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10 Best Practices for Implementing Automated Web Data Mining using BOTS

A famous manufacturer of household products, working with a number of retailers across the globe, wanted to  capture product reviews from retail websites. The objective was to understand consumer satisfaction levels and identify retailers violating the MAP (Minimum Advertised Policy) policy. The manufacturer partnered with a web scraping and distributed server technology expert to get an accurate, comprehensive and real-time overview of their requirements. It took them no time to get complete control over the retailers and pre-empt competitors with a continuous sneak peek into their activities. This example underscores the importance of web scraping as a strategic business planning tool.

Web scraping is the process of extracting unique, rich, proprietary and time sensitive data from websites for meeting specific business objectives such as data mining, price change monitoring contact scrapping, product review scrapping and so on. The data to be extracted is primarily contained in a PDF or a table format which renders it unavailable for reuse. While there are many ways to accomplish web data scraping, most of them are manual, and so, tedious and time-consuming. However, in the age of automation, automated web data mining has replaced the obsolete methods of data extraction and transformed it into a time saving and effortless process.

How is Web Data Scraping Done

 

Web data scraping is done either by using a software or writing codes. The software used to scrap can be locally installed in the targeted computer  or run in Cloud. Yet another technique is hiring a developer to build highly customized data extraction software to execute specific requirements. The most common technologies used for scraping are Wget, cURL, HTTrack, Selenium, Scrapy, PhantomJS and Node.js.

Best Practice for Web Data Mining

 

1) Begin With Website Analysis and Background Check

To start with, it is very important to develop an understanding about the structure and scale of the target website. Extensive background check helps check robot.txt and minimize the chance of getting detected and blocked; examine the sitemap for well-defined and detailed crawling; estimate the size of the website to understand the effort and time required; identify the technology used to build the website for seamless crawling and more. 

2) Treat Robot.txt -Terms and Conditions

The robots.txt file is a valuable resource that helps the web crawler eliminate the chances of being spotted, as well as uncover the structure of a website. It’s important to understand and follow the protocol of robot.txt files to avoid legal ramifications. Complying with access rules, visit times, crawl rate limiting, request rate helps to adhere to the best crawling practices and carry out ethical scrapping. Web scraping bots studiously read and follow all the terms and conditions.

3) Use Rotating IPs and Minimize the Loads

More number of requests from a single IP address, alerts a site and induces it to block the IP address. To escape this possibility, it’s important to create a pool of IP addresses and route requests randomly through the pool of IP addresses. As requests on the target website come through different IPs, the load of requests from a single IP gets minimized, thereby minimizing the chances of being spotted and blacklisted. With automated data mining, however, this problem stands completely eliminated.

4) Set Right Frequency to Hit Servers

In a bid to fetch data as fast as possible most web scraping activities send more number of requests to the host server than normal. This triggers suspicion about unhuman-like activity leading to being blocked. Sometimes it even leads to server overloads causing the server to fail. This can be avoided by having random time delay between requests and limit page access requests to 1-2 pages every time.

5) Use Dynamic Crawling Pattern

Web data scraping activities usually follow a pattern. The anti-crawling mechanisms of sites can detect such patterns without much effort because the patterns keep repeating at a particular speed. Changing the regular design of extracting information helps to escape a crawler from being detected by the site. Therefore, having a dynamic web data crawling pattern for extracting information makes the site’s anti-crawling mechanism believe that the activity is being performed by humans. Automated web data scraping ensures patterns are repeatedly changed.

6) Avoid Web Scraping During Peak Hours

Scheduling web crawling during off-peak hours is always a good practice. It ensures data collection without overwhelming the website’s server and triggering any suspicion. Besides, off-peak scrapping also helps to improve the speed of data extraction. Even though waiting for off-peak hours slows down the overall data collection process, it’s a practice worth implementing.

7) Leverage Right Tools Libraries and Framework

There are many types of web scraping tools. But it’s important to pick the right software, based upon technical ability and specific use case. For instance, web scraping browser extensions have less advanced features compared to open-source programming technologies. Likewise smaller web data scraping tools can be run effectively from within a browser, whereas large suites of web scraping tools are more effective and economical as standalone programs.

