Jul
29
2021
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4 key areas SaaS startups must address to scale infrastructure for the enterprise

Startups and SMBs are usually the first to adopt many SaaS products. But as these customers grow in size and complexity — and as you rope in larger organizations — scaling your infrastructure for the enterprise becomes critical for success.

Below are four tips on how to advance your company’s infrastructure to support and grow with your largest customers.

Address your customers’ security and reliability needs

If you’re building SaaS, odds are you’re holding very important customer data. Regardless of what you build, that makes you a threat vector for attacks on your customers. While security is important for all customers, the stakes certainly get higher the larger they grow.

Given the stakes, it’s paramount to build infrastructure, products and processes that address your customers’ growing security and reliability needs. That includes the ethical and moral obligation you have to make sure your systems and practices meet and exceed any claim you make about security and reliability to your customers.

Here are security and reliability requirements large customers typically ask for:

Formal SLAs around uptime: If you’re building SaaS, customers expect it to be available all the time. Large customers using your software for mission-critical applications will expect to see formal SLAs in contracts committing to 99.9% uptime or higher. As you build infrastructure and product layers, you need to be confident in your uptime and be able to measure uptime on a per customer basis so you know if you’re meeting your contractual obligations.

While it’s hard to prioritize asks from your largest customers, you’ll find that their collective feedback will pull your product roadmap in a specific direction.

Real-time status of your platform: Most larger customers will expect to see your platform’s historical uptime and have real-time visibility into events and incidents as they happen. As you mature and specialize, creating this visibility for customers also drives more collaboration between your customer operations and infrastructure teams. This collaboration is valuable to invest in, as it provides insights into how customers are experiencing a particular degradation in your service and allows for you to communicate back what you found so far and what your ETA is.

Backups: As your customers grow, be prepared for expectations around backups — not just in terms of how long it takes to recover the whole application, but also around backup periodicity, location of your backups and data retention (e.g., are you holding on to the data too long?). If you’re building your backup strategy, thinking about future flexibility around backup management will help you stay ahead of these asks.

Jul
20
2021
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How we built an AI unicorn in 6 years

Today, Tractable is worth $1 billion. Our AI is used by millions of people across the world to recover faster from road accidents, and it also helps recycle as many cars as Tesla puts on the road.

And yet six years ago, Tractable was just me and Raz (Razvan Ranca, CTO), two college grads coding in a basement. Here’s how we did it, and what we learned along the way.

Build upon a fresh technological breakthrough

In 2013, I was fortunate to get into artificial intelligence (more specifically, deep learning) six months before it blew up internationally. It started when I took a course on Coursera called “Machine learning with neural networks” by Geoffrey Hinton. It was like being love struck. Back then, to me AI was science fiction, like “The Terminator.”

Narrowly focusing on a branch of applied science that was undergoing a paradigm shift which hadn’t yet reached the business world changed everything.

But an article in the tech press said the academic field was amid a resurgence. As a result of 100x larger training data sets and 100x higher compute power becoming available by reprogramming GPUs (graphics cards), a huge leap in predictive performance had been attained in image classification a year earlier. This meant computers were starting to be able to understand what’s in an image — like humans do.

The next step was getting this technology into the real world. While at university — Imperial College London — teaming up with much more skilled people, we built a plant recognition app with deep learning. We walked our professor through Hyde Park, watching him take photos of flowers with the app and laughing from joy as the AI recognized the right plant species. This had previously been impossible.

I started spending every spare moment on image classification with deep learning. Still, no one was talking about it in the news — even Imperial’s computer vision lab wasn’t yet on it! I felt like I was in on a revolutionary secret.

Looking back, narrowly focusing on a branch of applied science undergoing a breakthrough paradigm shift that hadn’t yet reached the business world changed everything.

Search for complementary co-founders who will become your best friends

I’d previously been rejected from Entrepreneur First (EF), one of the world’s best incubators, for not knowing anything about tech. Having changed that, I applied again.

