Unfortunately, for many years and still today, public web data collection – or “web scraping” – has had a negative connotation for several organizations. But it’s time to face reality. To maintain a strong foothold in your industry, get the answers you need for your business, and thrive ahead, you must disregard several common myths. Let’s break them together:

#1 – It’s illegal.

The short answer is, no it’s not. If the website is public, or does not require a log-in, it’s legally accessible. This verdict was most recently displayed in the hiQ Labs vs. LinkedIn case, where the Ninth Circuit ruled data scraping to not be unlawful.

Public web scraping is performed by organizations of all sizes globally. It’s used to evaluate internal operations, back up key business decisions, and get a full grasp of the market to pursue new innovations and boost revenues. Of course, as part of this, compliance regulations must play a major role. Businesses (or their public web data collection providers) have guidelines they must follow to remain legal. This entails a strong understanding of what you are and aren’t allowed to collect. And since there is still limited regulation in the industry, companies are mainly held to moral and ethical standards when it comes to legal data collection.

#2 – It hinders your organization.

Contrary to this belief, public web scraping enhances your organization. It offers real-time, precise insights into your competitors and your customers. This could include anything from pricing to shopping habits, as well as crucial trends and innovations that you should take advantage of in the market.

The pandemic sparked a massive shift to a digital economy. Legacy business strategies like undercover shoppers therefore shifted to online data collection. Now, you can receive even greater and more accurate insights while cutting the time and energy required by your organization as much as 80%. You can increase your teams’ time spent on innovation and truly push your business forward. As result, public data collection strongly benefits consumers as well. They receive more appealing or advanced  products, obviously better pricing, and greater shopping experiences overall.

#3 – It’s legal, but unethical.

This falls on either the organization or the external web data provider. When accessing public data, they must be professional and act with transparency when sourcing the data. This includes all parties firmly abiding by both global compliance regulations and deeply-rooted ethical guidelines. To put it simply, ethical and legal public web scraping offers the same internet view, insights, and transparency that an individual user has access to – and enjoys.

#4 – The sources are private.

In fact, most of today’s web data is public. According to researchers, as of January 2022, roughly 62.5% of our global population (4.95 billion people) uses the internet. And of the data being created from this significant online use, it’s estimated that nearly 70% is public. Essentially, anything that can be opened via a standard browser without a log in. This is what businesses and providers are accessing through web scraping – and the data set only expands each year as more and more people use the internet globally.

#5 – It makes you untrustworthy.

The final common misconception we’ll walk through is that if you collect web data, then you’re up to no good. In reality, various organizations (from startups to large enterprises) around the world are acquiring, analyzing, and employing it to their day-to-day operations – even as you read this article. In order to succeed in today’s constantly moving and highly competitive business world, companies must receive the full picture by utilizing this massive data resource that is only growing.

The web data industry will continue to expand as more and more market sectors begin to take advantage of its benefits. To survive, and as part of our moral obligation, all participants must remember to act legally and ethically at all times. This is essential.

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People want to travel, but the conditions around travel are shifting so quickly that it’s increasingly difficult to predict what’s coming next for the travel industry. Basic questions like “what should a hotel room cost?” now require complicated answers. Data startups might simplify the equation.

Rather than flying blind, my company, hospitality business intelligence provider Fornova, turned to publicly available web data to keep up with the volatile blend of COVID spikes and travel demand. Through data collection across publicly accessible web sources worldwide, the hospitality industry can meet the changing needs of travelers across the world in real time.

But sourcing and analyzing public web data is a massive undertaking – one that online web data platform Bright Data does best for its customers.

“To address any of these issues, we must first collect enormous amounts of data, analyze this data, and then look for actionable insights within it,” Fornova CEO Dori Stein explained.

Raw public data from the web is a key ingredient for this process. Unlike traditional data sets, this kind of data comes from the daily activities of potential customers – a kind of data Bright Data CEO Or Lenchner calls alternative data.

Alternative data is driven by the growing demand for real-time insights from non-traditional data sources This living, breathing data source is essential to the travel industry’s future. Fornova’s collaboration with Bright Data allows each organization to bring their expertise to analyzing and acting upon the information.

The travel and hospitality industry will continue to face volatile and uncertain conditions as the post-COVID era emerges in different stages and paces around the world. With collaborations in big data though, companies can both meet the needs of travelers now and position their brands to succeed in the future.

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Unfortunately, and perhaps unsurprisingly, we are usually only presented with one side of a complex and fascinating story. The truth is that with the help of bots, tasks that used to take businesses weeks to complete can now be executed in a matter of seconds. By automating mundane, repetitive work, bots are freeing up time for creative, strategic thinking across a whole host of industries.

Robotic process automation

Robotic process automation (RPA), a market that is projected to reach $1.89 billion in revenues in 2021, is just one area where bots are proving invaluable. With RPA, businesses can automate repetitive tasks – like data entry, data extraction, and invoice processing – rather than relying on a human workforce to complete them. As such, RPA gives businesses unmatched scalability. A bot can, after all, perform the same process 10, 100 or even 10,000 times per day without issue. Throughout the pandemic, bots have enabled organizations to react quickly to the demand irregularities and supply chain bottlenecks that go hand in hand with economic uncertainty.

As businesses adjust to new ways of working, cost-saving remains a top priority – another benefit of RPA. For instance, Gartner estimates that using software robots could save financial services organizations up to 80% on processing costs. Plus, robots work with an unmatched level of precision.

What does this mean for employees? Rather than merely “stealing jobs”, bots typically free up time for problem-solving and building personal relationships. In a Forrester employee survey, 66% of respondents said RPA enabled them to have more human interactions, and 60% said RPA helped them to focus on meaningful, strategic tasks.

Data collection bots – fueling the real-time economy

Perhaps more than any other area, online data collection has been revolutionized by bots. The world’s largest database is the public internet and there’s no doubt that data fuels the digital economy. Today, the largest brands in e-commerce, finance, security, and more use up-to-the-minute data collected by bots to train algorithms and make smart decisions in near real-time.

Consider this example from the financial services sector. It’s becoming more commonplace for banks and financial institutions to collect publicly available alternative data to inform ESG (environmental, social and governance) investment decisions, which are designed to maximize both financial returns and social good. This data typically includes measurable metrics from areas such as energy use, emissions, discrimination lawsuits, board diversity, etc. In fact, recent research found that 95% of financial services organizations have relied on alternative data in the past year alone. As ESG investing becomes an increasingly established practice worldwide, this trend seems set to continue.

Bots – how to remain on the responsible side of the road

“At bottom, robotics is about us. It is the discipline of emulating our lives, of wondering how we work.” This thought, from Rod Grupen, renowned Professor of Robotics at the University of Massachusetts, perfectly encapsulates how we should be thinking about the role of bots in today’s society. Bots work on instructions given by humans, automating our actions, not our behavior. As such, it’s up to businesses to use them responsibly. Hearteningly, a recent survey of 4,000 decision-makers across the financial services and technology sectors found that the vast majority of organizations have clear guidelines in place to moderate bot use. In the US, 48% of organizations surveyed said they have guidelines in place to moderate all usage of bots, while another 48% said they have guidelines relating to some uses. In the UK, these figures are 57% and 40% respectively.

Like many fast-moving technological disciplines, the bot space is still largely unregulated. Though regulation would no doubt help to ensure that businesses use bots responsibly, it seems appetite for regulatory change is limited. The same survey found that a slim majority of respondents were satisfied with the current level of regulation related to enterprise bot use – 47% of US organizations and 60% in the UK. Meanwhile, 45% of US organizations and 33% of UK organizations actively wanted to see increased external regulation of bots.

Ultimately, with 95% of businesses planning to expand their bot usage in the next two years, it’s inevitable that they are here to stay. Personally, I’m excited by the potential of bots to drive forward innovation, as well as improving decision-making and employee experience – as long as organizations commit to using them responsibly.

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Data from the ONS indicate that e-commerce sales, particularly online sales within the fashion and textile category, have risen significantly YOY, with March 2021 seeing 78% higher online sales compared to March 2

020. Ecommerce Europe recently conducted a survey on the impact of COVID-19 on the e-commerce sector at the end of 2020 and highlighted that over 63% of those surveyed agreed that ‘Europe’s second lockdown benefited retail stores’ online sales’. Moreover, research from Vanson Bourne showed that 55% of shoppers participated in major online discount days such as Black Friday and Cyber Monday last year, with figures nearly doubling from 24% the year before.

The more we analyze these figures, the more customers we see shifting online, forcing wholesalers’ business models to shift online too, motivating older retail giants to get on the online bandwagon as well. Today, commerce is predominantly online, opening competition and changing the skin of the e-commerce game. To succeed, e-commerce brands are taking different approaches to their brand outlook. However, what some are failing to do – and where those that have made a big leap in profits are succeeding – is to collect, analyze and learn from their online data. The type of data ranges from the customer, logistics, support, or competitor comparison data.