8) Treat Canonical URLs

Sometimes, a single website can have multiple URLs with the same data. Scraping data from these websites leads to collection of duplicate data from duplicate URLs. This leads to a waste of time and efforts. The duplicate URL, however, will have a canonical URL mentioned. The canonical URL points the web crawler to the original URL. Giving due importance to canonical URLs during the scrapping process ensures there is no scraping of duplicate contents. 

9) Set a Monitoring Mechanism

An important aspect of web scraping bots is to find the right and most reliable websites to crawl. The right kind of monitoring mechanism helps to identify the most reliable website. A robust monitoring mechanism helps to identify sites with too many broken links, spot sites with fast changing coding practices and discover sites with fresh and top-quality data.

10) Respect the Law

Web scraping should be carried out in ethical ways. It’s never right to misrepresent the purpose of scrapping. Likewise it’s wrong to use deceptive methods to gain access. Always request data at a reasonable rate and seek data that is absolutely needed. Similarly, never reproduce copyrighted web content and instead strive to create new value from it. Yet another important requirement is to respond in a timely fashion to any targeted websites outreach and work amicably towards a resolution.

Conclusion

While the scope of web data scraping is immense for any business, it needs to be borne in mind that data scraping is an expert activity and has to be done mindfully. The above mentioned practices will ensure the right game plan to scrap irrespective of the scale and challenges involved.

 

 

 

7 Ways RPA Supports Digital Transformation Initiatives

After implementing Robotic Process Automation (RPA), a renowned bank was able to reduce consumer loan-processing time from 30 minutes to just ten minutes and expedite the process of customer verification from a few days to a few seconds. The reason being the technology obviates the need to copy-and-paste customer information from one banking system to another and enables automatic validation of customer data on government websites such as tax payment, DMV, or property-appraisal sites.

Digitization and RPA Made for Each Other

Like the bank, digitization is taking over every corner of the business world. To retain a competitive edge, it’s important for businesses to comply with this new order. However, adopting a single technology to digital transformation is not enough. Businesses need a set of tools to automate a range of activities traditionally assigned to workers. This would help them create a digital workforce across applications and systems.  As Robotic Process Automation makes this possible, adopting RPA as a part of digital transformation strategy has become an imperative.

RPA is the Way Forward

Robotic process automation is one of the technologies that can help companies across all industries to undergo digital transformation. While on the one hand it empowers organizations to tackle operational challenges, such as carrying out large amounts of back-office activities, on the other hand it enables businesses to gain knowledge about their business performance and workflow patterns. Companies can leverage this information build on their digital strategies and transform operations to make it more lean and agile.

How RPA Supports Digital Transformation Initiatives

Increase Customer Experience

Great brands have one secret tool for success – customer experience. And customer experience, as it stands today, is just not about delivering what you promised. It’s more about surprising your customer with extra care and support. With RPA it is possible to increase process speed and efficiency, provide instant response to customers, and handle multiple questions in less time. This makes your customers feel so valued and they turn into a community of advocates for your brand. 

The insurance industry stands out as a stellar example. With the help of chat bots, insurance carriers provide instant responses to customer queries and seamlessly handle the ever changing regulatory rules of the industry. Likewise RPA has enabled all-time customer support in the retail industry. From order payments to delivery, bots can send updates to customers to keep them in the loop and their worries at bay.

Digitalize Products and Services

One thing common to industries such as insurance, finance, mortgage, legal, hospitality utilities etc. is high volume, mundane, and time consuming processes. These activities are detrimental to the streamlined operation of business. RPA works to automate these activities. In other words, robotic processes take over these simple tasks like cut-and-paste and data migration, to more complex work like invoicing and automate them end-to-end thus maximizing visibility and productivity. In many environments, RPA assists to redesign the existing process to make it more fast, continuous and highly accurate.

Mortgage loan processing for instance is a time consuming and error prone task primarily because of human intervention. Fetching and compiling data from multiple sources, and comparing data has involved extraordinary levels of manual involvement. RPA based mortgage processing tools enable automated data mining and can transform unstructured data to structured digital data in a matter of seconds. The digitization of this service has led to expedited processes, reduced time and costs and complete accuracy.

