Around Q3 of last year, I started hearing the word “context” come up in many of my conversations. It was remarkable because previously, data was what everyone 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 something new (which is unusual).
So when I first heard “context” in the second half of 2025, it seemed appropriate to take its place next to synergy, pivot and alignment in the Corporate Speak Hall of Fame.
But “synergy” and “alignment” are two different ways of saying the same thing, while “data” and “context” are not. In fact, data had a legitimate problem as 2025 progressed, and it was more important than overuse.
More data no longer means more value.
This is true whether you are discussing an AI or GTM strategy in a B2B organization.
What were the limitations of Big Data strategy?
The concept of the Big Data era was simple: capture everything so we can learn more about our customers. We arrived; we captured; we build on-premises, and later, cloud-based storage facilities to store it all; release state-of-the-art analytics software; and we… found that, in fact, we have a lot of data.
We also realized that the data is just a record. It doesn’t tell you why someone is doing something or How they did it. More importantly, it doesn’t give much advice about what to do next.
If you were to take your data and train an LLM on it, you would just develop a parrot, who is good at telling you things you already know. Only by adding context about your product, your customers or your GTM strategy can you create an AI-driven assistant.
How does context work in a GTM strategy?
Most B2B GTM strategies are internally focused. They told the team they had reached $25 million in profits. They discuss the top five features of the product. They tell you that the CTO is your ICP.
What is missing from such a strategy is context, especially the external pressures that the entire organization faces. As a result, you end up with a difference. You are trying to sell growth to a company that needs help cutting costs. Your sales pitch sounds deaf. You don’t earn trust.
(If you want to explore 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 conversation after conversation, you’re probably wondering how we ever ran businesses without it.
The truth is, we didn’t.
The context lived for years in the heads of key and experienced workers, and it was good. But as organizations sought speed and scale – and especially as they struggled to achieve it – it was no longer possible for context to exist only in the minds of employees.
In a business world built for speed and scale, information silos cause as much damage as data silos. (I want to see here my theory that data silos are the technical manifestation of organizational silos.)
Complexity also mixes badly with human essence. Many businesses are struggling to be a part of what they see as a fast-moving global economy, too fragmented and too agile to rely on gut feelings and human experience.
Businesses have 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 faster. That is true, but it also removes the context because doing it yourself leaves no room for human anger.
That leads us to where we are today. We turn to technology in the hope that it can bring back the essence that has sunk into Big Data.
We can criticize this and say that we spent a lot of time and resources on Big Data and got little out of it. But I consider this a course correction. Yes, we collected exabytes of information to find the answers. It worked well in most cases.
But answers alone are not enough, and now, as transcendentalists, we find ourselves longing for an explanation.
