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cranefallesen60-blog · 6 years ago

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The 2-Minute Rule for it jobs

In many circumstances, the sufferer need to pay the cybercriminal inside of a set period of time o… little bit.ly/2DmeXWP pic.twitter.com/uQcl8gDMOr Ken Roberts became the team's promoter, and afterwards their basic supervisor, when no other Associates would do the job Together with the band on account of their erratic gig attendance record.[fourteen] In January 1975, the band booked itself at Radio Metropolis Songs Corridor in New York. The famed audio hall was only one-eighth occupied, and Stone and corporation needed to scrape together cash to return home.[15] Adhering to the Radio Metropolis engagement, the band was dissolved.[15] From The instant the team began touring following the achievements of Dance for the Songs, The Household Stone drew praise for his or her explosive live present, which captivated equal components black and white admirers. Share your understanding of this merchandise with other clients... Be the 1st to jot down a review Search for more products in a similar classification as this item: With RedSeal’s network modeling and threat scoring System, you’re ready to comprehend the condition of your community, measure electronic resilience, confirm compliance, and speed up incident investigation. The whole world of Sly Cooper is really a Variation of the actual globe that is certainly populated by anthropomorphic animals, with film noir and comic guide motifs. The main focus from the Tale is of Sly Cooper, a younger Grownup raccoon and the latest descendant in a very line of grasp intruders who move down their skilled techniques from era to generation using the "Thievius Raccoonus," a book which has many of the Cooper spouse and children's insider secrets and tricks. When the Cooper household has accrued an enormous amount of wealth through their thieving approaches, Sly areas increased price on his friendship with his two associates, Bentley, a turtle and also the brains of the gang, and Murray, a hippo who acts as being the brawn and also the getaway driver in the crew van. Perspective facts • Sly Gittens @SlyGittens Nov 22 The vacations are the perfect time for purchasers to hunt for a fantastic offer. It is also a major prospect for lousy actors to scam customers.⠀ In this article he remaining the stage immediately after indicating for the audience that "when waking up this early morning he realized he was outdated, and so he required to have a split now". He did the identical yet again at some point later, doing with the North Sea Jazz Pageant. Individuals serious about this work might be suitable for civilian employment, once the Army, by enrolling in the military PaYS program. The PaYS method is a recruitment possibility that assures a task job interview with military services friendly businesses that are searhing for skilled and educated Veterans to affix their Business. Find out more about the military PaYS Application at . Netsweeper is the initial Web content material filtering company to produce and utilize a form of hybrid “AI” (Synthetic Intelligence) technology to scan written content, assign content material to classes, and update its filter process without human intervention in serious-time. Direct With Knowledge : Data is definitely the cornerstone for fulfillment inside the electronic era. We help you unlock value out of your details for aggressive edge. 1. Find 'Equipment' with the prime menu within your browser and afterwards select 'Online choices', then click on the 'Privacy' tab 2. Be sure that your Privacy stage is ready to Medium or down below, which will enable cookies with your browser three. Configurations higher than Medium will disable cookies By the mid-nineteen seventies, Stone's drug complications and erratic actions successfully ended the group, leaving him to file numerous unsuccessful solo albums. In 1993, he was inducted to the Rock and Roll Corridor of Fame like a member with the group.[2] The "Web of Issues," or World-wide-web-linked products, has become A serious advancement in the knowledge technology industry the same way cell apps had been a number of years back.

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easyfoodnetwork · 5 years ago

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Instacart Is Suing Uber Over Its New Grocery Delivery Service

Photo: Tada Images/Shutterstock

Plus, KFC debuts plant-based fried chicken in California, and more news to start your day

Instacart filed a lawsuit against Uber’s rival grocery delivery service for alleged IP theft

Instacart is suing Cornershop, a rival grocery delivery service majority owned by Uber, for allegedly stealing its product images, descriptions, and pricing data in what amounts to intellectual property theft, the Information reports.

In a blog post, Instacart writes that the company has invested “tens of millions of dollars and a tireless amount of effort” to build its extensive grocery catalog, which it describes as “the world’s largest and most comprehensive” and a key to Instacart’s success. In the suit (available here via Axios), Instacart accuses Cornershop of stealing its copyrighted images, modifying file names to try to conceal the true ownership of those images, and recruiting engineers experienced in scraping data for this strategic effort.

“While we welcome competition and innovation, what Cornershop is doing is illegal,” writes Instacart, also noting that it had sent a cease and desist that Cornershop allegedly failed to heed.

In response, Uber shared the following statement with the Financial Times, Engadget, and other outlets: “Instacart is facing a new challenge in the US from a Chilean upstart, and it’s unfortunate that their first move is litigation instead of competition.” Cornershop, one of the largest delivery apps in Latin America, was acquired by Uber last year in an effort to bolster business outside of the company’s core ride-hailing service — an initiative that has become more urgent during the pandemic, as rideshares fall, while grocery delivery sees huge demand.

And in other news…

Target and the CVS are the latest major retail chains to require customers to wear face masks, following the likes of Walmart and Costco. [NPR]

Fast-food restaurant sales have just about returned to normal after the initial few months of the pandemic. [Restaurant Business]

KFC is rolling out its test of plant-based fried chicken to about 50 locations in California next week. The meatless product was originally unveiled in Atlanta last August, attracting lines around the building in the wake of the chicken sandwich wars. Suddenly it feels like 2019 again? [CNN]

Five handy takeaways from the USDA’s new dietary guidelines advisory report, which will inform the next five years of federal dietary guidance (spoiler alert: less booze and sugar). [The Counter]

Cameron Diaz’s new “clean” natural wine is apparently not actually all that clean. [SF Chronicle]

• All AM Intel Coverage [E]

from Eater - All https://ift.tt/3fEyML3 https://ift.tt/32ulsoz

Photo: Tada Images/Shutterstock

Plus, KFC debuts plant-based fried chicken in California, and more news to start your day

Instacart filed a lawsuit against Uber’s rival grocery delivery service for alleged IP theft

“While we welcome competition and innovation, what Cornershop is doing is illegal,” writes Instacart, also noting that it had sent a cease and desist that Cornershop allegedly failed to heed.

