Value created.
Value returned.

Executive Summary

This report examines the economics of Africa’s podcast and digital-audio market between 1 June 2025 and 31 July 2026. It addresses a question that has lingered over the continent’s creative economy: how much value do African creators generate for the global platforms on which they publish, and how much of that value returns to them?

The analysis covers 330 pieces of content: 227 YouTube assets and 103 Spotify episodes, selected and ranked using engagement scores. Based on available advertising rates, we estimate that this content generated $1,045,149 in Content Value for YouTube and Spotify during the period studied. Content Value refers to the estimated amount advertisers paid to reach the audiences attracted by this content.

Under the revenue-sharing arrangements used in our model, creators would receive an estimated $567,735, or 54.3%, while the platforms would retain approximately $477,413, or 45.7%. These figures describe how the value would be divided if the content were eligible for monetisation and the relevant payment systems worked as modelled.

The report’s central finding is that African podcast content is a commercially undervalued asset, not an underperforming one.

MODELLED REVENUE SPLIT / EXECUTIVE SUMMARY

The geography discount

If the same African content—with the same audience size and advertiser attention—were valued using advertising rates from higher-paying markets such as the United States, United Kingdom and Australia, its estimated Content Value would rise from $1,045,149 to $2,446,482. This represents a gap of $1,401,333.

We call this the geography discount: the reduction in commercial value that results from where an audience or creator is located, rather than from the content’s quality or performance.

The size of this discount differs sharply by market. It is approximately twofold in South Africa but can reach elevenfold in markets including Ghana, Uganda, Tanzania, Senegal and Egypt. The discount persists even when African content performs better than comparable content from higher-paying markets.

The sample recorded a weighted engagement rate of 2.75%, compared with a benchmark of 1.5% to 2.2% in higher-paying markets. Much of the sample also consists of long-form programmes lasting between 60 and 120 minutes.

Advertisers buying African podcast inventory are therefore gaining strong engagement, extended audience attention and trusted host relationships at a fraction of the rates paid elsewhere.

Creators can capture more of this value through direct agreements with brands and agencies, which command higher rates than platform-based advertising across the markets in this study. The commercial opportunity does not depend entirely on future platform reform: advertisers and creators can pursue it now through direct partnerships.

A growing audience, but a weak commercial system

Evidence from the wider market points to four important trends:

FOUR MARKET TRENDS

These conditions help explain why a rapidly growing audience has not yet produced a proportionate increase in creator income.

Unequal access to platform payments

The geography discount is only one part of the problem. Many African creators cannot access the platforms’ monetisation programmes at all.

During the period studied, Spotify’s Partner Program—its platform mechanism for sharing advertising revenue with eligible podcasters—was unavailable in every African market. YouTube’s Partner Program was available in only 13 of Africa’s 54 countries.

This creates two distinct disadvantages. The geography discount means that African content is assigned a lower price. The access gap means that many African creators have no route to platform advertising revenue through these programmes, whatever the value or performance of their work.

Some creators respond by registering accounts in markets where monetisation programmes are available or advertising rates are believed to be higher. An African creator may therefore operate an account officially registered in the United States, United Kingdom, Australia while producing the content elsewhere in Africa.

This practice can distort market data. Successful African content may be attributed to the country where an account is registered rather than the country where the creator lives and works. Official platform figures may therefore understate both the size and the geographic reach of Africa’s podcast economy.

YOUTUBE PARTNER PROGRAM / REPORTED COVERAGE

13 of 54 countries during the study period [11]

Each dot represents one country. Source claim retained from the report.

The employment potential

This report also translates estimated creator earnings into livelihoods. Applying a Full-Time-Equivalent employment model to the sample, we estimate that its current earnings could sustain approximately 352 full-time-equivalent creator livelihoods.

At advertising rates comparable to those in the United States, United Kingdom and Australia, the same content could sustain approximately 890 full-time-equivalent livelihoods. On this model, closing the geography discount would mean the difference between about 352 and 890 sustained jobs—without requiring an additional view, minute of listening or piece of content.

These estimates are not a count of named people in full-time employment. They express the economic value generated by the sample as the equivalent number of full-time livelihoods it could support. The appendix explains the method, assumptions and wage proxy used in the calculation.

The gap is likely to widen

The report’s most consequential forward-looking conclusion is that the divide between audience growth and creator income is likely to widen unless the market changes.

The evidence reviewed suggests that African podcast audiences are growing by approximately 20% - 28% a year, while the infrastructure needed to monetise those audiences is growing by only 7% - 14% a year. If these trends continue, a larger listening audience will produce more underpriced content and more unrealised employment rather than closing the existing gap.

This is not a self-correcting market. Closing the gap will require wider access to platform monetisation, stronger local advertising systems, direct relationships between creators and brands, and payment models suited to African audiences.

How to read the estimates

The figures in this report should not be interpreted as an estimate of the total size of Africa’s podcast market. They show the value generated by a defined sample during a specified period.

The report instead offers a model that can be applied to other content, markets and time periods. It provides creators, investors, advertisers and policymakers with a basis for estimating current value, testing different pricing assumptions and assessing future potential.

The main report concentrates on the findings, their meaning and their commercial implications. The appendix contains the detailed methodology, including the sample-selection process, engagement scoring, advertising-rate sources, revenue-sharing assumptions, country classifications, employment calculations and sensitivity tests.

