Executive Summary
Introduction
The SMS traffic headline data
The SMS spend headline dataThe A2P SMS Alternative View
The traffic rainbow
The SMS traffic rainbow definitions

Section 1: Market Overview
The A2P SMS industry view
The Covid effect
The A2P SMS opportunity (businesses using SMS)
Market overview 2017-2027
Average cost of SMS
Alternative View market potential

Section 2: Market Analysis
Do not underestimate the importance of SMS
WhatsApp is coming
International termination rates
The impact of pricing on traffic
WhatsApp Business use case pricing analysis
WhatsApp Business use case pricing analysis; OTP
SMS firewall deployments
Exclusivity gateway deals
Market model: Impact on businesses
The rise of the grey routes
Artificially Inflated Traffic

Section 3: Market forecasts: Traffic
Total traffic
Domestic / international traffic
Total white route traffic
Total grey route traffic
Total blue traffic
Total harmless grey traffic
Total orange traffic
Total red traffic
Total harmful traffic
Total harmless traffic
Total traffic lost to WhatsApp
Total regional traffic overview 2022
Total regional traffic overview 2023
Total regional traffic overview 2027

Section 4i: Market Forecasts: Spend – Total View
Total spend ($)
Total blue spend ($)
Total harmful spend ($)
Total harmless spend ($)
Total regional spendoverview 2022
Total regional spend overview 2023
Total regional spend overview 2027

Section 4ii: Market Forecasts: Spend – Value Chain
Value chain explainer
Total spend ($) – excluding blue
Total domestic spend ($)
Total international spend ($)
Total white spend ($)
Total grey spend ($)
Total harmless grey spend ($)
Total orange spend ($)
Total red spend ($)
Total mobile operator spend ($)
Total aggregator spend ($)
Total lost spend ($)
Total potential spend ($)

Section 5: A2P SMS by region
Total traffic / spend ($)
Africa traffic / spend ($)
Asia traffic / spend ($)
Caribbean traffic / spend ($)
East Europe traffic / spend ($)
Latin America traffic / spend ($)
Middle East traffic / spend ($)
North America traffic / spend ($)
Oceania traffic / spend ($)
West Europe traffic / spend ($)

Methodology

Our datasets include individual market data for the top 200 markets from around the world. Click here for a detailed overview of all markets. Top 30 markets by spend (2022) include;

• Afghanistan
• Argentina
• Australia
• Bangladesh
• Brazil
• Canada
• China
• Egypt
• Ethiopia
• France
• Germany
• India
• Indonesia
• Italy
• Mexico
• Netherlands
• Nigeria
• Pakistan
• Philippines
• Russia
• Saudi Arabia
• Spain
• Sri Lanka
• Taiwan
• Uganda
• Ukraine
• United Kingdom
• USA
• Uzbekistan
• Vietnam

For each of the 200 markets we cover, our SMS user data is split by:

• total unique mobile users (UMUs)
• total mobile subscriptions
• opt-in users by market vertical
• total users split out by device type: smartphone by OS/non-smartphone.

We split our A2P SMS messaging data out by 18 sectors + “Other”. This ensures we cover all the main market verticals in every market, but also can accommodate for national and regional variations. The verticals are:

Automotive / Broadcasters / Charity / Education / Enterprise software / Finance / Gambling / Healthcare / Internet streaming / Leisure & entertainment / Public services / Restaurants & fast-food / Retail & eCommerce / Social media & chat / Telecoms / Transport & logistics / Travel & tourism / Utilities / Other

For A2P SMS traffic types we apply 4 use cases:

Alerts / Marketing & Promotions / Reminders / Security (including One-Time Passwords (OTP))

To reflect the changing market dynamics, Mobilesquared has updated how it breaks out traffic (no longer just white & grey), as we have now identified 6 traffic types:

• White route traffic – legitimate
• Light blue route traffic – artifically inflated traffic (undelivered, phantom traffic, no consumer impact)
• Dark blue route traffic – artifically inflated traffic (delivered, consumer impacted)
• Grey route traffic – harmless (no threat to consumer)
• Orange route traffic – SIM Farm traffic (harmful aftershocks, potential threat to consumers)
• Red route traffic – harmful (Threat to consumer)