The last interview was a hackathon, where I met Raz. He was doing machine learning research at Cambridge, had topped EF’s technical test, and published papers on reconstructing shredded documents and on poker bots that could detect bluffs. His bare-bones webpage read: “I seek data-driven solutions to currently intractable problems.” Now that had a ring to it (and where we’d get the name for Tractable).

That hackathon, we coded all night. The morning after, he and I knew something special was happening between us. We moved in together and would spend years side by side, 24/7, from waking up to Pantera in the morning to coding marathons at night.

But we also wouldn’t have got where we are without Adrien (Cohen, president), who joined as our third co-founder right after our seed round. Adrien had previously co-founded Lazada, an online supermarket in South East Asia like Amazon and Alibaba, which sold to Alibaba for $1.5 billion. Adrien would teach us how to build a business, inspire trust and hire world-class talent.

Find potential customers early so you can work out market fit

Tractable started at EF with a head start — a paying customer. Our first use case was … plastic pipe welds.

It was as glamorous as it sounds. Pipes that carry water and natural gas to your home are made of plastic. They’re connected by welds (melt the two plastic ends, connect them, let them cool down and solidify again as one). Image classification AI could visually check people’s weld setups to ensure good quality. Most of all, it was real-world value for breakthrough AI.

And yet in the end, they — our only paying customer — stopped working with us, just as we were raising our first round of funding. That was rough. Luckily, the number of pipe weld inspections was too small a market to interest investors, so we explored other use cases — utilities, geology, dermatology and medical imaging.

Jun
30
2021
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How to cut through the promotional haze and select a digital building platform

Everyone from investors to casual LinkedIn observers has more reasons than ever to look at buildings and wonder what’s going on inside. The property industry is known for moving slowly when it comes to adopting new technologies, but novel concepts and products are now entering this market at a dizzying pace.

However, this ever-growing array of smart-building products has made it confusing for professionals who seek to implement digital building platform (DBP) technologies in their spaces, let alone across their entire enterprise. The waters get even murkier when it comes to cloud platforms and their impact on ROI with regard to energy usage and day-to-day operations.

Breaking down technology decisions into bite-sized pieces, starting with fundamental functions, is the most straightforward way to cut through the promotional haze.

Facility managers, energy professionals and building operators are increasingly hit with daily requests to review the latest platform for managing and operating their buildings. Here are a few tips to help decision-makers clear through the marketing fluff and put DBP platforms to the test.

The why, how and what

Breaking down technology decisions into bite-sized pieces, starting with fundamental functions, is the most straightforward way to cut through the promotional haze. Ask two simple questions: Who on your team will use this technology and what problem will it solve for them? Answers to these questions will help you maintain your key objectives, making it easier to narrow down the hundreds of options to a handful.

Another way to prioritize problems and solutions when sourcing smart-building technology is to identify your use cases. If you don’t know why you need a technology platform for your smart building, you’ll find it difficult to tell which option is better. Further, once you have chosen one, you’ll be hard put to determine if it has been successful. We find use cases draw the most direct line from why to how and what.

For example, let’s examine the why, how and what questions for a real estate developer planning to construct or modernize a commercial office building:

  • Why will people come? — Our building will be full of amenities and technological touches that will make discerning tenants feel comfortable, safe and part of a warm community of like-minded individuals.
  • How will we do it? — Implement the latest tenant-facing technology offering services and capabilities that are not readily available at home. We will create indoor and outdoor environments that make people feel comfortable and happy.
  • What tools, products and technology will we use?

This last question is often the hardest to answer and is usually left until the last possible moment. For building systems integrators, this is where the real work begins.

Focus on desired outcomes

When various stakeholder groups begin their investigations of the technology, it is crucial to define the outcomes everyone hopes to achieve for each use case. When evaluating specific products, it helps to categorize them at high levels.

Several high-level outcomes, such as digital twin enablement, data normalization and data storage are expected across multiple categories of systems. However, only an enterprise building management system includes the most expected outcomes. Integration platform as a service, bespoke reports and dashboarding, analytics as a service and energy-optimization platforms have various enabled and optional outcomes.

