Native, a company developing artificial intelligence (AI) tools for offline retail operations, has agreed to acquire Frontline Research Group, an African market intelligence provider, to strengthen its data capabilities across the continent’s traditional trade sector.
Matt McNabb, CEO of Native. Image source: Native
Financial terms of the transaction were not disclosed, and the deal remains subject to customary closing conditions.
The acquisition adds Frontline’s market share measurement panels, covering 14 African markets, to Native’s existing platform. The combined offering is designed to help consumer goods companies connect field execution data with independent market share insights, allowing them to assess whether commercial activities translate into measurable business outcomes.
The move also marks Native’s expansion from Latin America into Africa, where traditional retail continues to dominate consumer spending. According to the company, Africa accounts for approximately $1.7 trillion in annual consumer expenditure, with around 80% flowing through traditional trade channels. These channels consist of more than 10 million independently operated stores, many of which remain largely outside digital retail infrastructure.
Native develops software designed to digitize physical retail environments using machine-readable store data and AI-driven analytics. Its platform provides consumer goods companies with tools for field execution, distribution analysis and commercial planning in fragmented retail markets.
By integrating Frontline’s market share datasets, Native intends to add an independent measurement layer to its analytics platform. The company argues that combining operational data with market share information could improve decision-making for brands operating in traditional retail environments.
Commenting on the acquisition, Native CEO Matt McNabb said Frontline’s proprietary market share data provides information that is difficult to replicate through publicly available sources or automated data collection. He said integrating those datasets with Native’s AI platform would allow brands to better understand how in-store activity affects market performance and identify areas requiring commercial action.
“Most people would look at Frontline and see a regional research company. We see a proprietary data asset at the center of a $1.7 trillion consumer economy,” said Matt McNabb, CEO of Native. “Frontline has built market share signals in 14 African markets that cannot be credibly scraped, inferred or bought off the shelf. When that signal connects to Native’s 3D Store Graph and agentic workflows, the equation changes: brands can see what is happening in the store, understand whether share actually moved and know what to do next. That is the operating system we are building for the offline trade.”
Frontline has built its business around measuring market share and retail performance across African traditional trade channels. Its clients include multinational consumer goods companies such as AB InBev, Coca-Cola, Heineken, Diageo, Pepsi and Unilever.
Sean Barnes, Chief Executive Officer of Frontline Research Group, said the transaction combines Frontline’s regional market intelligence with Native’s AI and retail analytics technology, creating a broader platform for companies operating in offline consumer markets.
“Frontline has built a unique regional position in the market by delivering Traditional Trade market share and other market intelligence in some of the world’s most important offline consumer markets,” he added. “Native’s platform gives that data a new dimension, pairing our regional depth with major advancements in machine-readable retail, agentic AI and subscription software. That is a fundamentally stronger offering than either company could deliver alone, and it opens up an exciting new chapter for our team.”
Following completion of the acquisition, Barnes will join Native as Chief Strategy Officer.
The transaction reflects a broader trend of AI companies seeking access to proprietary datasets that can improve the performance of intelligent software systems. In retail, particularly across emerging markets where digital transaction data remains limited, independently collected market intelligence is increasingly viewed as a valuable asset for building AI models capable of supporting commercial decision-making.
