In a tech ecosystem enamoured with big bets and even bigger buzzwords, it’s easy to overlook the quiet shifts happening under the radar. But across Nigeria’s digital economy, a subtle transformation is taking shape. It is not driven by hype, but by habit.
Artificial intelligence is not yet dominating every boardroom conversation, but a different kind of intelligence is already reshaping how startups think. Not artificial. Not predictive. Just practical. Operational. Rooted in tools like Power BI, SQL, and the everyday logic of “what’s really happening in our business?”
This is the form of intelligence currently guiding how B2B and B2C startups in Nigeria make product, marketing, and operational decisions. And in the middle of this change are professionals who understand that effective innovation often begins with clean data, not just code.
One of them is John Itodo, a marketing and data analyst who, over the past five years, has transitioned from building ad campaigns to helping Nigerian tech brands build decision engines. His path, from vendor activations and social campaigns to internal BI tooling and automated insights, reflects the evolution of the modern analyst in emerging markets.
Back in 2019, Itodo led platform adoption for KePay, a B2B wallet developed by Fast Pay Nigeria Limited. His team is working on vendor onboarding and user acquisition in transport and MSME hubs like Unilag and Yaba. At the same time, OPay and PalmPay are expanding aggressively across Lagos. The fintech noise is loud. But internally, Itodo starts noticing gaps in visibility.
“We were doing activations. Users were signing up. But we didn’t know why the good ones stayed or why others dropped off. We were creating activity, not insight,” he says.
That insight gap becomes a new focus.
In 2020, Itodo joined LONTOR Hi-Tech, a retail-tech company managing electronic brands like Gree and LONTOR. His new role spans marketing intelligence, brand strategy, and national campaign planning. But beyond campaigns, he starts introducing store-level analytics, standardised reporting, and performance dashboards that align field teams with business goals.
Within six months, LONTOR sees a 20 per cent lift in revenue, in part because decisions are no longer based on assumptions. “You realise that good branding isn’t just visual identity,” John Itodo explains. “It’s also clarity on performance and direction.”
Data Before the Buzz: why intelligence still comes before AI
While the world is still watching how global players approach artificial intelligence, Nigeria’s tech ecosystem is taking smaller, more grounded steps toward intelligence. Across the African continent, this systems-first approach to growth is gaining ground.
A recent 2021 Partech Africa report highlights that startups in Nigeria, Kenya, and Egypt are investing more in marketing automation and business intelligence. These tools might not make global headlines, but they are giving African startups the edge to scale smarter.
According to a 2021 Partech Africa report, startups in Nigeria, Kenya, and Egypt have increasingly begun investing in marketing automation and business intelligence, especially in verticals like fintech, e-commerce, edtech and logistics. While full-scale AI deployment remains out of reach for most, lean intelligence tools are closing the gap between guesswork and evidence.
In practical terms, that means a product manager at a Lagos logistics startup can now visualise real-time drop-offs with Metabase, a marketer in Nairobi can map lead conversion with Power BI, and a customer success team in Accra can automate user segmentation in Airtable, all without building a single neural network. Even Google Data Studio already helps teams visualise real-time trends, understand user drop-offs, and optimise workflows.
These tools may not be headline-grabbing, but they’re building the habit that AI depends on: clean data, thoughtful modelling, and decision loops that reward insight over volume.
What Nigeria’s Mid-Market Tech is Prioritising in 2022
In this new landscape, intelligence does not always mean machine learning. Sometimes, it means knowing your actual funnel conversion rate. It means identifying why certain customers churn or why some agents outperform others. It means dashboards that guide actual decisions.
This shift is especially critical in mid-market startups, where bandwidth is expensive, margins are tight, and every hiring decision counts. And it is here that John continues to contribute.
At E-DoubleOne Academy, an edtech and workforce upskilling platform, John consults as a data and performance strategist. He doesn’t just track how many students apply or enrol. He works with the team to understand drop-off patterns, program completion rates, and what signals correlate with user success. The dashboards he builds inform hiring, budget planning, and even course restructuring.
“You don’t need to deploy a large language model to behave intelligently,” he says. “You just need structured data and the discipline to keep asking better questions.”
That sentiment is quietly resonating across Nigeria’s growing data and growth strategy communities. Events like DataFest Africa, meetups hosted by the Nigeria Data Science community, and the rise of analyst-focused roles in startups signal that more founders and operators now see insight as a competitive advantage.
In August 2022, Google released its multilingual BERT model, showing yet again that the future of AI is also deeply tied to understanding language and context. But for most African startups today, the foundation is still being laid. Teams are cleaning data, setting up relational databases, and working toward standardised insights. These are the steps that make future AI deployments viable.
And as for John? He is not trying to rush toward AI adoption. Instead, he is helping companies prepare for it. When asked what makes this moment different from previous tech cycles, he doesn’t mention ChatGPT, robotics, or any of the usual trends.
He simply says, “The companies that will do well in the AI era are the ones already learning how to use their data. That’s where it begins.”
