Marketing in Emerging Economies | Lecture
Lecture 1: Introduction to the Course and the Real-Life Case
- #DownToEarth
• Both space technologies and earth observation data have a lot of potential for earth
applications that is not yet fully tapped by business start-ups.
• Mission: To inspire and support start-ups to use space technologies to #
applications.
• How to organise start-ups are in the market? Competitions, Hackathons (i.e. come up with new
ideas in 24-hours), Programs, Astropreneurs (i.e. online/offline program), Venture Academy, ESA
business program.
• ESA Business Program: 2 years in the program, incubated in the company, and you can use
space technology and data. You must have a company not older than 5 years.
- Start-Up 1: Smart Farm Sensing
• Smart Farm Sensing is a Netherlands based agri tech consulting company providing services,
solutions and consultancy to the agriculture sector on intelligent sensor data and geospatial
information.
• Vision: fully operational satellite, aerial and ground remote sensing information supply chains
are key to increase the global agriculture productivity and to sustain our (future) food chain.
• Mission: to prove our clients with sensor networks, geo-information systems, spatial databases,
web-portals, and mobile apps.
• One of the products they are creating = AgrloT ground sensor network. They have sensors that
send specific information from the farm. Goal is to create low cost sensors that communicate with
a gateway (i.e. a large WiFi router).
• Market is the date fruits industry (dadels in Dutch).
• Palm tree management: mapping, registration and monitoring for palm trees.
• First Sensor = Insect Trap Management: mobile registration, recording and visualisation of Red
Palm Weevil traps. The trap has a sensor which counts how many weevils are in the traps. On an
hourly basis, Smart Farm Sensing knowns how many weevils are in the traps.
• Second Sensor = Soil Moisture Sensing: mobile visualisation of soil moisture condition with
sufficient soil moisture sensors real-time moisture distribution maps of the fields are provided.
• Figure of the system:
1
, • Plague and Water Pressure Map: monitoring plague and water pressure per date palm field.
• Date Palm Farms are the target market because stye produces 7.5 million metric tons of date
fruits per year (on average). It takes 7 years for date palm to produce fruits.
• Emerging Markets: Morocco, Egypt, UAE.
- Start-Up 2: Opt-Net
• Monitoring and fusing the data that comes from stations. It allows humans to respond quickly
and help the people affected to recover from the aftermath as soon as possible. It is like finding a
needle in a haystack - however, this company does that.
• The satellite collect imagery (SAR, SLSTR, etc.), then the AI Engine Analyses SAR data in real
time.
• Which data do they use? SAR data - specific type that is a radar, which scans the earth surface
for any changes. Large and small changes are detected, catalogued, and analysed. This data
humans can hardly comprehend, so other data is used to confirm that findings that the IA has
found.
• Still learning, because they are still using data trails to show that their data works better than
humans.
• Benefits for now:
- 99% more effective than humans are faster
- Economically feasible: 1/10th of the cost of comparable solutions.
- Accurate and timely detection: 24/7 coverage.
- Real time = <2 sec reaction time.
- Scalable: 1 TB of data per day.
• Commercialisation (not B2B): Government Agencies, Civilian Services, Geo Information System
Providers. Target global customers.
- Start-Up 3: FieldBee
• Global Problem: less than 2% of the world's population is employed in agriculture, while 100%
are consumers of food. Noticeably, world population is growing on average 1.21% YoY, which
entails that farmers need to produce 2 times more food by 2050. Precision agriculture can
improve yield by 70%, but its penetration is only 5%.
• Farmer problem:
- Farmers are overworked. They work more than 12 hours work per day while performing filed
operations.
- Farmers on average experience low profitability. Many risk losing their family business, because
competition is forcing farmers to find ways to increase margins, improve productivity, be more
precise in fieldwork, reduce waste and control costs.
- Inaccuracy or errors in execution often lead to severe consequences such as reduction of even
loss of their harvest.
• Solution:
- Precision farming can reduce up to 70% of costs of food production
- Precision farming can reduce vast and improve yield
- Precision farming can make farmers work easier
• What is it? Technologies enabled by GPS and GNSS systems, that make the practice of farming
2
, more accurate and controlled when it comes to the growing of crops and raising livestock.