Even within the limits of this sample, the conclusion is clear: African podcasts are already producing significant commercial value. The challenge is not simply to grow their audiences, but to ensure that the value those audiences create is properly recognised, priced and returned to the people producing the work.

How to Read the Two Value Tracks

All content-valuation estimates in this report are presented on two separate tracks:

TWO VALUE TRACKS

These estimates should not be conflated with confirmed payments to creators. Eligibility restrictions, account location and other barriers may prevent creators from receiving the modelled amount.

Throughout the report, we use the upper end of the available advertising-rate ranges. The results should therefore be understood as estimates of the content’s potential ceiling value, rather than conservative or typical-case estimates. The Methodology Appendix provides the formulas, rate sources and assumptions used.

2. Sector Value Chain and Market Size

2.0 The African Digital-Audio Value Chain

Africa’s podcast and digital-audio economy has four main parts: content creation, production, distribution and monetisation. African creators and production companies have expanded rapidly, but the platforms with the widest reach—and the greatest control over advertising revenue—remain largely international.

This imbalance affects who can reach audiences, who controls audience data and how much of the resulting value returns to African creators.

1. Content creation

Podcast production is highly fragmented. Most creators operate independently or through small, informal organisations, producing programmes on subjects ranging from local culture and social issues to business and technology.

Some shows have built large and highly engaged audiences, but no single creator or company dominates the market across the continent. This diversity is a creative strength, although fragmentation can make it harder for creators to sell advertising collectively or negotiate with platforms and large brands.

2. Production

A growing network of studios provides recording, editing and post-production services. Companies such as SemaBOX in East Africa and Glitch Africa Studios in West Africa allow creators to produce professional audio and video without individually bearing the full cost of equipment and technical staff.

These studios are increasingly important as podcasting becomes a visual as well as an audio medium.

3. Distribution

Distribution is dominated by international platforms, including YouTube, Spotify, Apple Podcasts and Boomplay. These services give African creators access to large audiences, but they also control discovery, audience data and many of the systems through which content is monetised.

Africa-specific user data is limited. Most major platforms do not publish sufficiently detailed figures showing how many active podcast listeners they have in individual African markets. This makes the sector difficult to measure and can obscure differences between countries.

Regional companies offer alternatives at a smaller scale. Afripods and iono.fm provide hosting, syndication and advertising tools, while services such as Pelevo, Wazo and Jamit focus on helping listeners discover African programmes. These companies compete through local-language content, regional knowledge and specialised services rather than through the scale of the global platforms.

Spotify has made some direct investments in the regional podcast sector, including the Africa Podcast Fund. Nevertheless, distribution at scale remains concentrated in platforms that were not developed primarily for African markets.

4. Monetisation and advertising technology

Monetisation is the least developed part of the value chain. Many creators can distribute content internationally but cannot convert their audiences into reliable income.

One reason is the limited reach of advertising technology designed for African markets. Atunwa Digital, for example, inserts targeted advertising into podcasts and livestreamed radio through its integration with AdsWizz. However, services of this kind do not yet operate at the scale required to connect large numbers of African podcasts with institutional advertising budgets.

Access to the platforms’ own advertising programmes is also uneven. During the period covered by this report, Spotify’s Partner Program was unavailable in African markets, while the YouTube Partner Program was available in only 13 of the continent’s 54 countries.

Distribution, in other words, does not guarantee monetisation.

The investment gap

The clearest gap in the value chain lies between distribution and monetisation. Africa has creators, studios and specialised regional platforms, but no African-owned audio platform currently operates at a scale comparable to the largest international distributors.

This creates an opportunity to invest in regional aggregation, advertising technology, audience measurement and payment systems. Local companies already demonstrate expertise in production, hosting, discovery and advertising services. The unresolved challenge is to connect these capabilities at sufficient scale.

THE FOUR-LAYER VALUE CHAIN

3.0 Determining the Size of the Market

Reliable data on Africa’s podcast economy is scarce. Major platforms publish little country-level information about audiences, advertising revenue or creator earnings. Conventional media research also tends to overlook podcast revenue that flows through direct sponsorships, informal agreements and creator-led sales rather than established advertising exchanges.

Geography creates a further difficulty. International studies frequently combine Africa with the Middle East or publish figures only for larger markets such as South Africa. These estimates cannot be treated as measurements of Africa’s podcast market without separating the countries, revenue sources and media formats included.

What existing estimates tell us

Published market estimates provide three broad points of reference:

Country-level estimates are also uneven. South Africa has the most substantial published valuation, at a reported $195.3 million, with projections of $1.35 billion by 2034.

Estimates for Nigeria and West Africa range from $80 million to $130 million, while those for Kenya and East Africa range from $45 million to $75 million.

These figures are not necessarily comparable: some describe individual countries, others describe regions, and their definitions of podcast revenue may differ.

For this reason, the report does not adopt any one published figure as the definitive size of the African market.

The report’s cross-check

This report develops a separate scenario model based on two inputs:

1. The estimated number of podcast episodes or platform assets published during a defined period; and
2. The estimated value of each item, based on the content in our sample.

The model retains the report’s two value tracks. It estimates both the gross Content Value generated for the advertising market and the Creator Earnings that could flow from that value. These figures must remain separate.

This approach can test whether published market estimates are plausible, but it cannot produce an exact continental total. The sample was selected and ranked partly by engagement, rather than drawn randomly from all African podcasts. Its average performance is therefore unlikely to represent the average performance of the entire market. The use of upper-end advertising rates is deliberate, intended to show also the unrealised potential value rather than typical or current revenue.

