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The Spoon

Daily news and analysis about the food tech revolution

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Spoonshot Raises $1M for its AI-Powered Flavor Trend Prediction Service

Spoonshot, a company that uses AI to predict new and different flavor combinations, announced today that it has raised $1 million in Seed funding. The round was led by SRI Capital and brings the total amount of funding for the company to $1.8 million.

The thesis behind Spoonshot is that companies looking to develop the next big thing in food need to look ahead. If your company only watches what is trending now, by the time it gets a product into market, that trend will already be over or commonplace.

To get ahead of the curve, Spoonshot’s platform examines data from across a vast number of food-related sources including online menus, food science, CPG ingredients and online food communities. Spoonshot runs this data through its proprietary machine learning and AI algorithms to help companies identify existing and novel flavor combinations.

The company launched its Ingredient Network product last October. At the time, we wrote:

Ingredient Networks lets you search ingredients for recommended flavor combinations and pairings. For example, when you search “banana,” it brings up what might be considered unusual recommendations like coffee concentrate and sunflower seed butter. But remember, what Spoonshot wants to do is surface flavors you probably haven’t considered. So bringing up something like chocolate or strawberries would be useless because you already know about them.

I spoke by phone this week with Kishan Vasani, Co-Founder and CEO of Spoonshot, and he said that the company has taken its Ingredient Network to the next level with its new Concept Generator.

Whereas Ingredient Network was more about exploring different flavor combinations and possibilities, the Concept Generator is more concrete. CPG companies can come to the service with a set idea in mind, like say, a cookie with blueberry as the main flavor. The Concept Generator then takes that information and returns with a blueprints of different blueberry cookies with different flavor combinations as well as all the ingredients that would go into making it.

Spoonshot’s tools are available at a unique time, given the pandemic. The lockdowns have people eating at home more and doing quite a bit of snacking. Giving CPG companies tools to quickly create new types of comfort foods could be quite appealing.

Vasani said that Spoonshot will be using the new money for marketing, something the company hasn’t really done up to this point, as well as hiring out its team.

Birdie Uses AI to Scour Reviews and Help Brands Understand Their Products

Thanks to our connected world, people who either love or hate a product, don’t have to keep their opinions to themselves. There is no shortage of platforms to express their thoughts.

This steady stream of opining is actually a source of fuel for Birdie, a company that uses AI to comb through product reviews and discussion forums (written in English) to surface product insights for CPGs and other other product brands.

For instance, by applying its AI to customer reviews of V8 juice, Birdie was able to show that people were often using the vegetable drink as a hangover remedy. By uncovering this data, V8 could then choose to create a specific line of drinks or marketing campaign that reaches this particular type of indulgent adult. The same idea applies to those pouches of pureed foods for toddlers. Birdie discovered that athletes and outdoors people carried these with them because they were easy to carry and loaded with nutrition.

Birdie is not a social media listening tool. It’s not just tallying up social mentions of a brand and analyzing timelines to see what is trending. Instead, the company is more focused on consumer product reviews on Amazon, Google and other places where purchases can be verified and are filled with more details about how the product arrived, how it was used, how long it lasted, etc.

“Our main differentiator is the fact that we chose to be very focused on products, and built a deep dictionary that relates to the buying journey of consumer products,” Patrícia Osório, CMO of Birdie told me by phone this week. “We capture the data related to a product attribute, or usage of the product, how they bought the product. With that, we can show our clients a detailed and easy to find view about how consumers are interacting with their brand.”

According to Osório, the number of product reviews in the U.S. has been growing quickly, with an increase of 60 percent year over year. She said there is an average of 621 new reviews written per day on food products, with an average of 342 reviews per SKU.

In a way, Birdie is like a distant cousin to Spoonshot, which applies its AI to vast datasets on food to uncover novel flavor combinations. Only in Birdie’s case it is uncovering novel uses for existing products.

Founded two and a half years ago, Birdie has raised $1.6 million in Seed funding and counts Procter & Gamble among its clients.

