Tag Archives: Cafe

Find Your Coffee

At cafehound.com, we endeavor to locate the best coffee in the world. Over the last eight years we’ve happily watched as globally, the options available to the public have exponentially increased and the public’s general awareness of specialty coffee has deepened. Although we still believe that tracking down the best coffee in the world is central to our mission, we recently decided to dip our toes into the area of recommending specific coffee(s) to coffee lovers based on a mixture of qualitative and empirical analysis.

espresso_2017

In two posts (1 and 2) from 2015, we took verbal reviews of specialty coffees from the site coffeereview.com,  and we employed various clustering algorithms to discover groupings of coffee (based on words used to describe them and other factors). This served as our initial foray into using Data Science on expert coffee reviews to improve our understanding of specialty coffee.

Over the past month, we’ve set out to improve upon that original work in order to empower java lovers to discover the perfect brew. Our years of cupping coffee and talking with experts have shown that – after a certain point – what constitutes a “good cup of coffee” is subjective and specific to the palette of the beholder.

With that in mind, cafehound.com chose to use a large, multiyear list of coffee reviews from Kenneth David’s coffeereview.com site to explore the relationship between the descriptions used to rate coffee aroma, flavor, aftertaste, body, acidity and finish. We hypothesized that there are distinct groupings of coffee based on their roast profile, body, and flavors that are relevant to informing consumer preferences in the overall marketplace. To clarify, a market segmentation based on a representative sample of surveyed consumer preferences may be more useful to marketing professionals, but that is outside of the scope of this post. Instead, we’re using the structure inferred from math and reviews of specific coffees to estimate categories of the potential “coffee experience.” These categories may provide coffee consumers with guideposts for exploring new specialty coffees.

Our results led to six broad categories of coffee that we’ve ordered from lightest to darkest roast (based on average Agtron ratings). Agtron ratings are a numerical representation of the consistency of the roast color (lower numbers indicate a darker roast <45, higher numbers indicate a lighter roast 50+). More than the roast determines the flavor profile and overall body of the coffee, which is why some of these segments may appear similar.

Initially, we bring this content to you via occasionally updated web pages. Depending on demand, we may scale our service to provide daily or weekly recommendation updates.

For now, follow the link below to Find Your Coffee.

cafehoundlogos01

For code share:

Shiny Segmentation and Prediction

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Data Science: Exploring CoffeeReview.com Top Coffees (Cntd.)

In the last post we began exploring the relationship between the language describing coffee (“cupping notes”) and price/brand/roaster. Our objective is to provide coffee consumers with a general understanding of particular groupings of coffee they can choose based on flavor profiles and mouthfeel characteristics. An example of the type of properties coffee professionals use to describe their craft is illustrated in the below flavor wheel from Counter Culture:

CC_FlavorWheel

After evaluating the segments that our initial k-means clustering (with a k of 5) produced, I was unsatisfied with the results. My decision to haphazardly throw the price variable (unscaled) into the model was wrong-headed and drove the algorithm to essentially classify segment membership solely based upon that. In some cases such an exercise may be useful, but for our objective of discerning whether specific language could be used to segment particular specialty coffees, this segmentation wasn’t going to do it for us.

Also, this initial segmentation helped me narrow my “business objective”. Now I wanted to segment by flavor profile, something that might actually help inform a potential consumer’s purchasing decisions.

In order to develop the cupping note variables that would inform our segmentation, I explored the text data from Kenneth Davids’ site and selected the most common and/or most distinguishing words to test. The list of words is below.

wordlist

A quick look at these led me to believe that certain words might not yield significant information gain in the algorithm due to lack of variance. Mouthfeel, sweet and acidity were present in 96%, 80% and 90% of reviews respectively. Their power as differentiating variables would be constrained by their existence in nearly all observations (with the possible exception of acidity).

However, in my initial quick cluster using SPSS, I included the three variables mentioned above and I still liked the results enough to move forward.

Segment 1: 16.9% of reviews

Segment 1: 16.9% of reviews

This segment was the most expensive (average $42.31 USD per pound) and highest rated (94.6). The segment was the highest indexed on floral, honey, complex, silk, delicate, intense, and peach cupping notes. It also indexed highly on nib, lemon and acidity. The most common producer countries in this mix were geisha panama and Colombia, Ethiopian, Kenyan and El Salvadoran coffees.