Estimating African podcast output

Counting African podcasts is difficult because open podcast feeds do not consistently record their country of origin. In addition, many African creators publish on YouTube without maintaining a conventional audio feed.

The report therefore combines several indicators, including:

• Information supplied by creators and publishers;
• Records from African hosting services, studios and advertising networks;
• Feed, website and channel-location data;
• References to African locations, organisations, sponsors and languages; and
• Manual checks of uncertain classifications.

No single indicator is sufficient. A local language, place name or channel setting may suggest a connection to an African market, but it does not establish where a programme is produced or who owns it. African creators in the diaspora may use the same languages and references, while creators based in Africa may register their accounts elsewhere to gain access to monetisation programmes.

The report therefore assigns confidence levels to its classifications and uses manual verification for ambiguous cases. The complete classification method is set out in the Methodology Appendix.

A second challenge is duplication. First, to clarify the definitions:

FOUR UNITS OF COUNTING

The same show may publish an audio feed and a video version of each episode. Adding all RSS feeds to all YouTube channels would count many shows—and possibly many episodes—twice. This is especially important because the report has already found that multi-format distribution is common among leading African podcasts.

The current inputs produce the following results:

The midpoint illustration is:

(10,000 × 21) + (20,000 × 25) = 210,000 + 500,000 = 710,000

Assumptions Used to Estimate Output

Because no single source records all African podcast production, the output estimate rests on four assumptions. Each affects the final range and is tested in the Methodology Appendix.

4. Advertising Rates and Platform Returns

4.1 How the Rates Were Selected

Africa’s large digital audience has not yet translated into equivalent advertising revenue for its creators. The gap between audience size and creator income cannot be attributed to one system alone. It reflects several connected factors: uneven access to platform monetisation programmes, fragmented advertising inventory, limited local advertising demand and payment systems that do not always suit African creators or advertisers.

Direct sales remain particularly important in African podcasting. Available research estimates that approximately 74% of podcast advertising revenue comes from host-read advertisements and sponsorships negotiated outside automated platform systems. This figure should be understood within the geographic and methodological limits of its source. It does not, by itself, prove that platform design is the sole cause of the market’s reliance on direct deals.

The table that follows compares the advertising rates available across platforms and markets. As explained in the methodology, the report uses the upper end of each sourced rate range. The results therefore represent an upper-bound scenario within the available evidence, not an estimate of average creator earnings.

The detailed rate sources, definitions, dates and calculations are provided in the Rate Sourcing Appendix. Each platform rate is compared on a like-for-like basis wherever the available data permits.

Full per-rate sourcing detail, including every disagreement between sources and why each figure was chosen, is maintained in the companion spreadsheet's 'CPM Sources & Methodology' sheet.

4.2 What Regional Advertising Infrastructure Would Need

Server-side dynamic ad insertion allows advertisements to be placed into an audio stream when a listener requests an episode. Wider adoption across African markets faces three practical barriers.

THREE PRACTICAL BARRIERS

An Illustrative Regional Advertising Model

A regional audio-advertising system could take several forms, including an advertising network, marketplace, sales house or supply-side platform. Whatever the model, it would need four core capabilities.

FOUR CORE CAPABILITIES

These capabilities do not need to sit within a single company. A viable regional system could combine advertising sales, insertion technology, independent measurement and payment services through partnerships. Its success would depend on attracting enough advertisers and creator inventory to cover its operating costs.

4.3 The Investment Case for Local Advertising Infrastructure

For investors considering Africa’s creative economy, local advertising infrastructure presents a potential opportunity to earn revenue from podcast audiences that are already being built but remain only partly monetised.

The table below compares the report’s estimate of current conditions with an illustrative mature-market scenario. The second column contains baseline estimates that require verification; the third contains operating targets rather than forecast results.

CURRENT CONDITIONS VERSUS AN ILLUSTRATIVE MATURE SYSTEM

At the midpoint of the stated CPM ranges, the model assumes an increase from $1.50 to $6.50—approximately 4.3 times the current rate. Achieving the target would also require sufficient advertiser demand, credible audience measurement, effective sales, appropriate targeting and enough participating creators to offer useful scale.

The proposed advertising operator could earn recurring revenue by retaining a percentage of the advertising it sells or by charging creators and publishers for software and related services. These are different revenue models that would have to be assessed separately.

Even with a proposed take rate of 20% to 30%, the operator would still need to pay for sales, technology, content delivery, measurement, customer support, payment processing and regulatory compliance. Its profitability would depend on whether the remaining revenue covered these costs.

The investment case therefore rests on three questions:

4.4 Performance and Pricing in the YouTube Sample

Advertising revenue alone does not provide a complete picture of how African podcasts perform. It must be considered alongside measures of audience response and content format.

The table below compares the report’s YouTube sample with selected benchmarks from higher-paying markets. The comparison separates content performance from the price assigned to that performance.

The clearest contrast is between engagement and price. Our sample records stronger interaction per view than the selected comparator benchmark, while its estimated advertising rate is substantially lower.

What the Comparison Means

Taken together, the findings show a market in which strong audience interaction is paired with comparatively low advertising rates. They support the report’s argument that the commercial value assigned to African content does not fully reflect its measured audience performance.

The sample is also distinctly long-form: more than 65% of the YouTube videos analysed run for between 60 and 120 minutes. This creates more potential space for sponsorships and advertising than shorter programmes provide. However, runtime alone does not determine how many advertisements an episode can carry. Audience retention, advertiser demand, platform rules and listener tolerance all affect the amount of inventory that can be sold without weakening the viewing experience.