Digitally Optimized Operations

To best understand this benefit let’s take a peek into the supply chain industry.  Maintaining effective communication between customers, suppliers, and manufacturers is critical to the smooth running of this industry. However, chaos and confusion caused by delays and obstacles to order fulfilment has always been the bane of this industry. Robotic process management has eliminated all these drawbacks by automating the communication process. As a result errors and duplicity in the process, manual input of purchase order, delay in response to requests and proposals, communication gap with suppliers etc. are a matter of the past. RPA has automated the process of supply and demand planning; vendor selection and procurement; order processing and payments and order traceability.

Like the supply chain industry RPA has helped digitalization across a range of industries such as financial sector with overall improvement in transparency and risk management; healthcare sector with higher throughput and improved quality and consistency; insurance sector with enhanced claims processing and underwriting; mortgage with improved compliance and origination and so on. 

Digital Skilling and Upskilling

The advent of digital transformation has significantly amplified the need for a rapid pace of innovation. While the debate over RPA replacing the human workforce will continue for some time to come, the fact that cannot be disputed is that it will create more jobs for people with relevant skill sets. This is because, the technology has triggered the need for up-skilling and re-skilling of the existing workforce in order to stay relevant in a fast changing ecosystem. Employees will drive themselves to imbibe skills to adapt to the demands of RPA, thereby acquiring strong problem solving and analytical skills. 

In the days ahead, employees will catch up with technological skills such as design thinking, analytics, robotics, autonomics,) and soft skills such as pattern-recognition, problem solving, intuition and leadership. With the change in learning, employees will be evaluated by quality of outcome than overall output.

IOT and Digitally Connected Products

IoT is a revolutionary concept of connecting a device with a virtual switch to the Internet. A company can leverage this technology to track the real-time movements of customers in a retail store or even to track products within a supply chain. As a platform, Robotic Process Automation has the abilities to help manage all of these capabilities. The collaboration between RPA and IoT can help to improve data management – turn unstructured data to structured data; optimize operations to improve the quality and speed of output; and execute routine tasks without human intervention like responding to unforeseen developments. 

The connection between RPA and IoT will grow with time as the two technologies perfectly complement each other – while one connects an object, the other uses the data produced by the object to identify issues. Manufacturers can leverage this combination to decrease asset repair and maintenance costs; improve compliance with regulatory standards; and enhance monitoring of efficiency. 

Digital Collaboration

Getting started with RPA can be a daunting task for any business. The only thing that can make businesses conquer the daunt is collaboration. Each business is an expert in its own field, and only partnerships can help them get the right start and scale thereafter. Businesses will collaborate to initiate the transition; set and measure out metrics and goals and analyze the outcomes. 

In this new age of digital collaboration, IT and businesses will work closely together than ever before. Similarly, collaboration between employees and customers will reach new heights and foster relationships. Even employees who never previously collaborated will come together to improve productivity together. So many employees will collaborate with BOTs to bring human judgement into the picture.  

Digital Workforce

The ability of RPA to relate to a number of different functions in an organization across industries will lead to the creation of a thriving digital workforce. The fact that RPA software can be used as an effective tool to tackle tasks for purchasing, accounts receivable, compliance, reconciliations, and meeting due diligence requirements or as data scraping bots for sorting, and scooping data from competitor sites, will lead to the creation of an automated and diverse digital work force that will work more efficiently towards meeting goals.

It is estimated that by the end of 2030,  there will be 4 million robots carrying out monotonous office tasks. In other words businesses will adopt RPA as an integral part of their workforce to ensure they face no issues with flexibility and scalability. 

Conclusion

While Robotic Process Automation is the future, your first step towards the transition, should be to prepare your business for the changeover. Going for staged transitions, picking the right processes for automation; training and onboarding employees and setting up the right expectations are critical to your business’s transition to RPA. Only when you have these prerequisites rightly aligned, your business can have a smooth transition to the new age necessity.

 

 

DATA MINING

9 Benefits of Automation in Data Mining Process

When retailers want to wean away customers from competitors, they must entice them with customized coupons. And to tailor personalized coupons, it’s important to understand a customer’s individual purchase history. The history must be analyzed to discover the products they prefer buying and the promotions that they would likely be interested in. But how do you get access to this information from an alien domain. By scraping information from their website. And the easiest and safest way to scoop data from your competitors website is through automated data mining

What Is Data Mining

We live in the age of massive data production. Every service or gadget we use generates a lot of information, and some of which like Facebook runs into hundreds of terabytes each day. All this data is a treasure mine of information which we can use to make a better product or deliver more efficient services. This process of collecting and analysing data to make sense of it is called Data Mining.

Automation Fuels Digital Transformation

Digital transformation is the process of transforming a business with advanced technology to improve efficiency and revenue streams. Unlike an isolated IT project like moving processes to the cloud, it consists of a combination of projects that transforms every component of your business to be digital-first. Among all the technologies involved, automation has proved to be the springboard for launching digital transformation initiatives.

Automation is the most critical step towards digitalization because when implemented end-to-end the entire team benefits from an improved, transparent and time saving workflow. Automating routine day-to-day workflows lies at the heart of successful digital transformation because it drives productivity, improves security, makes your process more compliant, flexible and scalable. 

Benefits of Automation in Data Mining

 

1) Automation Reduces Costs

Automation is the most viable option for business owners to save on costs. The biggest way of realizing cost savings through automation is reduction of employee hours. Automation has obviated the need to have an entire assembly line of people in manufacturing units because these tasks can now be done more quickly and less expensively. Further, automation has helped to streamline processes within a business. This has helped to identify and eliminate inefficiencies within the business resulting in cost savings. These asides, automation can be used to reduce incidental costs associated with a business process like eliminating the need to send physical invoices through mail service and replacing it with automated delivery of invoices through email. 

 

2) Increases Data Quality

Automation can recognize and take action on different types of data thus helping improve the overall quality of data generated. For example, an automated tool can recognize an email, address, credit card number, social security number to validate an entry or flag a compliance issue. This feature when put to use in a mortgage process can help to identify data inconsistencies and thereby spot errors or frauds. Likewise, automated data processing can help credit card departments match data to find out candidates eligible for credit cards.  Automation tools come equipped with advanced data profiling capabilities that can assess core data attributes to identify format, structure,  and other key characteristics. This feature helps in sorting data effectively and in the process improve data quality.

 

3) Scalability of Operations

As businesses grow they need to process orders at a scale that is far higher than human capability. This is an area where automation comes very handy. Automation scales up with a business and automatically allocates workload to the right department. For example, automating a fashion website, can help send the list of clothes ordered by a customer to appropriate departments. As a result it frees up time for the employees and sends packages out faster. It’s primarily because of end-to-end automated processing that Amazon has acquired the speed and accuracy needed to become a lead market player. This can be particularly helpful during seasonal business activity when there is a need to hire more workers. 

 

4) More Data Deeper Insights

Data insights refer to the understanding of a particular business phenomenon by analyzing incoming data streams. These insights allow users to understand the “behind the scenes,” developments, understanding which is very important for highly regulated industries like banking and healthcare. Likewise retail companies want insights for product recommendations or understand customers propensity to churn. Automation helps to understand and communicate meaningful insights with the right kind of data visualization and presentations for better understanding.  Once the value is  uncovered automatically it leads to improved and fast business decision-making.

 

5) Intelligent and Data Driven Decisions

Automated data insights can tell the likelihood of a customer to churn. When drilled down it can reveal the factors that drive churn rates. This allows decision-makers to make changes to business strategies and processes. When done regularly it translates to real business value in the form of right and timely decision making.  Data driven decisions for instance can help retailers determine what new items to introduce and which store locations need them the most.  Likewise, it can help the hospitality sector identify the key reasons for key fluctuations in demand for rooms and services or the food and beverages industry analyze customer foot fall in real-time and plan ahead and stock up menu items in demand. 

 

6) Real Time and Near Real Time Process

Some businesses need solutions that can process large volumes of data for prescriptive and predictive recommendations in real-time. For instance, those looking to travel or purchase a vehicle, want the best deal. Automated data mining can make this happen in real time by scraping data off websites, comparing it and showing the best deal. Businesses too can leverage automated data mining techniques to make decisions on the production line in real time, get timely information about allocated and de-allocated car spaces in real time, handle thousands of financial transactions between individuals and businesses in real time and so on. By automating processes that require laser-sharp precision, businesses can lower labor costs, reduce production waste and optimize yield significantly.

