Now, this is the big one. Scott Brinker himself is here to bless our eyes, ears, and anything in-between with his insight on big data and big ops.
So, let's see what Scott's got. And what Scott's got, is a lot. And it's hot. Sorry, I'll stop messing around.
And if after this, you're still not Scott-ed out, check out our latest interview with the Godfather of martech here. We delve into topics like the martech industry, the effects of the pandemic (of course), the challenges of martech, and more...
This sesh, if you were lucky enough to catch it, went into depth about the new foundations of marketing and customer experience.
But in case you haven't heard of him, sacrilegious as that is, Scott is the editor of chiefmartec.com, the VP Platform Ecosystem at HubSpot, and is the best selling author of 'Hacking Marketing'.
And, most notably, he's the mastermind behind the Marketing Technology landscape since 2011. And he's been standing side-by-side with the industry as it's grown 5,233% since 2011. In fact, we've seen the number of martech solutions grow from 150, to 8,000 in just under a decade.
But the truth is, says Scott, that's just the tip of the iceberg. In fact, more than 500m digital apps and services will be developed and deployed using cloud native approaches by 2023.
Not all of these will be commercially packaged apps like the ones on the martech landscape. But the vast majority will be custom apps, built for individual companies.
This is not our story today, but the catalyst. In fact, we are in an era moving away from big data, to the era of big ops.
So, how do we go from big data, with a scale and complexity of data collected, stored and analysed, to big ops, with the scale and complexity of apps and automation interacting with data.
Scott asks us to consider it this way. If you think of data as this big data lake, far away, where you need a professional guide to help you find it, and hike up to it. Big ops is instead like an interactive water park.
And this interaction is key. Though data is growing, the interactions with it are growing even faster.
This is triggered by a proliferation of ops related functions inside the modern digital business.
- Marketing ops with specialities depending on your company, including:
- Ad Ops
- Content Ops
- Web Ops
- Loc Ops
- Sales Ops
- Partner Ops
- Customer Success Ops.
- Sales Ops
- Business Ops
- IT Ops
- Finance Ops
- Legal Ops
- People Ops
- Data Ops
- ML Ops
- Analytics Ops
- Dev Ops
- Product Ops
Okay, let's stop listing these. Just take a peep at this behemoth of a graph:
So, Scott turned to his twitter followers to clarify the roles, and asked "What do other people think 'ops' roles do?"
- "Buy ALL the tools"
- "We say NO a lot"
- "Send emails all day"
- "Put milk & cookies out for the magic elves who come in at night and do all the hard work"
and Scott's favourite:
I am a laptop-wielding technology-wizard marketing Rockstar who's beloved by all."
Let's start with DevOps.
Basically, this meme sums it up.
But this is no joke. Okay, that's a little bit of a joke. But this is an actual problem.
Software used to be developed by software engineers, and then handed over to deployment. But this slowed stuff down, and encouraged finger pointing.
So, DevOps became all about embedding ops responsibility with the development teams.
But what does this have to do with marketing?
Websites & web apps. Mobile Apps. Product-Led Growth. Custom-developed martech. All of this is software. All of this is relevant to marketing.
Scott moves on to the custom martech side. He referenced research from our martech report (download here), specifically asking respondents "What best describes your organisation's customer/ marketing data platform?"
Now this is interesting, Scott says. 16% of respondents reported their platform is self built, either in-house or custom developed. 38.5% reported a hybrid platform, in-house or custom developed, and with vendor solutions. This totals to 54.5%.
Scott said someone on Twitter joked that half of this is probably spreadsheets (and they might not be 100% wrong). But there's still a lot of development happening.
But what Scott wants to do is to pull themes from DevOps.
The Three Themes of DevOps
Number One: Agile Culture
This accelerates the loop, to be able to develop, deploy, learn. And repeat. It's about bringing the agile cycle up to speed, and has been adapted for marketing.
In fact, 51% of marketing departments are using at least some parts of an agile marketing approach in 2021.
Number Two: Shifting left
This involves moving responsibilities in the 'Dev' of 'DevOps'. But this shift is also happening within marketing, with the growth of no-code marketing 'superpowers', for providing non-technical marketers the ability to perform "no-code" capabilities.
- Automation. This means being able to automate activities and processes.
- Augmentation. This means being able to be imbued with new powers to create and analyse.
- Integration. This means being able to be connected to other tools and data.
A big part of all this is automation.
Number three: Automation
This is certainly something that's been seen in the DevOps world, with 90% of high-maturity DevOps teams have automated the most repetitive tasks, compared to only 25% for low-maturity DevOps teams.