The following table breaks down a list of high-level outcomes and aligns them to a category of smart-building platforms available in the market. Expanded definitions of each item are included at the end of this article.

Jun
17
2021
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How to launch a successful RPA initiative

Robotic process automation (RPA) is rapidly moving beyond the early adoption phase across verticals. Automating just basic workflow processes has resulted in such tremendous efficiency improvements and cost savings that businesses are adapting automation at scale and across the enterprise.

While there is a technical component to robotic automation, RPA is not a traditional IT-driven solution. It is, however, still important to align the business and IT processes around RPA. Adapting business automation for the enterprise should be approached as a business solution that happens to require some technical support.

A strong working relationship between the CFO and CIO will go a long way in getting IT behind, and in support of, the initiative rather than in front of it.

A strong working relationship between the CFO and CIO will go a long way in getting IT behind, and in support of, the initiative rather than in front of it.

More important to the success of a large-scale RPA initiative is support from senior business executives across all lines of business and at every step of the project, with clear communications and an advocacy plan all the way down to LOB managers and employees.

As we’ve seen in real-world examples, successful campaigns for deploying automation at scale require a systematic approach to developing a vision, gathering stakeholder and employee buy-in, identifying use cases, building a center of excellence (CoE) and establishing a governance model.

Create an overarching vision

Your strategy should include defining measurable, strategic objectives. Identify strategic areas that benefit most from automation, such as the supply chain, call centers, AP or revenue cycle, and start with obvious areas where business sees delays due to manual workflow processes. Remember, the goal is not to replace employees; you’re aiming to speed up processes, reduce errors, increase efficiencies and let your employees focus on higher value tasks.

Feb
22
2021
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Winning enterprise sales teams know how to persuade the Chief Objection Officer

Many enterprise software startups at some point have faced the invisible wall. For months, your sales team has done everything right. They’ve met with a prospect several times, provided them with demos, free trials, documentation and references, and perhaps even signed a provisional contract.

The stars are all aligned and then, suddenly, the deal falls apart. Someone has put the kibosh on the entire project. Who is this deal-blocker and what can software companies do to identify, support and convince this person to move forward with a contract?

I call this person the Chief Objection Officer.

Who is this deal-blocker and what can software companies do to identify, support and convince this person to move forward with a contract?

Most software companies spend a lot of time and effort identifying their potential buyers and champions within an organization. They build personas and do targeted marketing to these individuals and then fine-tune their products to meet their needs. These targets may be VPs of engineering, data leaders, CTOs, CISOs, CMOs or anyone else with decision-making authority. But what most software companies neglect to do during this exploratory phase is to identify the person who may block the entire deal.

This person is the anti-champion with the power to scuttle a potential partnership. Like your potential deal-makers, these deal-breakers can have any title with decision-making power. Chief Objection Officers aren’t simply potential buyers who end up deciding your product is not the right fit, but are instead blockers-in-chief who can make departmentwide or companywide decisions. Thus, it’s critical for software companies to identify the Chief Objection Officers that might block deals and, then, address their concerns.

So how do you identify the Chief Objection Officer? The trick is to figure out the main pain points that arise for companies when considering deploying your solution, and then walk backward to figure out which person these challenges impact the most. Here are some common pain points that your potential customers may face when considering your product.

Change is hard. Never underestimate the power of the status quo. Does implementing your product in one part of an organization, such as IT, force another department, such as HR, to change how they do their daily jobs?

Think about which leaders will be most reluctant to make changes; these Chief Objection Officers will likely not be your buyers, but instead the heads of departments most impacted by the implementation of your software. For example, a marketing team may love the ad targeting platform they use and thus a CMO will balk at new database software that would limit or change the way customer segment data is collected. Or field sales would object to new security infrastructure software that makes it harder for them to access the company network from their phones. The head of the department that will bear the brunt of change will often be a Chief Objection Officer.

Is someone’s job on the line?