Birdie’s technology actually fits in with the larger hacker culture that we live in today. In addition to expressing their opinions, people love deconstructing and re-purposing existing products to fit their own needs, and sharing their findings with other people online. All this adds up to a never-ending source of data for Birdie’s algorithms, and more product insights for brands.

NPD: Restaurant Chain Transactions Down From Last Year, Digital Orders Up

New data from NPD Group is a real good news/bad news situation for restaurants. The bad news: for the week ending May 24, total major restaurant chain transactions declined 18 percent compared to the same time period last year. The good news? That’s up 25 percentage points from the biggest decline in transactions during this pandemic (-43 percent for the week ending April 12).

Of course, a big reason for that growth is that more cities and states began re-opening towards the end of May, so more people could once again actually go into a restaurant.

An NPD press release breaks the numbers down further, writing:

  • Major full service chain restaurant transactions declined by -42% versus same time year ago, a +7 point improvement from the prior week’s decline of -49% from year ago.
  • Transactions at quick service restaurant chains were down -17% in week ending May 24 compared to same week year ago, improving from the -20% decline in the prior week.

Another couple of interesting tid-bits from NPD’s recent data is that drive-thru, mostly at QSRs, made up almost half of all restaurant occasions, and that digital orders grew by 106 percent in April compared with last year. NPD says that digital orders now account for 20 percent of all restaurant occasions.

If you’ve been following my colleague Jenn Marston’s writing, this growth in digital orders and off-premises dining shouldn’t come as a surprise. In her excellent weekly restaurant tech newsletter this past Friday, she covered recent Black Box data that showed takeout orders are going back up. As Jenn wrote:

Presumably, people got excited about going back to restaurants instead of ordering takeout, then realized what a pain in the a$$ dine-in service is going to be for a long time to come. Guidelines vary from state to state in the U.S., but almost all of them include reduced capacity, reduced party sizes, no buffets, and in some cases a mask requirement. Add to that the trepidation most of us wear with our masks these days anytime we set foot in public, and it’s not exactly a recipe for a packed house.

As more cities and states ease shelter in place order, and summer gets into full swing, we’ll move from guessing about how consumers will react to restaurants’ re-opening and into hard numbers around what they are actually doing. Data like this from NPD helps chart those movements.

How Will the Black Swan of COVID-19 Impact Data Used in AI-Based Flavor Prediction?

In order to build an effective artificial intelligence (AI) platform, you need good data. Data feeds the algorithms that go into the AI; the better your data the better your AI system will function.

In the food tech world, there are a number of startups like Spoonshot, Analytical Flavor Systems and Tastewise have built intricate AI platforms that use tons of different data to help big CPG companies identify and predict culinary and flavor trends.

But what happens when a big catastrophic black swan event occurs like, oh, I don’t know, a global pandemic, which changes the eating and buying patterns of almost everyone on the planet all at once?

For instance. In February, it was easy to buy flour and yeast at your local grocery store. Fast forward to March and suddenly store shelves were empty and you had to resort to making your own yeast. Around that same time, instead of pictures of fancy restaurant meals, social media accounts were flooded with pictures of homemade bread.

Food predicting AI systems uses data points like restaurant menus, social media mentions and consumer purchasing patterns to determine future trends. But everyone didn’t start making sourdough bread at home because it was suddenly fashionable. It was because everyone was stuck inside.

How then, will AI systems handle this shock to the data system? Sheltering in place won’t last forever (knocks on wood), and who knows how long people will actually make their own bread. The popularity of it now is an aberration, does this mean that the data surrounding it is no good? Is bread making today indicative of anything other being bored or does it foretell a bigger trend?

To get a better sense I reached out to both SpoonShot and Analytical Flavor Systems to see how they are incorporating this massive disruption to our eating patterns into their own prediction process — and got two very different answers.

