Freshworks raises $150M Series H on $3.5B valuation

Freshworks, a company that makes a variety of business software tools, from CRM to help-desk software, announced a $150 million Series H investment today from Sequoia Capital, CapitalG (formerly Google Capital) and Accel on a hefty $3.5 billion valuation. The late-stage startup has raised almost $400 million, according to Crunchbase data.

The company has been building an enterprise SaaS platform to give customers a set of integrated business tools, but CEO and co-founder Girish Mathrubootham says they will be investing part of this money in R&D to keep building out the platform.

To that end, the company also announced today a new unified data platform called the “Customer-for-Life Cloud” that runs across all of its tools. “We are actually investing in really bringing all of this together to create the “Customer-for-Life Cloud,” which is how you take marketing, sales, support and customer success — all of the aspects of a customer across the entire life cycle journey and bring them to a common data model where a business that is using Freshworks can see the entire life cycle of the customer,” Mathrubootham explained.

While Mathrubootham was not ready to commit to an IPO, he said they are in the process of hiring a CFO and are looking ahead to one day becoming a public company. “We don’t have a definite timeline. We want to go public at the right time. We are making sure that as a company that we are ready with the right processes and teams and predictability in the business,” he said.

In addition, he says he will continue to look for good acquisition targets, and having this money in the bank will help the company fill in gaps in the product set should the right opportunity arise. “We don’t generally acquire revenue, but we are looking for good technology teams both in terms of talent, as well as technology that would help give us a jumpstart in terms of go-to-market.” It hasn’t been afraid to target small companies in the past, having acquired 12 already.

Freshworks, which launched in 2010, has almost 2,500 employees, a number that’s sure to go up with this new investment. It has 250,00 customers worldwide, including almost 40,000 paying customers. These including Bridgestone Tires, Honda, Hugo Boss, Toshiba and Cisco.

CTO.ai’s developer shortcuts eliminate coding busywork

There’s too much hype about mythical “10X developers”. Everyone’s desperate to hire these ‘ninja rockstars’. In reality, it’s smarter to find ways of deleting annoying chores for the coders you already have. That’s where CTO.ai comes in.

Emerging from stealth today, CTO.ai lets developers build and borrow DevOps shortcuts. These automate long series of steps they usually have to do manually thanks to integrations with GitHub, AWS, Slack, and more. CTO.ai claims it can turn a days-long process like setting up a Kubernetes cluster into a 15-minute task even sales people can handle. The startup offers both a platform for engineering and sharing shortcuts, and a service where it can custom build shortcuts for big customers.

What’s remarkable about CTO.ai is that amidst a frothy funding environment, the 60-person team quietly bootstrapped its way to profitability over the past two years. Why take funding when revenue was up 400% in 18 months? But after a chance meeting aboard a plane connected its high school dropout founder Kyle Campbell with Slack CEO Stewart Butterfield, CTO.ai just raised a $7.5 million seed round led by Slack Fund and Tiger Global.

“Building tools that streamline software development is really expensive for companies, especially when they need their developers focused on building features and shipping to customers” Campbell tells me. The same way startups don’t build their own cloud infrastructure and just use AWS, or don’t build their own telecom APIs and just use Twilio, he wants CTO.ai to be the ‘easy button’ for developer tools.

Teaching snakes to eat elephants

“I’ve been a software engineer since the age of 8” Campbell recalls. In skate-punk attire with a snapback hat, the young man meeting me in a San Francisco mission district cafe almost looked too chill to be a prolific coder. But that’s kind of the point. His startup makes being a developer more accessible.

After spending his 20s in software engineering groups in the Bay, Campbell started his own company Retsly that bridged developers to real estate listings. In 2014, it was acquired by property tech giant Zillow where he worked for a few years.

That’s when he discovered the difficulty of building dev tools inside companies with other priorities. “It’s the equivalent of a snake swallowing an elephant” he jokes. Yet given these tools determine how much time expensive engineers waste on tasks below their skill level, their absence can drag down big enterprises or keep startups from rising.

CTO.ai shrinks the elephant. For example, the busywork of creating a Kubernetes cluster such as having to the create EC2 instances, provision on those instances, and then provision a master node gets slimmed down to just running a shortcut. Campbell writes that “tedious tasks like running reports can be reduced from 1,000 steps down to 10” through standardization of workflows that turn confusing code essays into simple fill-in-the-blank and multiple-choice questions.