In addition, we will also break all traffic types out by:

• Domestic
• International
• Wholesale
• Retail
• Total traffic

Traffic data is then segmented further:

• annual traffic – split by country, MNO, source & route
• annual traffic per user – split by country, MNO, source & route
• annual traffic – split by country, vertical & use case
• annual traffic per SMS opt-in – split by country, vertical & use case

Our spend data is based on our traffic data. To achieve spend figures for each market, we apply the relevant SMS rates per market that we receive through our extensive on-going research (see Methodology below). From our data you will be able to access spend by:

• White route
• Light blue route
• Dark blue route
• Grey route
• Orange route
• Red route

And then by

• Domestic
• International
• Wholesale
• Retail
• Market vertical
• Use case
• Total spend

We also split out spend by value chain:

• Mobile operators
• Aggregators – we use aggregators as an umbrella term.

This is how spend appears in our datasets:

• Annual Spend – split by Country, MNO, Source, Route, Value Chain & Value
• Average Spend per User – split by Country, MNO, Source, Route, Value Chain & Value
• Annual Spend – split by Country, Vertical & Use Case
• Average Spend per SMS Opt-in – split by Country, Vertical & Use Case

We also look at the impact of fraud on A2P SMS spend, and how this impacts the overall market. Lost spend is based on if “grey/orange/red route traffic was actually white route traffic”, while Potential Spend takes into account the Lost spend and is applied to the total spend (for a more detailed explanation please read Methodology below).

• Lost Spend per User – split by Country, MNO, Source, Route, Value Chain & Value
• Potential Spend – split by Country, MNO, Source, Route, Value Chain & Value

To create our messaging forecasts, we have to generate a lot of background data, based on population, mobile subscriptions, unique mobile users, and device type (based on smartphone OS and non-smartphone), all of which is projected over our latest forecast period. We now include all of this data as supplementary to all our core datasets, to help provide you with a more holistic view of the market.

• Unique Population Access – by Country, User, Device, Gender & Age
• Unique SMS Users – by MNO, Device, Gender & Age
• Mobile Subscriptions – by MNO

Our A2P SMS data is viewed as the best & most robust messaging data available in the marketplace because we are constantly speaking to the messaging ecosystem and play a very active role within the Mobile Ecosystem Forum (MEF), and at major messaging events where we engage with the companies shaping this sector.

In 2023, when updating our messaging data we received data and insight from 290 companies, including:

• 160 mobile operators
• 130 aggregators, CSPs, vendors, hub providers, interconnect providers, regulators, firewall providers, and independent consultants.

Companies that have helped our research, include:

A1 Slovenija / A1 Telekom Austria / 2Mobile / Adaptive Mobile / Aegis Mobile / Afghan Wireless / AI Cross / Alchemy / Anam / Andorra Telecom / Apprentice Valley / Arelion / AT&T / Bandwidth / Beep / Bell Mobility / Bharti AirTel / BH Telecom / BICS / Bouygues Telecom / BT/EE / Bulk SMS / Cequens / Cheetah Mobile / China Mobile International / China Telecom Global / Cisco / Claro Dominicana / Comcom / Commify / Comviva / de / Deutsche Telekom / Direqt / Enabld / Eir / Ethio Group / Ethio Telecom / Etisalat / Fonix Mobile / Global Point / GMS / Go4Mobility / Google / GTC / GTS / Gupshup / Haud / Hrvatski Telekom / Hutchison Drei Austria / iBasis / iConectiv / Infobip / Interop Technologies / iTouch Messaging / Kaleyra / Karix / Lanck Telecom / Libyana / LINK Mobility / LivePerson / Mavenir / MEF / MegaFon / Melita / MessageBird / Messagio / Millicom / Mitto / MMDSmart / MobiFone Telecommunication Corp. / Mobileum / Mobivity / Modica Group / Monty Mobile / Movitext / MTN / MTN Global Connect / MTN Irancell / MTN Nigeria / Neustar / Nova Iceland / Nuevatel PCS de Bolivia / O2 / Oi / OmanTel / Ooredoo / Openmind / Orange / Out There Media / Oxygen8 / Panacea Mobile / PCCW Global / Phronesis / PolkomTel / Quiubas Mobile / RD Com / RealNetworks / Reliance Communication / Route Mobile / Salesforce / Samsung / SFR / Sinch / SMS Highway / Softbank / Somos / Soprano / STC / Summit Tech / Sunrise / Swisscom / Synchronoss / Syniverse / Tatango / Tanla / Tata / Telecom Italia / Telefonica Group / Telefónica Móviles España / Telekom Slovenije / Telenor / Telesign / Telia / Telia Carrier / Telnyx / TelQ Telecom / Thales / Three / Three Ireland / TI Sparkle / T-Mobile / T-Mobile US / Tomia Global / True Corporation / Tunisie Telecom / Turk Telekom International / Twilio / TWW / Tyntec / Uganda Telecom / Unifonic / Unitel / UnoTelos / US Cellular / Verizon / Viber / Vietnam posts and telecommunications group / VimpelCom / Vodafone / Vonage / Vovitel Communications / Vox / Wavecrest / Wavy / WhatsApp / WIND / WMC Global / XConnect / Zain / Zain Kuwait

Does your data have a KPI?

It does. To ensure the risk of double counting is removed from our numbers, the key performance indicator for Mobilesquared is the number of messages received per unique mobile user.

Is the traffic Mobile Originated or Mobile Terminated?

Because our KPI is based on messages delivered, our data only focuses on Mobile Terminated.

Where is the data from?

Mobilesquared is omnipresent within the messaging ecosystem, constantly talking to companies, attending events, and playing a very active role within the Future of Messaging Working Group in the Mobile Ecosystem Forum. In 2021, the data and forecasts were based on information and data shared by 290 companies.

A2P SMS methodology 2023

Our data is based on extensive research over an on-going period, starting back in 2010, and has continued ever since. Between January 2021 to October 2021 we interviewed/surveyed/received data from almost 290 companies (160 mobile operators and mobile operator groups, and 131 messaging ecosystem companies, including aggregators, CSPs, solutions providers, firewall providers, independent consultants and regulators). Throughout 2022, we connected with 150 companies, with the main research for this report kickstarting in happening in 4Q 2022. By the time Mobilesquared closed the research we had connected with 225 companies, based on the companies listed above.

Mobilesquared applies a three-pronged research strategy for A2P SMS.

1. Online surveys

Mobilesquared developed online surveys for each business messaging channel, running continuously via the company website. For A2P SMS, we have developed two online surveys, one for mobile operators monetising A2P SMS traffic, and a separate survey for the broader A2P SMS messaging ecosystem. In both surveys, companies not monetising A2P SMS traffic, or have no intention of monetising A2P SMS traffic, are screened out.

2. 1-2-1 and 1-2-many interviews

Mobilesquared uses its extensive reach throughout the messaging ecosystem to interview companies operating within, or whom have knowledge and insight of, the A2P SMS landscape.

3. Data sharing

Mobilesquared shares existing data with clients and non-clients. We have over 70 A2P SMS clients and the majority provide feedback, data, trends, growth and insight on our (at the time) existing A2P SMS data and projected growth, based on their view of the industry. For clients we shared key data points from 2022 in order to receive their market data for 2022, and expectations for 2023. For non-clients we shared data points from 2021 and asked for their market data for 2021 and 2022, and their expectations for 2023.

Where requested, Mobilesquared has entered into NDAs with companies as part of a data exchange.

All data and insight is then processed, anonymised and aggregated (where there is input from multiple sources), modelled and sense-checked.

Mobilesquared updates its business messaging forecasts on an annual basis, with smaller updates occurring throughout the year.