SpoonShot’s AI uses more than 3,000 sources across 22 data sets including menu, social and pattern data. Kishan Vasani, Co-Founder & CEO of SpoonShot, didn’t seem to think that COVID-19-induced eating changes would impact his company’s predictive capabilities at all. “Algorithms shouldn’t be overly sensitive to black swan data,” he said, “If you think about it, AI essentially means having enough relevant and appropriate data to process and predict.”

In other words, if your AI system is worth its salt, you should be able to weather big changes like this. “Everything goes back to the data and data sources,” Vasani said, “Menu data is significantly slowed down, but that’s compensated for with cooking platforms.”

On the other hand Jason Cohen, Founder and CEO of Analytical Flavor Systems, thinks the pandemic and subsequent lockdowns are a big deal. “Companies will say, ‘no no no, we can make predictions,'” Cohen said, “I do not believe that. This is the most rapid and intense change to consumer behavior since World War II.”

Cohen believes that with quarantines already in place for more than 60 days, new habits will definitely have formed. People will still be baking bread at home. What’s important is to meet this new data where it lives, literally.

Up until the pandemic, Analytical Flavor Systems used a 50 person panel of tasters as part of its data collection. This panel would come into the office to try various on-market foods. But since lockdown, the company has moved entirely to at-home testing. “In addition to CPG products, we are asking them to taste profile their homemade bread and soups,” Cohen said, “The point is we need to see those flavors, aromas and textures they are exposing themselves to.”

Cohen doesn’t think that past data is invalidated, but rather that data needs to be collected before during and after this crisis. Something which I think Vasani would agree with.

The thing about predictions now is that we won’t know if they were accurate for a long time. SpoonShot looks out 18 months and is even considering pushing that out to two years.

Hopefully we’ll be able to eat bread at a restaurant again by then.

Survey: 60 Percent of US Shoppers “Fearful” of Shopping Inside Grocery Stores

If coronavirus has you a little nervous about buying your food at the actual supermarket, you’re not alone. Results of a new survey from C+R Research shows that 60 percent of American shoppers are “now fearful” to shop at grocery stores, with 73 percent saying they are shopping less at physical stores.

Not surprisingly, C+R’s survey also found that grocery delivery has shot up 3.5x during the pandemic. Whereas consumers used to take an average of 2.3 weekly trips to the grocery store before the COVID-19 outbreak, they now average 1 trip a week.

While we’ve seen previous studies on the surge in online shopping, C+R’s survey highlights the emotional reactions people are having. In addition to being fearful of grocery stores, C+R found that 60 percent of respondents feel a sense of panic or anxiety when shopping, and 45 percent disinfect groceries when they get home.

This is actually completely understandable. Whereas grocery shopping used to be somewhere between fun and banal, the COVID-19 pandemic has changed all that. Aside from forced sheltering in place limiting our non-essential movements, the coronavirus grocery store is a far cry from what is was just a few months ago. Salad and hot bars are removed, workers and shoppers wear masks and gloves and there are plexiglass shields up around cashiers. This dystopian aesthetic, combined with a legitimate fear of catching a deadly virus, should cause a certain amount of fear.

The C+R survey reached 2,012 consumers from March 27 to March 28, 2020 via Amazon’s Mechanical Turk. As the pandemic continued domestically throughout the month of April, the question now is how deeply embedded have these fears become and will there be a new normal for grocery shopping? The virus may recede, but how long will its effects last on the way we interact with other people in public? If fear of supermarkets is making online grocery shopping the new normal, perhaps more grocery stores should go dark and just act as fulfillment centers for e-commerce.

People will always need to shop for food, so I’d be curious to see C+R follow up this study on a regular basis to check-in on how people continue to cope with the ever-changing world.

According to Yelp and Foursquare Data, Pizza, Fast Food, and CSAs are Up in Wake of Coronavirus

There’s a lot of news swirling around there about how COVID-19 is hurting local businesses, and for restaurants, things are looking especially grim. But what does the data actually say? Yelp and Foursquare recently released some analysis of internal data that gives insight into how our relationship with restaurants, dining, and more is shifting dramatically during this very abnormal time.

Yelp notes that many of the changes in restaurant and food business are a direct result of “the home’s rising status as the place to eat.” Considering we’re supposed to be social distancing — and a growing number of restaurants are forced to close their doors to diners, anyway — that’s not exactly surprising.

The numbers are pretty bleak for restaurants. Yelp reports that U.S. consumer interest in restaurants has fallen by about 54 percent. They only looked at data from the data range of March 8 to 18, so the number has probably increased as more and more cities and states restrict dine-in capabilities for restaurants. Simultaneously, Yelp notes that delivery and take-out are “2X more popular than usual.”

What sort of food is popular during the corona-pocalypse? Basically, anything that is suited for delivery and pickup. That means dim sum restaurants, French restaurants, and other spots geared towards more leisurely meals eaten in the restaurant dining room are suffering. Sales from food trucks and breweries are also down.

The news isn’t bad for all restaurants, though — some are actually thriving in the new normal of COVID-19. Sales from pizzerias and fast food restaurants are up 44 percent and 64 percent, respectively. Unsurprisingly, Yelp says that sales of beer, wine, and spirits are up 63 percent. And in your daily dose of heart-warming news, Community Supported Agriculture (CSA), or deliveries of farm produce, are up a whopping 405 percent.

Foursquare released its own data examining the change in foodservice foot traffic from February 19 to March 13. Like Yelp, it showed that QSRs are actually experiencing an uptick in traffic, though it cited a much smaller rise of 11 percent. Foursquare noted that QSR visits are down in areas with higher infection rates, like Washington state, but up in areas of the country with lower alert levels.

Seems like people still love their chicken sandwiches. [Photo: Foursquare]

Yelp points out that these shifts haven’t affected all of the U.S. in the same way. The impact is most significant near the coasts and more muted in the Midwest and Southeast, despite the fact that many cities and states have mandated dine-in closures in those areas. However, Yelp notes that every state reflects, at least to some degree, “the new reality of the coronavirus economy — that is, until it changes quickly again.”

To help restaurants struggling with this new reality, Yelp announced today that it would contribute $25 million to support local restaurants in the form of waived advertising fees and even free advertising.

That’s nice and all, but all the advertising in the world might not be enough to keep restaurants afloat. Some spots don’t have enough saved to keep paying rent/staff with significant diminished income. Others aren’t able to effectively pivot to a delivery- or pickup-only menu.

I don’t want to end this post on a glum note, but faced with cold, hard numbers, it can be hard not to feel scared for the future of local restaurants. So do what you can to support — go buy a gift card, tip a bartender virtually, or just place a pick-up order to support your favorite neighborhood spot. Maybe together we can help change some of these numbers.

CES 2020: AntX and FlowWaste Use Data to Cut Cafeteria Food Waste

I don’t know about you, but whenever I’m in a cafeteria dining situation — school, offices, Whole Foods hot bar — I always load up my plate high and… never finish it all. Maybe technology from AntX and FlowWaste, both of which exhibited at CES 2020’s Eureka Park this week, will someday help all of us cut down on food waste from cafeterias.

AntX has a smart scale that helps track exactly what you’re eating. The scale, which can be installed under food offerings at places like cafeterias, hot bars, and fast-casual restaurants, give instant feedback when you serve yourself.  

Say you’re eating at a school cafeteria and want some mac & cheese. With AntX, you’d grab a plastic AntX tracking card at the door then fill up your plate. As you add a scoop of mac & cheese, the scale will tell you exactly how much weight you’re getting, how many calories are in the serving, and how much it’ll cost you. 

After you’ve served yourself you swipe the card on the scale, which will keep track of how much you’ve got. It’s then swiped at the register where you not only get the total cost of your meal, but can also see the nutritional breakdown of everything you’ve served yourself. All of that data is saved in the AntX app, so you can look back and see nutritional data about what you’ve eaten.

Sure, it’s nice to see exactly how much of any food you’re taking so that you don’t get sticker shock when you weigh and pay for your food. AntX’s CEO Wicky Zhang, who gave me a demo of the tech on the show floor (see video below), pointed out that it’s also a way to curb overeating and food waste; when people are confronted with the exact calorie breakdown of their food, they tend to eat less. 

CES 2020: AntX's Smart Scale Collects Data for Cafeterias

But the real selling point here is the data. For consumers, especially those trying to stick to diets, it’s an easy way to track what they’ve eaten. For the foodservice providers, it’s even more valuable. They can look through consumer data to better optimize their food offerings. Say, for example, chicken teriyaki sells really well when displayed next to rice, but not well when it’s next to pasta. Or that people tend to eat less meat on Mondays. The restaurant can use that information to better inform menu decisions, as well as the layout of their foods.

AntX’s operates off of a subscription model, charging partners a monthly fee (which Zhang did not disclose) to use their system. The hardware — which can be a single scale or a full-on cafeteria buffet setup — will be either a low up-front cost or free. According to Zhang, the company is already working with 40 college and office cafeterias in China. It’s making its U.S. debut in two weeks in the cafeteria of Silicon Valley company Deepmap.

AntX comes into play at the beginning of your cafeteria journey, but FlowWaste appears at the end. The startup makes a camera that attaches to the tray rack of a dish station in cafeterias. As you stack your finished plate, the camera takes a photo of how much food is left behind and sends that data to the cafeteria operators, so they can tweak their portion sizes, menu offerings, dish pairings, and more. 

FlowWaste’s camera detects leftover food. [Photo: Catherine Lamb]

According to a FlowWaste rep, the first four weeks the camera trains to recognize all of the offerings in a cafeteria. After that, its image recognition software is sophisticated enough to “see” different food items and instantly recognize them. 

We’ll soon see just how effective this technology can be. FlowWaste will begin trialing in early Spring in the Indiana area with university and corporate cafeterias. The company, which is currently part of an incubator system at Notre Dame, operates on a subscription service which will cost around $1,000 per month. 

As we all know, food waste is a pressing issue up and down the food chain. Companies like Winnow and Leanpath are helping curb waste in restaurants’ back of house by optimizing ingredient ordering, but thus far there hasn’t been a lot of tech-focused on reducing consumer food waste in the front-of-house.

Hopefully that’s starting to change. Who knows, maybe next year the CES cafeterias will have AntX and FlowWaste up and running — and we’ll see a lot less food go in the trash. 

SKS 2019: Think of AI as Augmented Intelligence, and is the Future Just-in-Time Farming?

Artificial intelligence (AI) is a vague, slightly tech-y term that is overused by marketing departments trying to show some bona fides. But if you want some real insights on what artificial intelligence is and what it can do, then you should check out these talks that Chris Satchell of Zume and Erik Andrejko of Evolv (the venture arm of Kraft-Heinz) each did onstage at our recent Smart Kitchen Summit.

But before you can begin talking about AI you must understand the importance of data. Not just plenty of it or the right kind, as Satchell points out in his presentation. Before you can get into algorithms you need clean, tagged data that is centralized. He recommends that you don’t spread out your data teams across the company, and instead cluster them together to get the best results.

With your data organized and your models in place, then you can start to analyze and gain insights. For Zume, that means making the food supply chain more efficient. When we talk about last mile delivery, we’re actually talking about the last five or seven mile delivery. Zume is using predictive analytics to know ahead of time what food will be ordered, when and where. From that information they can place mobile kitchens directly in those neighborhoods to make the delivery process more efficient for the cooks, the couriers and the consumer.

Satchell wants to take this type of AI-based prediction up the food stack to improve supply chains and even create predictive farming. This type of just-in-time farming would help farmers understand what types of crops to grow and when in order to help reduce food waste.

As Andrejko pointed out in his talk, agriculture is already changing thanks to analytics and AI. Though Andrejko would like people to think of AI as “Augmented Intelligence,” not “Artificial Intelligence.” On the farm, this means that data and algorithms can be used to optimize how fertilizer is applied, using more on acres that need it and less where it doesn’t. Or with emerging fruit-picking robots that can use computer vision to automatically harvest at peak times for ripeness.

Andrejko also sees augmented intelligence at our kitchen tables, giving us more human connection at dinner time. Say you want to cook a butternut squash chili for dinner. Eventually you’ll be able to say that request to a voice assistant, which will break down the list of ingredients and place the order, which will be brought to your house via a self-driving delivery vehicle, which also uses AI to travel to your door.

These talks, along with the panel discussion with Satchell and Andrejko afterwards, are great deep dives into AI for anyone curious about the trendy term or for any company looking to add that arrow to their quiver. At least have the marketing department in your life check it out.

SKS 2019: How AI Will Reshape Food Markets

Move Over Virtual Kitchens, Zume Shows Off Mobile Kitchen Model with &Pizza

Sometimes there is a difference between the news and the story. For instance, the news today is Zume, Inc., the parent company of Zume Pizza, announced that its mobile kitchen technology will be used by the &Pizza chain.

Technically, &Pizza has already been using Zume’s mobile kitchen at one location in Washington D.C., but that is just the beginning of the partnership. According to the press release sent to The Spoon, the mobile kitchens will be used to expand &Pizza’s brand in new markets and test new products before adding them to &Pizza’s brick and mortar location menus.

So that’s the news. But the story here is actually how Zume is creating a new category of kitchen, one that exists somewhere between the traditional restaurant, virtual kitchen and food truck.

To recap: Zume’s mobile kitchens are pretty much what you would imagine: big trucks outfitted with appliances that can be parked in neighborhoods, closer to customers, to ideally make food delivery faster. Place a food order and the WiFi enabled devices on board the mobile kitchen guide the cooks, make the meal, coordinate delivery pickup and keeps you up to date the entire time.

Right now, &Pizza is just using the Zume’s mobile kitchens, but Zume also offers a full-stack solution that includes predictive analytics and packaging. In theory, this should bring a new level of efficiency to a restaurant looking to expand its operations. Here’s how:

A mobile kitchen requires less investment than a traditional brick and mortar restaurant because you don’t have to build out and maintain a permanent location. This is also the pitch of virtual kitchen spaces like Kitchen United, which lease out commercial restaurant infrastructure for delivery-only restaurant concepts. But while virtual kitchens remain static in one location, a mobile kitchen can park out in different neighborhoods for closer proximity to a restaurant’s customers. A food truck has the mobility, but they are based around nearby foot traffic, so their potential market size is limited.

Even with all promised flexibility around its mobile kitchens, the main hook with Zume has always been its predictive analytics. As we wrote previously:

Zume takes into consideration hundreds of data points, such as day of the week, weather, school calendars and more to develop predictions around how much pizza and what types of pizza will be ordered in a given location. From there a food delivery vehicle cooks up the pizza on the move and delivers it with precise timing.

Zume Inc. subsidiary, Zume Pizza, knows which neighborhoods will order pizza (and gets the proper permitting to set up camp), what types and how many pizzas will be ordered. From there, it can pre-make those pizzas in a central facility and store them in the mobile kitchen so when the orders come in, they just need to be baked and delivered. The limited space of mobile kitchens can be stocked efficiently, delivery drivers can make more dropoffs because they aren’t driving around town, and the food arrives fresher for the consumer because it hasn’t traveled very far. Zume even offers special compostable packaging that restaurants can use.

And it’s not just pizza. Zume opened up its data platform to all types of cuisine last year so Thai or Chinese restaurants or whatever can be outfitted with custom mobile kitchens with the necessary equipment to do the same.

Zume already got $375 million from SoftBank last year, with another potential $375 million more as part of that deal. So the company has the money to scale out operations to different restaurants and regions. &Pizza and Zume may have made news today, but the story to watch over the coming year is how many other restaurants license Zume’s technology.