The CTO.ai platform offers a wide range of pre-made shortcuts that clients can piggyback on, or they can make and publish their own through a flexible JavaScript environment for the rest of their team or the whole community to use. Companies that need extra help can pay for its DevOps-As-A-Service and reliability offerings to get shortcuts made to solve their biggest problems while keeping everything running smoothly.

5(2X) = 10X

Campbell envisions a new way to create a 10X engineer that doesn’t depend on widely mocked advice on how to spot and capture them like trophy animals. Instead, he believes 1 developer can make 5 others 2X more efficient by building them shortcuts. And it doesn’t require indulging bad workplace or collaboration habits.

With the new funding that also comes from Yaletown Partners, Pallasite Ventures, Panache Ventures and Jonathan Bixby, CTO.ai wants to build deeper integrations with Slack so developers can run more commands right from the messaging app. The less coding required for use, the broader the set of employees that can use the startup’s tools. CTO.ai may also build a self-service tier to augment its seats plus complexity model for enterprise pricing.

Now it’s time to ramp up community outreach to drive adoption. CTO.ai recently released a podcast which saw 15,000 downloads in its first 3 weeks, and it’s planning some conference appearances. It also sees virality through its shortcut author pages, which like GitHub profiles let developers show off their contributions and find their next gig.

One risk is that GitHub or another core developer infrastructure provider could try to barge directly into CTO.ai’s business. Google already has Cloud Composer while GitHub launched Actions last year. Campbell says its defense comes through neutrally integrating with everyone, thereby turning potential competitors into partners.

The funding firepower could help CTO.ai build a lead. With every company embracing software, employers battling to keep developers happy, and teams looking to get more of their staff working with code, the startup sits at the intersection of some lucrative trends of technological empowerment.

“I have 3-year-old at home and I think about what it will be like when he comes into creating things online” Campbell concludes. “We want to create an amazing future for software developers, introducing automation so they can focus on what makes them such an important aspect. Devs are defining society!”

[Image Credit: Disney/Pixar via WallHere Goodfon]

Startup Benchmarks

All Good to Great companies began the process of finding a path to greatness by confronting the brutal facts about the reality of their business. When you start with an honest and diligent effort to determine the truth of your situation, the right decisions often become self-evident.”

— Jim Collins, author of Good to Great

I joked the other day that some of the best fairytales are written in Excel. Forecasting is sometimes done by dragging the mouse based on many assumptions, because it’s hard to predict the future.

One question that keeps coming up when speaking with early stage entrepreneurs when it comes to funding, is what metrics the company needs to hit to raise seed/series A/B etc:

  • What’s a good conversion rate?
  • What should our MRR growth be?
  • Is my churn rate below the category average?

While there isn’t a single magic number or set formula, understanding industry benchmarks can be really helpful to keep a finger on the pulse to measure the health of the company and make more informed forecasts. Benchmarks are typically specific to stage/business model/geo.

In this post I’ll focus on benchmarking resources for seed and series A in the following three categories:

  • SaaS
  • B2C / Consumer apps
  • Deep tech

The following table from Rob Go at NextView Ventures is a great start to help answer the question of what traction/milestones are needed to raise seed and series A (US focus).

Source: Rob Go on Medium

It’s important to mention that benchmarks alone can’t guarantee funding. Investors look beyond top line metrics to assess other important factors. In Rob Go’s words:

For seed and Series A deals, investors will also need to see a high-potential team with founder/market fit, a large and attractive market opportunity, and a business model with increasing returns to scale. Top-line metrics are indicators of success, not the one bar to clear to raise funding for your startup.

Rob Go: How Much Traction Do You Really Need to Raise a Seed or Series A Round?

Software as a Service (Saas) benchmarks

In SaaS the main benchmarks being measured are revenue growth, sales efficiency (unit economics), churn and burn rate. One of my favourite resources for SaaS benchmarking is The SaaS Napkin by Point Nine Capital. If nothing else, for its simplicity (back of the napkin) but also for the fund’s commitment to keep updating the metrics since 2016. You can read more about the methodology here and download a high res PDF here.

Source: The SaaS Napkin

Other interesting SaaS benchmarking tools/figures:

Example of Baremetrics revenue per user benchmarks

Consumer apps and services

The main B2C benchmarks have to do with traction: growth in user acquisition, user retention/churn, monetisation, as well as the effectiveness of consumer marketing + virality. 500 Startups created a helpful primer on key B2C metrics.

B2C benchmarks tend to be specific to the type of service or business model. eCommerce is different than free consumer apps, games are on a league of their own, etc. With the explosion in DTC products (see my post on VC Cafe), they probably deserve a category of benchmarks on their own.

Andrew Chen is a partner at Andreessen Horowitz consumer team, and I particularly enjoyed his series of tweets and LinkedIn posts on ‘what good looks like in consumer tech’.

For example, this post on 10 magic metrics indicating a consumer tech startup probably has product/market fit

  1. cohort retention curves that flatten (stickiness)
  2. actives/reg > 25% (validates TAM). power user curve showing a smile — with a big concentration of engaged users (you grow out from this strong core)
  3. viral factor >0.5 (enough to amplify other channels)
  4. dau/mau > 50% (it’s part of a daily habit)
  5. market-by-market (or logo-by-logo, if SaaS) comparison where denser/older networks have higher engagement over time (network effects)
  6. D1/D7/D30 that exceeds 60/30/15 (daily frequency)
  7. revenue or activity expansion on a *per user* basis over time — indicates deeper engagement / habit formation
  8. >60% organic acquisition with real scale (better to have zero CAC)
  9. For subscription, >65% annual retention (paying users are sticking)
  10. >4x annual growth rate across topline metrics

Other resources on B2C benchmarks:

Benchmarks for deep tech startups

Deep tech is harder to measure/compare, especially in the early stage. Deep tech startups can take a risk on market timing, which means that there’s less traction to evaluate and more emphasis is put on the team and the defensibility of the IP. Part of the challenge in deep tech is getting to revenue and scaling it. There’s a slower adoption curve than SaaS or consumer, and often requires market education and selling services to enter the market.

Other resources for benchmarking deep tech startups:

Startup Benchmarks

All Good to Great companies began the process of finding a path to greatness by confronting the brutal facts about the reality of their business. When you start with an honest and diligent effort to determine the truth of your situation, the right decisions often become self-evident.”

— Jim Collins, author of Good to Great

I joked the other day that some of the best fairytales are written in Excel. Forecasting is sometimes done by dragging the mouse based on many assumptions, because it’s hard to predict the future.

One question that keeps coming up when speaking with early stage entrepreneurs when it comes to funding, is what metrics the company needs to hit to raise seed/series A/B etc:

  • What’s a good conversion rate?
  • What should our MRR growth be?
  • Is my churn rate below the category average?

While there isn’t a single magic number or set formula, understanding industry benchmarks can be really helpful to keep a finger on the pulse to measure the health of the company and make more informed forecasts. Benchmarks are typically specific to stage/business model/geo.

In this post I’ll focus on benchmarking resources for seed and series A in the following three categories:

  • SaaS
  • B2C / Consumer apps
  • Deep tech

The following table from Rob Go at NextView Ventures is a great start to help answer the question of what traction/milestones are needed to raise seed and series A (US focus).

Source: Rob Go on Medium

It’s important to mention that benchmarks alone can’t guarantee funding. Investors look beyond top line metrics to assess other important factors. In Rob Go’s words:

For seed and Series A deals, investors will also need to see a high-potential team with founder/market fit, a large and attractive market opportunity, and a business model with increasing returns to scale. Top-line metrics are indicators of success, not the one bar to clear to raise funding for your startup.

Rob Go: How Much Traction Do You Really Need to Raise a Seed or Series A Round?

Software as a Service (Saas) benchmarks

In SaaS the main benchmarks being measured are revenue growth, sales efficiency (unit economics), churn and burn rate. One of my favourite resources for SaaS benchmarking is The SaaS Napkin by Point Nine Capital. If nothing else, for its simplicity (back of the napkin) but also for the fund’s commitment to keep updating the metrics since 2016. You can read more about the methodology here and download a high res PDF here.

Source: The SaaS Napkin

Other interesting SaaS benchmarking tools/figures:

Example of Baremetrics revenue per user benchmarks

Consumer apps and services

The main B2C benchmarks have to do with traction: growth in user acquisition, user retention/churn, monetisation, as well as the effectiveness of consumer marketing + virality. 500 Startups created a helpful primer on key B2C metrics.

B2C benchmarks tend to be specific to the type of service or business model. eCommerce is different than free consumer apps, games are on a league of their own, etc. With the explosion in DTC products (see my post on VC Cafe), they probably deserve a category of benchmarks on their own.