The department with the largest number of automation is not surprisingly IT and Engineering, with 39.8%. But what is surprising is the second is Finance (26.4%) and the third is sales and marketing (13.3%).
This gets us into data ops.
There are so many water-themed references in this space, Scott says. Data Lake, Data Stream, Data Cloud, and when it's bad - Data Swamp.
But there's a few lesser known data water metaphors. These are:
- Data Bourne - Stored identity data
- Data Creek - Trickle-down data
- Data Fjord - Steep learning curve data
- Data Gulf - Can't quite reach the data
- Data Moat - Unique Competitive data
- Data Puddle - Excel Spreadsheet
And there's one more water metaphor. The Water Cycle. You'll find there's a similar ecosystem for data.
So, you'll see the data being all pooled around. Another water reference.
And it wouldn't be a S.B presentation without some sort of landscape:
And this is just a sample.
Next up, two ideas from Data Ops, which are relevant to all Big Ops.
Two Ideas from DataOps
Number One: Aggregation
First up, its aggregation over consolidation. But what's the difference?
Well, consolidation is about reducing a lot of different sets of things, into a smaller number of things, or just one.
Aggregation, on the other hand, is making a large set of things easier to consume or access through a single source.
For example, Social media platforms are highly consolidated, but have millions of social creators.
So, this is something Scott's looked at with martech.
"With integration, we have the mechanisms to do aggregation" at the data level, workflow, UI, and governance, he says.
So, you see aggregation in the following layers:
- Data: Data warehouses/data Lakes; specialised data; shared spreadsheets.
- Workflow (logic): iPaaS, Workflow Automation and BPM; Robotic Process Automation; Data Pipelining and ETL automation.
- UI (presentation): Shared collaboration tools; Shared analytics tools; Domain platforms.
- Governance: SaaS management; Privacy and data governance; Identity access management.
What's exciting about this aggregation, says Scott, is that it's taking us from an age where fragile tech stacks break when new apps or data is added, to antifragile stacks which gain value from new apps and data.
This is because aggregation platforms get more value as more is added, as they have more things to aggregate through them.
This is how we make our tech stacks as agile as the rest of our business needs to be.
Number Two: Reintegration of Martech
The CMO council asked a number of c-suite leaders "Where do you see leadership holes or gaps in your marketing organisation?"
- 42% said modernisation of marketing organisation, systems, and operations
- 40% said proficient, technically savvy managers in key digital roles
- 37% report it to be greater customer knowledge and market understanding
- 34% claim adaptive, informed decision-making based on good data
Actually all these things are all related around the technology and data infrastructure of marketing"
How did marketing fall behind?
In many ways martech was leading the charge of digitisation of modern business, says Scott.
Well, the truth is the rest of the organisation has caught up with its maturity. And increasingly there's a demand for martech to be re-integrated into the rest of the IT platform.
That doesn't mean that marketing won't have some of their own tools, but these tools need to integrate with the other enterprise systems. And in some cases where there's universal enterprise systems that work for marketing needs too, so there's a need to be able to take advantage of them seamlessly.
And finally, we have:
This involves pooling together marketing ops, partner ops, and sales ops. We can go back to the meme, he says:
In many ways, Scott suggests, the relationship between marketing and sales, and customer success, is often like the parable of the blind men and an elephant. No, it's not about an elephant being trained as a service animal.
Instead, the men are all touching a different piece, and describe what they see, with very mixed perspectives. So, in our case, it translates to 'the parable of the blind department and a customer'. Or mis-aligned systems and data, and processes.
And really, at its heart, RevOps is about aligning systems and data, and processes, across marketing, sales and customer service.
A way to look at the power of RevOps is to look at the seven roles that it can play in the modern organisation.
"RevOps sitting above these three departments can be the cartographer of the entire customer journey", not just through marketing or sales, but the end-to-end, says Scott.
What's exciting is all seven of these roles are all connected to the data that is being managed.
The other roles include:
- Cartographer of the customer journey map...mapping the context of data.
- Curator of the customer data and assets...standardising data organisation.
- Architect of customer systems and services...generating and processing data.
- Orchestrator of processes and automations...building data-triggered workflows.
- Analyst of insights and performance...analysing and refining data.
- Outfitter of self-service capabilities...enabling self-service use of data.
- Guardian of quality and compliance...assuring data quality and compliance.
How do DevOps, DataOps and RevOps all connect?
Scott believes that we are early on in this journey of big ops, and that's what's exciting about this.
Just as many marketing operations and marketing tech people led this first generation of the martech revolution, the second generation of the martech revolution, in a much larger context of big ops, has so much opportunity”
He leaves us with this quote from MarTech Alliance fave Darrell Alfonso: