Around Q3 of last year, I started hearing the word “context” pop up in many of my conversations. It was noticeable because previously, data was all anyone wanted to talk about.
We all know how the vocabulary of the business world works. When everyone starts talking about something, we come up with a different word to make it sound like we’re talking about a new thing (which usually isn’t the case).
So when I started hearing “context” in the second half of 2025, it seemed poised to take its place alongside synergy, pivot and alignment in the Corporate Speak Hall of Fame.
But “synergy” and “alignment” are really two different ways of saying the same thing, while “data” and “context” are not. In fact, data had a legitimate problem as 2025 went on, and it was more significant than over-use.
More data no longer meant more value.
This is true whether you’re discussing AI or GTM strategy in a B2B organization.
What were the limits of Big Data strategy?
The idea behind the era of Big Data was simple: capture everything so we can learn even more about our customers. We came; we captured; we built out on-premise, and later, cloud-based storage environments to store it all; we deployed fancy analytics software; and we… found out we did, in fact, have a lot of data.
We also realized that data is just a record. It doesn’t tell you why someone did something or how they did it. More importantly, it doesn’t give much advice about what you should do next.
If you were to take your data and train an LLM on it, you would simply engineer a parrot, well-versed in telling you things you already knew. Only by adding context about your brand, your customers or your GTM strategy would you create an AI-driven assistant.
How does context apply to GTM strategy?
Most B2B GTM strategies are inwardly focused. They tell the team to reach $25 million in revenue. They discuss the five top product features. They tell you the CTO is your ICP.
What’s missing from such a strategy is context, specifically the external pressures every organization faces. As a result, you end up with a mismatch. You try to sell growth to a company that needs help cutting costs. Your sales pitch sounds tone deaf. You don’t gain trust.
(If you want to geek out on context and externalities in GTM, I highly recommend spending time with the work of MarTech contributor Mark Stouse.)
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As context works its way into discussion after discussion, you’re probably wondering how we ever ran businesses without it.
The truth is, we didn’t.
Context lived for years in the heads of valuable and experienced employees, and it was good. But as organizations demanded speed and scale — and especially as they struggled to achieve them — it was no longer feasible for context to exist solely in employees’ minds.
In a business world built for speed and scale, knowledge silos wreak just as much havoc as data silos. (I want to recognize here my theory that data silos are simply a technical manifestation of organizational silos.)
Complexity also mixes poorly with human-based context. Many businesses strive to be part of what they see as a fast-moving, global economy, which is too dispersed and too fast to rely on the gut feelings and experience of mere humans.
Businesses addressed many of their issues around speed, scale and complexity with automation. And why not? When you automate business processes, you move faster and get results sooner. That’s true, but you also strip away context because automation leaves no place for human nuance.
That leads us to where we are today. We’re turning to technology in hopes it can bring back the context that sank to the bottom of Big Data.
We can be cynical about this and say we wasted a lot of time and resources on Big Data and got little out of it. But I view this as a course correction. Yes, we collected exabytes of information in order to find answers. It worked well in many cases.
But answers alone aren’t enough, and now, much like transcendentalists, we find ourselves desperate to find meaning.
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