What happens when growth hacking grows up? We call it “The Rise of Operations”.

This article is extracted from Captain Data’s white paper “The Rise of Operations”, examining how leading companies are adapting their data practices to fit today’s business needs.

To download the full .pdf, head over here.

In the first era of doing business on the internet – a period running from the late ‘90s up through the bursting of the first tech bubble and until the arrival of smartphones in the late 2000s – many companies shared a basic competitive advantage: Since so few people had clearly understood the exponential power of the internet, simply being an early mover was enough to give you a pretty good shot at success.

In the early 2010s, things changed

This was the period in which the internet moved from being a novelty to being a major part of our everyday lives.

As the internet anchored itself in our world, it began to collect more and more data.

With large swaths of the population walking around with smartphones in their pockets, the data floodgates opened. 

That swiftly led to a bit of a Wild West moment in business development: everyone was hunting for competitive advantages that would allow them to sprint ahead in an environment with few guidelines, let alone rules or regulations.

That hunt was often led by a new discipline developed by technology enthusiasts looking to reach and expand their target audiences: growth hacking.

Quick reminder: What is growth hacking?

Growth hacking focused on finding ways to accelerate growth, using methods that varied depending on the stage of the company.

or companies that hadn’t yet found product-market fit (PMF), growth hackers tried to experiment as much as possible: landing pages, social media ads, cold emailing...

The goal was to rapidly test every intuition and get market feedback that would let you iterate and improve. 

In post-PMF companies, growth hacking tried to double down on growth levers, pulling on them as hard as possible with focused, rapid experimentation.

Once a channel had been identified, it would be bombarded to maximize reach and conversion.

A/B testing techniques would be used throughout the entire customer journey.

Growth hackers looked for acquisition and retention loops, using data and tools they often coded themselves.

A cottage industry of knowledge soon developed, spread over thousands of blog articles and via books such as Traction by DuckDuckGo founder Gabriel Weinberg and Blitzscaling by LinkedIn co-founder Reid Hoffman.

This knowledge distribution had a big effect, in that it started to send growth hacking back to where it truly belonged, under the umbrella of product design and marketing.

On some levels, this intermediary period provided benefits for everyone.

Businesses were able to use data to identify market opportunities more quickly and eventually target their potential customers.

Consumers had more options when it came to solving their various problems and were seeing more pertinent advertising based on their interests and needs.

Marketers operated in the middle, trying to increase reach and enjoying the benefits of expanding global markets.

But there were also drawbacks. One big issue began to attract attention, namely that consumers were uneasy with the sheer quantity of data they were putting on the internet and how that data was being used.

As more information about “big data” came out, and particularly as some players exploited data with less than noble intentions, it became clear that things would have to change.

Revenue Operations emerges to increase productivity and automate data processes

This data free-for-all led to various reactions which now shape how businesses use data today.

The EU instituted its General Data Protection Regulation (GDPR), Apple made major changes to the data tracking permissions given by users within its ecosystem, and businesses – or to be more precise, post-PMF businesses – began to incorporate the lessons of growth hacking while simultaneously moving toward more sustainable, polished practices.

In a word, the data landscape went from the Wild West to requiring a much more disciplined, structured approach.

The ultimate goal of a structured approach to data is to create true alignment across the various departments within a business.

For many companies, this has put a new emphasis on a key function: revenue operations. 

Like all evolutions, the move from growth hacking to revenue operations has been facilitated by the arrival of new tools.

The foundations of today’s structured data movement started to be laid in the early 2010s, when early companies such as Mixpanel and Zapier began to allow businesses to become increasingly data-driven and process-efficient.

As these tools gained traction, they encouraged the creation of ever more focused tools. All of a sudden, B2B SaaS was booming.

“As they stand today, revenue operations-oriented roles form a bridge between the tech and business sides of a company.” – Guillaume Odier, co-founder and CEO, Captain Data

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Bridging the gap between tech and business has grown in importance because finding new competitive advantages in business today has become very complex.

In no small part, this complexity has been driven by that massive increase in tools now available to help businesses access and exploit data and services.

Every department – sales, marketing, customer support, etc. – is using data-driven tools to better understand their activities.

While each individual tool is (ostensibly) meant to help your business save time and earn money, the sheer quantity of tools has turned mastering these techniques into full-time jobs.

What’s more, revenue operations is growing rapidly because there are significant benefits to be gained by breaking down departmental silos and using multiple tools together.

Why is Revenue Operations such a critical part of building a great business today?

Developing your company’s revenue operations functions is an effort to make every customer-facing aspect of your business work together in a symbiotic, mutually-reinforcing way. 

In doing so, you’re recognizing that product, sales, marketing, and customer service all need to be aligned in order to thrive in today’s competitive world. 

By industrializing that alignment, operational roles build on the experiment-friendly ethos of growth hacking, adapting it to fit a highly structured data environment. 

That’s why the rise of the operators is bringing with it a rise in data automation.

And that’s where Captain Data comes in 🙂

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Looking for more clarity on how to structure your company’s data revenue operations, and in particular how to take advantage of data automations? Download our complete guide to “The Rise of the Operators” here.