The investment implication is therefore conditional. Better advertising sales, measurement and delivery systems could help creators earn more from this content. But the opportunity depends on increasing advertising demand and fill rates while preserving the audience relationships that make the programmes valuable.

5. Regional Pricing and the Geography Discount

This report has found that African podcast content generates measurable commercial value, but the rate assigned to that content varies sharply by market. This section compares its estimated value under the rates used in the report with a counterfactual in which every view is valued at the same Tier-1 benchmark.

The difference between the two figures is the report’s geography discount. It is a modelled pricing gap, not money that the platforms necessarily earned and withheld from creators. It estimates how much more the same number of views would be worth if priced at the benchmark rate.

5.1 Country-Level Comparison

What the country comparison shows

The model produces three distinct pricing levels:

• South Africa has the narrowest country-specific gap, at approximately 1.98 times.
• Nigeria and Kenya have substantially wider gaps, at 6.83 and 6.17 times respectively.
• Egypt, Ghana, Uganda, Tanzania and Senegal all produce a 10.97-times gap because the model assigns each the same $1.80 fallback CPM.

The identical result in those five markets should not be interpreted as evidence that their advertising markets perform identically. It is a consequence of using the same fallback rate where a reliable country-specific rate was unavailable.

The Nigeria Diaspora segment illustrates how strongly the applied rate affects the model. South Africa has approximately 31% more views, but Nigeria Diaspora produces about 51% more Applied Content Value because its assumed CPM is almost twice as high.

More broadly, advertising rates are usually influenced by where viewers are located, not simply by the creator’s nationality, production location or channel registration.

The $1.80 rate is a shared fallback ceiling across five markets; it is not a separately measured market-specific rate. Nigeria Diaspora is already priced at parity.

Bars start at zero; all values are US dollars per thousand views.

Spotify Market Performance & Valuation Analysis

Across the 103-episode post-filter dataset, the mode in this report yields 34.56 million total streams, generating $141,928 in Applied Content Value and $682,560.00 USD under Tier-1 Parity – a potential 5x revaluation.

*Note: Creator Earnings represent a theoretical ceiling subject to Spotify Partner Program regional availability.

5.2 The Combined Result

Combining the revised 227-item YouTube sample with the 103 Spotify episodes produces a total sample of 330 items.

Under the report’s model, pricing the same content at Tier-1 rates increases its estimated Content Value by approximately $1.42 million. Applying the stated YouTube and Spotify creator shares produces an additional $752,723 in modelled Creator Earnings.

This comparison holds the content and audience activity constant. It assumes no additional views, listens, likes or minutes watched. Its purpose is to show how sensitive the valuation is to the advertising rates applied.

The difference is a counterfactual estimate, not revenue that the platforms necessarily collected and withheld. Nor is the modelled creator allocation equivalent to money that would automatically reach creators. Actual payment would still depend on programme eligibility, monetised impressions, the revenue base to which each platform applies its share and the availability of payment systems.

The result nevertheless demonstrates the scale of the pricing difference: under otherwise unchanged assumptions, the rate applied to the content has a greater effect on its modelled value than any change in audience performance.

5.3 Why the Modelled Discount Varies by Market

The country-level differences arise from the rates used in the model.

South Africa, Nigeria and Kenya have separate country-level CPM inputs. Nigeria Diaspora is assigned the full Tier-1 benchmark. Egypt, Ghana, Uganda, Tanzania and Senegal are assigned the same $1.80 fallback rate because the research did not identify sufficiently reliable country-specific benchmarks.

The resulting multiples therefore contain two kinds of information:

• For markets with documented country-specific inputs, the multiple compares that rate with the Tier-1 benchmark.
• For markets using the fallback input, the multiple shows the effect of the report’s assumption.

The absence of a reliable published benchmark is itself an important data gap. South Africa’s narrower gap is consistent with the possibility that a larger and more developed digital-advertising market supports higher rates.

The report is not necessarily arguing that African advertisers should immediately pay US, UK or Australian prices. Its narrower finding is that the same quantity of audience attention receives very different modelled valuations when different geographic rates are applied. The size of that difference warrants closer examination of how African advertising rates are formed and what would be required to increase them sustainably.

The 2026 CAIR African YouTube Top 10

A 10-minute minimum runtime applies to this list. Entries marked * are borderline African-domiciled (diaspora or ownership-unverified) and retained pending further review, not excluded outright. Value created is shown at the Tier-1 blended CPM of $19.75.

Bars show views on a common scale (pink = African-domiciled; dark = borderline African-domiciled, marked *). Value created is calculated at the Tier-1 blended CPM ($19.75 per thousand views).

6.0 Revaluing the African Content Economy: The Value of Human Attention

At the centre of the podcast economy is human attention. A minute spent watching a podcast represents the same quantity of human time whether the viewer is in Nairobi or London. Its commercial price, however, can differ sharply.

Advertising markets do not price time alone. They also consider advertiser demand, purchasing power, expected sales, audience location, available consumer data and competition within the advertising market. Still, this report’s argument is that the large pricing differences identified in the sample cannot be explained by content performance alone.

6.1 The Trust Economy

Our sample’s engagement rate exceeds the selected comparator benchmark, while long-form programmes dominate its format. Together, these findings suggest that audiences have active relationships with the content and its hosts rather than merely encountering it passively.