Another common pain point when deploying a new software solution is that one or more jobs may become obsolete once it’s up and running. Perhaps your software streamlines and outsources most of a company’s accounts payable processes. Maybe your SaaS solution will replace an on-premise homegrown one that a team of developers has built and nurtured for years.

Feb
18
2021
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Why do SaaS companies with usage-based pricing grow faster?

Today we know of HubSpot — the maker of marketing, sales and service software products — as a preeminent public company with a market cap above $17 billion. But HubSpot wasn’t always on the IPO trajectory.

For its first five years in business, HubSpot offered three subscription packages ranging in price from $3,000 to $18,000 per year. The company struggled with poor churn and anemic expansion revenue. Net revenue retention was near 70%, a far cry from the 100%+ that most SaaS companies aim to achieve.

Something needed to change. So in 2011, they introduced usage-based pricing. As customers used the software to generate more leads, they would proportionally increase their spend with HubSpot.  This pricing change allowed HubSpot to share in the success of its customers.

In a usage-based model, expansion “just happens” as customers are successful.

By the time HubSpot went public in 2014, net revenue retention had jumped to nearly 100% — all without hurting the company’s ability to acquire new customers.

HubSpot isn’t an outlier. Public SaaS companies that have adopted usage-based pricing grow faster because they’re better at landing new customers, growing with them and keeping them as customers.

Image Credits: Kyle Poyar

Widen the top of the funnel

In a usage-based model, a company doesn’t get paid until after the customer has adopted the product. From the customer’s perspective, this means that there’s no risk to try before they buy. Products like Snowflake and Google Cloud Platform take this a step further and even offer $300+ in free usage credits for new developers to test drive their products.

Many of these free users won’t become profitable — and that’s okay. Like a VC firm, usage-based companies are making a portfolio of bets. Some of those will pay off spectacularly — and the company will directly share in that success.

Top-performing companies open up the top of the funnel by making it free to sign up for their products. They invest in a frictionless customer onboarding experience and high-quality support so that new users get hooked on the platform. As more new users become active, there’s a stronger foundation for future customer growth.

Jan
29
2021
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Subscription-based pricing is dead: Smart SaaS companies are shifting to usage-based models

Software buying has evolved. The days of executives choosing software for their employees based on IT compatibility or KPIs are gone. Employees now tell their boss what to buy. This is why we’re seeing more and more SaaS companies — Datadog, Twilio, AWS, Snowflake and Stripe, to name a few — find success with a usage-based pricing model.

The usage-based model allows a customer to start at a low cost, while still preserving the ability to monetize a customer over time.

The usage-based model allows a customer to start at a low cost, minimizing friction to getting started while still preserving the ability to monetize a customer over time because the price is directly tied with the value a customer receives. Not limiting the number of users who can access the software, customers are able to find new use cases — which leads to more long-term success and higher lifetime value.

While we aren’t going 100% usage-based overnight, looking at some of the megatrends in software —  automation, AI and APIs — the value of a product normally doesn’t scale with more logins. Usage-based pricing will be the key to successful monetization in the future. Here are four top tips to help companies scale to $100+ million ARR with this model.

1. Land-and-expand is real

Usage-based pricing is in all layers of the tech stack. Though it was pioneered in the infrastructure layer (think: AWS and Azure), it’s becoming increasingly popular for API-based products and application software — across infrastructure, middleware and applications.

API-based products and appliacation software – across infrastructure, middleware and applications.

Image Credits: Kyle Poyar / OpenView

Some fear that investors will hate usage-based pricing because customers aren’t locked into a subscription. But, investors actually see it as a sign that customers are seeing value from a product and there’s no shelf-ware.

In fact, investors are increasingly rewarding usage-based companies in the market. Usage-based companies are trading at a 50% revenue multiple premium over their peers.

Investors especially love how the usage-based pricing model pairs with the land-and-expand business model. And of the IPOs over the last three years, seven of the nine that had the best net dollar retention all have a usage-based model. Snowflake in particular is off the charts with a 158% net dollar retention.

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