And in other news…

Target and the CVS are the latest major retail chains to require customers to wear face masks, following the likes of Walmart and Costco. [NPR]

Fast-food restaurant sales have just about returned to normal after the initial few months of the pandemic. [Restaurant Business]

Five handy takeaways from the USDA’s new dietary guidelines advisory report, which will inform the next five years of federal dietary guidance (spoiler alert: less booze and sugar). [The Counter]

Cameron Diaz’s new “clean” natural wine is apparently not actually all that clean. [SF Chronicle]

• All AM Intel Coverage [E]

from Eater - All https://ift.tt/3fEyML3 via Blogger https://ift.tt/2ZDJcoL

#Blogger #cooking #Eater #food #recipes

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herokita · 5 years ago

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What are your competitors prioritizing as we head toward 2020? The Upwork 100 is a quarterly index that ranks the top 100 skills—skills that have grown quickly and experienced a high level of demand on Upwork in Q3 of 2019. The list: Sheds light on current trends in the independent labor market and tech industry Serves as a barometer of the skills businesses are looking (and competing) for Indicates the most in-demand skills provided by independent professionals The Upwork 100 balances real-time insights with consistent patterns based on real work that’s been completed. Analyzing the results, Upwork Chief Economist Adam Ozimek, PhD, highlighted the following three trends from the list: 1. U.S. workers are in demand around the world U.S.-based freelancers work with businesses around the world. While U.S. companies lead demand, 38 percent of projects for the Top 100 skills are being hired by non-U.S. companies such as Canada, United Kingdom (UK), Australia, India, Israel, Germany, Singapore, United Arab Emirates (UAE), and China. 2. Average rates for the Top 100 skills are higher than what the majority of workers in the U.S. economy earn per hour The average hourly rate for the Top 100 skills in Q3 is $43.72. This is more per hour than 88 percent of U.S. workers1 and higher than the median hourly rate for freelancers doing skilled services overall ($28 per hour). 3. Fortune 500 companies across a range of industries leverage independent talent “[Our] data shows that a diverse range of industries are leveraging independent professionals to access the skills they need, when they need them,” said Dr. Ozimek. “More than 30 percent of the Fortune 500 use Upwork today, and we expect that number to increase.” Click for larger version. For a more detailed look at these trends, check out the press release. The Upwork 100: Q3 2019 .NET Core TypeScript Landing pages eBooks Android Electronic design Presentation Sketch Research Technical recruiter Bank reconciliation Slack Google Tag Manager Sourcing Amazon Web Services (AWS) Video post-editing LinkedIn recruiting Data visualization Interviewing Interior design System administration Kubernetes Data scraping Technical documentation Project scheduling Adobe Premiere Pro 2D animation Firebase Customer retention marketing Salesforce Lightning DevOps Selenium Accounts receivable management Microsoft Windows Azure Database design AutoCAD Usability testing C development Accounts payable management Lead generation Product descriptions Certified Public Accountant (CPA) Circuit design eLearning Google Docs Docker GitHub Redux for JavaScript Business planning Data entry Motion graphics Infographics Architecture ASP.NET Asana Instagram marketing Shopify development Search Engine Optimization (SEO) Architectural rendering PostgreSQL administration Salesforce app development Python Magento 2 Link building MongoDB Bootstrap SEO writing Web scraping Animation Network security 3D rendering Agile project management Administrative support Data mining Internet research English grammar Squarespace Elasticsearch Startup consulting AWS Lambda Branding Media relations Appointment setting 3D design Bookkeeping Romance writing Budgeting and forecasting Product design Financial accounting Adobe After Effects Zendesk Accounting Virtual assistant Google Cloud Platform Postgre SQL programming Tax preparation Embedded systems Audio editing Google Analytics Amazon S3 The goal of the Upwork 100 is to highlight the fastest-growing skills that also have a consistent and substantial level of demand. To do this, using data sourced from the Upwork.com database, we first limit the analysis to skills that are the most in-demand by including only skills that have been in the top 500 on Upwork.com in terms of freelancer billings for the past four complete quarters. Within that, we then rank the top 100 fastest-growing skills based on year-over-year growth rates in freelancer billings for Q3 2019 versus Q3 2018. The next Upwork 100 report will be released winter 2020. 1 Economic Policy Institute. 2019. Current Population Survey Extracts, Version 0.6.13. HEROKITA.com | Digital Talents On Demand Source link

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shirlleycoyle · 5 years ago

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‘You Couldn’t Swipe Fast Enough’: How the Pandemic Devastated Instacart Workers

This article appears in VICE Magazine's Algorithms issue, which investigates the rules that govern our society, and what happens when they're broken.

In 2019, Lisa, a single mother, lost her job as the media relations director at a firm in Nashville, Tennessee, moved south to her hometown Jacksonville, Florida, and signed up to deliver groceries for Instacart.

With the $1,000 she earned each week shuttling groceries from supermarkets to her clients, she could make payments on her $2,300 a month mortgage, and car and utility bills, with enough left over to order novels from Amazon and household gadgets from QVC.

The arrival of COVID-19 pandemic in Florida changed all of that. In May, Lisa’s weekly earnings hurtled downward from $1000 to $500 to $90 (recovering partially in June and July). She spent her days glued to her phone, refreshing the Instacart app for hours. Each time a new batch, or set of delivery orders, would flash on her phone screen, someone else in her area would snatch them up in a matter of seconds, often before she had time to react.

The pandemic had prompted more households than ever before to sign up for Instacart’s grocery delivery service, making it profitable for the first time since its founding in 2012, but Lisa—a pseudonym, so she could speak candidly about her working conditions—was barely scraping by, and had picked up a second part time job at a local Publix grocery store to make ends meet.

“I had to be refreshing my phone all the time, sometimes waiting for three hours that I wasn’t getting paid [for], before I got a good order,” she told Motherboard. “You have to be attached to your phone. I couldn’t do anything else.”

In late April, the San Francisco-based start-up announced it had hired 300,000 new gig workers to meet rising demand for grocery delivery during the first two months of the pandemic, and had plans to bring on an additional 200,000 workers. The hiring boom in on-demand grocery delivery across the country wasn't limited to Instacart. The Target-owned delivery platform, Shipt, hired tens of thousands of shoppers during the pandemic. As of early August, the delivery service Amazon Flex was actively recruiting in 17 cities. Almost overnight, hundreds of thousands of laid off or underemployed Americans had transformed into grocery delivery gig workers.

But the demand for groceries didn’t keep pace with the number of Americans flocking to grocery and food delivery apps for available work, and workers found themselves competing against each other while refreshing their phones into oblivion. If heartwarming stories of mutual aid, where communities have banded together to care for, shelter, and feed one another during the pandemic have shown the power of solidarity in the absence of a strong social safety net, then the hundreds of thousands of desperate Americans gravitating towards gig work, and competing under and against a regularly shifting algorithm for an elusive supply of grocery delivery orders, paint a less inspiring picture.

A spokesperson for Instacart told Motherboard that shopper earnings have actually increased from their pre-pandemic levels, based on customer and shopper marketplace data. "In the wake of COVID-19, shopper earnings have increased by as much as 60% and shopper NPS – a measure of shopper happiness and overall sentiment – is at the highest level in company history," the spokesperson said.

"To further support this community, our team has introduced new recognition programs, product features, shopper perks, and resources to enhance the shopper experience," they continued. "We’ll continue to invest in this important community as we focus on delivering the best possible experience for all shoppers across North America.”

In early 2020, Lisa ranked near the top of 390 Instacart shoppers in the Jacksonville Beaches metro area, a sprawling island community to the north of Florida’s largest city. But during the pandemic, she says the app had hired an additional 900 shoppers in her area.

Adding to her difficulties, in March, Instacart had suspended its algorithmic ranking system, which rewards gig workers with the highest customer ratings by offering them the most lucrative orders first. The company explained in an announcement that, due to the “national state of emergency, all ratings below 5 stars” would be “forgiven.” (As of July, Instacart had reinstated the ranking system.) For veteran Instacart workers like Lisa, who had worked hard to achieve near-perfect ratings over hundreds of orders, this meant drastically lower earnings. As another Instacart shopper explained to me, the difference between a perfect 5 star average rating and a 4.97 star average rating can mean everything for access to the most lucrative orders under normal circumstances.

At the same time, in Instacart forums on Facebook, rumors circulated widely that the decline of work was primarily linked to the rise of third-party bots which snatched up orders quicker than a human could, and sold them to shoppers willing to pay a high price to game the system.

“When coronavirus got bad here in May, third-party bots popped up. We ran into them at stores. You could tell who they were because they didn’t know the layout of the stores. One guy bragged about it to me in an Aldi grocery store. He was a bot,” Lisa said. (Shoppers often refer to other shoppers who pay for automated tools as “bots.”)

Some of the rumors were blatantly racist, accusing undocumented shoppers of using the bots to game the system. Motherboard viewed posts on Instacart Facebook groups that linked the bots to rings of non-English-speaking, Latinx immigrants who shopped in large groups.

Multiple opportunists had developed bots that gave gig workers who paid, in some cases, thousands of dollars, the advantage of being able to scoop up orders faster than those who didn’t. But skeptical Instacart shoppers say the bots were mostly scams, the rumors were racist, and bots were not responsible for a significant portion of competition for orders—Instacart’s massive hiring spree was.

“Bot services have existed for Instacart for nearly two years, but bots have never been nearly as popular or common as many shoppers believe they are,” Heidi Carrico, an Instacart shopper and organizer with Gig Workers Collective, said. “The true problem is that Instacart hired 500,000 new Shoppers, while demand and order volume has declined from its peak at the beginning of the pandemic, creating a dynamic of fierce competition for orders.”

Instacart has claimed that the bots violate the companies’ trademarks and terms of service, and sent cease-and-desist letters to third-parties. In late July, Instacart sent out an email informing shoppers that it has partnered with a security platform “to develop a bot bounty program, specifically built to combat bots on the Instacart platform,” and promised to deactivate any shoppers who used third-party apps.

Veteran Instacart shoppers have noted that the pandemic is not the first time they’ve dealt with saturated markets and times when it’s difficult to get orders. Most years, usually in the fall, for reasons not entirely clear, orders slow down, competition rises, and Instacart slashes pay, prompting some contingent of shoppers to quit working on the app.

“Things have started to get better,” Lisa told Motherboard in July. “It’s a combo effect. The bots are being handled and slowly but surely the oversaturation is starting to come down. All of these people who signed up to delivery groceries thought it was easy. Now we’re back to our rating system and that’s how we get batches.”

Though gig workers that Motherboard spoke to said their earnings recovered partially in June and July, suggesting that some of the new hires quit working on Instacart once restaurants and retail stores reopened, longtime workers say the number of shoppers are still above pre-pandemic levels and wages remain down.

Bill, an Instacart shopper in Houston, originally started working on the app nearly two years ago to supplement his income (he previously owned a food truck), and was finding it hard to quit gig work, until the pandemic hit and helped him with the decision.

“I was making $700 to $800 a week, then things just went bonkers. The orders were coming in so fast, you couldn’t swipe fast enough. I don’t know how a human can react that fast. Suddenly I was making $60 a week,” Bill said. “I was a mess. It used to be like anything else: ‘Doing this sucks but I know I can get batches, and I know I can make at least $500.’ All of the sudden it just disappears. Your income just goes. It’s very stressful.”

While many gig workers who provide services that involve close human interaction (such as Uber and Lyft drivers, TaskRabbit workers who enter client’s homes, and Wag and Rover dog walkers) have seen their income plunge, as the New York Times recently reported, on-demand grocery delivery and food-delivery apps have boomed, making record profits. Experts say that though the influx of grocery delivery workers will likely fall as businesses reopen, many workers who sign up for gig economy apps as a temporary job end up staying much longer than they had planned, either because they can’t find more lucrative job opportunities or because making income on the app consumes so much time and leaves few hours of the day for job hunting.

“You notice people of all walks of life are out of work doing Instacart,” said Bill. “People who work in hospitality, restaurants, bars, and I don’t begrudge them. Everybody’s just trying to do the best for themselves. What sucks most is that it’s taken any hope of making money.”

During past economic crises laid off and unemployed workers have always gravitated to less secure forms of work—hustling to string jobs together. In fact, the emergence of platform gig economy companies grew out of the 2008 recession, a period of high unemployment and slow job growth. Gig economy start-ups Uber, Instacart, TaskRabbit, Lyft, Postmates, DoorDash, and Caviar were all founded in the span of four years, between 2008 and 2012.

“Gig work is often marketed as a solution to unemployment, or economic downturn. A lot of these gig economy jobs have low barriers to entry,” said Alexandrea Ravanelle, a professor of Sociology at the University of North Carolina at Chapel Hill who is leading a National Sciences Foundation-funded study on the impact of COVID-19 on gig workers. “During COVID-19, we’ve seen an influx of people turning to gig work as a social safety occupation of last resort.”