This report describes that relationship as the trust economy: the commercial value created when audiences regard hosts as credible guides, commentators or members of a shared community. Such relationships may make host-read sponsorships and extended brand integrations particularly valuable.

6.2 What Platform Metrics Capture—and Miss

Long-form content can generate substantial total watch time, but length alone does not guarantee recommendation or revenue.

YouTube’s recommendation systems consider several signals, including watch time, viewer satisfaction and an individual user’s viewing behaviour. A 90-minute podcast that holds attention for 40 minutes may generate more total watch time than a short video. It is not, however, automatically promoted more widely. Click-through rate, percentage viewed, satisfaction signals, subject matter and competition also influence discovery.

But longer videos also offer more opportunities for advertising. Videos above YouTube’s minimum-length threshold can be eligible for mid-roll advertisements. Actual delivery depends on advertiser demand, viewer location, platform decisions, creator settings and the suitability of each placement.

The commercial opportunity in long-form African podcasting therefore lies not simply in inserting more advertisements. It lies in measuring attention more accurately, selling appropriate placements and preserving the audience trust that gives the content its value.

Reported metrics from Sections 1, 4.2 and 6; different measures shown together for context.

6.3 The Advertiser Opportunity: African Podcasts and Global Brands

Brands evaluating African podcasts should consider more than audience size and headline CPM. The sample suggests that engagement and programme format can provide useful additional information about the quality of the advertising opportunity.

The sample supports a clear but limited conclusion: advertisers who assess African podcasts only by total reach may overlook programmes with active audiences and strong potential for integrated brand communication.

Engagement Is an Indicator, Not Proof of Trust

Comments, likes and shares show that audiences are responding to content. They do not reveal whether those responses are positive, whether viewers trust the host or whether an endorsement will influence a purchase.

High engagement may reflect loyalty, debate, controversy or disagreement. The content of the interactions matters as much as their number.

Ghana and Uganda record the highest country-level engagement rates in the sample despite having fewer total views than the largest markets. This is consistent with the possibility that some smaller audiences interact more intensively, but whether this is specific to these two countries or generalisable to Africa as a whole is worth investigating further.

The Value of Host-Led Advertising

Host-read advertising allows a brand message to be delivered in the creator’s voice and adapted to the programme’s context. This may make it more relevant than a generic advertisement placed without the host’s involvement.

That advantage is not automatic. It depends on:

WHAT THE ADVANTAGE DEPENDS ON

The transfer of a host’s credibility can also create risk. A poorly matched product, misleading claim or excessive advertising can damage both the creator’s audience relationship and the advertiser’s reputation.

How Brands Should Test the Opportunity

Rather than assuming that engagement will convert into sales, advertisers should begin with measurable campaigns.

They should:

SIX STEPS FOR TESTING THE OPPORTUNITY

The present pricing gap may offer advertisers good value, particularly where engagement is strong and advertising rates remain comparatively low. But “value for money” should ultimately be demonstrated through campaign outcomes, not inferred from CPM or runtime alone.

6.4 Crucial Correction: The Spotify Partner Program Eligibility Gap

The Spotify calculations require an important qualification.

During the period covered by this report, participation in the Spotify Partner Program required a creator to have a legal address in one of 14 eligible markets and to meet Spotify’s additional hosting, audience and publishing requirements. No African country was on that list.

The programme’s 50% creator share is also narrower than the model previously implied. Spotify states that an enrolled creator receives 50% of the revenue Spotify recognises when an advertisement monetised by Spotify plays in the creator’s content. It is not a 50% share of all estimated Content Value, total advertiser expenditure or Premium video revenue.

Premium video revenue is calculated separately using Spotify’s proprietary formula. Eligibility for either revenue stream depends on admission to the Partner Program.

The Spotify Creator Earnings figures in this report should therefore be understood as a theoretical creator allocation under platform parity. They estimate what the creator share might be if:

ALL SIX CONDITIONS WOULD NEED TO HOLD

For a creator whose only legal address was in an African country during the research period, the Partner Program advertising payout available through this mechanism was $0. That creator could publish on Spotify and build an audience there, but could not apply for this particular revenue-sharing programme.

This does not mean that every creator in the Spotify sample necessarily earned nothing. A creator may have had a legitimate legal address in an eligible country, used subscriptions, secured direct sponsorships, worked through an enterprise publisher or earned from the same content on another platform. Actual earnings cannot be determined without creator-level eligibility and payment records.

7. Jobs and Livelihoods: What Can This Report Estimate?

This report has estimated the value generated by the sampled content and the share that creators could receive under each platform’s stated revenue-sharing rules. It has not verified how much creators actually received.

The next question is how many livelihoods this economic activity could support. Answering it requires a clear distinction between actual employment and hypothetical income capacity.

7.1. The Oxford Economics Approach

Oxford Economics has used a consistent economic-impact framework in its studies of YouTube’s creator economy. The framework combines creator surveys, platform data, official statistics and economic modelling.

It does not calculate creator employment by simply dividing revenue by an average wage. Instead, Oxford Economics estimates:

• creator FTEs from survey data on the number of hours creators spend working on YouTube;
• employee jobs from information supplied by creators and media businesses;
• direct GDP from revenue after subtracting production costs; and
• indirect and induced effects through input-output modelling.

An FTE is a measure of labour time, not necessarily one person. Two people working half-time may together represent one FTE.

The modelling tools also vary by country. IMPLAN is used for the United States, while Oxford Economics uses its own input-output models and national economic data for other markets.

