3 data strategies for selling to developers

Welcome to Extra Crunch Tuesday

Many consumers are open to a slick sales pitch, but software developers generally know better.

Successful dev-focused marketing efforts steer these users toward free tools, but unless you know exactly what data to look for and how to measure it, your efforts will have limited impact.

Software companies hoping to connect with developers should treat end users like the “go-to-market side of the team,” advises Sam Richard, senior director of growth at OpenView, which has invested in companies like Datadog, Expensify and Calendly.

For example: Instead of simply pulling analytics from your production database, what if your GTM team polled stakeholders who touch revenue about the data points they use to make decisions? If you assigned a product manager to address their needs, draft a roadmap and develop an MVP, you might be surprised by what you learn.

“Don’t overthink it,” says Richard. “Selling to developers isn’t impossible — it’s just difficult.”

We’re making a virtual visit to western Pennsylvania today with TechCrunch City Spotlight: Pittsburgh, which starts at 10:30 a.m. PDT on Hopin.

Managing Editor Matt Burns will interview Pittsburgh Mayor Bill Peduto, Duolingo Head of Engineering Karin Tsai and CMU President Farnam Jahanian before a pitch-off where local startups have two minutes to put their best foot forward. Today’s event is free to attend, so we hope to see you there.

Thanks very much for reading Extra Crunch!

Walter Thompson
Senior Editor, TechCrunch
@yourprotagonist

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Late-stage capital is having a ‘cascading effect’ on European VC activity

Anna Heim and Alex Wilhelm spoke to a handful of international investors to learn more about how an influx of late-stage capital is driving larger and earlier funding rounds that have created widespread valuation expansion.

In Europe, this new trend where larger VC firms are hunting down Series A and B rounds is creating a cascading effect, “one in which formerly pre-IPO investors are reaching down to the Series C market, while Series C investors are also looking earlier,” they report.

Here’s who they spoke to:

• Vinoth Jayakumar, partner, Draper Espirit (London)
• Jai Das, president and partner, Sapphire Ventures (Palo Alto)
• Seth Pierrepont, partner, Accel (London)
• Michael Tolo, principal, Blackbird Ventures (Australia)

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Summer Sale: Save 10% on Extra Crunch membership

Sponsored by TechCrunch

From now until July 5, we are offering 10% off annual Extra Crunch memberships. This offer is valid for readers in the US, UK, Canada, Europe and Israel.

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VCs discuss the opportunities – and challenges – in Pittsburgh’s startup ecosystem

Ahead of today’s TechCrunch City Spotlight: Pittsburgh, Brian Heater spoke to Mayor Bill Peduto and Dave Mawhinney, the executive director of Carnegie Mellon University’s Swartz Center for Entrepreneurship, about the Steel City’s startup scene and what venture investing looks like.

“I think we’ve been able to convince investors from the coast that the companies don’t need to leave Pittsburgh in order to be highly successful and see their investment pay off,” Peduto told TechCrunch.

“However, I believe if we had more venture capital arriving here to help take early-stage companies into that critical next stage of expansion, it would build off itself and it would excel growth in all of the industry cluster, significantly.”

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SentinelOne’s upgraded IPO pricing is good news for Tiger, public markets and your local VC

The Exchange noted last week that SentinelOne’s IPO would be a “good heat check for the IPO market.” Given rapid growth and steady losses, how investors value it will help “explain the public market’s current appetite for loss-making startups,” Alex Wilhelm writes. “Today’s news implies healthy appetites.”

On Monday, the company bumped up its IPO price range to $31 to $32 per share, up from an initial price of $26 to $29 per share.

“It’s not a surprise to see the company moving toward strong IPO pricing,” Alex notes. “But golly gee, this is ‘spensive, right?”

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Why is Didi worth so much less than Uber?

Chinese ride-hailing behemoth Didi is worth “several tens of billions of dollars” less than U.S. counterpart Uber, Alex Wilhelm noted last week.

“And we can’t quite figure out why,” he writes.

It won’t be clear until Didi finally prices, but Alex ran through some numbers and noodled on why the Didi seems to be worth so much less.

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A startup’s guide to software delivery

“One of the biggest factors in the success of a startup is its ability to quickly and confidently deliver software,” Rob Zuber, the CTO of CircleCI, notes in a guest column.

“As more consumers interact with businesses through a digital interface and more products embrace those interfaces as the opportunity to differentiate, speed and agility are paramount. It’s what makes or breaks a company.”

Zuber notes that as your company grows, your software delivery strategy must evolve with you, and he lays out a strategy for making sure you avoid “time-consuming problems that could have been avoided” as your startup scales.

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Like the US, a two-tier venture capital market is emerging in Latin America

Alex Wilhelm and Anna Heim continued their exploration of the early-stage venture capital market, this time focusing on Latin American startups.

They uncovered that the dynamic of slow Series A rounds and speedy B rounds is not exclusively a phenomenon in the United States.

“The two-tier venture capital market is also showing up in Latin America, a globally important and rapidly expanding startup region,” they wrote. They noted, however, that the money isn’t equally distributed, tending to land in the pockets of “elite status” startups.

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Deep Science: Keeping AI honest in medicine, climate science and vision

Research papers come out far too frequently for anyone to read them all. That’s especially true in the field of machine learning, which now affects (and produces papers in) practically every industry and company.

This column, by Devin Coldewey, aims to collect some of the more interesting recent discoveries and papers — particularly in, but not limited to, artificial intelligence — and explain why they matter.

Last week, Devin contributed a number of entries aimed at identifying or confirming bias or cheating behaviors in machine learning systems, or failures in the data that support them, plus a purely visually appealing project from the University of Washington being presented at the Conference on Computer Vision and Pattern Recognition.

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