Andrew Chen is a partner at Andreessen Horowitz consumer team, and I particularly enjoyed his series of tweets and LinkedIn posts on ‘what good looks like in consumer tech’.

For example, this post on 10 magic metrics indicating a consumer tech startup probably has product/market fit

  1. cohort retention curves that flatten (stickiness)
  2. actives/reg > 25% (validates TAM). power user curve showing a smile — with a big concentration of engaged users (you grow out from this strong core)
  3. viral factor >0.5 (enough to amplify other channels)
  4. dau/mau > 50% (it’s part of a daily habit)
  5. market-by-market (or logo-by-logo, if SaaS) comparison where denser/older networks have higher engagement over time (network effects)
  6. D1/D7/D30 that exceeds 60/30/15 (daily frequency)
  7. revenue or activity expansion on a *per user* basis over time — indicates deeper engagement / habit formation
  8. >60% organic acquisition with real scale (better to have zero CAC)
  9. For subscription, >65% annual retention (paying users are sticking)
  10. >4x annual growth rate across topline metrics

Other resources on B2C benchmarks:

Benchmarks for deep tech startups

Deep tech is harder to measure/compare, especially in the early stage. Deep tech startups can take a risk on market timing, which means that there’s less traction to evaluate and more emphasis is put on the team and the defensibility of the IP. Part of the challenge in deep tech is getting to revenue and scaling it. There’s a slower adoption curve than SaaS or consumer, and often requires market education and selling services to enter the market.

Other resources for benchmarking deep tech startups:

This startup is making customized sexual harassment training that it says employees won’t hate (or forget)

If you work for someone else, you likely know the drill: in comes that annual email reminding you that it’s time for unconscious bias or sexual harassment training, and if you could please finish up this mandatory module by this date, that would be terrific.

The email — not to mention the programming itself — is straight out of “Office Space.” Little surprise that when Anne Solmssen, a Harvard-trained computer scientist, happened to call a friend recently who was clicking through his own company-sponsored training program, his answer to how it was going was, “It’s more interesting when I have baseball on.”

Solmssen has some other ideas about how to make sexual harassment training far more interesting and less “cringe-worthy.” Indeed, she recently joined forces with Roxanne Petraeus, another Harvard grad, to create Ethena, a software-as-a-service startup that’s promising customizable training delivered in bite-size segments that caters to individuals based on how much they already know about sexual harassment in the workplace. The software will also be sector-specific when it’s released more widely in the first quarter of next year.

The company first came together this past summer led by Petraeus, who joined the U.S. Reserve Officers’ Training Corps to help defray the cost of her Ivy League education and wound up spending seven years in the U.S. Army, including as a civil affairs officer, before co-founding an online meals marketplace, then spending a year with McKinsey & Co. to get a better handle on how businesses are run.

Petraeus says that across her experience, and particularly in the Army, she had “great leaders” who were “thoughtful about their [reports’] development goals and what was happening in their personal lives, and brought out the best in their people, rather than making them feel less than or marginalized.”

Still, she was aware that from an institutional standpoint, most harassment training is not thoughtful, that it’s a matter of checking boxes on an annual basis to ensure compliance with different state laws, depending on where an organization is headquartered. She marveled that so much of the content employees are being forced to consume seems “designed for a 1980s law firm.”

Solmssen was meanwhile working for a venture-backed public safety software company, Mark43. She was getting along just fine, too, but when a friend put the two in touch on the hunch that their engineering talent and vision could amount to something, that instinct proved right.

“I’d been working for Mark43 for four years, and I wasn’t particularly interested in starting a business,” Solmssen says. “But I fell in love with Roxanne and this idea, and I came to this thinking that someone needs to make [this training process] better. We’re still using the tools and technologies that we’ve had since 1997.”

So how is what they’re building different than what’s currently available? In lots of ways, seemingly. For starters, Ethena doesn’t want employees to “knock it out all at once” in an hour or two of training at the end of each year. Instead, it’s creating what it calls monthly “nudges” that deliver relevant studies and questions on a monthly basis — information that can then be used in an all-hands meeting, for example, helping to reinforce its goals.

It’s also focused on sending content and questions to people that’s iterative and that evolves based on how an individual responds. A new hire might answer very differently than a sponsor of other women within an organization, for example. It’s a stark contrast to to the black-and-white scenarios that every employee is typically presented. (Think: “Judy and Brian go to a bar after work.”)

These subtleties are a significant development, argues Petraeus, because “traditional training implicitly tells employees that going to spending time together outside of work is bad for mentorship. It’s why you hear things like, ‘I just hired my first female analyst; can I get into an Uber with her when we’re traveling?’ ” Turning every mixed-gender occasion into a potential minefield is “not the message we should be conveying.”

Yet it’s a message that’s being absorbed. According to a survey conducted earlier this year by LeanIn.Org and SurveyMonkey, 60% of managers who are men are now uncomfortable participating in a common work activity with a woman, such as mentoring, working alone or socializing together. That’s a 32% jump from a year ago. According to that same survey, senior-level men are now 12 times more hesitant to have one-on-one meetings with junior women, nine times more hesitant to travel together and six times more hesitant to have work dinners together.

Even the U.S. Equal Employment Opportunity Commission thinks sexual harassment training has gone wrong somewhere, noting that it hasn’t worked as a prevention tool in part because it’s been too focused on simply avoiding legal liability. Indeed, a few years ago, a task force studying harassment in the workplace on behalf of the EEOC concluded that “effective training cannot occur in a vacuum – it must be part of a holistic culture of non-harassment that starts at the top.” Similarly, it added, “one size does not fit all: training is most effective when tailored to the specific workforce and workplace and different cohorts of employees.”

Toward that end, and with compliance in mind, Ethena is also modernizing the content it delivers, including as it pertains to dating at work, which definitely happens; and inclusivity around pregnant colleagues, who are often subtly marginalized; and transgender colleagues, who can also find themselves feeling either misunderstood or overlooked by current sexual harassment training materials.

There’s also a heavy focus on analytics. If 60% of employees don’t know about a company’s policies around office dating, for example, or employees in an outfit’s marketing department appear to know less about an organization’s values than other departments, it will flag these things so managers can take preventative action. (“Say there’s a new manager in the LA office where employees seem to be answering less consistently,” suggests Solmssen. “We can provide additional training to get that person up to speed.”)

For Petraeus — who is the daughter-in-law of retired general and former CIA director David Petraeus — the overarching goal is to kill off mandatory yearly training where the takeaway for many employees, the fundamental standard, is, “Can I go to jail for this comment?”

It’s too soon to say if Ethena will be successful. It’s only halfway through a pilot training program at the moment. But Solmssen and Petraeus are strong pitchmen, and they say their software will be available beginning in the first quarter of next year for $4 per employee per month, which is on a par with other e-learning programs.

The startup has also won the support of early backers who’ve already given the months-old outfit $850,000 to start hiring. Among those investors: Neo, a venture fund started last year by serial entrepreneur Ali Partovi; Village Global; and Jane VC, which is a fund focused on women-led startups.

Numerous angel investors have also written Ethena a check, including Reshma Saujani, who is the founder of the organization Girls Who Code, and a handful of military veterans.

As for the last group, “they’re not a group that’s typically represented in startup ventures,” observes Petraeus, “but in terms of leadership and thinking about how to get a diverse team oriented around the same goal,” they’re hard to match.

Market research platform Milieu Insight raises $2.4 million to launch in more Southeast Asian countries

Milieu Insight, a Singapore-based market research and data platform, announced today that it has raised $2.4 million in pre-A funding. The round, led by MassMutual Ventures Southeast Asia, will be used on product development and to launch in four new Southeast Asian countries, Malaysia, Indonesia, the Philippines and Vietnam. The startup’s platform, called Milieu Surveys, is already available in Singapore and Thailand and has signed more than 45 clients.

This brings Milieu Insight’s total funding so far to $3.15 million, including a seed round announced in November 2018. Founded in December 2016 by CEO Gerald Ang, who previously worked at global research firms including GfK and YouGov, Milieu Insight seeks to make market research and data analysis accessible to smaller businesses and organizations. Milieu Portraits, its consumer segmentation tool, returns insights about specific demographics, including what products, media and brands they prefer, while Milieu Studies allows companies to create their own studies.

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COO Stephen Tracy told TechCrunch in an email that the startups’ four new markets were picked because “they are in high demand among existing research buyers who want to study consumer trends, particularly because the market dynamics in these countries are evolving fast.” Milieu focuses exclusively on mobile data since smartphone penetration is still growing quickly in many Southeast Asian markets.

He added “one other dynamic that makes us particularly excited about expanding across Southeast Asia is that, through our investment in tech and automation, we’re able to sell market research solutions at considerably more affordable price points (i.e. research studies as low as US$350). Meaning our platform can also activate new spending among businesses/organizations who couldn’t previously afford it, such as charities/non-profits, academic institutions and startups.”

Milieu Insight’s competitors include traditional research firms like Kantar and YouGov for Milieu Studies and Global Web Index for Milieu Portraits. Tracy says the startup’s competitive edge is its end-to-end solution. “That is, there’s no other company that offers a single platform that connects an audience (i.e. our managed consumer panel) with a SaaS service that allows you to access consumer profiling data on-demand as well as launch bespoke consumer studies and get results in just a few hours, all within a self-serve environment.”

In a press statement, MassMutual Ventures managing director Anvesh Ramineni said “Milieu’s impressive team has built a world-class product, making market research services affordable, accessible and more relevant in today’s mobile first landscape. We are pleased to lead Milieu’s current round and look forward to supporting the company as it scales across the region.”

Why per-seat pricing needs to die in the age of AI

Pricing is the most important, least-discussed element of the software industry. In the past, founders could get away with giving pricing short shrift under the mantra, “the best product will ultimately win.” No more.

In the age of AI-enabled software, pricing and product are linked; pricing fundamentally impacts usage, which directly informs product quality. 

Therefore, pricing models that limit usage, like the predominant per-seat per month structure, limit quality. And thus limit companies.

For the first time in 20 years, there is a compelling argument to make for changing the way that SaaS is priced. For those selling AI-enabled software, it’s time to examine new pricing models. And since AI is currently the best-funded technology in the software industry — by far — pricing could soon be changing at a number of vendors.

Why per-seat pricing needs to die in the age of AI

Per-seat pricing makes AI-based products worse. Traditionally, the functionality of software hasn’t changed with usage. Features are there whether users take advantage of them or not — your CRM doesn’t sprout new bells and whistles when more employees log in; it’s static software. And since it’s priced per-user, a customer incurs more costs with every user for whom it’s licensed.

AI, on the other hand, is dynamic. It learns from every data point it’s fed, and users are its main source of information; usage of the product makes the product itself better. Why, then, should AI software vendors charge per user, when doing so inherently disincentivizes usage? Instead, they should design pricing models that maximize product usage, and therefore, product value.

Per-seat pricing hinders AI-based products from capturing value they create

AI-enabled software promises to make people and businesses far more efficient, transforming every aspect of the enterprise through personalization. Software tailored to the specific needs of the user has been able to command a significant premium relative to generic competitors; for example, Salesforce offers a horizontal CRM that must serve users from Fortune 100s to SMBs across every industry. Veeva, which provides a CRM optimized for the life sciences vertical, commands a subscription price many multiples higher, in large part because it has been tailored to the pharma user’s end needs.

AI-enabled software will be even more tailored to the individual context of each end-user, and thus, should command an even higher price. Relying on per-seat pricing gives buyers an easy point of comparison ($/seat is universalizable) and immediately puts the AI vendor on the defensive. Moving away from per-seat pricing allows the AI vendor to avoid apples-to-apples comparisons and sell their product on its own unique merits. There will be some buyer education required to move to a new model, but the winners in the AI era will use these discussions to better understand and serve their customers.

Per-seat pricing will ultimately cause AI vendors to cannibalize themselves

Probably the most important upsell lever software vendors have traditionally used is tying themselves to the growth of their customers. As their customers grow, the logic goes, so should the vendors’ contract (presumably because the vendor had some part in driving this growth). 

Tethering yourself to per-seat pricing will make contract expansion much harder.

However, effective AI-based software makes workers significantly more efficient. As such, seat counts should not need to grow linearly with company growth, as they have in the era of static software. Tethering yourself to per-seat pricing will make contract expansion much harder. Indeed, it could result in a world where the very success of the AI software will entail contract contraction.

How to price software in the age of AI

Here are some key ideas to keep top of mind when thinking about pricing AI software:

  • Start by using ROI analysis to figure out how much to charge

This is the same place to start as in static software land. (Check out my primer on this approach here.) Work with customers to quantify the value your software delivers across all dimensions. A good rule of thumb is that you should capture 10-30% of the value you create. In dynamic software land, that value may actually increase over time as the product is used more and the dataset improves. It’s best to calculate ROI after the product gets to initial scale deployment within a company (not at the beginning). It’s also worth recalculating after a year or two of use and potentially adjusting pricing. Tracking traditionally consumer usage metrics like DAU/MAU becomes absolutely critical in enterprise AI, as usage is arguably the core driver of ROI.