7.2. What This Report Can—and Cannot—Claim

This report does not contain the creator surveys, working-hour data, production-cost records or national input-output tables required to reproduce the Oxford Economics method. It also does not contain verified payout records for every creator in the sample.

The report therefore cannot yet estimate:

• the number of people employed by the sampled shows;
• the number of full-time-equivalent jobs they currently support; or
• the indirect and induced jobs created through suppliers and household spending.

What the report can estimate is income-equivalent livelihood capacity: the number of annual incomes that the modelled creator allocation could theoretically fund at a stated income benchmark.

This is a scenario measure, not an employment count. Any such estimate must be presented as:

Potential income-equivalent livelihoods supported by the modelled creator allocation

A future employment study should survey creators and production teams directly, recording working hours, staffing, costs and actual income from platforms, sponsorships and other sources.

7.3. Why Published GDP-to-FTE Ratios Cannot Be Transferred

Oxford Economics reports both the GDP contribution and the FTE employment supported by YouTube’s creative ecosystem. Dividing one result by the other produces the following comparison:

The underlying US and Indian figures are published estimates from Oxford Economics’ YouTube impact studies. However, the final column is this report’s own calculation.

The large difference between the US and Indian ratios may be attributed to a wage-differential, but may also reflect differences in productivity, prices, economic structure, creator-business models, supply chains and the assumptions used in each national model.

Most importantly, the ratios compare total GDP contribution with total FTE employment supported. Both measures include more than direct creator earnings. They cannot therefore be applied to this report’s modelled Creator Earnings to calculate direct employment.

7.4. What the Sample Can Show

This report estimates that the sample’s theoretical creator allocation increases from $492,839.59 at applied rates to $1,245,562.18 at Tier-1 parity rates.

Tier-1 parity would increase the modelled creator allocation by approximately 153%, or 2.53 times. This additional income could support more creator labour, production spending and related economic activity.

The available data cannot determine exactly how many jobs that income would support. Doing so would require evidence on actual creator receipts, working hours, staffing, production costs and the countries in which the work takes place.

However, what is clear is that the geography discount reduces the income available to fund African creative work. Closing it would substantially increase the sample’s capacity to support creators and production teams, without requiring additional views or content.

7.5. A Second Lens: Creator-Income Equivalents

The Africa Creator Economy Report 2.0 found that approximately six in ten surveyed African creators earned less than $100 per month from their creative work.

This provides a locally relevant comparison point, although it is not an employment standard, living-wage measure or estimate of the income required to sustain a creator.

Because this report covers 14 months, one $100 monthly income equivalent equals $1,400 over the study period:

These figures show how many 14-month income units of $100 per month the modelled allocation represents. At applied rates, the allocation is equivalent to approximately 352 such income units. At Tier-1 parity, this increases to approximately 890, an additional 538 units without any increase in views or content volume – starkly illustrating the potential income effect of the geography discount.

Limitations

These estimates are illustrative scenarios, not an employment-impact study.

First, the Creator Earnings figures are modelled allocations. They are not verified creator receipts, and access to platform monetisation varies by country and platform.

Second, $100 per month is a survey income boundary, not a finding that $100 is sufficient to support a creator. Because the survey reports that creators earned less than this amount, it also cannot be treated as their average or typical income.

Third, the calculation assumes equal distribution. In practice, creator income is unevenly distributed, and a small number of high-performing shows may receive a large share of the available revenue.

Fourth, the calculation does not deduct production costs, taxes, management fees or payments to editors, camera operators and other contributors.

Finally, the sample represents 330 content assets rather than the African podcast industry as a whole. The figures should therefore be read only as scenarios for this sample and study period.

8. Creator Origin, Operating Location and Audience Geography

This report identified an attribution problem that was not part of its original research question: a podcast can be African in its creators, production and subject matter while its platform account is associated with another country.

YouTube’s public channel metadata includes a country associated with the channel. However, this field can be selected and updated by the channel operator. It is therefore just one classification signal, not as proof of a creator’s nationality, residence or production location.

This creates five different geographic questions:

FIVE GEOGRAPHIC QUESTIONS

These questions may have different answers. A creator may be Ethiopian, record in Nairobi, operate through a Canadian company and reach an audience spread across Ethiopia, Europe and North America.

The distinctions matter for two separate reasons.

First, platform access can depend on operating location. YouTube states that Partner Program eligibility depends on the channel’s selected country or region and requires creators to live in a market where the programme is available. A channel’s public country setting alone therefore does not prove that its owner qualifies for monetisation in that market.

Second, advertising value is influenced by audience location. YouTube notes that CPM can change with viewer geography because advertisers choose the markets they want to reach. The country attached to the channel and the country generating its advertising value are not necessarily the same.

How This Report Handles Attribution

For the purposes of this report, no channel is classified as African or non-African using the platform country field alone. Classification instead considers:

• the creator’s publicly stated identity and location;
• where the programme is produced;
• the channel’s editorial focus and intended audience;
• the location of the operating company or production studio; and
• audience geography, where reliable data are available.

Where these indicators point to different countries, the report records the content as cross-border or diaspora-led rather than assigning it entirely to one national market.

This approach allows African creative activity to remain visible without assuming that creator nationality, account location and audience geography are interchangeable. It also prevents diaspora success from being attributed automatically to a creator’s country of origin when the underlying audience and advertising markets are elsewhere.