Gallup: 81 Percent of Americans “Never” Order Groceries Online (But That’s Still Good News for Grocers)

A survey out from Gallup last week showed that the vast majority of Americans are not shopping for groceries online. According to Gallup, “Eighty-one percent of Americans say they never order groceries online, while 11% say they do so at least once a month.”

Gallup posited the following explanation for American hesitancy when it comes to online grocery shopping, writing:

The slow adoption of online food ordering could indicate that people enjoy picking their own groceries in person or that they don’t see sufficient savings of time or money to justify the switch. The delivery charges that go along with food delivery may be a factor in that.

That sounds pretty dire for the grocery industry, which is investing pretty heavily in online ordering and fulfillment mechanisms. But one of the good things about this stat is that we have a similar Gallup poll from almost exactly a year ago to compare it to. If you are looking for a silver lining, last year Gallup found that 84 percent never bought groceries online. So there’s been a three percent drop in the number of “nevers.”

Additionally, there’s more (relatively) good news to be found if you dig into the numbers a bit. Last year Gallup found that 14 percent of adults with children under 18 bought groceries online at least monthly. The 2019 survey found that 19 percent of those with children under 18 bought groceries online at least monthly. So if you’re playing the (very) long game, there are more families online grocery shopping, and they are raising a new generation that will grow up believing online shopping is the normal way to get groceries.

The Gallup stats should be taken as a piece of a bigger set of data around the evolution of grocery shopping. While it was small, Gallup did find an increase in the number of people who have at least tried online grocery shopping this year. In May, Coresight Research found that between 2018 and 2019, there was an increase of 35 million people who shopped for groceries online. And in July, a Field Agent survey found that 66 percent of its respondents expect to be buying their groceries online in the next five years.

Having said all that, in-store shopping is still the way to go when it comes to groceries for most Americans. Gallup’s 2019 found that 83 percent say that they shop at grocery stores at least once a week, which is why the biggest opportunity for grocers may be investing in curbside pickup (which many are already doing). Curbside pickup allows people to maintain their regular life schedules, and gives them an opportunity to inspect items at the store in case any need to be returned.

My guess would be this time next year, Gallup will show another year of incremental growth in online grocery shopping. But as big investments from Walmart, Kroger and Albertsons move out of testing and into real life, the adoption for online grocery shopping will accelerate soon after that.

Will Data Ruin Dining Out?

If given the choice, my eight-year-old son would eat the same thing for every meal: kid’s bean-n-cheese burrito with black beans (no rice) and sour cream and guacamole. Every. Time. As a parent, I’m fine with this, because it means he’s at least eating. As an adult, however, I crave more variety in my meals and want subtle differences from dish to dish.

But I fear those subtleties and nuances in food will get lost as hardware and software innovations push restaurants towards greater data-driven insights. These insights will translate into actions that will increase predictability. This predictability can mean more profits for business, but more meal monotony for customers.

I got to thinking about this when I wrote about Nectar this week. That company uses high-tech bottle caps to monitor pours and provide real-time analysis of how much booze bartenders are using on any given drink. On its face, it’s a way for bars, already working on thin margins, to better manage their alcohol inventory and spending. But painstakingly monitoring every ounce of every pour could also limit a bartender’s ability and willingness to get creative with their cocktails. Why experiment on the mango-tini if you’re just going to get called out for wasting booze or, in the case of owners, watch every extra drop put in a drink become data that tells you how much money you’re wasting?

And it’s not just impacting what happening behind the bar. Earlier this month at Google I/O, the internet giant launched a new Google Lens feature that combines machine learning, computer vision and a whole bunch of data to let people know what’s popular at a restaurant at that moment. From the Google blog post announcement:

Say you’re at a restaurant, figuring out what to order. Lens can automatically highlight which dishes are popular–right on the physical menu. When you tap on a dish, you can see what it actually looks like and what people are saying about it, thanks to photos and reviews from Google Maps.

