The 30+ companies utilising big data analytics in the food and drink world

The 30+ companies utilising big data analytics in the food and drink world

By
Louise Burfitt
July 20, 2021

📊 What is it?

  • What connects next year’s hottest plant-based burger, a trip to your local grocery store and a farm on the other side of the world? Well, all are taking advantage of big data to improve the way they work and what they offer to consumers. 
  • The next big thing in plant-based? Created thanks to data-powered predictive analytics. Freshly stocked supermarket shelves? Big data helped the manager monitor the store’s inventory in real time. And the farm down under? Smart sensors control crop fertilisation and watering, saving the farmer time and money. 
  • Big data is simply the collection of massive (think in the billions and up!) amounts of data, which is then selectively analysed to glean insight and predictions into the topic at hand. This process often utilises the power of artificial intelligence (AI) to manage the mountains of data to be processed.

🤔 Tell me more…

  • The Oxford Dictionary recently added the term ‘big data’ to their listings, a sure sign that a trend is here to stay. It described big data as ‘extremely large data sets that may be analyzed computationally to reveal patterns, trends and associations’. 
  • These data sets are the key to big data’s advantages when it comes to the F&B industry: when properly analysed, this trove of information can help to predict consumer desires, pinpoint new food and drink trends, and streamline operations for farmers, grocery stores and restaurants - among many others.

🤷 Why?

  • With the F&B industry more competitive than ever, companies who make the most of big data analytics can achieve a distinct competitive advantage. Done well, predictive analytics can help companies to expand their growth, streamline their strategy and increase their profit margins. 
  • Data-assisted solutions are also providing answers to some of the biggest questions of our age when it comes to the food industry - whether that’s reduced spoilage and food waste, improved freshness or more eco-friendly delivery routes.
  • And the way that big data allows companies to utilise customer insights and behaviour essentially in real time makes it revolutionary for brands who use it right - allowing them to stay one step ahead of trends and create products tailored to consumer desires.

🔍 How is it shaping up?

  • Big data is helping restaurants and grocery stores to streamline their operations, tracking inventory, monitoring the quality and safety of foods using sensors and keeping track of customer preferences. QSR brands have also been quick to jump on the big data train, analysing consumer behaviour, optimising menus and creating enhanced loyalty programmes thanks to huge data sets. 
  • Smarter use of data analytics and high-tech solutions is helping to improve delivery experiences for consumers - and reducing the cost of these services for retailers. Routific, for example, is a delivery optimization software that utilises data to improve tracking and optimise routes for grocery delivery. Deliveroo also exploits data insights to make their delivery service more efficient. 
  • Predictive analytics is also a hot new trend that is only likely to grow in the coming years: usually powered by AI algorithms, this type of data analytics allows companies to predict possible results and potential problems, meaning brands can identify and amend their desired strategies in advance. That’s obviously a boon in several F&B sectors - who doesn’t want to predict the future? Several startups are using this advanced analytics to develop on-trend new food products - including Singapore’s Ai Palette, Israel’s Tastewise, and Spoonshot and Climax Foods in the US. The latter are using data in combination with machine intelligence tools to discover new plant-based foods that can compete with conventional meat and dairy.
  • Farmers are also making the most of advances in big data and data analysis technology - whether to manage and monitor crops and cattle, quickly identify pests and diseases, increase yields, or predict the exact amount of fertiliser needed. Companies working in the precision agriculture sector include Ag-Analytics in the USA, AgFlow and Gamaya in Switzerland, and Semios in Canada. 
  • Big data isn’t just about maximising profit for businesses, either: many companies are using data to enhance the greater good. Shelf Engine in the USA helps grocery stores reduce waste (and saves them money in the process) while Seebo offers a data-powered food waste reduction service in Israel. TeakOrigin in the US are meanwhile using data to help health-conscious consumers make informed food choices.
View our database of 40+ AI & Big Data companies

👀 Who? (30+ companies in this space)

  • Aeris (data-connected cold chain monitoring, USA)
  • Ag-Analytics (precision data for farming, USA) 
  • AgFlow (data and market insight for agricultural commodities buyers, Switzerland) 
  • Agrio (AI-powered data analytics for pest and disease protection in farming, Israel)
  • AgShift (food quality inspection using the best of IoT, computer vision and machine learning, USA)
  • Ai Palette  (AI-assisted food product creation, Singapore)
  • Aromyx Corporation (data-assisted digital aroma technology, USA)
  • Climax Foods (machine intelligence tools to create new plant-based foods, USA) 
  • CropX (cloud-based software solutions with wireless sensors for farming, Israel)
  • Eden Technologies by Walmart (using data analytics to streamline grocery operations, USA) 
  • FlavorWiki (consumer insights and data management solution, Switzerland)
  • FoodUnite (AI-assisted food innovation, Switzerland)
  • FreshDirect (data-assisted online fresh grocery platform with delivery, USA)
  • Gamaya (precision agriculture solutions for large-scale monitoring of crops, Switzerland)
  • Gastrograph AI (design flavour profiles with the world's largest AI sensory data set, USA)
  • GrainSense (data-powered hand-held device for grain protein measurement, Finland)
  • IBM Food Trust (blockchain to support the food industry, USA)
  • Journey Foods (AI-powered ingredient + nutrient analytics, USA)
  • McDonald’s Dynamic Yield (data-powered consumer predictions, USA) 
  • Plant Jammer (AI flavour pairing, Denmark)
  • Protix (data-assisted insect protein production, Netherlands) 
  • Routific (third-party delivery optimization software that brands can use to improve tracking and optimise routes, Canada) 
  • Seebo (AI-assisted and data-powered food waste reduction, Israel)
  • Semios (precision agriculture-as-a-service, Canada)
  • Shelf Engine (using data to reduce grocery wastage, USA) 
  • Spoonshot (AI-assisted consumer food predictions, USA)
  • Swiggy (data-enabled & AI-assisted food delivery, India)
  • Tastewise (AI-assisted food product innovation, Israel)
  • TeakOrigin (data-powered service to help consumers make informed food choices, USA) 
  • Telit (data-powered IoT solutions for the food & beverage industry, UK)
  • The Live Green Co (data-driven creation of new food products, Chile)

