots of capabilities and configurable tool sets.
With so many assistants proliferating globally, voice will become a commodity like a website or an app. And that’s not a bad thing — at least in the name of progress. It will soon (read: over the next couple years) become table stakes for a business to have voice as an interaction channel for a lovable experience that users expect. Consider that feeling you get when you realize a business doesn’t have a website: It makes you question its validity and reputation for quality. Voice isn’t quite there yet, but it’s moving in that direction.
Voice assistant adoption and usage are still on the rise
Adoption of any new technology is key. A key inhibitor of technology is often distribution, but this has not been the case with voice. Apple, Google, and Baidu have reported hundreds of millions of devices using voice, and Amazon has 200 million users. Amazon has a slightly more difficult job since they’re not in the smartphone market, which allows for greater voice assistant distribution for Apple and Google.
Image Credits: Mark Persaud
But are people using devices? Google said recently there are 500 million monthly active users of Google Assistant. Not far behind are active Apple users with 375 million. Large numbers of people are using voice assistants, not just owning them. That’s a sign of technology gaining momentum — the technology is at a price point and within digital and personal ecosystems that make it right for user adoption. The pandemic has only exacerbated the use as Edison reported between March and April — a peak time for sheltering in place across the U.S.
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