eBooks - Pakistan | Statista Market Forecast

eBooks - Pakistan

Pakistan

Highlights

The eBooks market in Pakistan is projected to experience significant growth in the coming years.
By 2024, the revenue in this market is expected to reach a staggering US$5.17m.
This growth is predicted to continue, with a compound annual growth rate (CAGR) of 3.17% between 2024 and 2027.
As a result, the market volume is projected to reach US$5.68m by 2027.
Furthermore, the number of readers in the eBooks market is expected to increase substantially, reaching 12.3m users by 2027.
This indicates a growing interest in digital reading among the population in Pakistan.
In terms of user penetration, it is estimated to be 4.4% in 2024 and is expected to rise to 4.9% by 2027.
This indicates that a larger percentage of the population will be engaged in reading eBooks market during this period.
The average revenue per user (ARPU) is predicted to be US$0.49.
This measure gives an indication of the average spending of eBook readers in Pakistan.
When compared globally, United States is projected to generate the highest revenue in the eBooks market.
In 2024 alone, the US market is expected to generate a revenue of US$5.34bn.
This showcases the dominance of the US market in the global eBook industry.
Overall, the eBooks market in Pakistan is poised for significant growth, with increasing revenue, readership, and user penetration.
This presents an opportunity for publishers and authors to tap into the growing digital reading trend in the country.
The eBook market in Pakistan has been rapidly growing, with an increasing number of readers turning to digital platforms for their reading needs.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on the ePublishing market. ePublishing is defined as paid editorial/written content distributed over the internet, including eBooks (fiction, non-fiction, and academic publications), digital editions (replicas) of consumer and trade/business magazines (eMagazines), as well as daily or weekly newspapers (ePapers). All monetary figures refer to consumer spending on digital goods or subscriptions in the respective market. This spending factors in discounts, margins, and taxes.

Modeling approach / market size:

The market size is determined through a bottom-up approach. We use annual financial reports of the market-leading companies and industry associations, third-party studies and reports, survey results from our primary research (e.g., the Statista Global Consumer Survey), as well as performance factors (e.g., user penetration, price per product, usage) to analyze the markets. To estimate the market size for each country individually, we use relevant key market indicators and data from country-specific industry associations, such as various macroeconomic indicators, historical developments, current trends, and reported performance indicators of key market players. In particular, we consider average prices and annual purchase frequencies.

Forecasts:

We apply a variety of forecasting techniques, depending on the behavior of the relevant market. For instance, the S-curve function and exponential trend smoothing are well suited for forecasting digital products and services due to the non-linear growth of technology adoption. The main drivers are GDP per capita, consumer spending per capita, and 4G coverage.

Additional notes:

The data is modeled using current exchange rates. The market is updated twice a year in case market dynamics change. The impact of the COVID-19 pandemic is considered at a country-specific level. The data is modeled using current exchange rates. The impact of the COVID-19 pandemic and the Russia-Ukraine war are considered at a country-specific level. The market is updated twice a year. In some cases, the data is updated on an ad hoc basis (e.g., when new, relevant data has been released or significant changes within the market have an impact on the projected development). GCS data is reweighted for representativeness.