List of Segment One Coffees 

Seg1_L1 Seg1_L2

Segment 2: 27.8% of reviews

Segment 2: 27.8% of reviews

This segment was the least expensive (average $26.72 USD per pound) and moderately rated (94.45) while coming from the most diverse sampling of producer countries. It indexed highest on rich, deep, resonant and pungent cupping notes. Whereas the other segments did not include any coffees from Bolivia, Brazil, Mexico or Papa New Guinea, this segment did.

List of Segment Two Coffees 

Seg2_L1Seg2_L2Seg2_L3

Segment 3: 13.9% of reviews

Segment 3: 13.9% of reviews

This segment was middle of the road in terms of cost and ratings (average $37.09 USD per pound and rated 94.52 on average). It indexed highest as juicy, tart, acidity, nib, bright, sweet, and was also well above average in complexity and floral notes. The range of producing countries varied quite a bit in this segment, with several bourbon varietals from Guatemala, Costa Rica, Hawaii – still other Geishas from Panama, Colombia and Guatemala – several Ethiopian Yirgacheffe coffees and a few honey processed coffees from El Salvador (Pacamara) and Hawaii (Maragogype ($75/lb)).

List of Segment Three Coffees 

Seg3_L1 Seg3_L2

Segment 4: 20.3% of reviews

Segment 4: 20.3% of reviews

This segment was the least expensive ($28.46 USD per pound) and lowest rated (94.33) – all things relative to a very highly rated group of coffees. It indexed highest for fruit, sweet, lemon and light while also coming in pretty strong in the tart department as well. This segment is composed of a mixture of coffees from Ethiopia, Kenya, Burundi, Indonesia and Honduras. A few peaberry coffees are included, the red caturra from Rusty’s Hawaiian, a few stray Geisha coffees, and a decently heavy sampling of Sumatra, Yirgacheffe, Sidamo, and various Kenyan single-origins. For the value, this is a very attractive and diverse segment of coffees. See our site visit to Rusty’s in Hawai’i in 2011.

List of Segment Four Coffees 

Seg4_L1 Seg4_L2

Cupping With Miguel At Lorie's Home

Cupping With Miguel At Lorie’s Home

Segment 5: 21.1% of reviews

Segment 5: 21.1% of reviews

Segment five is highly rated (94.58) and quite expensive ($37.73 USD per pound on average). This segment indexes the highest for tart, rich, acidity, syrup, pungent, and mouthfeel, while also scoring highly for honey and bright notes. Panama, Colombia, Hawaii and Ethiopia are the most heavily represented producer countries in this grouping. This segment is probably the most populated by Geishas followed by exotic Ethiopian and Kenyan coffees.

List of Segment Five Coffees 

Seg5_L1Seg5_L2

 

 

For more information on the roasters evaluated in this data from the coffeereview.com website, see the links and data below:

ML_1ML_2ML_3ML_4

And I’ll leave you with a bit of a refresher on the Cup of Excellence Scoring Categories for thinking about and communicating coffee quality/taste.

Cup of Excellence® Scoring Categories

DEFECTS

Phenolic, rio, riado automatic disqualification Ferment
Oniony, sweaty

CLEAN CUP
+ purity | free from measurable faults | clarity – dirty | earthy | moldy | off-fruity

SWEETNESS (prevalence of…)
+ ripeness | sweet
– green | undeveloped | closed | tart

ACIDITY
+ lively | refined | firm | soft | having spine | crisp | structure | racy – sharp | hard | thin | dull | acetic | sour | flabby | biting

MOUTHFEEL (texture, viscosity, sediment, weight, astringency)
+ buttery | creamy | round | smooth | cradling | rich | velvety | tightly knit – astringent | rough | watery | thin | light | gritty

FLAVOR (nose + taste)
+ character | intensity | distinctiveness | pleasure | simple-complex | depth

(possible notations: nutty, chocolate, berry, fruit, caramel, floral, beefy, spicy, honey, smokey…)

– insipid | potato | peas | grassy | woody | bitter-salty-sour | gamey | baggy

AFTERTASTE
+ sweet | cleanly disappearing | pleasantly lingering
– bitter | harsh | astringent | cloying | dirty | unpleasant | metallic

BALANCE
+ harmony | equilibrium | stable-consistent (from hot to cold) | structure | tuning | acidity-body – hollow | excessive | aggressive | inconsistent change in character

OVERALL (not a correction!)
+ complexity | dimension | uniformity | richness | (transformation from hot to cold…) – simplistic | boring | do not like!