The companies marketed themselves as technological innovations that created millions of new jobs and allowed workers the opportunity and flexibility to pick their own hours and schedules free from the scrutiny of a boss. But the catch was that gig workers, as independent contractors, did not receive any of the typical benefits such as minimum wage guarantees, health insurance, overtime pay, and paid sick leave offered to employees.

Thus, critics of Uber and Instacart charge that their main contribution has been the creation of precarious, low-wage, dead-end jobs that offer no guarantee of job security or income—an unfortunate reality Instacart workers who’ve seen their earnings diminish overnight learned during the pandemic.

Marvin, a shopper who lives outside Huntsville, Alabama, took up Instacart in April 2019, for supplemental income. When he lost his job as a flight attendant last fall, it became a full time gig.

Marvin also saw his wages steadily decline during the pandemic. He was forced to dip into his savings, often spending 10 hours-day waiting in parking lots “listening to every song in the world” and refreshing his phone until orders came in. “No, I don’t enjoy sitting in my car for that long,” he told Motherboard. “I survived on a lot of Spam.”

At the same time, the number of Instacart shoppers in his metro area tripled from 40 to 120. (We know this because Instacart posts the number of active shoppers in each metro area on its app by rank.) “A lot of waitresses, waiters, teachers, housewives, and exotic dancers came out of the woodwork,” said Marvin, who has befriended many shoppers in the area.

Marvin, who is 28, says he cuts out the unpaid time he spends waiting by juggling Instacart work with less lucrative orders on DoorDash in his area, usually at fast food restaurants, which often pay less than $10. The goal is never to earn less than he spends on gas and the costs of maintaining his car.

On a day in late July, Marvin logged his order for Motherboard; he visited Kroger three times with trips interspersed to McDonald’s, Arby’s, and Chick-Fil-A, earning $99.33 in six hours, and sometimes traveling up to 17 miles to make a delivery.

“I try to fit in one or two DoorDash orders for every Instacart order. It doesn’t always work out that way but that’s what I try to do not to have any idle time,” Marvin said. “I’ll often pick up $5 orders from Taco Bell or McDonalds.”

For Instacart and other gig workers, learning to identify lucrative orders takes time and practice. Workers told Motherboard they tend to gravitate to the stores with layouts they know best, customers who’ve tipped and rated well in the past.

“Our ranking [and ability to get good orders] depends on what the customer rates. It’s solely up to them,” Lisa, the Instacart shopper in Florida, said. “We’re at their mercy. If they don’t like how something was bagged, they could give us a four. I had one lady say, 'I never give out a five star rating.' I don’t want to be dinged for that.”

Workers prefer orders with shorter distances, tending to avoid apartment buildings with long flights of stairs. Similarly, accepting orders with multiple repeat items from different customers like frozen pizzas, cat food, or bananas is easier than traversing back and forth in search of obscure products.

“At first it was taking me four minutes per item at my local Sprouts supermarket. Now it takes 30 seconds,” said Bill, the Instacart shopper in Houston. “You learn quickly that you make more money the faster you can complete an order.”

Now that Instacart has reinstated its ranking system, veteran shoppers say they hope to see their earnings increase, as they’re awarded more lucrative orders, while shoppers hired during the pandemic have to undergo the learning curve that they once did. Experts say that it’s difficult to know at this point how the surge of workers competing for gigs on food and grocery delivery apps will last; due to poor reporting systems, there aren’t reliable statistics on gig workers.

“The Great Recession brought about an economic contraction and lots of people took up gig work. It was hard for people to get back into jobs they once were in,” Ravanelle, the sociologist at UNC Chapel Hill said. “We’ll probably see something similar in terms of COVID. We’ll feel this for a very long time.”

Follow Lauren Gurley on Twitter.

‘You Couldn’t Swipe Fast Enough’: How the Pandemic Devastated Instacart Workers syndicated from https://triviaqaweb.wordpress.com/feed/

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syntellisolutionsinc · 5 years ago

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Using Big Data to Attract and Retain the Digital Banking Customer

As customers begin to use more online banking services, their expectations have increased and changed. In years past, customers were happy with basic online account management that let them view details for existing accounts.

Now, customers want to have the ability to send money to a variety of accounts, access credit card rewards, and customize their account settings from anywhere. They look for a bank that has the features they need and the customer service they deserve, especially as they travel and spend online in more ways than before.

As big data in digital banking gets smarter and faster, banks are brainstorming more ways to market their services and help their customers make better financial choices. Banks can increase new sign-ups and customer retention by investing in engaging, relevant features that take advantage of the wealth of data available on consumers.

What Are the Benefits of Digital Banking?

Customers have a wide range of needs depending on the services they’re accessing, their lifestyles, and the technology available to them. Digital banking reduces in-person staffing and customer service costs and gives customers easier access to payment systems.

The added convenience of digital banking makes it easier for customers to pay their bills on-time whenever they remember, instead of dealing with paper forms or phone calls. This can reduce late payments and fees, boosting customer satisfaction and trust.

1. Reducing Fraud

Customers trust that banks will protect their accounts, and banks can improve and advertise their security efforts to attract and retain customers. In recent years, big data has become a key part of modern fraud detection algorithms. By using machine learning to teach AI programs about customer trends scraped from big data, banks can detect and flag transactions that are unusual and likely to be fraudulent.

Customers don’t like dealing with false alarms, so banks have to get the financial services analytics company to keep false positives to a minimum. When customers feel their account information is securely protected, they are less likely to close credit cards or take other actions to reduce their reliance on a bank.

2. Customer Shopping Habits

The link between consumers’ habits and their banking needs is a critical example of the relationship between digital banking and big data. Groceries, gas, bills, and other expenses reveal even more about a customer’s life than their general demographic features.

Many banks already track customer sales data and use that to provide better recommendations for financial services. However, big data can supplement this information and provide more insight into what customers buy using cash or competitors’ credit cards.

With data analytics in financial services, there is huge potential for customized marketing campaigns based on customer shopping habits.

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Individuals with high income and more discretionary spending can be sent emails advertising a prestigious credit card, while individuals who aren’t using their cards often can be sent emails with special offers encouraging them to use their cards more.