📈 The figures

  • Worldwide, the food and drink industry is worth $81 trillion - so it goes without saying that there’s a wealth of data just waiting to be utilised by brands. 
  • The sector that encompasses global agriculture analytics is forecast to reach $1.4bn by 2025.
  • And the market for big data itself in the food industry is forecast to reach $2.1bn by 2026.
The two Tastewise Co-Founders

👅 Case study: Tastewise

  • Tel Aviv startup Tastewise is using data to predict the future, at least where consumer food preferences are concerned. The company’s trademark platform uses data and AI to find out why consumers opt for certain foods and the trends driving these choices. 
  • By analysing literal billions of consumer data points - including social media shares, digital menus and online food content - the company can forecast future food fashions, enabling restaurants and CPG makers to identify gaps in the market and speed up product innovation.
  • In September 2020, the startup released a data-powered report on the business opportunities in functional foods, to help the F&B industry prioritise new product launches and hone their marketing based on in-depth analysis of consumer desires. Particular niches identified by the company included immunity-boosting products and fermented foods.
  • The Israeli company can boast total funding to the tune of $7.6m and raised $3m in its latest funding round last autumn. 
  • Last year Tastewise also launched their data-enabled food prediction platform in the UK, merging data from 183k restaurants and menus and 2.8bn social media posts into their offering. 
  • Future plans to expand the platform to other countries are full speed ahead in 2021.

🍟 Case study: McDonald’s Dynamic Yield 

  • From a startup to a mega-conglomerate: household-name QSR McDonald’s bought Israeli startup Dynamic Yield in 2019, for a reported fee of $300 million.
  • The software uses customer data analytics to amend a digital drive-thru or kiosk menu according to the time of day, menu item popularity or the weather. And it is already being used in 12,000 locations in North America. 
  • As a truly sprawling food multinational, McDonald’s has a distinct advantage when it comes to data. Serving 70 million customers in 118 countries every single day, this means that the purveyors of the Golden Arches have an extraordinary huge data set to work with. 
  • And they’re putting it to beneficial use: as well as enhancing the drive-thru experience with Dynamic Yield tech, the fast food giant is using the technology to increase customer loyalty by offering tailored offers through their app and analyse patterns to dream up new burgers and fries.
  • It’s not all been plain sailing though: just last month, privacy concerns surrounding the use of big data came back to bite Maccy D’s. The company is being sued for allegedly collecting customers’ biometric data without consent at their AI-powered drive-thrus.
  • Court case notwithstanding, in the not-too-distant future, the underlying algorithm will be able to personalise menus in ever greater detail, basing recommendations for individual customers on their past purchases. Ordering kiosks may also be replaced by AI-enabled voice command self-service stations.

👍 The good

  • Access to data can help actors in the F&B industry to simplify the decision-making process, and quickly deal with any problems that arise. In many areas, it can help companies to streamline, optimise and enhance their services. 
  • In the long run, using big data analytics can save businesses money, allowing them to invest in areas where data shows it is most wise to, and run a more efficient profit model. 
  • For customers, the big benefit of big data usage is a more customised service, fully personalised to their needs and desires - as we’ve seen from the example of McDonald’s. 
  • Predictive analytics is also a massive opportunity for F&B companies to accelerate product innovation, make predictions about consumer behaviour and predict future trends.

👎 The bad

  • When it comes to big data, privacy remains a key concern. As with any new tech, legal regulations have to catch up, leaving some nervous about anonymity and consent. Companies need to communicate transparently about how customer data will be used and demonstrate how the advantages outweigh the security risks.
  • Big data is also pretty much worthless unless your brand has the tools and skills needed to effectively interpret the data and what it represents for your business. 
  • As with any digital innovations, there’s always the risk of technological glitches and hacks - a particularly big issue where confidential data is concerned - so companies need to treat information with care and make sure the relevant safety nets are in place.

 💡The bottom line

  • Big data represents a huge opening for businesses across all fields of the F&B industry - presenting new ways for brands to align with customer behaviour and hone their offering. 
  • But big data also throws up new challenges, from privacy to using the right analysis tools. With confidential data comes important responsibility, and those who make the most of this golden opportunity will bear all that and more in mind.

How did you like today's Trends?

Love it 😁 Meh 😐 Hate it 🙁

FoodHack Database

Become a member

to get unlimited access

  • Weekly Trend Reports | Access 60+ Reports
  • Startups & Investors Database | Browse 500+
  • FoodHack+ Insiders Community | Coming soon

📊 What is it?