9.0 The CAIR Podcasting 2026 Intelligence Briefing

This report identifies five priorities for strengthening Africa’s podcast economy: better market data, wider access to platform monetisation, investment in advertising infrastructure, improved payment systems and more deliberate buying by advertisers.

A. Recommendations for Policymakers

1. Establish market-transparency standards

African advertising markets lack consistent, public information on realised CPMs, RPMs, fill rates and creator payouts. This makes it difficult for creators, advertisers and investors to value podcast inventory.

Policymakers and industry bodies should establish a voluntary—or, where appropriate, regulated—reporting framework covering:

• realised CPM and RPM ranges by country;
• the share of inventory receiving advertisements;
• advertiser demand and fill rates;
• creator payouts by platform and market; and
• access to platform monetisation programmes.

Because advertising prices are set through auctions and private transactions, the objective should not be to publish a single official CPM. Platforms should instead report aggregated ranges and market trends using appropriate privacy thresholds.

2. Support local advertising and payment infrastructure

Governments should consider regulatory sandboxes, investment incentives and interoperability standards for businesses developing:

• dynamic ad insertion;
• regional advertising exchanges;
• independent measurement and verification;
• local-currency advertiser payments; and
• compliant payouts to creators.

Any tax incentive should be tied to measurable outcomes such as locally monetised inventory, creator payouts, reporting transparency and employment.

3. Build formal links with the African diaspora

Diaspora creators, audiences and businesses connect African content with higher-value advertising and consumer markets. Public policy can strengthen these links through co-production funds, export support, diaspora-focused advertising initiatives and cross-border creative-business programmes.

These programmes should distinguish creator origin, operating location and audience geography so that diaspora activity is recognised without being double-counted as domestic activity.

B. Recommendations for Investors

1. Prioritise the infrastructure constraint

The evidence in this report is strongest for investment in the systems connecting content with advertising demand. Priority areas include:

• catalogue aggregation and commercial representation;
• dynamic ad insertion;
• audience measurement and campaign verification;
• local advertiser sales platforms;
• cross-platform inventory management; and
• creator payment systems.

This does not mean that content and intellectual property are poor investments. It means that infrastructure is the most consistently documented constraint across the markets examined.

2. Test the investment thesis through measurable pilots

Investors should require pilots to report:

• monetised share of available inventory;
• change in realised CPM;
• campaign renewal rates;
• creator payout times;
• production and customer-acquisition costs; and
• creator retention.

C. Recommendations for YouTube and Spotify

1. Expand access to creator monetisation

YouTube’s Partner Program is available in the eight African countries represented in this report’s country table, although access across the continent remains uneven.

As of 12 October 2026, Spotify’s Partner Program is available in 19 markets, none of them in Africa. Spotify has announced a further expansion from 20 October 2026, but the published list still contains no African market.

Spotify should test a phased African rollout, beginning with high-activity markets such as Kenya, Nigeria and South Africa. The pilot should measure creator participation, eligible consumption, advertiser demand and payout performance before wider expansion.

2. Publish country-level market indicators

Both platforms should publish aggregated country-level information on realised advertising rates, inventory fill, audience geography and creator payouts. Reporting ranges would improve transparency without disclosing individual creator or advertiser data.

3. Improve geographic metadata

A channel’s country setting should not be treated as a substitute for creator nationality, production location or audience geography.

Rather than introducing a single “nationality” field, platforms should consider optional, separately labelled fields for:

• principal production location;
• operating or business location;
• markets served; and
• creator-declared cultural or regional affiliation.

These fields should be voluntary, capable of representing more than one country and protected against misuse. Platforms should not infer nationality from language, names or content.

4. Test African podcast advertising packages

Both platforms should test advertising products that bundle high-engagement, long-form African content for regional and global buyers. These pilots could include minimum campaign rates or revenue guarantees where advertiser demand supports them.

The results should be assessed through completed views, watch time, brand lift, conversion and creator revenue—not engagement alone.

D. Payment Infrastructure

Payment constraints affect both sides of the market: advertisers need reliable local-currency purchasing, while creators need compliant and affordable payouts.

The severity of these constraints varies substantially by country. The remaining question is whether these systems can support compliant advertising purchases and creator payouts across borders.

Policymakers, platforms, banks and payment providers should test:

• local-currency advertising purchases;
• foreign-exchange conversion;
• tax and identity verification;
• cross-border settlement;
• mobile-money creator payouts; and
• dispute and refund procedures.

Country pilots should be designed with the relevant financial regulators and payment providers rather than assuming that a single pan-African payment model will work everywhere.

E. Recommendations for Advertisers

1. Add engagement and format depth to media selection

The sample’s weighted engagement rate of 2.75% and its concentration of 60–120-minute content justify including African podcasts in advertiser shortlists.

Advertisers should test them against campaign outcomes such as completed views, referral traffic, brand recall and conversion.

2. Test host-read advertising directly

Host-read advertising should be evaluated through structured pilots rather than assumed to outperform automatically. Campaigns should use trackable links, promotional codes, audience surveys or brand-lift studies to compare host-read placements with standard programmatic advertising.

3. Treat under-documented markets as opportunities requiring due diligence

Markets without published CPM benchmarks may offer attractive direct-buy opportunities, but the absence of data does not itself prove that inventory is undervalued.

Advertisers should assess:

• audience relevance;
• creator credibility;
• brand safety;
• production consistency;
• verified reach; and
• expected campaign outcomes.