Unsurprisingly, the collection of publicly available data online has become a crucial part of e-commerce. Not only does it help save overall business costs, but it can also bring in good business if used efficiently. We live in a real-time economy, and data is the new water fueling it. The collection of publicly available online data has become the main resource for fast and high-performance decision-making, profit, and innovation.

Here are some of the best and most powerful ways in which data collection can redefine an aspiring e-commerce business’s strategy, customer journey, and experience, to ultimately increase profit margins.

Establishing the data needed for real-time success

What do consumers want?

 This age-old question has mystified retailers for years. It’s clear now that consumers want to pay more for eco-friendlier products; they also want to reduce shipping costs and make sure that their products are ethically and sustainably produced. The bigger question is, how do businesses find this information? The answer is very simple: through near-live online data-gathering. Gaining an on-the-spot market view has translated into the need for almost-live consumption of online data as frequently as possible. This realization has accelerated the perception around data, further establishing it as a must-have commodity. This shift is also visible in the real-time economy that governs our countries, as we now need more real-time data.

To summarize, you need to first establish the type of data needed to re-define a typical consumer journey and bring real-time analysis to the table. And there are a few options to choose from, especially in the open-web public data analysis of customers’ reviews and sentiments. There’s also the type of data used by other companies or even competitors. Businesses also leave a trail of data in their wake, such as customer purchases / transactional data, or bulk buys on items, cars leased, houses put up for rent and others. Once you’ve figured out the ‘what’ and the ‘how’, the rest is up to you to make use of. This means analyzing the data sets and making informed business decisions based on them.

Too much data is too much – a balancing act is needed

A big problem for most retailers and e-commerce businesses is data saturation. The industry perception is that more is better, when in fact the opposite is true. As a sector, we’ve been fascinated with hoarding data sets and less worried about what to do with them once we have them. However, think of it much in the same way you would a city. If the city expands, the roads will get bigger, leading to more traffic, overcrowding, and slowed down traveling time. The same can be said of data. The more you have, the more it costs and the more costs you take on, and the more you will find yourself drowning in it. Without a systematic approach to collecting and managing data, you may end up on the verge of ‘infobesity’. The best rationale is to take the data you need now, validate it, and make sure it serves you well, and only then scale up if needed. Without this approach, you will soon find yourself in a quicksand of information, wasting time and resources, drilling into it for analysis, wasting critical real-time decision-making and market input, and ultimately losing your competitive advantage.

Using the data, the way it was intended

Analyzing data, pouring over every little detail and using them to make decisions is a complex and tedious process. This is why businesses must look towards the advantage that data analysis provides.

A good example of this is e-commerce companies seeking to make intelligent pricing decisions that are based on their competition base. Leveraging automated online data collection allows them to see what their competitors are charging for, say, a pair of black jeans. Then, they can optimize the price they charge based on this data, ensuring that they keep their prices attractive and, consequently, their consumer base loyal to their brand. Another strong example is when companies test a new product or offer to market. Public social media reviews, as well as product reviews, can provide e-commerce brands with a swift measurement of just how positive the offer/product is among their consumer base. Online data collection can also help businesses stock the right products too, and much more.

Such data is based on openly available insights taken from across the web channels and then incorporated into a fast-moving strategy. By observing what is selling out, businesses gain more insights that allow them to stock goods in the right quantities, in the right locations, and at the right time. Data collection encourages healthy market competition, too. As we all know, competition is good for both businesses and consumers. It drives them to continue optimizing their offers for more competitive prices as well as better products.

My final advice is this: for e-commerce businesses that are unsure about taking up data collection, I can tell you this, now is the right time to get started. Start small, focus on your data-defined parameters and requirements, and go from there. With so many businesses rapidly evolving online, every decision counts. And with so much competition out there, data can guide you towards the correct market decision. Laser focus on the data that matters the most and don’t be confused by non-relevant sources of data. While no business or individual can precisely predict the future, with online data collection, you can come very close to doing just that.  

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Companies are now increasingly looking at data collected from non-traditional sources, like social media, to determine the creditworthiness and potential investment risk of modern companies. Though online data – such as the number of employees listed on LinkedIn – could easily slip under the radar to many, a sudden rise or fall in reported employee numbers can give a real-time indication of financial issues at a given company well before an official announcement is made.

Publicly available online data – including information on funding rounds or recent appointments – can be collected from websites such as Crunchbase. This information can provide an up-to-the-minute (and free) early warning system about the financial future of companies. This data has the potential to give investors the insights they need to remain competitive in an environment where risk premiums are harder to calculate than ever – especially as COVID-19 continues to fundamentally disrupt the business models of companies worldwide.