  • What connects next year’s hottest plant-based burger, a trip to your local grocery store and a farm on the other side of the world? Well, all are taking advantage of big data to improve the way they work and what they offer to consumers. 
  • The next big thing in plant-based? Created thanks to data-powered predictive analytics. Freshly stocked supermarket shelves? Big data helped the manager monitor the store’s inventory in real time. And the farm down under? Smart sensors control crop fertilisation and watering, saving the farmer time and money. 
  • Big data is simply the collection of massive (think in the billions and up!) amounts of data, which is then selectively analysed to glean insight and predictions into the topic at hand. This process often utilises the power of artificial intelligence (AI) to manage the mountains of data to be processed.

🤔 Tell me more…

  • The Oxford Dictionary recently added the term ‘big data’ to their listings, a sure sign that a trend is here to stay. It described big data as ‘extremely large data sets that may be analyzed computationally to reveal patterns, trends and associations’. 
  • These data sets are the key to big data’s advantages when it comes to the F&B industry: when properly analysed, this trove of information can help to predict consumer desires, pinpoint new food and drink trends, and streamline operations for farmers, grocery stores and restaurants - among many others.

🤷 Why?

  • With the F&B industry more competitive than ever, companies who make the most of big data analytics can achieve a distinct competitive advantage. Done well, predictive analytics can help companies to expand their growth, streamline their strategy and increase their profit margins. 
  • Data-assisted solutions are also providing answers to some of the biggest questions of our age when it comes to the food industry - whether that’s reduced spoilage and food waste, improved freshness or more eco-friendly delivery routes.
  • And the way that big data allows companies to utilise customer insights and behaviour essentially in real time makes it revolutionary for brands who use it right - allowing them to stay one step ahead of trends and create products tailored to consumer desires.

🔍 How is it shaping up?

  • Big data is helping restaurants and grocery stores to streamline their operations, tracking inventory, monitoring the quality and safety of foods using sensors and keeping track of customer preferences. QSR brands have also been quick to jump on the big data train, analysing consumer behaviour, optimising menus and creating enhanced loyalty programmes thanks to huge data sets. 
  • Smarter use of data analytics and high-tech solutions is helping to improve delivery experiences for consumers - and reducing the cost of these services for retailers. Routific, for example, is a delivery optimization software that utilises data to improve tracking and optimise routes for grocery delivery. Deliveroo also exploits data insights to make their delivery service more efficient. 
  • Predictive analytics is also a hot new trend that is only likely to grow in the coming years: usually powered by AI algorithms, this type of data analytics allows companies to predict possible results and potential problems, meaning brands can identify and amend their desired strategies in advance. That’s obviously a boon in several F&B sectors - who doesn’t want to predict the future? Several startups are using this advanced analytics to develop on-trend new food products - including Singapore’s Ai Palette, Israel’s Tastewise, and Spoonshot and Climax Foods in the US. The latter are using data in combination with machine intelligence tools to discover new plant-based foods that can compete with conventional meat and dairy.
  • Farmers are also making the most of advances in big data and data analysis technology - whether to manage and monitor crops and cattle, quickly identify pests and diseases, increase yields, or predict the exact amount of fertiliser needed. Companies working in the precision agriculture sector include Ag-Analytics in the USA, AgFlow and Gamaya in Switzerland, and Semios in Canada. 
  • Big data isn’t just about maximising profit for businesses, either: many companies are using data to enhance the greater good. Shelf Engine in the USA helps grocery stores reduce waste (and saves them money in the process) while Seebo offers a data-powered food waste reduction service in Israel. TeakOrigin in the US are meanwhile using data to help health-conscious consumers make informed food choices.
View our database of 40+ AI & Big Data companies

👀 Who? (30+ companies in this space)

  • Aeris (data-connected cold chain monitoring, USA)
  • Ag-Analytics (precision data for farming, USA) 
  • AgFlow (data and market insight for agricultural commodities buyers, Switzerland) 
  • Agrio (AI-powered data analytics for pest and disease protection in farming, Israel)
  • AgShift (food quality inspection using the best of IoT, computer vision and machine learning, USA)
  • Ai Palette  (AI-assisted food product creation, Singapore)
  • Aromyx Corporation (data-assisted digital aroma technology, USA)
  • Climax Foods (machine intelligence tools to create new plant-based foods, USA) 
  • CropX (cloud-based software solutions with wireless sensors for farming, Israel)
  • Eden Technologies by Walmart (using data analytics to streamline grocery operations, USA) 
  • FlavorWiki (consumer insights and data management solution, Switzerland)
  • FoodUnite (AI-assisted food innovation, Switzerland)
  • FreshDirect (data-assisted online fresh grocery platform with delivery, USA)
  • Gamaya (precision agriculture solutions for large-scale monitoring of crops, Switzerland)
  • Gastrograph AI (design flavour profiles with the world's largest AI sensory data set, USA)
  • GrainSense (data-powered hand-held device for grain protein measurement, Finland)
  • IBM Food Trust (blockchain to support the food industry, USA)
  • Journey Foods (AI-powered ingredient + nutrient analytics, USA)
  • McDonald’s Dynamic Yield (data-powered consumer predictions, USA) 
  • Plant Jammer (AI flavour pairing, Denmark)
  • Protix (data-assisted insect protein production, Netherlands) 
  • Routific (third-party delivery optimization software that brands can use to improve tracking and optimise routes, Canada) 
  • Seebo (AI-assisted and data-powered food waste reduction, Israel)
  • Semios (precision agriculture-as-a-service, Canada)
  • Shelf Engine (using data to reduce grocery wastage, USA) 
  • Spoonshot (AI-assisted consumer food predictions, USA)
  • Swiggy (data-enabled & AI-assisted food delivery, India)
  • Tastewise (AI-assisted food product innovation, Israel)
  • TeakOrigin (data-powered service to help consumers make informed food choices, USA) 
  • Telit (data-powered IoT solutions for the food & beverage industry, UK)
  • The Live Green Co (data-driven creation of new food products, Chile)