3. Solutions for Every Location and Device

Even tech-savvy customers who predominantly use mobile apps and websites will occasionally need in-person services. Currency exchange services, ATMs, and other cash needs must be relatively nearby for a customer to continue using a particular bank as their primary provider.

Big data strategies for financial services can inform company decisions about where to build brick-and-mortar locations. If a majority of customers live in the suburbs but work and shop in the city, then banks may find that small downtown locations are just as valuable as suburban ones.

Big data can also provide insights on the types of devices customers own and which devices they use to access mobile services and websites. By investigating which devices customers are and aren’t using to access services, banks can discover which versions of their apps are worth investing more in.

4. Better Credit Card Rewards

Credit card points and rewards have been a part of banking services for years, but they are still not used as frequently as they could be, even as online shopping and mobile app usage have become more popular. Smarter digital banking with big data must include tangible perks for customers to increase perceived and actual value of services.

Banks can also use big data to tweak their cash back percentages and other reward criteria to meet the needs of their target demographic. For example, young urban professionals without cars won’t benefit from bonus points on gas purchases, so banks need to offer a different perk to attract that demographic.

13 Digital Transformation Opportunities for Financial Services

Financial institutions are a part of everyday life in the US but recruiting and retaining customers isn’t easy. Satisfactory customer experience and customer trust are crucial to banking, investing, and loan services, especially when there are so many competitors nationwide. Read More

5. Predicting Customer Questions

The use of data analytics in banking can provide insights as to what services customers will need next, which can also predict the questions they have. Banks can use cutting-edge data mining to predict questions customers are likely to have and even point them toward relevant written FAQ pages while customers are using the service.

By predicting customers’ questions and addressing them in advance, banks can reduce the amount of resources they spend providing phone- and chat-based customer service. It can also improve customer satisfaction by sharply reducing or eliminating the amount of time customers spend waiting for help.

6. Mortgage Marketing

Young people tend to put off buying their first home until after age 35, but this trend can still vary based on economic factors. Big data can inform financial institutions of which customers are actually searching for homes, regardless of age and other factors.

Since customers don’t want to receive too many marketing emails or in-app notifications for offers, it makes sense for banks to use big data to only show services likely to be of interest to a particular customer. However, existing customers may turn to another lender for their mortgage needs unless they have a trusting relationship with their current bank and have a reason to believe that their current bank provides the best service and value.

This requires proactive and carefully-tailored marketing that advertises the best rates and loan options to customers whose big data suggests they are ready. Marketing can be tailored even further to educate first-time homebuyers, who may have lower financial literacy or knowledge of mortgages simply because they haven’t experienced the process yet.

7. Smarter and Forward-Thinking Digital Banking

Getting the most out of big data requires a multi-faceted approach and a complex data analytics system. All sizes and types of financial institutions have unique needs, and data science experts can provide customized solutions that incorporate data safely and securely.

Syntelli Solutions is a leader in modern big data, AI, and predictive analytics for financial services and other industries. We have a track record of success with small and large clients alike, with projects ranging from basic open source migration to in-depth reworking of CRM systems. Contact us today to learn more about our team and services.

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The post Using Big Data to Attract and Retain the Digital Banking Customer appeared first on Syntelli Solutions Inc..

https://www.syntelli.com/using-big-data-attract-retain-digital-banking-customer

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mobileapp14 · 2 years ago

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Recruitment Mobile App Data Scraping: A Comprehensive How-To Guide

Aug 14, 2023

Mobile App Scraping' Recruitment Mobile App Data Scraping Services revolutionize how organizations streamline recruitment processes. Our advanced scraping technology and expertise enable us to extract valuable data from various recruitment mobile apps, job boards, and career mobile apps. With our service, you can effortlessly gather comprehensive candidate profiles, job listings, skills data, and other relevant information to fuel your recruitment strategies. Boost your recruitment efficiency, access top talent, and make informed hiring decisions by leveraging our Recruitment Mobile App Data Scraping Services.

Which Recruitment Mobile Apps And Job Boards Can Be Included In Mobile App Scraping’ Data Scraping Process?

Mobile App Scraping' Data Scraping process can include many widespread mobile recruitment apps and job boards. While the specific platforms can be customized to meet your requirements, here are some examples of commonly included sources:

LinkedIn: As a leading professional networking platform, LinkedIn offers various candidate profiles and job listings across various industries and roles.

Indeed: Known for its extensive job board, Indeed aggregates job postings from multiple sources, making it a valuable platform for data scraping.

Glassdoor: Glassdoor provides insights into company reviews, salary information, and job postings, making it a valuable source for employers and job seekers.

CareerBuilder: This widely used job board features various job opportunities from various industries and locations.

With its extensive reach, Monster offers a vast collection of job listings and resumes, making it a valuable platform for data scraping.

ZipRecruiter: ZipRecruiter is a popular job board that connects employers with job seekers across various industries and locations.

SimplyHired: Known for its user-friendly interface and comprehensive job search options, SimplyHired provides access to various job postings.

Careerjet: Careerjet is a global job search engine that aggregates job listings from various sources, making it a valuable platform for data scraping.

Naukri.com: A leading job portal in India, Naukri.com features an extensive database of job postings and resumes across diverse industries. It's important to note that the specific platforms and job boards included in the data scraping process can be tailored to your specific requirements and target audience. Mobile App Scraping' scraping service is flexible and adaptable to meet your unique needs in the recruitment industry.

What Types Of Data Can Be Extracted From Recruitment Mobile Apps, Such As Candidate Profiles, Job Descriptions, Or Company Information?

Mobile App Scraping' Recruitment Mobile App Data Scraping service can extract various data types from mobile recruitment apps. The specific data that can be extracted depends on the features and information available within each app. Here are some common types of data that can be extracted:

Candidate Profiles: This includes information such as candidate names, contact details, work experience, education, skills, certifications, and other relevant details provided by candidates in their profiles.

Job Descriptions: Extracting data from job listings involves gathering details like job titles, descriptions, responsibilities, qualifications, experience requirements, and any additional information provided by employers or recruiters.

Company Information: The scraping service can extract data related to companies posting job vacancies, including company names, locations, descriptions, industry, size, and other relevant details.

Job Locations: This involves extracting data on the geographic locations of job vacancies, providing insights into regional job markets and opportunities.

Salary Information: Extracting salary data can include details on salary ranges, compensation packages, bonuses, and other related information mentioned in job listings or candidate profiles.