Data Science: Exploring CoffeeReview.com Top Coffees

Over the past few years, I’ve transitioned my career from government-oriented management consulting to the field of advanced analytics and data science.

 

In general terms, this has required me to climb a significant learning curve in the related areas of computer programming languages and advanced statistical methods. While it has been challenging, the rewards of being able to more effectively and efficiently extract insights from various types of information/data is encouraging.

With the objective of exploring my love of specialty coffee, I chose to practice a few basic data science methods on a relatively well-known specialty coffee review website: coffeereview.com .

The goal was to apply web scraping, text analytics, segmentation, and some visualization techniques to coffee review data in order to explore correlations between price, producer country, roaster, and quality over time.

My colleague and I discussed the objective over Memorial Day weekend and set out on parallel paths to scrape review data from the website. He used a Python script to scrape the website, and I used an R script to do the same. In the end, his Python script achieved a more efficient scrape, producing a column separated variable (.csv) file that could be imported into a statistical computing software package like SPSS or R.

The website we targeted in this scrape was the 21 pages of: http://www.coffeereview.com/highest-rated-coffees/

 

From there, I cleaned up the file (using R packages such as “dplyr”, “stringr” and “sqldf” to get things to a point where we could calculate price per pound amounts and country of origin for most of the coffees reviewed. I was also able to pull down city/state location data for each of the roasters and their websites.

One of my first business questions involved the type of descriptive language used to review the website’s top-rated coffees. Where there any particular words that we could associate with the best rated coffee out there, according to coffeereview.com?

A relatively straightforward way to investigate that question is to use a Word Cloud to illustrate the words with the highest frequency of mention in individual review comments.

Most frequent words describing top rated coffees.

Most frequent words describing top rated coffees.

Clearly, if you want to appear to know the jargon for communicating your delight about a quality cup of java, you should say something like, “This coffee’s intense aroma of flowers, baker’s chocolate and fruit is only bested by its complex, rich flavor with tart tinges of acidity and a balanced, silky, syrupy, honey finish…”. Okay…so that sounds ridiculous…but you get the point.

Exploring the data

What is the range of ratings found on the top rated page?

The maximum rating any single coffee receives on this page (of highest rated coffees) is 97, while the minimum is 94. There isn’t a lot of variance. Most of the top rated coffees are rated 94, a third are 95, and the remaining15 percent are either 96 or 97. We will revisit this data later.

Distribution of Top Rated Coffees from CoffeeReview.com

Distribution of Top Rated Coffees from CoffeeReview.com

What years of ratings do we have the most robust data for in order to do more specific analysis on our variables?

We decided to drop all years prior to 2010 (which had 29 coffees reviewed that year).

year count
2014 70
2013 58
2012 40
2011 39
2015 24
2010 20
Which coffee roasters were the most frequently reviewed and top rated by coffeereview.com between 2010 and roughly six months into 2015?

JBC Coffee Roasters from Madison, Wisconsin was the favorite by far in terms of its 26 reviews on the website in the time span specified. Followed by Temple Coffee and Tea in Sacramento, CA (20) and PT’s Coffee Roasting Company in Topeka, Kansas (13). This was a surprise to me, as I have never sampled ANY coffee from these roasters and feel like I have been missing out. In order to show the table of roasters, i used the combination of R packages “RGraphics” and “gridExtra” to save some nice incremental (sets of 15) graphics.

roasters_1_15

roasters_16_30 roasters_31_45 roasters_46_60 roasters_61_73

A quick visualization of the top rated coffees by year, price per pound and origin country shows some semi-distinct segments within the data based on price alone. This led me to ponder if we could use a clustering algorithm (such as k-means using dummy variables for each country, price per pound, and rating) in order to more clearly segment particular coffees by segment. Instead of using R for this exploration, I exported the data into a .csv and imported it into SPSS to run the analysis there.

Price per pound by origin country and year ($US).

Price per pound by origin country and year ($US). United States = Hawai’i.

A five-way cluster solution seemed the most suitable for segmenting the data in a way that illustrated differences across price and producer country.

Price unreasonably drove the segmentation, as seen in this graphic.

Price unreasonably drove the segmentation, as seen in this graphic.

The segments broke out into groupings containing the following number of coffee reviews each:

Segment                       Count               $US/lb

1                                       174                   $21
2                                       8                      $121
3                                       35                    $44
4                                       1                       $243
5                                       20                    $84

Segment 1: No Geisha or Hawaiian Coffees, Espresso Blends
Segment 2: Panama and Colombian Geishas
Segment 3: Mix of Geishas, Ethiopian, and Hawaiian
Segment 4: Semeon Abay Ethiopia
Segment 5: Mid-priced Geisha, Hawaiian and Ethiopian

Interestingly, a few roasters exhibited a bit of dispersion across the segments due to the variety of awesome tasting coffees they had reviewed. Those roasters included:

PT’s Coffee Roasting Co.

5 (Seg 1)
3 (Seg 2)
3 (Seg 3)
2 were (Seg 5)

Barrington Coffee Roasting Co.

3 were (Seg 1)
4 were (Seg 3)
1 was (Seg 4)
3 were (Seg 5)

Bird Rock Coffee Roasters

6 were (Seg 1)
1 was (Seg 2)
3 were (Seg 3)
1 was (Seg 5)

Paradise Roasters

6 were (Seg 1)
1 was (Seg 2)
1 was (Seg 3)
2 were (Seg 5)

After exploring the data in this way, I wondered if 1) my approach to segmentation was appropriate 2) what the comments from these segments looked like comparatively. To answer the first question: no, but that will be the topic of my next blog post. To answer the second, let’s explore some word clouds below.

Word Cloud: Segment 1

Word Cloud: Segment 1

Word Cloud: Segment 2

Word Cloud: Segment 2

Word Cloud: Segment 3

Word Cloud: Segment 3

Word Cloud: Segment 4

Word Cloud: Segment 4

Word Cloud: Segment 5

Word Cloud: Segment 5

 

Perhaps clustering by cupping notes is a better way to segment groups…stay tuned.

Coffee Logistics: Specialty Coffee On-Demand?

Source: The Atlantic – Robinson Meyer

A barista at Ritual Roasters in San Francisco pours hot coffee into Thermoses about to be shipped around the country. (Courtesy Thermos)

Last week, Thermos overnighted me a cup of hot coffee from Minneapolis to Washington, D.C., to see if it could. It was a bald-faced PR stunt. It succeeded in both senses: The coffee was still hot by the time it reached me, and I am writing about it now.

Now you’ve been warned: This is an article about a PR stunt. It was, however, an extraordinary PR stunt—well-executed, conceptually simple, and bubbling with zeitgeist. And I accepted the hot coffee for reasons beyond my love of roasted arabica.

The stunt was ostensibly to promote Thermos’ vacuum-insulated 40-ounce Stainless King beverage bottle. The company claims the Stainless King can keep hot things hot and cold things cold for 24 hours, and indeed my own experience with this monarch of thermoses bore that out.

The stunt’s part of a larger contest (and context). In May, Thermos shipped 25 of its Facebook fans in the contiguous U.S. free coffee overnight from Ritual Coffee in San Francisco. This month, the second time it ran the contest, it chose a more midwestern provider: Spyhouse Coffee in Minneapolis.

Courtney Fehrenbacher, a marketing manager at Thermos, told me that the company hopes to re-run the contest every other month, at least until the end of the year. Altogether, Spyhouse will hand 35 of its steaming envoys over to FedEx to be distributed across the country.

But, dare I say, the stunt was about even more than Thermos, Spyhouse, the Stainless King, or the Iron Throne. It was about logistics.

***

The box, as it arrived in D.C. (Robinson Meyer/The Atlantic)

As best as I can assemble it, here is the trajectory of the Stainless King and its erstwhile contents.

The coffee inside the Stainless King was Spyhouse’s Las Nubes roast: a coffee variety indigenous to Kenya and grown in El Salvador. The varietal was brought to El Salvador in the early 20th century when that country’s economy rested on its coffee production. This bean was grown on a similarly old farm, high-altitude land owned by the same family since the 1920s. (Or, at least, that’s the story Spyhouse tells.)

This bean, though. It was harvested sometime last winter before it entered its customary months of rest. Afterward, it was shipped to Spyhouse, which roasted the beans on July 21, 2014. It became the shop’s Las Nubes lot.

I presume it roasted those beans in the morning, because by the afternoon it was brewing the coffee. Around 4 p.m., the team got out their 10 Stainless Kings (designated for me and fellow members of the media) and filled them with Las Nubes, which they dripped. Then they put them in Thermos’s special packages—augmented with a bag of freshly roasted Las Nubes—and drove the boxes “about a quarter mile away” to the local FedEx facility.

According to a FedEx spokeswoman, the package was placed in a modified McDonnell Douglas DC-10, called an MD-10*. That plane’s a couple decades old, at least—McDonnell stopped making them in 1989—and FedEx owns more than anyone else. FedEx indisputably owns the largest private cargo fleet in the world, and, according to the trade journal Supply Chainthe fourth-largest aircraft fleet, period. 

Someone at Spyhouse knew how to pack a box. (Robinson Meyer / The Atlantic)

Perhaps the package was stopped and exchanged in one of FedEx’s global or national hubs, in Memphis, or Indianapolis. Eventually, though, it arrived in D.C. in the wee hours of the July 22. Unloaded from the plane, sorted, loaded onto a truck, and carried to The Atlantic’s office/cement island-fortress, the Watergate, it reached its destination at 7:21 a.m. The coffee had been roasted less than 24 hours before.

Of course, the coffee wouldn’t reach its final destination—my belly—for another hour or so. I got to work during the eight o’clock hour, hoping to intercept the Stainless King, and discovered Santa had already arrived.

With my colleague Adrienne, I unboxed the long-traveling liquid. Like Max’s dinner in Where the Wild Things Are, it was still hot.

***

This sticker sealed the box that arrived from Spyhouse. (Robinson Meyer / The Atlantic)

Talking to Spyhouse’s founder and owner, Christian Johnson, I’ve been able to piece together the coffee’s temperature-history. Spyhouse uses water at exactly 203 degrees Fahrenheit to brew Las Nubes. Johnson estimates that by the time that liquid—now coffee—departs the brew shuttle, it’s between 175 and 180 degrees. Then it was capped, vacuum-sheathed, and sent on its way.

But still the conditions outside changed. “Depending on the exact placement of the package inside the aircraft, temperatures range from 40 to 70 degrees Fahrenheit during an average flight, with the average temperature being about 60 degrees,” a Fedex spokeswoman said of the Thermos’ cargo transit. And the pressure changed outside as well, rising to the equivalent of 8,000 feet above sea level.

It was about 72 degrees in the district as the package trundled through, and a few degrees cooler in my almost-refrigerated office. When we uncapped the Thermos, we measured its temperature to be 151 degrees.

Can you see the steam coming off the just-opened Stainless King? Maybe not? Okay, well, it totally was. (Robinson Meyer/The Atlantic)

 “Wow. That’s amazing,” said Johnson, after I shared this heat conservation with him. “So really you only lost 25 degrees between when we capped the thermos to when you opened it.”

He added that the other factors involved in long-form transit—the altitude, the pressurization—shouldn’t have significantly affected the coffee’s taste. I think that sounds right. I found Las Nubes as described, similar to other El Salvadorean coffee I’ve had that didn’t migrate: acidic in a citrusy way, a little sweet.

***

According to Fehrenbacher, the idea for the contest came from an anecdote that Thermos’s president would tell. Once upon a time, the story went, a client had paid the company to regularly overnight coffee from across the country. (No one seems to remember just which client this was.) Why not see if they could recreate the story for marketing purposes?