4. Treat diaspora audiences as a distinct buying segment

The Nigeria Diaspora category is the largest single Content Value line in the report’s YouTube country table. This supports a clear commercial case for diaspora-focused campaigns in remittances, travel, telecommunications, financial services and consumer goods.

1. Sample period defined as June 1, 2025 to July 31, 2026 across YouTube Data API v3 and Spotify chart extracts.
2. Content Value calculated on a CPM basis representing aggregate gross platform advertiser outlay.
3. Revenue split applies 55% YouTube creator share (Made on YouTube 2025) and 50% Spotify Partner Program share.
4. Audio streaming growth data corroborated by SQ Magazine (2026) and Spotify regional growth announcements.
5. Multi-format publishing metric derived from 330-asset primary sample analysis (68.2% dual video/audio feeds).
6. Host-read advertising share sourced from Sub-Saharan media buyer survey data (The Creative Brief Africa 2026).
7. ARPU range derived from regional mobile money payment gateways and membership patronage reports.
8. Tier-1 CPM comparison baseline ($19.75) calculated as average of US ($30), UK ($20), AU ($18), and EU ($11) via VloggingPro (2026).
9. South Africa CPM ($10.00) vs. Sub-Saharan fallback ($1.80) yields a range from 1.98x to 10.97x discount multiple.
10. Weighted aggregate engagement rate = Sum(Likes + Comments) / Sum(Views) * 100 across 227 YouTube assets.
11. YouTube Partner Program (YPP) regional coverage verified across 13/54 African countries via Google Support.
12. Income baseline derived from Africa Creator Economy Report 2.0 ($100/mo threshold across 14 months = $1,400).
13. Market size benchmarks cross-referenced with Grand View Research, PwC Africa E&M Outlook, and Statista.
14. CPM rate ranges synthesized from Lenos, upgrowth.in, mykitchenincome.com, and VloggingPro 2026 benchmarks.

Appendix A: Valuation Methodology

This appendix details the explicit formulas, rate ranges, and assumptions used to calculate CPM-based Content Value and RPM-based Creator Earnings.

Formula 1: Content Value (CPM Basis) = (Views / 1,000) × Applied CPM Rate

Formula 2: Creator Earnings (RPM Basis) = Content Value × Platform Revenue Share (0.55 for YouTube / 0.50 for Spotify)

Every rate applied in this report uses the upper end of its sourced range to estimate ceiling value rather than typical averages. For instance, South Africa's $10.00 CPM reflects the high end of available rate cards, while Tier-3 Sub-Saharan markets use a $1.80 fallback ceiling.

Appendix B: Value-Chain Organisations and Platform Access

Detailed profiles of key regional ecosystem players and platform access benchmarks:

Spotify Footprint: Spotify entered South Africa in 2018, expanded to 39 African markets in 2021, established a regional Johannesburg office, and launched the $100,000 Africa Podcast Fund in 2022 via Africa Podfest.

SemaBOX (Nairobi): East Africa's leading podcast studio network providing multi-camera physical production and digital distribution tools (Wazo app).

Glitch Africa Studios (Lagos): West Africa's primary studio hub driving high-production video-first podcast shows.

Afripods & iono.fm: Regional hosting, syndication, and ad-tech networks operating across East and Southern Africa.

Atunwa Digital: Specialized African ad-tech platform deploying server-side Dynamic Ad Insertion (DAI) into audio streams via AdsWizz integration.

Appendix C: Methodology of market estimation

Search results do not provide a neutral map of African podcasting. They are shaped by the language of the search terms, the information creators include in their accounts, the popularity of existing channels and the way platforms rank results.

The methods used to construct the sample may therefore favour established creators in large English-speaking markets. Emerging creators in Francophone and Lusophone Africa—and in smaller markets more broadly—are likely to be less visible in the dataset.

Senegal, for example, is represented by only two episodes in the sample. This should be read as a limitation of the sample, not as evidence that Senegal has a small podcast sector. Country-level counts in this report describe the content captured by the research method; they should not be interpreted as each country’s share of the continental market.

To mitigate this, classification involved multi-layered verification: entity parsing, indigenous language tags (Swahili, Yoruba, Amharic, Hausa, Zulu, Wolof), ccTLD web analysis, and manual origin reviews.

Appendix D: Investment Models and Operating Requirements

Detailed operational requirements for regional capital deployment across three primary vectors:

D.1 Regional Dynamic Ad Insertion (DAI) Networks: Deployment of server-side DAI ad-tech combining RSS audio impressions with YouTube video slots, utilizing multi-currency self-serve advertiser portals and mobile money settlement.

D.2 Catalogue Aggregation & IP Vehicles: Media holding entities acquiring or managing commercial rights for top-performing independent podcast catalogues to command premium CPMs.

D.3 Direct Audience Payment Infrastructure: Building direct patronage, pay-per-episode, and premium audio feeds native to local mobile money rails (M-Pesa, MTN MoMo, Airtel Money).

THREE INVESTMENT MODELS

Appendix E: Market-Size Unit Definitions & Deduplication Procedure

To prevent double-counting across multi-format shows publishing simultaneously on RSS feeds and YouTube, this report applies strict analytical definitions:

This distinction prevents one video-and-audio podcast from being counted as two separate shows.

Deduplication Formula: Unique Episodes = RSS Episodes + YouTube-Only Episodes - Verified Cross-Posted Multi-Format Duplicates.

Platform assets = RSS publications + YouTube uploads

ANALYTICAL UNITS

Show ≠ channel ≠ episode ≠ platform asset