📈 The figures

  • Worldwide, the food and drink industry is worth $81 trillion - so it goes without saying that there’s a wealth of data just waiting to be utilised by brands. 
  • The sector that encompasses global agriculture analytics is forecast to reach $1.4bn by 2025.
  • And the market for big data itself in the food industry is forecast to reach $2.1bn by 2026.
The two Tastewise Co-Founders

👅 Case study: Tastewise

  • Tel Aviv startup Tastewise is using data to predict the future, at least where consumer food preferences are concerned. The company’s trademark platform uses data and AI to find out why consumers opt for certain foods and the trends driving these choices. 
  • By analysing literal billions of consumer data points - including social media shares, digital menus and online food content - the company can forecast future food fashions, enabling restaurants and CPG makers to identify gaps in the market and speed up product innovation.
  • In September 2020, the startup released a data-powered report on the business opportunities in functional foods, to help the F&B industry prioritise new product launches and hone their marketing based on in-depth analysis of consumer desires. Particular niches identified by the company included immunity-boosting products and fermented foods.
  • The Israeli company can boast total funding to the tune of $7.6m and raised $3m in its latest funding round last autumn. 
  • Last year Tastewise also launched their data-enabled food prediction platform in the UK, merging data from 183k restaurants and menus and 2.8bn social media posts into their offering. 
  • Future plans to expand the platform to other countries are full speed ahead in 2021.

🍟 Case study: McDonald’s Dynamic Yield 

  • From a startup to a mega-conglomerate: household-name QSR McDonald’s bought Israeli startup Dynamic Yield in 2019, for a reported fee of $300 million.
  • The software uses customer data analytics to amend a digital drive-thru or kiosk menu according to the time of day, menu item popularity or the weather. And it is already being used in 12,000 locations in North America. 
  • As a truly sprawling food multinational, McDonald’s has a distinct advantage when it comes to data. Serving 70 million customers in 118 countries every single day, this means that the purveyors of the Golden Arches have an extraordinary huge data set to work with. 
  • And they’re putting it to beneficial use: as well as enhancing the drive-thru experience with Dynamic Yield tech, the fast food giant is using the technology to increase customer loyalty by offering tailored offers through their app and analyse patterns to dream up new burgers and fries.
  • It’s not all been plain sailing though: just last month, privacy concerns surrounding the use of big data came back to bite Maccy D’s. The company is being sued for allegedly collecting customers’ biometric data without consent at their AI-powered drive-thrus.
  • Court case notwithstanding, in the not-too-distant future, the underlying algorithm will be able to personalise menus in ever greater detail, basing recommendations for individual customers on their past purchases. Ordering kiosks may also be replaced by AI-enabled voice command self-service stations.

👍 The good

  • Access to data can help actors in the F&B industry to simplify the decision-making process, and quickly deal with any problems that arise. In many areas, it can help companies to streamline, optimise and enhance their services. 
  • In the long run, using big data analytics can save businesses money, allowing them to invest in areas where data shows it is most wise to, and run a more efficient profit model. 
  • For customers, the big benefit of big data usage is a more customised service, fully personalised to their needs and desires - as we’ve seen from the example of McDonald’s. 
  • Predictive analytics is also a massive opportunity for F&B companies to accelerate product innovation, make predictions about consumer behaviour and predict future trends.

👎 The bad

  • When it comes to big data, privacy remains a key concern. As with any new tech, legal regulations have to catch up, leaving some nervous about anonymity and consent. Companies need to communicate transparently about how customer data will be used and demonstrate how the advantages outweigh the security risks.
  • Big data is also pretty much worthless unless your brand has the tools and skills needed to effectively interpret the data and what it represents for your business. 
  • As with any digital innovations, there’s always the risk of technological glitches and hacks - a particularly big issue where confidential data is concerned - so companies need to treat information with care and make sure the relevant safety nets are in place.

 💡The bottom line

  • Big data represents a huge opening for businesses across all fields of the F&B industry - presenting new ways for brands to align with customer behaviour and hone their offering. 
  • But big data also throws up new challenges, from privacy to using the right analysis tools. With confidential data comes important responsibility, and those who make the most of this golden opportunity will bear all that and more in mind.

How did you like today's Trends?

Love it 😁 Meh 😐 Hate it 🙁

📊 What is it?

