TechCrunch Newsletters - Dogs of Lordstown

Welcome to Extra Crunch Tuesday

Lordstown Motors released its Q1 earnings yesterday, and the electric vehicle manufacturer is facing a few challenges.

Expenses were higher than expected, it plans to slash production by about 50%, and the company reported zero revenue and a net loss of $125 million. Oh, it also needs more capital.

“But there’s more to the Lordstown mess than merely a single bad quarter,” writes Alex Wilhelm.

“Lordstown’s earnings mess and the resulting dissonance with its own predictions are notable on their own, but they also point to what could be shifting sentiment regarding SPAC combinations.”

In light of the company’s lackluster earnings report (and a pending SEC investigation), Alex unpacks the company’s Q1, “but don’t think that we’re only singling out one company; others fit the bill, and more will in time.”

Join TechCrunch reporter Ron Miller and Patrik Liu Tran, co-founder and CEO of automated real-time data validation and quality monitoring platform Validio, on Thursday, May 27  at 9 a.m. PT/noon ET for a Clubhouse chat about ensuring data quality in the era of Big Data.

The world produces 2.5 quintillion bytes of data daily, but modern data infrastructure still lacks solutions for monitoring data quality and data validation.

Among other topics, they’ll discuss the build versus buy debate, how to better understand data failures, and why traditional methods for to identify data failures are no longer operational.

Click here to join the conversation.

Thanks very much for reading Extra Crunch; have a great week!

Walter Thompson
Senior Editor, TechCrunch
@yourprotagonist

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Here are five key predictions for what this road to further penetration will hold.

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If you fail to spot the warning signs, you’ll live to regret it. But do your due diligence and work constructively with them and, together, you might actually build a sustainable future.

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Connecting consumers with products they need through channels they already know and trust is both a massive revenue opportunity and a social good, providing financial resilience to families at a time when they need it most.

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Zeta Global’s IPO filing uncovers modest growth, strong adjusted profitability

Zeta Global raised north of $600 million in private capital in the form of both equity financing and debt, making it a unicorn worth understanding.

The gist is that Zeta ingests and crunches lots of data, helping its users market to their customers on a targeted basis throughout their individual buying lifecycles. In simpler terms, Zeta helps companies pitch customers in varied manners depending on their own characteristics.

You can imagine that, as the digital economy has grown, the sort of work Zeta Global supports has only expanded. So, has Zeta itself grown quickly? And does it have an attractive business profile?

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Develop a buyer’s guide to educate your startup’s sales team and customers

Every company wants to be innovative, but innovation comes with its share of difficulties. One key challenge for early-stage companies that are disrupting a particular space or creating a new category is figuring out how to sell a unique product to customers who have never bought such a solution.

This is especially the case when a solution doesn’t have many reference points and its significance may not be obvious.

Some buyers could use a walkthrough of the buying process. If you are building a singular product in a nascent market that necessitates forward-looking customers and want to drastically shorten sales cycles, create a buyer’s guide.

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Deep Science: Robots, meet world

This column aims to collect some of the most relevant recent discoveries and papers — particularly in, but not limited to, artificial intelligence — and explain why they matter.

In this edition, we have a lot of items concerned with the interface between AI or robotics and the real world. Of course, most applications of this type of technology have real-world applications, but specifically, this research is about the inevitable difficulties that occur due to limitations on either side of the real-virtual divide.

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Dividing responsibilities lets each leader play to their strengths and shortens the learning curve by 50%. So why aren’t more startups doing it?

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