 

7) Free Up Time

Data management automation lends unprecedented speed and accuracy to processes which in turn leads to significant time savings. For instance, few time consuming marketing processes like booking an appointment, qualifying cold leads and prospects, and customers on boarding can be automated and the overall time needed to carry out these processes can be reduced by one tenth the usual time.  Similarly an ecommerce company can automate processes like product launches, communication based on customer purchase behavior, abandoned cart email sequences, communication with suppliers etc. With businesses being freed up with more time focusing on money-making or other productive tasks becomes a lot easier.

 

8) Increase Productivity

Automation can lead to big productivity gains. The productivity gained in an IT organization can be a good example to discuss. Centralized ticketing, reporting, and logging obviates the need for an administrator to notice an issue and act. Issues are addressed no sooner they arise, keeping backlogs at bay and maintaining optimum efficiency levels. Automation also helps IT engineers track recurring issues with customers and address them proactively. Likewise in mortgage operations lenders need not wait for days to establish the financial credentials of borrowers. Automated data mining fetches all financial information in just a few seconds thus helping the underwriter to arrive at an early decision. 

 

9) Increase Operational Efficiency

Operational efficiency is a metric that measures profits earned over operating costs. And operational efficiency is determined by workflow. If the workflow is dependent largely on siloed and legacy systems, paper-based forms and excel spreadsheets, then it becomes more human-dependent, time consuming and error prone. The cumulative effect of this is reduced efficiency. As automation, streamlines workflow and removes human dependency operational efficiency takes a quantum leap. It empowers businesses to do more with less and equips them with a competitive edge as they can deliver high quality products or services to customers more cost-effectively. For financial institutions the jump in efficiency comes with reduced risks. 

 

Conclusion

Automated data mining techniques help data scientists execute tests for scenarios that they could not have done before. Also, it allows them to experiment with more use cases as it reduces the time taken to come to a conclusion. In the world of data science, automation is a game-changer and promises a lot more than we can imagine.

WEB SCRAPING FOR SMALL BUSINESS

Web Scraping for Small Business

10 Reasons Why Small Businesses Explore Automated Web Data Scraping

In a competitive business world big businesses always find the going a lot easier than small businesses. Being on top they determine and set the rules of the market. Besides, they have various other advantages at their command such as huge finances for adopting evolving technologies, a great number of people working with market research, and endless possibilities to innovate. Small businesses have to compete with large businesses without any of these which is why surviving in the market becomes an endless struggle for them. 

However, there is one lever which small businesses can always use to their advantage – the lever of information. In a fiercely competitive landscape the power of insider information is unbeatable. Knowing what the high and mighty are up to and how they are planning their next moves can give the right direction to  your strategy. As small businesses pre-empt the moves of big businesses and realign their strategy accordingly they stand a chance of seizing the early bird advantage. The process of gathering this insider information is called web scraping.

 

What is Web Data Scraping?

Web scraping is the general term for  automated web mining carried out to scoop information from competitors. It is done with the help of a software which simulates human web browsing to collect information from webs without letting them know the intent. Web scraping for small businesses can keep them informed in real time about everything relevant to their business. The two most competitive information they can procure are establishing a sales pipeline and finding how competitors are setting their prices. There are hosts of other benefits as well.

 

Digitization & Robotic Process Automation

Digitization entails integrating underlying processes in order to transform the workflow of an organization. And it’s here that automation is key. Automation helps to make fundamental changes to how the organizations process flows thus making it more streamlined and efficient. It eliminates redundancies and helps businesses build on their full potential. 

 

How Small business can Explore and Benefit from Web Data Scraping

1) Monitor competitors

Web scraping BOTs helps a business understand what the competition is doing very right and what it is doing wrong. This insight can help them alter service or sales strategies and better combat potential losses. For instance if a streaming platform finds there are few takers for its funny videos, it can scrap competitor sites on funny video titles  with over 1 million views to understand what kind of titles are working well. Likewise, businesses can scrape for particular keywords to understand why and when people are using that keyword.