Examples: more accurate tractor driving, watering, measuring of costs/yields, spreading of
fertilisers and enabling surveys with drones and identification of exact locations with crop
diseases, and issues, bugs.
• Precision farming already happened in the 80s, but only 5% of the farmers use them today,
because they were complex, didn't pay on invests and very expensive.
• eFarmer is making precision available to every farmer.
• eFarmer is offering affordable easy to use solutions that works on smartphones/tablets.
• Products much much cheaper than competitors, about 10%.
• Cloud technologies used.
• Customers: all farmers with tractors, small and medium farmers worldwide (90% of all
farmholds).
• FieldBee works already in 46 countries.
• Emerging markets interested in: Latin America, Africa, India.
• , +31652688925
Lecture 2: Marketing Strategy and Value Proposition in EE
- An Emerging Market is a country that has some characteristics of a developed market, but does
not satisfy standards to be termed a developed market. This includes countries that may become
developed markets in the future or were in the past. The 10 Big Emerging Markets economies
are: Argentina, Brazil, China, India, Indonesia, Mexico, Poland, South Africa, South Korea and
Turkey. Egypt, Iran, Nigeria, Pakistan, Russia, Saudi Arabia, Taiwan, and Thailand are other major
emerging markets.
- Global challenges:
1. The drive for prosperity and development
2. The desire to retain identity and traditions
“... Half the world - sometimes half the same country, sometimes half the same person - was still
caught up in the fight over who owns which olive tree.” (Friedman 2000, The Lexus and Olive
Tree)
- Westjohn and Magnusson (2017) assess the conditional effects of discretionary marketing
adaptation on export performance. The main idea here is:
• How do we do marketing across borders, while world is becoming “borderless”?
• Should we adapt or standardise marketing programs, especially in EEs?
- Standardisation involves having similar market segments across countries, where customers seek
similar features and products have universal features.
- Adaptation involves national preference, where the firm accounts for differences in customer
needs.
3
, - The Big Picture Framework:
- Differentiating types of adaptations:
1. Mandatory Adaptation: necessary for products to be sold in a local market.
2. Discretionary Adaptation: not necessary but may be beneficial.
- Literature so far, in light of Westjohn and Magnusson's (2017) research:
4
Lecture 1: Introduction to the Course and the Real-Life Case
- #DownToEarth
• Both space technologies and earth observation data have a lot of potential for earth
applications that is not yet fully tapped by business start-ups.
• Mission: To inspire and support start-ups to use space technologies to #
applications.
• How to organise start-ups are in the market? Competitions, Hackathons (i.e. come up with new
ideas in 24-hours), Programs, Astropreneurs (i.e. online/offline program), Venture Academy, ESA
business program.
• ESA Business Program: 2 years in the program, incubated in the company, and you can use
space technology and data. You must have a company not older than 5 years.
- Start-Up 1: Smart Farm Sensing
• Smart Farm Sensing is a Netherlands based agri tech consulting company providing services,
solutions and consultancy to the agriculture sector on intelligent sensor data and geospatial
information.
• Vision: fully operational satellite, aerial and ground remote sensing information supply chains
are key to increase the global agriculture productivity and to sustain our (future) food chain.
• Mission: to prove our clients with sensor networks, geo-information systems, spatial databases,
web-portals, and mobile apps.
• One of the products they are creating = AgrloT ground sensor network. They have sensors that
send specific information from the farm. Goal is to create low cost sensors that communicate with
a gateway (i.e. a large WiFi router).
• Market is the date fruits industry (dadels in Dutch).
• Palm tree management: mapping, registration and monitoring for palm trees.
• First Sensor = Insect Trap Management: mobile registration, recording and visualisation of Red
Palm Weevil traps. The trap has a sensor which counts how many weevils are in the traps. On an
hourly basis, Smart Farm Sensing knowns how many weevils are in the traps.
• Second Sensor = Soil Moisture Sensing: mobile visualisation of soil moisture condition with
sufficient soil moisture sensors real-time moisture distribution maps of the fields are provided.
• Figure of the system:
1
, • Plague and Water Pressure Map: monitoring plague and water pressure per date palm field.
• Date Palm Farms are the target market because stye produces 7.5 million metric tons of date
fruits per year (on average). It takes 7 years for date palm to produce fruits.
• Emerging Markets: Morocco, Egypt, UAE.