Our industry research is supplemented by consumer research, updated on an annual basis, and enterprise research which is updated on an ad hoc basis. Mobilesquared last conducted consumer research in 1Q2022, and this data will feed into the A2P SMS engagement data to be included in the 2023 updates. The consumer research was based on 10,000 people across 10 markets (Australia, Brazil, Colombia, France, Germany, Malaysia, Mexico, Singapore, UK, and USA). Consumer research forms the basis of our opt-in user data. Mobilesquared has supplemented consumer research with actual market data from partners to cover additional markets. Where we do not have national specific data we have applied a regionalised average per market.

A2P SMS forecast methodology

The data in our global A2P SMS messaging forecasts is based on data modelling (traffic or pricing), whereby Mobilesquared takes an average where two or more sources of actual market data were available. Across the 200 markets tracked by Mobilesquared, forecasts by market are based on an average of 18 data points. As a result of the greater input, we have been able to model each of the 200 markets individually for market size, split of international and domestic traffic, and growth over 2019, 2020, 2021, 2022, and into 2023, and throughout the forecast period up to 2027.

The starting point for these A2P SMS messaging forecasts is our mobile operator subscriptions database. We research the top 200 markets worldwide collating information from regulators, mobile operators and mobile operator groups. Data-only contracts and M2M accounts have been excluded (where available). Subscription forecasts are modelled based on previous growth records, overall mobile penetration rates and expected population growth.

Average A2P SMS pricing and pricing forecasts for the 200 markets covered (termination and wholesale rates) are based on country-by-country information obtained from mobile operators, mobile operator groups, aggregators, cloud service providers, and hubs.

Traffic and traffic growth forecasts for the 200 markets covered are based on our ongoing interviews, discussions and online surveys, looking at total volumes of authorised and unauthorised traffic, and the number of messages received per subscriber per month. The level of unauthorised traffic has also been applied according to our research into the per mobile operator deployment of SMS firewalls and SS7 protection, because of Information provided from firewall vendors and solutions providers on the rollout and adoption of SMS firewalls. This has been further segmented from 2023 research (and historic research between 2018-2021) to breakout the new traffic types (subsets of white traffic and grey traffic) based on differing fraud types: blue, orange and red.

Mobilesquared has made the assumption that approximately 5% of each operator’s A2P traffic will always be grey-route due to the nature of companies looking to expose and exploit loopholes, and approximately 10% will always be white-route due to direct agreements between mobile operators and the enterprise.

We have assumed that where no SMS firewall is in place that at least 80% of traffic is grey. We have also assumed there will be varying rates of protection where SMS firewalls are in place due to differences in managed solutions, hosted solutions, on-premise solutions, or blended solutions. Mobilesquared research reveals SMS firewalls typically block 80%-90% of all traffic, and this has been applied as the basis when modelling fraudulent traffic.

We have assumed that no exclusivity agreements of preferred partner deals are in place per mobile operator, unless Mobilesquared has received data from industry through the research process of such a deal. At the time of publishing the 2023 update, over 200 known deals were in place, and these have been taken into account when looking at pricing, and the varying types of traffic activity that can associated with such deals.

Domestic and international traffic volumes, messages by sector and associated forecasts are based on our ongoing interviews, discussions and research (including detailed survey information conducted throughout 2021, 2022, and 2023). Sector traffic, and sector traffic split out by use case, has previously only been attributed to white route messaging, but from 2023, this will be applied to white/grey, international and domestic, and retrospectively applied back to 2017 using historic data.

Pricing data for each mobile operator covered in this Databook was received from multiple sources – both discount and premium messaging providers, as well as mobile operators and operating groups.

Pricing

The basis for all international spend are the latest international termination rates (as of 2Q2023) for every mobile operator. Where we have received the latest domestic rates, these have been applied. Consequently, we have used three separate rate cards for our pricing:

• A discount international rate for large-volume providers – with an approximate 10-20% mark-up on the cost of purchase from mobile operators in 2023 (we applied an average 15% mark-up).
• A premium international rate – with an approximate 30-40% mark-up on the cost of purchase from mobile operators in 2021 (we applied an average 35% mark-up)
• A domestic rate (where available) – typically 20-33% of the relevant international rate for discount or premium providers with the same mark-up applied.