  • What connects next year’s hottest plant-based burger, a trip to your local grocery store and a farm on the other side of the world? Well, all are taking advantage of big data to improve the way they work and what they offer to consumers. 
  • The next big thing in plant-based? Created thanks to data-powered predictive analytics. Freshly stocked supermarket shelves? Big data helped the manager monitor the store’s inventory in real time. And the farm down under? Smart sensors control crop fertilisation and watering, saving the farmer time and money. 
  • Big data is simply the collection of massive (think in the billions and up!) amounts of data, which is then selectively analysed to glean insight and predictions into the topic at hand. This process often utilises the power of artificial intelligence (AI) to manage the mountains of data to be processed.

🤔 Tell me more…

  • The Oxford Dictionary recently added the term ‘big data’ to their listings, a sure sign that a trend is here to stay. It described big data as ‘extremely large data sets that may be analyzed computationally to reveal patterns, trends and associations’. 
  • These data sets are the key to big data’s advantages when it comes to the F&B industry: when properly analysed, this trove of information can help to predict consumer desires, pinpoint new food and drink trends, and streamline operations for farmers, grocery stores and restaurants - among many others.

🤷 Why?

  • With the F&B industry more competitive than ever, companies who make the most of big data analytics can achieve a distinct competitive advantage. Done well, predictive analytics can help companies to expand their growth, streamline their strategy and increase their profit margins. 
  • Data-assisted solutions are also providing answers to some of the biggest questions of our age when it comes to the food industry - whether that’s reduced spoilage and food waste, improved freshness or more eco-friendly delivery routes.
  • And the way that big data allows companies to utilise customer insights and behaviour essentially in real time makes it revolutionary for brands who use it right - allowing them to stay one step ahead of trends and create products tailored to consumer desires.

🔍 How is it shaping up?

  • Big data is helping restaurants and grocery stores to streamline their operations, tracking inventory, monitoring the quality and safety of foods using sensors and keeping track of customer preferences. QSR brands have also been quick to jump on the big data train, analysing consumer behaviour, optimising menus and creating enhanced loyalty programmes thanks to huge data sets. 
  • Smarter use of data analytics and high-tech solutions is helping to improve delivery experiences for consumers - and reducing the cost of these services for retailers. Routific, for example, is a delivery optimization software that utilises data to improve tracking and optimise routes for grocery delivery. Deliveroo also exploits data insights to make their delivery service more efficient. 
  • Predictive analytics is also a hot new trend that is only likely to grow in the coming years: usually powered by AI algorithms, this type of data analytics allows companies to predict possible results and potential problems, meaning brands can identify and amend their desired strategies in advance. That’s obviously a boon in several F&B sectors - who doesn’t want to predict the future? Several startups are using this advanced analytics to develop on-trend new food products - including Singapore’s Ai Palette, Israel’s Tastewise, and Spoonshot and Climax Foods in the US. The latter are using data in combination with machine intelligence tools to discover new plant-based foods that can compete with conventional meat and dairy.
  • Farmers are also making the most of advances in big data and data analysis technology - whether to manage and monitor crops and cattle, quickly identify pests and diseases, increase yields, or predict the exact amount of fertiliser needed. Companies working in the precision agriculture sector include Ag-Analytics in the USA, AgFlow and Gamaya in Switzerland, and Semios in Canada. 
  • Big data isn’t just about maximising profit for businesses, either: many companies are using data to enhance the greater good. Shelf Engine in the USA helps grocery stores reduce waste (and saves them money in the process) while Seebo offers a data-powered food waste reduction service in Israel. TeakOrigin in the US are meanwhile using data to help health-conscious consumers make informed food choices.
View our database of 40+ AI & Big Data companies

👀 Who? (30+ companies in this space)

  • Aeris (data-connected cold chain monitoring, USA)
  • Ag-Analytics (precision data for farming, USA) 
  • AgFlow (data and market insight for agricultural commodities buyers, Switzerland) 
  • Agrio (AI-powered data analytics for pest and disease protection in farming, Israel)
  • AgShift (food quality inspection using the best of IoT, computer vision and machine learning, USA)
  • Ai Palette  (AI-assisted food product creation, Singapore)
  • Aromyx Corporation (data-assisted digital aroma technology, USA)
  • Climax Foods (machine intelligence tools to create new plant-based foods, USA) 
  • CropX (cloud-based software solutions with wireless sensors for farming, Israel)
  • Eden Technologies by Walmart (using data analytics to streamline grocery operations, USA) 
  • FlavorWiki (consumer insights and data management solution, Switzerland)
  • FoodUnite (AI-assisted food innovation, Switzerland)
  • FreshDirect (data-assisted online fresh grocery platform with delivery, USA)
  • Gamaya (precision agriculture solutions for large-scale monitoring of crops, Switzerland)
  • Gastrograph AI (design flavour profiles with the world's largest AI sensory data set, USA)
  • GrainSense (data-powered hand-held device for grain protein measurement, Finland)
  • IBM Food Trust (blockchain to support the food industry, USA)
  • Journey Foods (AI-powered ingredient + nutrient analytics, USA)
  • McDonald’s Dynamic Yield (data-powered consumer predictions, USA) 
  • Plant Jammer (AI flavour pairing, Denmark)
  • Protix (data-assisted insect protein production, Netherlands) 
  • Routific (third-party delivery optimization software that brands can use to improve tracking and optimise routes, Canada) 
  • Seebo (AI-assisted and data-powered food waste reduction, Israel)
  • Semios (precision agriculture-as-a-service, Canada)
  • Shelf Engine (using data to reduce grocery wastage, USA) 
  • Spoonshot (AI-assisted consumer food predictions, USA)
  • Swiggy (data-enabled & AI-assisted food delivery, India)
  • Tastewise (AI-assisted food product innovation, Israel)
  • TeakOrigin (data-powered service to help consumers make informed food choices, USA) 
  • Telit (data-powered IoT solutions for the food & beverage industry, UK)
  • The Live Green Co (data-driven creation of new food products, Chile)