While ROI is a good way to determine how much to charge, do not use ROI as the mechanism for how to charge. Tying your pricing model directly to ROI created can cause lots of confusion and anxiety when it comes time to settle up at year-end. This can create issues with establishing causality and sets up an unnecessarily antagonistic dynamic with the customer. Instead, use ROI as a level-setting tool and other mechanisms to determine how to arrive at specific pricing.

Former SAP CEO Bill McDermott taking over as ServiceNow CEO

When Bill McDermott announced he was stepping down as CEO at SAP a couple of weeks ago, it certainly felt like a curious move — but he landed on his feet pretty quickly. ServiceNow announced he would be taking over as CEO there. The transition will take place at year-end.

If you’re wondering what happened to the current ServiceNow CEO, John Donahoe, well he landed a job as CEO at Nike. The CEO carousel goes round and round (and painted ponies go up and down).

Jeff Miller, lead independent director on the ServiceNow board of directors, was “thrilled” to have McDermott fill the void left by Donahoe’s departure. “His global experience and proven track record will provide for a smooth transition and continued strong leadership. Bill will further enhance ServiceNow’s momentum and reputation as a digital workflows leader committed to customer success, and as a preferred strategic partner enabling enterprise digital transformation,” Miller said in a statement.

Jennifer Morgan and Christian Klein replaced McDermott as co-CEOs at SAP, and during the announcement, McDermott indicated he would stay until the end of the year to help with the transition. After that, no vacation for McDermott, who will apparently start at ServiceNow after his obligations at SAP end.

As Frederic Lardinois wrote regarding McDermott’s resignation:

I last spoke to McDermott about a month ago, during a fireside chat at our TechCrunch Sessions: Enterprise event. At the time, I didn’t come away with the impression that this was a CEO on his way out (though McDermott reminded me that if he had already made his decision a month ago, he probably wouldn’t have given it away).

ServiceNow is a much different company than SAP. SAP was founded in 1972 and was a traditional on-premises software company. ServiceNow was founded in 2004 and was born as a SaaS company. While McDermott was part of a transition from a traditional, on-premises enterprise software company to the cloud, working at ServiceNow he will be leading a much smaller organization. Published estimates have SAP at around 100,000 employees, while ServiceNow now has around 10,000.

It’s worth noting that the company made the announcement after the market closed and it announced its latest quarterly earnings. Wall Street did not appear to the like news, as the stock was down $13.34, or 5.84%, in early after-hours trading.

Aurora Insight emerges from stealth with $18M and a new take on measuring wireless spectrum

Aurora Insight, a startup that provides a “dynamic” global map of wireless connectivity that it built and monitors in real time using AI combined with data from sensors on satellites, vehicles, buildings, aircraft and other objects, is emerging from stealth today with the launch of its first publicly-available product, a platform providing insights on wireless signal and quality covering a range of wireless spectrum bands, offered as a cloud-based, data-as-a-service product.

“Our objective is to map the entire planet, charting the radio waves used for communications,” said Brian Mengwasser, the co-founder and CEO. “It’s a daunting task.” He said that to do this the company first “built a bunker” to test the system before rolling it out at scale.

With it, Aurora Insight is also announcing that it has raised $18 million in funding — an aggregate amount that reaches back to its founding in 2016 and covering both a seed round and Series A — from an impressive list of investors. Led by Alsop Louie Partners and True Ventures, backers also include Tippet Venture Partners, Revolution’s Rise of the Rest Seed Fund, Promus Ventures, Alumni Ventures Group, ValueStream Ventures, and Intellectus Partners.

The area of measuring wireless spectrum and figuring out where it might not be working well (in order to fix it) may sound like an arcane area, but it’s a fairly essential one.

Mobile technology — specifically, new devices and the use of wireless networks to connect people, objects and services — continues to be the defining activity of our time, with more than 5 billion mobile users on the planet (out of 7.5 billion people) today and the proportion continuing to grow. With that, we’re seeing a big spike in mobile internet usage, too, with more than 5 billion people, and 25.2 billion objects, expected to be using mobile data by 2025, according to the GSMA.

The catch to all this is that wireless spectrum — which enables the operation of mobile services — is inherently finite and somewhat flaky in how its reliability is subject to interference. That in turn is creating a need for a better way of measuring how it is working, and how to fix it when it is not.