How publicly available online data offers a different approach to fraud prevention

All industries face, these days, significant pressure daily to make – and keep – money. But for some industries, like insurance, the added complication of the pandemic’s impact can be overwhelming. In the United States, professional services network Deloitte has issued warnings that the impacts of COVID-19 will be felt for months, if not years, to come across a broad variety of insurance specialties. The impacts range from disrupted investments, finance and capital, underwriting, claims, and actuarial functions due to catalytic events ranging from the closure of nonessential businesses to changes in state and federal regulations.

But with the large insurance pay-outs caused by COVID-19, insurance companies anticipate a pronounced spike in fraud attempts, as difficult economic circumstances tempt businesses to try their luck. The Internal Revenue Service, the Federal Trade Commission, and the Social Security Administration have all issued warnings to be aware of fraudsters trying to take advantage of consumers and businesses during the pandemic. Insurance companies that have furloughed or laid off employees as a result of the pandemic, may struggle to process these claims in a timely manner.

By using automated online data collection solutions, insurers can verify these claims faster. Freely available online data can be a useful tool when it comes to checking on their validity. Online data can help to identify if a claimant’s online profile is at odds with the claim presented. However, large enterprises are constantly generating relevant details, all of which needs to be cross-referenced and analyzed as part of the assessment. Details like stock prices and employees fluctuate constantly, making it nearly impossible for insurers to keep track of these large-scale details manually. This makes an automated data collection solution that gathers data according to defined requirements in real-time even more necessary.

By employing an automated data collection solution, insurers will have real-time indications when something is wrong. This is an example of how publicly available online data can stop fraud in its tracks while allowing multiple legitimate claims to be paid faster. When insurance companies are no longer bleeding money to fraudulent claims, they’ll have more resources for honest businesses whose finances (and employee wellbeing) are under significant threat.

How online data collection can improve insurance underwriting

Without the best tools on hand, collecting all the available online data needed to verify claims can be not only difficult but also immensely time-consuming. Automated online data collection enables insurers to collect more data than if purely traditional means were utilized. It also speeds up the process for claimants who would no longer need to manually fill out endless forms to provide the requisite information. More online data means better risk assessment, which leads to smarter pricing, increased gross margins, and a fundamentally improved underwriting process. It can also make for a much faster onboarding process for new customers, allowing for the insurance company to increase its customer base at a faster rate.

For example, if an insurer wants to ascertain if a struggling hotel chain is creditworthy, automatic data collection solutions can be utilized to scrape public or open data from a number of websites (including 3^rd parties like Booking.com) to see how many rooms are available, and the price they are charging in key locations. This data can give a more realistic assessment of how well the hotel chain is performing financially, which might not be as evident in traditional forms and based on traditional data means.  As insurers can receive these types of updates in real-time (alongside other relevant data like corporate news or stock prices) this represents a superior option to slower-moving avenues. After all, the current occupancy rate is a much better indicator of revenue than more formal financial reports that may be from several weeks or even months ago when the economic picture was much different than it is now due to the fast-paced market changes we’re facing now.

As the economic consequences of the pandemic will almost certainly lead to more sudden spikes in insurance claims, having as much of the data collection process automated and real-time as possible gives businesses the infrastructure necessary to rapidly scale to handle the number of claims they will be inundated with.

What is the right approach to online data collection?

Collecting massive amounts of data at true scale can be arduous if you do not have the right tools and the right operation in place. These challenges can be easily solved with the right data collection set-up. In our competitive market reality, many websites block any activity which seems like it could originate from competitors trying to collect large amounts of data, or that could indicate malicious activity such as botnets. The information available to typical consumers (a.k.a. the general public) is not the same as is the data that’s available to businesses. Therefore, it’s best for businesses to use some form of a data collection network based on residential IP addresses knowingly contributed by global consumers, as this will allow the data to appear as a typical consumer would when collecting online data. By using these types of networks, they can run scenarios that mimic real-time users – like an android user in Thailand or an iPhone user in California – and effectively collect data in any part of the world without restriction.

The new set of challenges brought by the pandemic for the insurance industry should lead them to embrace a new set of technological solutions. If the industry wants to be able to adequately protect itself and come out on the other end of the barrage of new claims 2021 could bring, they need to have the wealth of data necessary to process them quickly and accurately. Taking an open-minded and efficient approach to the type of data that they use will be a big part of this, and embracing publicly available online data will be a key element of the transition to a more modern and efficient approach to data-driven insurance.

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Online retail isn’t a new frontier for millennials and Generation Z. These and future generations that are born into a digital era will be more than familiar with online marketplaces. However, thanks to restrictions on visiting brick-and-mortar stores, the unique circumstances presented to both retailers and consumers in 2020 has changed the landscape and opened new online markets.