- Start-Up 2: Opt-Net
• Monitoring and fusing the data that comes from stations. It allows humans to respond quickly
and help the people affected to recover from the aftermath as soon as possible. It is like finding a
needle in a haystack - however, this company does that.
• The satellite collect imagery (SAR, SLSTR, etc.), then the AI Engine Analyses SAR data in real
time.
• Which data do they use? SAR data - specific type that is a radar, which scans the earth surface
for any changes. Large and small changes are detected, catalogued, and analysed. This data
humans can hardly comprehend, so other data is used to confirm that findings that the IA has
found.
• Still learning, because they are still using data trails to show that their data works better than
humans.
• Benefits for now:
- 99% more effective than humans are faster
- Economically feasible: 1/10th of the cost of comparable solutions.
- Accurate and timely detection: 24/7 coverage.
- Real time = <2 sec reaction time.
- Scalable: 1 TB of data per day.
• Commercialisation (not B2B): Government Agencies, Civilian Services, Geo Information System
Providers. Target global customers.
- Start-Up 3: FieldBee
• Global Problem: less than 2% of the world's population is employed in agriculture, while 100%
are consumers of food. Noticeably, world population is growing on average 1.21% YoY, which
entails that farmers need to produce 2 times more food by 2050. Precision agriculture can
improve yield by 70%, but its penetration is only 5%.
• Farmer problem:
- Farmers are overworked. They work more than 12 hours work per day while performing filed
operations.
- Farmers on average experience low profitability. Many risk losing their family business, because
competition is forcing farmers to find ways to increase margins, improve productivity, be more
precise in fieldwork, reduce waste and control costs.
- Inaccuracy or errors in execution often lead to severe consequences such as reduction of even
loss of their harvest.
• Solution:
- Precision farming can reduce up to 70% of costs of food production
- Precision farming can reduce vast and improve yield
- Precision farming can make farmers work easier
• What is it? Technologies enabled by GPS and GNSS systems, that make the practice of farming
2
, more accurate and controlled when it comes to the growing of crops and raising livestock.
Examples: more accurate tractor driving, watering, measuring of costs/yields, spreading of
fertilisers and enabling surveys with drones and identification of exact locations with crop
diseases, and issues, bugs.
• Precision farming already happened in the 80s, but only 5% of the farmers use them today,
because they were complex, didn't pay on invests and very expensive.
• eFarmer is making precision available to every farmer.
• eFarmer is offering affordable easy to use solutions that works on smartphones/tablets.
• Products much much cheaper than competitors, about 10%.
• Cloud technologies used.
• Customers: all farmers with tractors, small and medium farmers worldwide (90% of all
farmholds).
• FieldBee works already in 46 countries.
• Emerging markets interested in: Latin America, Africa, India.
• , +31652688925
Lecture 2: Marketing Strategy and Value Proposition in EE
- An Emerging Market is a country that has some characteristics of a developed market, but does
not satisfy standards to be termed a developed market. This includes countries that may become
developed markets in the future or were in the past. The 10 Big Emerging Markets economies
are: Argentina, Brazil, China, India, Indonesia, Mexico, Poland, South Africa, South Korea and
Turkey. Egypt, Iran, Nigeria, Pakistan, Russia, Saudi Arabia, Taiwan, and Thailand are other major
emerging markets.
- Global challenges:
1. The drive for prosperity and development
2. The desire to retain identity and traditions
“... Half the world - sometimes half the same country, sometimes half the same person - was still
caught up in the fight over who owns which olive tree.” (Friedman 2000, The Lexus and Olive
Tree)
- Westjohn and Magnusson (2017) assess the conditional effects of discretionary marketing
adaptation on export performance. The main idea here is:
• How do we do marketing across borders, while world is becoming “borderless”?
• Should we adapt or standardise marketing programs, especially in EEs?
- Standardisation involves having similar market segments across countries, where customers seek
similar features and products have universal features.
- Adaptation involves national preference, where the firm accounts for differences in customer
needs.
3
, - The Big Picture Framework:
- Differentiating types of adaptations:
1. Mandatory Adaptation: necessary for products to be sold in a local market.
2. Discretionary Adaptation: not necessary but may be beneficial.
- Literature so far, in light of Westjohn and Magnusson's (2017) research:
4