📈 The figures

  • Worldwide, the food and drink industry is worth $81 trillion - so it goes without saying that there’s a wealth of data just waiting to be utilised by brands. 
  • The sector that encompasses global agriculture analytics is forecast to reach $1.4bn by 2025.
  • And the market for big data itself in the food industry is forecast to reach $2.1bn by 2026.
The two Tastewise Co-Founders

👅 Case study: Tastewise

  • Tel Aviv startup Tastewise is using data to predict the future, at least where consumer food preferences are concerned. The company’s trademark platform uses data and AI to find out why consumers opt for certain foods and the trends driving these choices. 
  • By analysing literal billions of consumer data points - including social media shares, digital menus and online food content - the company can forecast future food fashions, enabling restaurants and CPG makers to identify gaps in the market and speed up product innovation.
  • In September 2020, the startup released a data-powered report on the business opportunities in functional foods, to help the F&B industry prioritise new product launches and hone their marketing based on in-depth analysis of consumer desires. Particular niches identified by the company included immunity-boosting products and fermented foods.
  • The Israeli company can boast total funding to the tune of $7.6m and raised $3m in its latest funding round last autumn. 
  • Last year Tastewise also launched their data-enabled food prediction platform in the UK, merging data from 183k restaurants and menus and 2.8bn social media posts into their offering. 
  • Future plans to expand the platform to other countries are full speed ahead in 2021.

🍟 Case study: McDonald’s Dynamic Yield 

  • From a startup to a mega-conglomerate: household-name QSR McDonald’s bought Israeli startup Dynamic Yield in 2019, for a reported fee of $300 million.
  • The software uses customer data analytics to amend a digital drive-thru or kiosk menu according to the time of day, menu item popularity or the weather. And it is already being used in 12,000 locations in North America. 
  • As a truly sprawling food multinational, McDonald’s has a distinct advantage when it comes to data. Serving 70 million customers in 118 countries every single day, this means that the purveyors of the Golden Arches have an extraordinary huge data set to work with. 
  • And they’re putting it to beneficial use: as well as enhancing the drive-thru experience with Dynamic Yield tech, the fast food giant is using the technology to increase customer loyalty by offering tailored offers through their app and analyse patterns to dream up new burgers and fries.
  • It’s not all been plain sailing though: just last month, privacy concerns surrounding the use of big data came back to bite Maccy D’s. The company is being sued for allegedly collecting customers’ biometric data without consent at their AI-powered drive-thrus.
  • Court case notwithstanding, in the not-too-distant future, the underlying algorithm will be able to personalise menus in ever greater detail, basing recommendations for individual customers on their past purchases. Ordering kiosks may also be replaced by AI-enabled voice command self-service stations.

👍 The good

  • Access to data can help actors in the F&B industry to simplify the decision-making process, and quickly deal with any problems that arise. In many areas, it can help companies to streamline, optimise and enhance their services. 
  • In the long run, using big data analytics can save businesses money, allowing them to invest in areas where data shows it is most wise to, and run a more efficient profit model. 
  • For customers, the big benefit of big data usage is a more customised service, fully personalised to their needs and desires - as we’ve seen from the example of McDonald’s. 
  • Predictive analytics is also a massive opportunity for F&B companies to accelerate product innovation, make predictions about consumer behaviour and predict future trends.

👎 The bad

  • When it comes to big data, privacy remains a key concern. As with any new tech, legal regulations have to catch up, leaving some nervous about anonymity and consent. Companies need to communicate transparently about how customer data will be used and demonstrate how the advantages outweigh the security risks.
  • Big data is also pretty much worthless unless your brand has the tools and skills needed to effectively interpret the data and what it represents for your business. 
  • As with any digital innovations, there’s always the risk of technological glitches and hacks - a particularly big issue where confidential data is concerned - so companies need to treat information with care and make sure the relevant safety nets are in place.

 💡The bottom line

  • Big data represents a huge opening for businesses across all fields of the F&B industry - presenting new ways for brands to align with customer behaviour and hone their offering. 
  • But big data also throws up new challenges, from privacy to using the right analysis tools. With confidential data comes important responsibility, and those who make the most of this golden opportunity will bear all that and more in mind.

How did you like today's Trends?

Love it 😁 Meh 😐 Hate it 🙁

📊 What is it?

  • What connects next year’s hottest plant-based burger, a trip to your local grocery store and a farm on the other side of the world? Well, all are taking advantage of big data to improve the way they work and what they offer to consumers. 
  • The next big thing in plant-based? Created thanks to data-powered predictive analytics. Freshly stocked supermarket shelves? Big data helped the manager monitor the store’s inventory in real time. And the farm down under? Smart sensors control crop fertilisation and watering, saving the farmer time and money. 
  • Big data is simply the collection of massive (think in the billions and up!) amounts of data, which is then selectively analysed to glean insight and predictions into the topic at hand. This process often utilises the power of artificial intelligence (AI) to manage the mountains of data to be processed.