Most notably, the research found an increase in consumers aged 65+ who do the majority of their shopping online, jumping from 15% a year ago to 39% today. A majority cited increased convenience as a leading factor in their shift online, with 69% including this in their top three reasons. Older customers historically have been reluctant to shop online. This shift in attitude highlights the changing retail landscape. This is encouraging news for retailers, but presents them with a new challenge to attract customers this Christmas and beyond.

Retailers must adapt and respond to consumers who are increasingly savvy when shopping online. Gone are the days when it took a long time to compare products and prices. There are now entire platforms that do the hard work for consumers and present them with the most attractive offers. Consumers are using these tools. The research found more than half of shoppers (55%) use comparison sites to find the most attractive deal.

How do online retailers compete in this new landscape?

From groceries to flights, winning the business of savvy consumers is key to success. Businesses must have a clear view in real-time of every move their competitors make. You need to be aware and respond quickly if a competitor selling a similar product drops their price by a couple of dollars to attract consumers who are using price comparison tools. Large retailers, travel providers, and many more sophistication online businesses have perfected this ability, thanks to large-scale online data collection. By regularly collecting online data providers have ‘near live’ view of the market and can adapt accordingly. 

This process isn’t limited to large businesses. Some small and medium sized businesses that will be dipping their toes into ecommerce for the first time need to be competitive in their domain. It is time for all retailers to future-proof processes and embrace the digital world now that consumers of all ages are showing a preference for online shopping. There can be no doubt that 2020 has caused the retail landscape to change, but this has presented a golden opportunity to retailers. To take this opportunity retailers must be guided by online data and the insights it provides. Data is being created by every action taken online. The faster retailers can collect, adapt, and respond to the latest trends, the more successful they will be.

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Traditionally, investors and financial institutions leveraged the data that’s readily available to them when they make their investment decisions. This data includes quarterly or monthly reports published by companies outlining growth, revenue, earnings, and loss. It also includes a market outlook for the upcoming time frame, be it months, quarters, or years.

But, these aren’t normal times. While these reports are usually helpful, they were created in a pre-pandemic world. They’re no longer relevant for today’s market realities, thus rendering them useless to investors looking to get a leg up. This is why finding and using alternative, or external, datasets is critical for financial institutions.

What is alternative data?

Alternative data is information that can inform investors and financial institutions beyond traditional datasets like earnings or credit reports. This data can come from a wide variety of publicly available sources, such as social media activity, online reviews, or data on mobile spending trends. Because this is real-time information, gathered “live,” it paints a much more up-to-date and accurate picture for financial professionals to base decisions around investment opportunities and loan evaluations in the current market ecosystem.

For example, if a retailer has not released a quarterly earnings statement since before the pandemic hit, online data collection can be used to measure the level of activity on the website in the past few months, along with measuring the sentiment of reviews left by consumers. This type of data can give an investor the insights they need to inform projections and help develop an investment plan for their clients.

Alternative data can help banks, too, when it comes to lending and assessing risk. Data collected from public sources like social media pages as well as inventory and pricing on ecommerce websites can paint a picture of who the bank is lending to, beyond just their credit score. This is crucial for banks right now, as many consumers have also taken an economic hit and are taking out personal loans to help tide them over.

Many financial institutions know the value of this data. Per research from Greenwich Associates, alternative data budgets increased 52 percent in 2019, and 74 percent of firms surveyed said that alternative data has made a significant impact on their institutional investing. In times of global crisis, however, alternative data will become even more important, especially when no one knows what the future holds. Those who don’t have the infrastructure set up to collect this data will find it hard to remain competitive going forward.

Overcoming data collection challenges

Despite how useful alternative data is for investors, it’s not as simple as clicking a download link on a website and accessing a report. Alternative data, by nature, does not follow a structure, nor does it follow patterns. This can make capturing and analyzing the data difficult.

This is why it’s so crucial for financial institutions to put time and investment into data analysis. It’s not enough to simply have this data. It takes detailed analysis to turn raw numbers and unstructured data into a digestible source of reliable information for investment decisions. Businesses should be leveraging analysis tools such as AI and machine learning to automatically consume this public data and create reports that are easy to digest. Investors must also understand just how important it is to keep in line with local and federal data privacy regulations, so alternative datasets can be collected ethically and legally.

Alternative data is a huge opportunity for investors and financial institutions looking to get ahead in an economy that’s poised to restart after a rough few months because of the pandemic. Taking a look beyond the traditional can give them exactly the edge they need to come out on top and win.

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