The gimmickry of the stunt seemed to attract Johnson to the idea. But when he spoke to me, he obligingly remarked too on the pop-cultural power of Thermos. He and the other baristas carried Thermos-made lunch boxes as kids; they respected Thermos as a stalwart American product. Now, they were proud to partner with the company for the contest.

The hot coffee, a few minutes after arriving—it held its temperature in the mug. (Robinson Meyer / The Atlantic)

And Thermos is an enviable tool for that reason. It embodies “do one thing well”in the world of beverage receptacles. People buy it because they want something that does what a Thermos does—and every time, without fail, without system reboots or lag, it dispatches this task admirably. (Though if I have one quarrel with the Stainless King, its top cap was sometimes very, very hard to screw off.)

Talking to Thermos and Spyhouse, I was struck by the image at the top of this post: A Ritual roster, pierced and bearded, pouring single-origin coffee into that most mainstream of food receptacles: the Thermos. It’s more than urban-meets-rural: It’s the new dream of artisanal, ethical food preparation meeting the old dream of mass-produced American plenty.

Packing the boxes at Ritual Roasters (courtesy Thermos)

It reminds me of the most recent product of K-Hole, a kind of art collective that mocks corporate trends-casting reports by issuing its own. K-Hole calls the aesthetic that gives rise to artisanal coffee “Mass Indie”:

Mass Indie ditched the Alternative preoccupation with evading sameness and focused on celebrating difference instead. […] Whether you’re soft grunge, pastel goth, or pale, you can shop at Forever 21.

But as Mass Indie becomes mass-er, it starts to hit snags. “Individuality was once the path to personal freedom—a way to lead life on your own terms,” says K-Hole’s report. “But the terms keep getting more and more specific, making us more and more isolated.” Each product, slightly different and catering to a slightly different audience, winds up isolating people in islands of taste and difference:

Feast.ly, Fast.ly, Vid.ly, Vend.ly, Ming.ly, Mob.ly: each provides a specific service, finetuned to a specific user need, brought to life by a specific entrepreneurial urge. They’re all targeting different audiences, but the general public can’t remember who’s who.

As Mass Indie approaches cultural domination, its elites flee. They’re alone on their perfectly curated and indecipherable islands of taste. They instead embrace—and please, please, do not stop reading when you encounter this word—normcore.

Normcore moves away from a coolness that relies on difference to a post-authenticity coolness that opts in to sameness. But instead of appropriating an aestheticized version of the mainstream, it just cops to the situation at hand. To be truly Normcore, you need to understand that there’s no such thing as normal. […]

Normcore seeks the freedom that comes with non-exclusivity. It finds liberation in being nothing special, and realizes that adaptability leads to belonging.

“If you live in the middle of nowhere,” Fehrenbacher told me, lauding her own company’s stunt, “you get to try some of the country’s best coffee.” Thermos has already shipped hot coffee to central Florida, northern Michigan, and (of course) New York City.

Looking at that picture of the bearded barista and the line of identical Thermoses, I thought, what could be more normcore than this?

But there’s something that enables all of this, from my supping of the coffee to your reading this now: the global supply chain. The ability to fling ingredients and products from coast-to-coast and continent-to-continent makes not only Thermos’s contest but Spyhouse’s very business possible. It’s the supply chain that moves coffee beans from El Salvador to Minneapolis, where they can be roasted and sipped in days. It’s the supply chain—in the form of FedEx, which, remember, has the world’s fourth largest collection of aircraft—that performs the final stunt of getting coffee around the lower 48 in half a day.

Behind every ingredients list stand the movers and shippers of our world: each, like FedEx, possessing a private army of execution. I accepted Thermos’s coffee contest because it seemed a spectacle of logistics. But every single day of our lives is already that.


* This post originally described the plane which shipped the Thermos as a DC-10. It is properly an MD-10: a DC-10 modified by FedEx to have a larger cockpit and different hull. We regret the error.

Cafe Hounding: Verve Coffee

Verve Coffee Roasters
816 41st Avenue
Santa Cruz, CA 95062
Phone: (831) 475-7776

http://www.vervecoffeeroasters.com/

Awesome service, attention to coffee, and people.