🤔 Tell me more…

  • The Oxford Dictionary recently added the term ‘big data’ to their listings, a sure sign that a trend is here to stay. It described big data as ‘extremely large data sets that may be analyzed computationally to reveal patterns, trends and associations’. 
  • These data sets are the key to big data’s advantages when it comes to the F&B industry: when properly analysed, this trove of information can help to predict consumer desires, pinpoint new food and drink trends, and streamline operations for farmers, grocery stores and restaurants - among many others.

🤷 Why?

  • With the F&B industry more competitive than ever, companies who make the most of big data analytics can achieve a distinct competitive advantage. Done well, predictive analytics can help companies to expand their growth, streamline their strategy and increase their profit margins. 
  • Data-assisted solutions are also providing answers to some of the biggest questions of our age when it comes to the food industry - whether that’s reduced spoilage and food waste, improved freshness or more eco-friendly delivery routes.
  • And the way that big data allows companies to utilise customer insights and behaviour essentially in real time makes it revolutionary for brands who use it right - allowing them to stay one step ahead of trends and create products tailored to consumer desires.

🔍 How is it shaping up?

  • Big data is helping restaurants and grocery stores to streamline their operations, tracking inventory, monitoring the quality and safety of foods using sensors and keeping track of customer preferences. QSR brands have also been quick to jump on the big data train, analysing consumer behaviour, optimising menus and creating enhanced loyalty programmes thanks to huge data sets. 
  • Smarter use of data analytics and high-tech solutions is helping to improve delivery experiences for consumers - and reducing the cost of these services for retailers. Routific, for example, is a delivery optimization software that utilises data to improve tracking and optimise routes for grocery delivery. Deliveroo also exploits data insights to make their delivery service more efficient. 
  • Predictive analytics is also a hot new trend that is only likely to grow in the coming years: usually powered by AI algorithms, this type of data analytics allows companies to predict possible results and potential problems, meaning brands can identify and amend their desired strategies in advance. That’s obviously a boon in several F&B sectors - who doesn’t want to predict the future? Several startups are using this advanced analytics to develop on-trend new food products - including Singapore’s Ai Palette, Israel’s Tastewise, and Spoonshot and Climax Foods in the US. The latter are using data in combination with machine intelligence tools to discover new plant-based foods that can compete with conventional meat and dairy.
  • Farmers are also making the most of advances in big data and data analysis technology - whether to manage and monitor crops and cattle, quickly identify pests and diseases, increase yields, or predict the exact amount of fertiliser needed. Companies working in the precision agriculture sector include Ag-Analytics in the USA, AgFlow and Gamaya in Switzerland, and Semios in Canada. 
  • Big data isn’t just about maximising profit for businesses, either: many companies are using data to enhance the greater good. Shelf Engine in the USA helps grocery stores reduce waste (and saves them money in the process) while Seebo offers a data-powered food waste reduction service in Israel. TeakOrigin in the US are meanwhile using data to help health-conscious consumers make informed food choices.
View our database of 40+ AI & Big Data companies

👀 Who? (30+ companies in this space)

  • Aeris (data-connected cold chain monitoring, USA)
  • Ag-Analytics (precision data for farming, USA) 
  • AgFlow (data and market insight for agricultural commodities buyers, Switzerland) 
  • Agrio (AI-powered data analytics for pest and disease protection in farming, Israel)
  • AgShift (food quality inspection using the best of IoT, computer vision and machine learning, USA)
  • Ai Palette  (AI-assisted food product creation, Singapore)
  • Aromyx Corporation (data-assisted digital aroma technology, USA)
  • Climax Foods (machine intelligence tools to create new plant-based foods, USA) 
  • CropX (cloud-based software solutions with wireless sensors for farming, Israel)
  • Eden Technologies by Walmart (using data analytics to streamline grocery operations, USA) 
  • FlavorWiki (consumer insights and data management solution, Switzerland)
  • FoodUnite (AI-assisted food innovation, Switzerland)
  • FreshDirect (data-assisted online fresh grocery platform with delivery, USA)
  • Gamaya (precision agriculture solutions for large-scale monitoring of crops, Switzerland)
  • Gastrograph AI (design flavour profiles with the world's largest AI sensory data set, USA)
  • GrainSense (data-powered hand-held device for grain protein measurement, Finland)
  • IBM Food Trust (blockchain to support the food industry, USA)
  • Journey Foods (AI-powered ingredient + nutrient analytics, USA)
  • McDonald’s Dynamic Yield (data-powered consumer predictions, USA) 
  • Plant Jammer (AI flavour pairing, Denmark)
  • Protix (data-assisted insect protein production, Netherlands) 
  • Routific (third-party delivery optimization software that brands can use to improve tracking and optimise routes, Canada) 
  • Seebo (AI-assisted and data-powered food waste reduction, Israel)
  • Semios (precision agriculture-as-a-service, Canada)
  • Shelf Engine (using data to reduce grocery wastage, USA) 
  • Spoonshot (AI-assisted consumer food predictions, USA)
  • Swiggy (data-enabled & AI-assisted food delivery, India)
  • Tastewise (AI-assisted food product innovation, Israel)
  • TeakOrigin (data-powered service to help consumers make informed food choices, USA) 
  • Telit (data-powered IoT solutions for the food & beverage industry, UK)
  • The Live Green Co (data-driven creation of new food products, Chile)