Application Deadlines: The scraping service can gather data on application deadlines or closing dates for job postings, enabling timely application submissions.

Industry and Job Categories: The scraping service can categorize job listings based on specific industries, sectors, or job categories, providing insights into market trends and job distribution.

Skills and Keywords: Extracting data on skills or keywords mentioned in job descriptions or candidate profiles can help identify sought-after skills and industry trends.

Application Process Details: This involves extracting data related to the application process, including instructions, required documents, and any specific application procedures mentioned in job listings.

It's important to note that data availability and structure may vary across recruitment mobile apps. Mobile App Scraping' scraping service can be tailored to target specific data points based on your requirements, ensuring you receive the most relevant and valuable information for your recruitment processes.

Can The Scraped Data By Mobile App Scraping Be Filtered Based On Specific Criteria, Such As Location, Industry, Or Experience Level?

Yes, Mobile App Scraping can filter the scraped data based on specific criteria per your requirements. We understand that filtering the data lets you focus on the most relevant information for your recruitment processes. Here's how we can incorporate filtering into the data scraping service:

Location: The scraped data can be filtered based on specific locations or geographic regions. Whether you are looking to target candidates or job postings within a particular city, state, or country, we can customize the scraping process to extract data relevant to those locations.

Industry: If you are interested in specific industries or sectors, Mobile App Scraping can implement filters to extract data only from those industries. This lets you narrow your focus and concentrate on candidates or job opportunities within your desired sectors.

Experience Level: Filtering the data based on experience levels, such as entry-level, mid-level, or senior-level positions, is possible. This helps in identifying candidates or job listings suitable for specific experience requirements.

Job Category or Function: The scraped data can be filtered based on job categories or functions. Whether you are interested in specific roles like marketing, finance, IT, or engineering, we can customize the scraping service to extract data about those job categories.

Keywords or Skills: Mobile App Scraping can incorporate filters to extract data based on specific keywords or skills mentioned in candidate profiles or job descriptions. This allows you to target candidates with specific qualifications or competencies relevant to your hiring needs.

By implementing these filters, Mobile App Scraping ensures that the scraped data is refined and tailored to meet your specific criteria. Providing highly targeted information that aligns with your recruitment objectives saves you time and effort.

Is The Scraped Data Provided In A Structured Format By Mobile App Scraping That Can Be Easily Integrated Into Existing Recruitment Systems?

Yes, Mobile App Scraping provides scraped data in a structured format that can be easily integrated into existing recruitment systems. We understand the importance of seamless integration and compatibility with your systems and processes. Here's how we ensure the data is delivered in a structured and usable format:

Data Fields: We organize the scraped data into specific fields or columns based on the relevant information extracted. For example, candidate profiles may include names, contact details, work experience, education, skills, etc. Job listings may have fields such as job title, description, location, salary, and company details. Structuring the data into well-defined fields makes it easier to map and integrate it into your existing systems.

Customization: Mobile App Scraping can customize the structure and format of the scraped data to match the requirements of your recruitment systems. We can align the field names, data types, and formatting conventions to ensure a seamless integration experience.

Mapping Guidelines: If you provide us with your existing recruitment systems' specifications or mapping guidelines, we can tailor the scraped data accordingly. This ensures that the data is delivered in a compatible and consistent format with your system's data model.

By delivering the scraped data in a structured format and accommodating customization based on your requirements, Mobile App Scraping ensures a smooth integration process, allowing you to seamlessly leverage the extracted data within your existing recruitment systems.

How Does Mobile App Scraping Handle Data Privacy And Security Concerns While Scraping Recruitment Mobile App Data?

At Mobile App Scraping, we prioritize data privacy and security while scraping recruitment mobile app data. We understand the sensitivity of the information involved and take the following measures to ensure the confidentiality and security of the data:

Compliance with Data Protection Regulations: We adhere to applicable data protection regulations, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). We ensure that our data scraping processes align with legal requirements to safeguard personal and sensitive information.

Consent and Authorization: Before initiating the data scraping process, we ensure that proper consent and authorization are obtained, adhering to mobile recruitment apps' and job boards' terms and conditions. We respect the privacy policies and guidelines of the platforms and operate within their specified limits.

Data Encryption: We employ robust encryption protocols and secure data transfer mechanisms to protect the data in transit. This ensures the scraped data remains secure and protected from unauthorized access or interception.

Restricted Access and Confidentiality: Mobile App Scraping maintains strict access controls and follows strict confidentiality policies. Only authorized personnel with a need-to-know basis have access to the scraped data, and we ensure that our employees adhere to strict non-disclosure agreements.

Data Anonymization: In cases where personal information needs to be processed, we employ data anonymization techniques to remove identifiable or sensitive information. This ensures that the data cannot be linked back to specific individuals, further protecting privacy.

Secure Infrastructure: We maintain a secure infrastructure with robust firewalls, intrusion detection systems, and security protocols to safeguard against unauthorized access, data breaches, or cyber threats.

Data Retention: Mobile App Scraping retains the scraped data for only the necessary duration required to fulfill the agreed-upon services. Once the retention period expires, we securely dispose of the data in compliance with data protection regulations.

Confidentiality Agreements: We are open to signing or non-disclosure agreements with our clients to provide additional assurance regarding data privacy and security.

At Mobile App Scraping, we understand the critical importance of data privacy and security. By implementing stringent measures and best practices, we ensure your data remains confidential, secure, and protected throughout the data scraping process.

What Are The Benefits Of Hiring Recruitment Mobile App Data Scraping From Mobile App Scraping?

Hiring Mobile App Scraping for Recruitment Mobile App Data Scraping offers several benefits that can significantly enhance your recruitment processes. Here are some key advantages:

Comprehensive Data Acquisition: Mobile App Scraping' data scraping service enables you to gather comprehensive and up-to-date data from various recruitment mobile apps and job boards. This broadens your access to potential candidates, job listings, and industry insights, giving you a competitive edge in talent acquisition.

Time and Cost Savings: Manual data collection from multiple recruitment platforms can be time-consuming and labor-intensive. By outsourcing data scraping to Mobile App Scraping, you save valuable time and resources, allowing your team to focus on more strategic aspects of recruitment.

Real-time and Accurate Data: Our advanced scraping technology ensures you receive real-time and accurate data, reflecting the latest candidate profiles, job listings, and other relevant information. This empowers you to make informed decisions based on current market trends and candidate availability.

