Here are some types of data we frequently collect:

• Companies
• Funding rounds
• Investors (i.e. the set of institutional and individual investors—categorized by type—which lead and participate in funding rounds)
• Funds (the discrete pools of capital raised by institutional investment firms)
• Exits i.e acquisitions and IPOs

• Our data collection process is both automated and manual. We, therefore, rely mainly on a data entry team for this.
• Most of the data is collected from public sources like press releases, reputable media coverage and by contacting the organizations.
• We also crowdsource data from our users, but this is fact-checked for accuracy.
• All monetary data is kept in US dollars unless otherwise indicated.

We rely on three things, incorporation, headquarters and primary market. Once the company satisfies any of the three, then we classify it as African. If the company is headquartered on the continent, we take that. To find out the headquarters, we check the company website, and if no information is available, then we check the company’s Linkedin page. If there's no information on LinkedIn, too, but the management team is based in one location, that’s what we consider as the headquarters. If the management team is based in different locations, we use the CEO’s location as the decider. If the CEO’s location is not available, we use the location of the next most senior member of the management team. If no other sources are available, we check media reports to see if there’s mention of the company’s headquarters.

• We will avoid classifying companies under “Others” unless absolutely necessary.
• Our data entry team will check the definition of the industries and get constantly familiarized with them.
• Companies that are classified as an industry should match the industry’s definition.
• All companies will be classified under one industry and sub-industry only.
• For companies that could fit into two or more industries or sub-industries, always gauge what is the primary business activity of the company and classify accordingly.

We avoid classifying companies under “Others” unless necessary. Our data entry team always checks the definition of the industries and get instantly familiarised with them. All companies are classified under only one industry and sub-industry. For companies that could fit into two or more industries or sub-industries, we always gauge what is the primary business activity of the company and classify accordingly.

For now, the focus is to ensure that our research and reports are easily understood yet relevant. Therefore, we shall focus on a few industries where there’s much activity. As other sectors pick momentum, we shall continue to break them away from Generalization terms like Other Technologies. It is, however, important to note that these classifications apply to startups and technology companies. We classify companies according to Industries and Sub-industries (though they can be used interchangeably as Sectors and Sub-sectors). Right now, we have categorised all companies under 11 sectors. Before we organise a company under a given sector, we carefully study it to find out if its solution and operations do not and cannot significantly overlap into another.

The broader industries are: Agriculture, Commercial and Professional Services, Communication Services, Financial Services, E-Commerce, Energy & Resources, Education, Media & Entertainment, Health and Pharma, Transport and Logistics, Travel and Leisure, Real Estate, Retail, Utilities and Telecommunication Services,.

The industries are further broken down into verticals which are more specific. These are; 3D printing, Adtech, Advanced Manufacturing, Agtech, Artificial intelligence and Machine Learning, Audiotech, Augmented Reality, Autonomous cars, B2B Payments, Beauty, Big data, Cleantech, Construction technology, Cryptocurrency/Blockchain, Cybersecurity, Ecommerce, Edtech, Ephemeral content, eSports, Fintech, Foodtech, Gaming, Healthtech, HR Tech, Impact investing, Industrials, Infrastructure, Insurtech, Internet of Things (IoT), Life sciences, LOHAS and wellness, Manufacturing, Marketing tech, Mobile Commerce, Mortgage Tech, Nanotechnology, Oil and Gas, Oncology, Pet Technology, Real Estate Technology, Restaurant Technology, Retail Technology, Ridesharing, Robotics and drones, SaaS (software as a service), Space Technology, TMT (Technology, media and telecommunications), Virtual reality and Wearables.

Our deals are broken down into three categories: investment, exits and funds. Investment refers to funding raised by companies, exits usually refer to acquisitions and IPOs while funds refer to the funding raised by fund managers from limited partners.

All investment or funding rounds are classified under the following stages: Grant, Debt Financing, Private Equity, Growth Equity, Initial Coin Offerings, Pre-Seed, Seed, Series A, Series B, Series C, Series D, Series E etc. Each company can only use a funding stage once. In cases where the company states that it raised for the same round - let’s say Series A - then we mark the first one as Series A I and the second one as Series A II. But the two are aggregated into a single Series A round for analysis. Some funding rounds may include loans. If so, we put them under the Debt Financing Stage. For example, if a $10m Series A round includes $2m in loans, the data input is $8 million as Series A and $2 million as Debt Financing.

When recording the details if the deal, unless stated, we take the date when it was announced to the media. For example, if a deal closed in May 2018 but published in October 2018, we would go with October unless the startup points out that the deal closed in May 2018. We use the Date format of mm/dd/yyyy but usually with the month in words. For example, 12/08/2018 would be written as Dec 08, 2018.