2) Sales leads

Gathering the right leads is a painstaking as well as a time taking job. By the time a small business has a list ready the opportunity might get lost or the scenario might change. As time matters more than anything else in a competitive set up, getting the right information in the shortest possible time is critical to steal a lead. Web scraping ensures you have the right leads before you are ready with your strategy. For instance, let’s take the example of email address gathering. Having them on a platter can give small businesses a head start.  

3) Price optimization

If you are a small ecommerce business it’s imperative you stay on top and set competitive prices against your competition. For example, if you raise prices in September to match your competitors, and see a fall in sales in October, it must be because they have lowered their cost. But how do you know? Is it possible to manually analyze 250 competitors? However you can gather all this information almost in no time by scraping their sites. An automated web scraper helps you get the information real time and strategize accordingly.

4) Product Portfolio Optimization

Automated web data scraping helps you optimize your products and brace for competition. Manufacturers like Tesla, Rolls Royce, and Aerospace are using this technique to collect data on various parameters and identify features that will help them improve on their process or revamp it to their advantage. for instance, teams in the semiconductor industry can get advanced information about how adding a certain type of material in IC chips can be a game changer and even the performance of the chip when simulated for different real-world scenarios.

5) Smarter investment decisions

Goldman Sachs Asset Management team scrapped information from Alexa.com to know that there was a sudden and significant increase in visits to the HomeDepot.com website. The asset manager was quick to procure the stock before the company increased its outlook and reap the benefits when its stock appreciated. Like Goldman Sachs, small hedge fund businesses too can leverage web data crawling to bring to light, precise trading signals to identify profitable investment opportunities. Likewise, analysts can scrap financial statements to evaluate the health of a company and advise clients on whether or not to invest in a company.

6) Marketing automation

A web crawler makes a marketers jobs a lot easier than before. It helps marketers generate qualified leads in as good as no time and establish the right touch points at lightning speed.  Once they get this information on a platter they can take things to the next level by automating and personalizing the outreach sequence. Automated web scraping also helps marketers automate the process of content gathering; understand customer perspective of competitors through social media discussions and get valuable insights form competitor reports. 

7) Increase Customer Engagement

One of the top ways in which small businesses can engage with customers is by offering them personalized engagement. This means delivering only relevant, targeted content and offers based on the history of their engagement with different brands. Web scraping and  engagement automation lets you gather information about your customers throughout a conversation across channels, so that you can personalize the experience along the way. This way, you can wean them away from your competitors.

8) Drive Digital Initiatives

Automation helps small businesses drive digital initiatives. For instance, for a marketer, digital is all about getting rid of cold calling and making way for social selling. Your customers are already active in social media and you want to engage with them on platforms, reviews sites, forums, and communities. Automation helps you identify who your prospects are and what is keeping then dissatisfied and then make a personalized offer. Besides, it also helps you reduce expenses on marketing activities, such as billboards, direct mail and television advertisements. With automation small businesses do not have to wait for the phone to ring. They can get proactive and provide a resolution even before the call comes.

9) Cost savings

If you are a start-up financial institution, you may need to employ several staff to verify applications and carry out background checks. Automating the process helps them eliminate the expenditure incurred in maintaining the staff.  For instance, automation helps small businesses build a rule-based program to check for common errors and data inconsistencies and save on costs. Similarly having beforehand knowledge of pattern changes can provide a huge advantage to small businesses. Scraping data from a lot of websites can help them understand the change faster and in a cost saving way. 

10) Productivity

Automation helps small businesses improve productivity levels by several notches. It frees up time for the marketer, the operations team, and the service team, and provides them with all the time needed to focus on core business activities or strategize better. For instance, Freedom Mortgage, a leading mortgage lender automated its loan origination process to validate borrowers within a few seconds. This equipped them with the capability of analysing several thousand applications in a day and cut down on loan closing pipelines. 

Conclusion

Web data crawling can be an invaluable asset for small businesses  only if they know how to leverage it to the hilt. Given that data scraping is both an art and science that requires expert programming skills, innovative methodologies, adequate mathematical expertise and scientific ingenuity, small businesses need to choose a proven expert to get the most out of this advanced data mining technique. 

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