Enhanced Candidate Sourcing: With access to a broader pool of candidate profiles, you can effectively identify and connect with top talent for your job vacancies. Mobile App Scraping' data scraping service allows you to filter candidates based on specific criteria such as skills, experience, and location, streamlining your candidate sourcing process.

Improved Recruitment Efficiency: Mobile App Scraping eliminates manual data entry and reduces human error by automating the data gathering process. This leads to improved efficiency in processing and managing large volumes of recruitment data.

Customization and Integration: Mobile App Scraping offers a customizable service tailored to your requirements. The scraped data can be provided in a structured format that seamlessly integrates into your existing recruitment systems, ensuring a smooth transition and utilization of the data.

Competitive Advantage: Accessing comprehensive and real-time recruitment data lets you stay ahead. You can identify emerging talent trends, gain insights into industry dynamics, and adapt your recruitment strategies accordingly, giving you a competitive advantage in attracting and hiring top candidates.

By leveraging Mobile App Scraping' Recruitment Mobile App Data Scraping service, you can streamline recruitment efforts, save time and resources, access a wider talent pool, and make data-driven decisions. Partner with Mobile App Scraping to unlock the full potential of data-driven recruitment and gain a competitive edge in the market.

Mobile App Scraping' Recruitment Mobile App Data Scraping service offers a powerful solution for enhancing recruitment processes. With our comprehensive data acquisition, real-time updates, and customization options, you can access many candidate profiles, job listings, and industry insights. By outsourcing your data scraping needs to Mobile App Scraping, you can save time, improve efficiency, and gain a competitive advantage in attracting top talent. Our commitment to data privacy and security ensures the confidentiality of your information throughout the scraping process. So, why wait? Take advantage of Mobile App Scraping' expertise and cutting-edge technology to revolutionize recruitment strategies. Contact us today to explore how our Recruitment Mobile App Data Scraping service can transform your talent acquisition efforts and drive your organization's success.

know more: https://www.mobileappscraping.com/recruitment-mobile-app-data-scraping.php

#RecruitmentAppDataScraping #extractmobileappdata #scrapedatafrommobileapp #scrapeRecuitmentmobiledata

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iwebscrapingblogs · 5 years ago

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Scrape Glassdoor Data

Glassdoor is amongst the fastest-growing recruiting and job websites. Glassdoor has an increasing database of lots of company reviews, salary reports, CEO approved ratings, interview questions and reviews, office photos, benefits reviews, and more. Not like other job websites, all the information is completely shared by people who know the company best, its employees.

Scrape Glassdoor Data

Companies like 3i Data Scraping provides the best Glassdoor web scraping services including the requirements to scrape job posting from Glassdoor, scraping Glassdoor reviews, and scrape glassdoor data. You will get the Glassdoor web scraping services in addition to all the recent jobs. No other website permits you to go through which companies are hiring, what actually loves the job or the interview as per the employees as well as how much you could earn. You can also use Glassdoor through the mobile app, including Android and iOS platforms.

#Glassdoor Data Scraping #glassdoor review #web scraping #data scraping #website data scraping #web data extraction #Web Data Mining #3idatascraping #usa #3idatascrapingservices #india #canada #jobpostingscraping #job posting data scraping #datamining #job post data extract

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omcik-blog · 8 years ago

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New Post has been published on OmCik

New Post has been published on http://omcik.com/hedge-funds-are-seeing-a-gold-rush-in-data-mining/

Hedge funds are seeing a gold rush in data mining

When Under Armour, the sportswear maker brought to prominence in Oliver Stone’s American football epic Any Given Sunday, reported its latest earnings in early August, it was an unpleasant surprise for many investors.

The company reported a second straight quarter of losses, cut its sales outlook for the rest of the year and announced a large restructuring programme that it warned would halve its operating profits in 2017. The shares tumbled almost 9 per cent on the day and have kept sagging since.

But for some hedge funds that were sold bespoke data on the company, the dismal results might not have been such a surprise. In recent years there has been a proliferation of new “alternative data vendors” that trawl through vast pools of digital information and sell it to investment groups desperate for an edge in markets.

These vendors often scoop up the digital “exhaust” that people, companies and countries throw out through the normal course of their business and turn it into valuable intelligence.

For example, hints of Under Armour’s downturn could have been detected in a decline in job listings on its website, the internal rating of its chief executive by employees on Glassdoor, the recruitment site, or a dip in the average price of clothes on its website. But this is just the tip of the alternative data iceberg, and investors are waking up to the fact.

Types of alternative data: 1. Website scraping

Many data vendors scrape public websites for information that might be valuable, ranging from downloads of apps and user reviews to what airlines and hotels are receiving bookings through Expedia and Priceline, for instance. Social media sites can also be scraped for hints on consumer views and trends.

“In order to generate sustained [returns] investors must embrace the task of acquiring, analysing and understanding the ever-growing data universe,” BlackRock said in a recent paper. “Those that fail to do so run the risk of falling behind in a rapidly changing investment landscape.”

Many of our online activities leave a digital fingerprint. Our mobile phones can be tracked, our emails scanned and our online purchases monitored. Companies release vast amounts of data on their websites and even local and national governments are digitising many aspects of their operations.

The vendors scrape this “big data” — for everything from geolocation details to consumer trends and sentiment analysis — and turn it into tradable signals. Investment groups have often looked outside traditional information sources such as economic data releases or earnings reports. Some now think this digital treasure trove can underpin the future of the money management industry.

However, there is disquiet over the unregulated nature of the industry, which Tabb Group estimates will double in size in the next five years to $400m in annual sales. Some fear information that may appear public may in fact be legally protected, while others worry that hedge funds signing deals for exclusive access to certain valuable data sets will open themselves up to close scrutiny in what is a legally grey area.

2. Credit card tracking

The most valuable seam of data for hedge funds is information that shows directly what consumers are spending money on, and credit card companies are the main gold mine. Although it only offers a partial view of sales trends, combined with other data sets it can offer vital insights.

“It’s a brave new world,” says Jonathan Streeter, a former federal prosecutor who led the insider trading case against Raj Rajaratnam, co-founder of the Galleon Group hedge fund. Mr Streeter is now a partner in New York at Dechert, a law firm with a large hedge fund client base, where he advises on what data sets are legal to purchase and use.