We have assumed approximately 90% of non-direct traffic between mobile operators and brands is discounted, and the remaining 10% is premium.

We have also assumed that 5-15% of all traffic delivered to a mobile operator will be the result of a direct relationship with brands, priced without the above mark-up.

Large mobile operating groups, and mobile operators in mature markets, are likely to see more direct traffic than smaller, independent mobile operators, in developing markets.

Input on the cost of grey route traffic varied from 15-70% of the discount rate. We have applied a rate of 46%.

All monetary values show the actual income for each part of the value chain – mobile operator or aggregator. Total spend is what a brand pays for messaging with the income from that then split (where appropriate) between mobile operator and aggregator.

Mobile operator white route revenues are calculated based on varying small degrees of direct spend, according to our ongoing interviews, discussions and research (including detailed survey information conducted in the summer of 2021). The majority of mobile operator revenue is based on the average wholesale rates paid by aggregators.

Aggregator white route revenues are calculated based on the difference between the average termination and wholesale rate per market. Mobilesquared has allocated aggregators 100% of grey route revenues, even though a proportion could be attributed to mobile operators from, for example, the sale of SIM cards used in SIM farms. SIM farm traffic is included as grey route traffic in our data.

Artificially Inflated Traffic (AIT) (aka labelled blue traffic by Mobilesquared) has been modelled using a spend-down approach, and these have been calculated on a country and mobile operator basis. Please note, only the country data will be released by Mobilesquared for the foreseeable future because of the sensitive nature of the traffic. AIT spend per market has only been applied to international traffic (based on research), and has been calculated on the following:

• Mobilesquared’s understanding of the traffic split/messaging spend by the top 30 senders of international traffic;
• the trusted assumption that these top 30 companies account for 80% of total traffic;
• spend data from Twitter, and other OTT providers, based on insight shared with Mobilesquared.
• Market-by-market data shared by industry
• Analysis of historic research reveals AIT has always been present but held a minimal subterranean presence in terms of threat level.

To generate the forecasts, based on research, Mobilesquared has assumed AIT occurs in every market with vastly differing degrees of activity. We have assumed that where the international termination rate is low, AIT activity is extremely restricted but is present nonetheless. Where the international termination rate is high, we have applied high levels of AIT activity.

Traffic volumes were derived from dividing the total spend per market by the international termination rate cost per mobile operator, or the average international termination cost per market. Please note, the methodology to generate AIT forecasts is focused on spend, with traffic levels an output of this spend total. Mobilesquared acknowledges that this approach does not take into account the discounts negotiated by the major brands sending bulk messages globally. Because Mobilesquared believes the spend figure is an accurate reflection of AIT spend throughout the forecast period, Mobilesquared clients could apply known discounted international termination rates to get (what could) be a more accurate reflection of traffic levels on a market-by-market basis.

Please note II, AIT (blue traffic) has a permanent presence throughout the traffic section of this report, and is clearly stated where it is featured. However, due to the uncertainty and inconsistency in the data shared by industry relating to where brand spend in AIT is (and should be) allocated in the value chain, Mobilesquared has only applied AIT to total spend on a market level basis, and its inclusion within the A2P SMS datasets and report has been restricted to market spend data associated with fraud, such as the “Harmful” view of the industry. Where Mobilesquared has split out spend by value chain, we have removed blue (AIT) spend altogether, i.e. section 4ii of the report that looks at spend on different traffic types across the value chain. Where AIT has not been applied in the spend forecasts, it will be clearly labelled as such.

For dark blue traffic (AIT delivered to a consumer), Mobilesquared has applied a percentage of total traffic from the light blue traffic (AIT blocked) based on data from industry. However, because of the miniscule number of messages delivered, Mobilesquared has sidelined this traffic type for the time being.

Potential/Lost revenue

Our calculations for potential income treat all traffic (both white and grey-route) as official white-route, with pricing as above.

The lost income is therefore the difference between the actual, and the potential, income.