“Wireless spectrum is one of the most critical and valuable parts of the communications ecosystem worldwide,” said Rohit Sharma, partner at True Ventures and Aurora Insight board member, in a statement. “To date, it’s been a massive challenge to accurately measure and dynamically monitor the wireless spectrum in a way that enables the best use of this scarce commodity. Aurora’s proprietary approach gives businesses a unique way to analyze, predict, and rapidly enable the next-generation of wireless-enabled applications.”

If you follow the world of wireless technology and telcos, you’ll know that wireless network testing and measurement is an established field, about as old as the existence of wireless networks themselves (which says something about the general reliability of wireless networks). Aurora aims to disrupt this on a number of levels.

Mengwasser — who co-founded the company with Jennifer Alvarez, the CTO who you can see presenting on the company here — tells me that a lot of the traditional testing and measurement has been geared at telecoms operators, who own the radio towers, and tend to focus on more narrow bands of spectrum and technologies.

The rise of 5G and other wireless technologies, however, has come with a completely new playing field and set of challenges from the industry.

Essentially, we are now in a market where there are a number of different technologies coexisting — alongside 5G we have earlier network technologies (4G, LTE, Wifi); a potential set of new technologies. And we have a new breed of companies are building services that need to have close knowledge of how networks are working to make sure they remain up and reliable.

Mengwasser said Aurora is currently one of the few trying to tackle this opportunity by developing a network that is measuring multiples kinds of spectrum simultaneously, and aims to provide that information not just to telcos (some of whom have been working with Aurora while still in stealth) but the others kinds of application and service developers that are building businesses based on those new networks.

“There is a pretty big difference between us and performance measurement, which typically operates from the back of a phone and tells you when have a phone in a particular location,” he said. “We care about more than this, more than just homes, but all smart devices. Eventually, eerything will be connected to network so we are aiming to provide intelligence on that.”

One example are drone operators who are building delivery networks: Aurora has been working with at least one while in stealth to help develop a service, Mengwasser said, although he declined to say which one. (He also, incidentally, specifically declined to say whether the company had talked with Amazon.)

5G is a particularly tricky area of mobile network spectrum and services to monitor and tackle, one reason why Aurora Insight has caught the attention of investors.

“The reality of massive MIMO beamforming, high frequencies, and dynamic access techniques employed by 5G networks means it’s both more difficult and more important to quantify the radio spectrum,” said Gilman Louie of Alsop Louie Partners, in a statement. “Having the accurate and near-real-time feedback on the radio spectrum that Aurora’s technology offers could be the difference between building a 5G network right the first time, or having to build it twice.” Louie is also sitting on the board of the startup.

Greylock GP Sarah Guo is as bullish on SaaS as ever

Hello and welcome back to Equity, TechCrunch’s venture capital-focused podcast, where each week we discuss other people’s money and what sense their investment choices make (or don’t).

This week was honestly a treat. We had Kate Clark in the studio along with Alex Wilhelm and a special guest, Sarah Guo from Greylock Partners, a venture firm (obviously). Guo has the distinction of having the best-ever fun fact on the show.

We kicked off with Grammarly, a company that recently put $90 million into its accounts. We chatted about for whom it was built, and if we use it today. One thing that felt clear was that consumers are more willing than before to pay for their tooling. And that means that companies like Grammarly may prove strong investment candidates.

Next, we hit on two more rounds, namely Tiger Global’s investment into Lattice and Clari’s $60 million Series D. Starting with Lattice, a performance management company founded by none other than Sam Altman’s brother, Jack. The startup raised $25 million from Tiger Global; read more about that here.

Clari led us to a discussion of vertical SaaS, and Guo’s views on the future of SaaS products (she’s bullish). Alex and Guo had a lot to say on this subject.

After talking over a few rounds, the discussion turned to the Q3 venture market. A few things stood out from the data and projections. First, that early-stage fundraising was a little light in the quarter. It could be a single-quarter wobble, but the data was worth chewing on all the same. And, second, that seed deal and dollar volume were hot once again.

And we wrapped with a discussion of Tempest, a new sobriety-focused startup that raised a $10 million round. Honestly, we aren’t sure how we feel about the business model. Please let us know if you have thoughts.

It was a good time. A big thanks to Guo for coming on the show, and a shout-out to the team that makes Equity happen: Chris Gates and Henry Pickavet.

Equity drops every Friday at 6:00 am PT, so subscribe to us on iTunesOvercast, Pocketcast, Downcast and all the casts.