📈 The figures

  • Worldwide, the food and drink industry is worth $81 trillion - so it goes without saying that there’s a wealth of data just waiting to be utilised by brands. 
  • The sector that encompasses global agriculture analytics is forecast to reach $1.4bn by 2025.
  • And the market for big data itself in the food industry is forecast to reach $2.1bn by 2026.
The two Tastewise Co-Founders

👅 Case study: Tastewise

  • Tel Aviv startup Tastewise is using data to predict the future, at least where consumer food preferences are concerned. The company’s trademark platform uses data and AI to find out why consumers opt for certain foods and the trends driving these choices. 
  • By analysing literal billions of consumer data points - including social media shares, digital menus and online food content - the company can forecast future food fashions, enabling restaurants and CPG makers to identify gaps in the market and speed up product innovation.
  • In September 2020, the startup released a data-powered report on the business opportunities in functional foods, to help the F&B industry prioritise new product launches and hone their marketing based on in-depth analysis of consumer desires. Particular niches identified by the company included immunity-boosting products and fermented foods.
  • The Israeli company can boast total funding to the tune of $7.6m and raised $3m in its latest funding round last autumn. 
  • Last year Tastewise also launched their data-enabled food prediction platform in the UK, merging data from 183k restaurants and menus and 2.8bn social media posts into their offering. 
  • Future plans to expand the platform to other countries are full speed ahead in 2021.

🍟 Case study: McDonald’s Dynamic Yield 

  • From a startup to a mega-conglomerate: household-name QSR McDonald’s bought Israeli startup Dynamic Yield in 2019, for a reported fee of $300 million.
  • The software uses customer data analytics to amend a digital drive-thru or kiosk menu according to the time of day, menu item popularity or the weather. And it is already being used in 12,000 locations in North America. 
  • As a truly sprawling food multinational, McDonald’s has a distinct advantage when it comes to data. Serving 70 million customers in 118 countries every single day, this means that the purveyors of the Golden Arches have an extraordinary huge data set to work with. 
  • And they’re putting it to beneficial use: as well as enhancing the drive-thru experience with Dynamic Yield tech, the fast food giant is using the technology to increase customer loyalty by offering tailored offers through their app and analyse patterns to dream up new burgers and fries.
  • It’s not all been plain sailing though: just last month, privacy concerns surrounding the use of big data came back to bite Maccy D’s. The company is being sued for allegedly collecting customers’ biometric data without consent at their AI-powered drive-thrus.
  • Court case notwithstanding, in the not-too-distant future, the underlying algorithm will be able to personalise menus in ever greater detail, basing recommendations for individual customers on their past purchases. Ordering kiosks may also be replaced by AI-enabled voice command self-service stations.

👍 The good

  • Access to data can help actors in the F&B industry to simplify the decision-making process, and quickly deal with any problems that arise. In many areas, it can help companies to streamline, optimise and enhance their services. 
  • In the long run, using big data analytics can save businesses money, allowing them to invest in areas where data shows it is most wise to, and run a more efficient profit model. 
  • For customers, the big benefit of big data usage is a more customised service, fully personalised to their needs and desires - as we’ve seen from the example of McDonald’s. 
  • Predictive analytics is also a massive opportunity for F&B companies to accelerate product innovation, make predictions about consumer behaviour and predict future trends.

👎 The bad

  • When it comes to big data, privacy remains a key concern. As with any new tech, legal regulations have to catch up, leaving some nervous about anonymity and consent. Companies need to communicate transparently about how customer data will be used and demonstrate how the advantages outweigh the security risks.
  • Big data is also pretty much worthless unless your brand has the tools and skills needed to effectively interpret the data and what it represents for your business. 
  • As with any digital innovations, there’s always the risk of technological glitches and hacks - a particularly big issue where confidential data is concerned - so companies need to treat information with care and make sure the relevant safety nets are in place.

 💡The bottom line

  • Big data represents a huge opening for businesses across all fields of the F&B industry - presenting new ways for brands to align with customer behaviour and hone their offering. 
  • But big data also throws up new challenges, from privacy to using the right analysis tools. With confidential data comes important responsibility, and those who make the most of this golden opportunity will bear all that and more in mind.

How did you like today's Trends?

Love it 😁 Meh 😐 Hate it 🙁

FoodTech News Digested ✉️
Every Monday (12pm CET) & Friday (1pm CET) in your inbox

Reports

The 50+ companies driving the shift to plant-based chicken
The 30+ companies utilising big data analytics in the food and drink world
The 30+ companies giving vending machines a healthy, high-tech makeover
‘Upcycled’ food and drink: the brands going circular and transforming trash into treasure
A brave new world: exploring how the Internet of Things (IoT) can help the food industry
Exploring the holy grail of alt-meat: whole-cut plant-based meat and seafood
Alt-Eggs: Meet the startups scrambling to hatch the latest egg substitutes
Fava Beans: Is the humble fava bean the next big thing in plant-based?