Kris checked this place out when stopping through Santa Cruz while galavanting through California per usual.  The life of a professor… The atmosphere at Verve is relaxing in true Californian style.  Plenty of natural light and wood and metal decor reminiscent of Urban Outfitters in its layout.  The shop is located only a couple of blocks from the Pacific Ocean, which undoubtedly adds to the tranquil feel.

The beans are roasted next door in their own facility – it appears they also sell wholesale across the country. Check out their website to make sure. Verve is among the most raved about roasters in the continental US and their baristas are talented enough to consistently make a splash at the annual SCAA barista competitions.  Unfortunately for Kris, during his visit the top baristas were actually in Houston competing in the SCAA annual competition on the national stage.  The staff are super fun and friendly and the wifi is very, very free.

Two paws up for this place.  We look forward to continuing to sample their coffee throughout 2012!

– Cafe Hound

Cafe Hounding: Echo Coffee

Echo Coffee
2902 N 68th St, Ste 135
Scottsdale, AZ 85251
Phone: (480) 422 4081

http://www.echocoffee.com
Groovy spot in Phoenix suburbs.

Kris visited this spot in December 2011 and noted that they roast coffee on site every other day in small batches.  Echo, owned by Steve Belt, opened in mid-2010 by the inspired graduate of Tempe, Arizona’s major university, Arizona State University.

Steve chatted briefly with Kris while roasting beans and briefly mentioned his origins from Portland, Oregon.  With a modern, high-ceiling, loft-like layout and a good selection of pastries – Echo is a good place to set up shop, use the free wifi, and get on with life over a delicious cup of Papua New Guinea, Cameroon, and Kenyan coffees sourced from a local importer who claims the beans are “carbon neutral.”

Make sure to check this place out if you’re stopping through!

– Cafe Hound

Market News: Crop Fears Drive Kenyan Coffee Prices

Source: Agrimoney.com

The coffee industry has been experiencing incredible upward pressures on ‘C Grade’ prices over the past year.  The specialty coffee market is facing even more acute pressures as demand surges and supply is scarce.  Nairobi’s Coffee Exchange illustrates the scenario playing out in specialty coffee hotspots globally with the recent sale of one 340kg lot of premium AA for $1,011 per 50kg bag (approximately US$9.20/lb) in country! Applying standard export mark-up premiums to such a large purchase, assuming a US specialty coffee buyer was interested, could fetch anywhere between $30-60 a pound for this same coffee by the time it retailed in the United States.

Agrimoney Article Begins:

Could coffee become more valuable than your average base metal?

It is beginning to look that way – at least for top quality arabica beans in Kenya, where dry weather has dashed hopes of a production rise this season.

A lot of premium AA grade coffee sold at the Nairobi Coffee Exchange on Tuesday for $1,011 per 50kg bag, 40% higher than it was achieving last month.

The 340kg lot originated from a central Kenyan growers co-operative, Kiomothai, and was bought by East African specialist C Dormans, which sells to foreign markets besides running a chain of Kenyan coffee shops.

Dornams paid the equivalent of more than $20,000 tonne, making the coffee more than twice as expensive as copper, and approaching the levels that the likes of aluminium, nickel and tin trade at.

‘Outlook robust’

The price reflected the dearth of high quality beans for sale, Daniel Mbithi, a Nairobi Coffee Exchange official, said.

“There is no coffee and the market is grabbing the few available offers,” he told Reuters, the news agency, adding that “the price outlook remains robust going into the coming weeks”.

“Supplies remain tight.”

Production downgrade

Kenya, unlike some other African countries, has suffered poor coffee growing weather with unusually late and heavy rains early in 2010 damaging flowering before dry conditions later in the year damaging yields of fruit which did set.

The Kenya Coffee Board on Monday cut to 40,000 tonnes its forecast for the country’s coffee output in 2010-11, from a previous forecast of 49,000-55,000 tonnes, and leaving the crop on track to fall short of the previous season’s output of 45,000 tonnes.

The influential International Coffee Organisation last week lifted its estimate for world coffee production this season citing better weather in many major African producing nations, with the likes of Ethiopia, Tanzania and Uganda enjoying improved conditions.

In New York, arabica futures for March delivery stood 1.0% higher at 234.60 cents a pound, equivalent to $5,172 a tonne, at 11:45 GMT