“I don’t know of a case that’s been brought, but everyone anticipates that there will be one soon and [prosecutors] would like to bring one,” Mr Streeter says. “This is a hot topic. I get a lot of calls from clients.”

This year, a senior executive from the family investment office of Steve Cohen, the billionaire whose SAC Capital Advisors hedge fund was shut down by federal authorities in 2013 over insider trading, was praising “big data” as its new edge over the market.

Speaking at a conference on alternative investments at the London School of Economics, Matthew Granade, Point72’s chief market intelligence officer, bragged that they scrutinise 80m credit card transactions every day. Coupled with satellite images that can scan car parks and geolocation data from mobile phones to show how many people are visiting various stores, the investment group can get a real-time idea of how companies are doing, long before their results are released.

One LSE student asked how all this data could help Point72 if everyone had access to the same information. The answer was exclusivity agreements, Mr Granade said: “The great thing about this area is you can arrange deals where you are the only ones who get it.”

3. Geolocation

Smartphones are equipped with location services that allow us to use map or weather functions, but also let mobile carriers know where we are at any time. That data can be valuable to see what shops, hotels or restaurants we are visiting, a gold mine for hedge funds looking for clues on consumer trends.

Hedge funds have always sought an advantage, whether by taking executives out for lavish dinners to glean a sense of how their business was doing, or hiring pollsters to conduct their own surveys ahead of elections or referendums. Increased regulation and a crackdown on insider trading have reduced some of those avenues, but alternative data can offer different routes.

The biggest challenge for investors is the sheer extent of how much digital information is generated every day. There are more than 1bn websites with more than 10tn individual web pages, with 500 exabytes (or 500bn gigabytes) of data, according to Deutsche Bank. And more than 100m websites are added to the internet every year.

To help navigate through the morass, an expanding range of companies offer to scrape, clean and sell this data to the investment community. They sit between the generators of information — such as app stores, telephone and credit card companies or social media sites — and the buyers of the data.

Alternative Data Insider, an information provider backed by YipitData, one of the vendors, has counted more than 100 companies in the field, with money pouring in. SpaceKnow, a satellite imaging company that looks for clues on economic activity in China and Africa, raised $4m this year, while Prattle, a sentiment analysis company that uses artificial intelligence to turn material such as central bank speeches into tradable intelligence, raised $3.3m.

4. Satellite imagery

In previous decades an investor might send a junior trainee to a local shopping mall to count how many visitors it gets, or to local farms to check on the health of the latest barley crop. Such information gathering can now be done more comprehensively and automatically by accessing the data of satellite “eyes in the sky”.

“Alternative data will only be alternative for so long, eventually becoming a core part of any portfolio manager’s toolkit,” Greenwich Associates, a market consultancy, wrote in a recent industry report.

There is no suggestion that any hedge fund or alternative data vendor are doing anything illegal by using these new digital data sets. But lawyers urge caution, arguing that some aspects of the business, such as how providers collect the information they sell to hedge funds, and whether it is legal for funds to enter into “exclusivity” agreements with providers, are attracting the interest of regulators and prosecutors concerned that hedge funds are getting an unfair market advantage. The laissez-faire attitude of some of their colleagues and parts of the data vendor community is also under scrutiny.

Hedge funds also worry that some vendors do not do a good enough job of scrubbing personally identifiable data from their troves of information. Many therefore have dedicated internal teams that clean the data before it is involved in the investment process. Indeed, some hedge fund managers say they would welcome federal regulators such as the Securities and Exchange Commission taking a closer look at alternative data.

“It’s like the Wild West and ultimately it will come under the purview of the regulators,” says one fund manager, who says legal opinions on the subject vary. “I have yet to see a clean legal opinion on all this. And we’ve looked for one.”

Hedge funds have good reason to be wary. After a series of arrests from 2010, the industry was upendedwhen dozens of traders, portfolio managers and analysts were prosecuted for using information they gleaned from so-called “expert-network” companies which, like data vendors, tried to match investors with information.

The Wall Street traders used company insiders, doctors and others to expand their knowledge of industry trends or companies. The authorities cracked down when traders got their hands on confidential information, such as unpublished drug trial results.

To break insider trading rules an individual needs to act on “material, non-public information” received in violation of a duty to keep it confidential. While lawyers say the data sets sold must be material by definition because an investor is willing to pay for them, the vendors typically have permission to sell the aggregate data once a user clicks the box agreeing to terms and conditions. But with few legal precedents and different standards between countries or even states in the US there is little clarity.

Mr Streeter of Dechert believes it will probably be a high bar for prosecutors to bring insider trading charges against funds that have used data not deemed to be public. For instance, mobile geolocation data, which can show how many people visit Walmart, Sears or Ralph Lauren over a given period, could well be viewed as material information, and if 50 hedge funds pay say $100,000 for exclusive use of the data, it would be hard to argue that it is public. The crux is whether the owners of the information, such as AT&T or Verizon, have received consent from their customers to sell it on to third parties, he says.

“You look in the small print and there’s probably somewhere in there that says Verizon can sell that data. Verizon would then sign an agreement with a data provider. So under US law [there would be] no breach of duty, no insider trading,” the former prosecutor says.

Many more vendors scrape information from websites, and even if it is in the public domain lawyers say they may not always have the legal right to sell it on to third parties.

Rado Lipus, head of Neudata, which vets data sets on behalf of investment groups, says “exclusive data sets are a double-edged sword”. While they can be profitable, they are clearly not public data and some investors — especially bigger ones — prefer to avoid them to avert even a whiff of controversy. Several large hedge funds such as Man Group and AQR Capital Management go further, saying exclusive data sets are not worth the expense or legal risk.

Lawyers say they are advising clients against using some data sets, given the legal and reputational damage even the slightest sense of impropriety could cause. But experts believe the greatest risk of prosecution comes from the New York attorney-general, Eric Schneiderman, who is tackling financial fraud under the Martin Act and could stop hedge funds from using exclusive data. He has intervened before. In 2013, under pressure from Mr Schneiderman, Reuters stopped providing some exclusive content to its premium subscribers.

Sandy Rattray, chief investment officer of Man Group, says he has at least two people a week offering him exclusive data, but that it is too expensive and in any case they would analyse it differently than other funds. “There’s a gold rush in data mining,” he says. “Most people that went off to prospect for gold came back penniless, but that doesn’t mean there wasn’t any gold.”