This, too, however, seems to be a good news/bad news scenario, as my colleague Jenn Marston wrote at the time:

On the one hand, it could provide valuable information for restaurants when it comes to figuring out what is and isn’t selling on the menu, so chefs and operators could better adjust their planning and inventory (potentially helping them avoid food waste and keep costs down).

But what this will do to the adventure of going out to eat? Part of the fun of the restaurant experience is the guesswork, which would be gone were we to rely too heavily on data-driven recommendations. This seems unlikely at higher-end restaurants and places designed for adventurous foodies, with robust appetites for the unknown. For all the places in between, though, too much knowledge might make the restaurant experience just a little too predictable.

Obviously, when presented with all this new data, restaurants will want to act on it, and what better way to combine precisely monitored food creation with consistency than with a robot?

We cover robots a lot here at The Spoon. (Heck, we dedicated an entire conference to food robots.) A big theme we’ve found again and again when it comes to restaurants and robots is that a robotic workforce can do repetitive tasks far more precisely and consistently than any human, which means little to no variation in the end product. The machine will make the meal the same way, every time.

Again, this isn’t necessarily a bad thing in and of itself. The robot-created cheeseburger at Creator is delicious, and if I go back to San Francisco, I know it will be delicious in all the same ways if I order another one.

But if restaurants have the tools to know exactly what food sells and when, and they have a machine that will successfully replicate those popular meals over and over, then what we’ll get is… the same meals over and over and over. The ability for cooks (or customers) to experiment will be limited at best, eradicated at worst. The restaurant experience becomes more like a pre-determined assembly line constructing widgets, rather than a real meal.

The question of data insight versus art certainly isn’t a new one, just ask baseball. The difference for the restaurant industry, though, is scale. Everyone eats (even at baseball games), and restaurants, in an effort to drive more sales and eke out more profits, will optimize their businesses around data. The end result will probably taste good, but in a way that feels more mandated from management.

As long as they serve bean-n-cheese burritos, I know at least one person who will be happy.

Join us to talk restaurant tech at the Smart Kitchen Summit, our flagship foodtech conference on Oct 7-8th in Seattle. 

Study: More US Consumers Buying Groceries Online, Amazon Still Top Place People Buy Them

Coresight Research released its “US Online Grocery Survey 2019” this week, finding that 36.8 percent of U.S. consumers bought groceries online over the past year, representing a jump from 23.1 percent in the firm’s 2018 survey. Year over year, Coresight says this is an increase of roughly 35 million more consumers buying groceries online.

However, that doesn’t mean every aspect of the online grocery biz is rosy. Coresight found that while more people may be buying groceries online, the vast majority aren’t buying much. According to the survey, “72.4 percent buy only a small proportion of their groceries online while 11.8% buy a lot of their groceries online.”

When consumers are buying groceries online, Amazon.com is the top place to do it. Coresight says 62.5 percent of who bought groceries online did so through Amazon, which commands a double digit lead over competitors like Walmart and Target (see below). It should be noted, however, that most of this shopping is through Amazon proper, not Amazon Fresh or Prime Now, and that Amazon shoppers generally spend less on groceries there then at Walmart.com, Target.com or Kroger.com, making Amazon shoppers “occasional or small-basket online shoppers.”

While Amazon may be in the lead when it comes to the number of online grocery shoppers, Walmart and Target are both making gains. Coresight’s study found the portion of people buying groceries online who bought from Walmart was 37.4 percent, up from 25.5 percent in 2018, same goes for Target.com, which nabbed 15.7 percent of online grocery shoppers, up from 6.9 percent in 2018.

News of this growth comes at a time when retailers are investing heavily in automation to speed up the fulfillment and delivery of these online grocery orders. Albertsons and Walmart are piloting in-store micro-fulfillment and Kroger is building out robot-driven warehouses and self-driving delivery vehicles. This ability to expedite online order processing will make online grocery ordering for consumers more convenient and should spur even more online grocery order growth.