Thursday, 30 April 2015

Lawyers & Attorneys Website Data Scraping Services

There are so many instances where one end’s up needing information from lawyers or bar associations. However, if you approach them directly or look for other ways to get information it might either be difficult or you might not get the information you are looking for. Thus, the best way to go about the scraping lawyer data.

Scraping lawyer data allow you to get information from various attorney websites, bar association websites, or other related websites. Using web scraping tools for getting such information makes it much easier to get all the relevant and important information without actually having to worry about the same.

If you wish to scrape data from lawyer, you are entitled to information such as lawyer name, firm names, address, contact details, history about the lawyers, educational qualifications, the bar association they are part of and much more.

Scraping lawyer data ensure that you also have images of the lawyer you are concentrating on. The result of scrape data form lawyer can be obtained in any format the user wants such as csv, excel, MySql etc. Scraping lawyer data also ensures that none of the information provided are repetitive or redundant.

If you are in need of information regarding any lawyer such as their contact details, address etc. it could end up being a huge and difficult task to get it manually or physically. Thus, taking off the help of scraping tools would ensure that you get all the needed information without actually having to bother about anything at all. The presence of lots of attorney websites and the fact that more and more lawyers are moving to the internet makes getting information easy with the help of some great tools. Scraping data is a very useful and handy method in which one can get all the required and relevant information and that too in a very easy to read format, which makes the method even worthier.

There are quite a few tools or services that you can take help of to get lawyers data scraped. Most of these services also provide with a sample demo and that free of cost. From the sample one can decide if they wish to continue with the services or try some other services. Thus, if you want any information from attorney websites or information about any lawyers, data scraping is a great way to get the same.

Source: https://3idatascraping.wordpress.com/2014/03/18/lawyers-attorneys-website-data-scraping-services/

Tuesday, 28 April 2015

A Guide to Web Scraping Tools

Web Scrapers are tools designed to extract / gather data in a website via crawling engine usually made in Java, Python, Ruby and other programming languages.Web Scrapers are also called as Web Data Extractor, Data Harvester , Crawler and so on which most of them are web-based or can be installed in local desktops.

Its main purpose is to enable webmasters, bloggers, journalist and virtual assistants to harvest data from a certain website whether text, numbers, contact details and images in a structured way which cannot be done easily thru manual copy and paste method. Typically, it transforms the unstructured data on the web, from HTML format into a structured data stored in a local database or spreadsheet or automates web human browsing.

Web Scraper Usage

Web Scrapers are also being used by SEO and Online Marketing Analyst to pull out some data privately from the competitor’s website such as high targeted keywords, valuable links, emails & traffic sources that were also perform by SEOClerk, Google and many other web crawling sites.

Includes:

•    Price comparison
•    Weather data monitoring
•    Website change detection
•    Research
•    Web mash up
•    Info graphics
•    Web data integration
•    Web Indexing & rank checking
•    Analyze websites quality links

List of Popular Web Scrapers

There are hundreds of Web Scrapers today available for both commercial and personal use. If you’ve never done any web scraping before, there are basic

Web scraping tools like YahooPipes, Google Web Scrapers and Outwit Firefox extensions that it’s good to start with but if you need something more flexible and has extra functionality then,  check out the following:

HarvestMan [ Free Open Source]

HarvestMan is a web crawler application written in the Python programming language. HarvestMan can be used to download files from websites, according to a number of user-specified rules. The latest version of HarvestMan supports as much as 60 plus customization options. HarvestMan is a console (command-line) application. HarvestMan is the only open source, multithreaded web-crawler program written in the Python language. HarvestMan is released under the GNU General Public License.Like Scrapy, HarvestMan is truly flexible however, your first installation would not be easy.

Scraperwiki [Commercial]

Using a minimal programming you will be able to extract anything. Off course, you can also request a private scraper if there’s an exclusive in there you want to protect. In other words, it’s a marketplace for data scraping.

Scraperwiki is a site that encourages programmers, journalists and anyone else to take online information and turn it into legitimate datasets. It’s a great resource for learning how to do your own “real” scrapes using Ruby, Python or PHP. But it’s also a good way to cheat the system a little bit. You can search the existing scrapes to see if your target website has already been done. But there’s another cool feature where you can request new scrapers be built.  All in all, a fantastic tool for learning more about scraping and getting the desired results while sharpening your own skills.

Best use: Request help with a scrape, or find a similar scrape to adapt for your purposes.

FiveFilters.org [Commercial]   

Is an online web scraper available for commercial use. Provides easy content extraction using Full-Text RSS tool which can identify and extract web content (news articles, blog posts, Wikipedia entries, and more) and return it in an easy to parse format. Advantages; speedy article extraction, Multi-page support, has a Autodetection and  you can deploy  on the cloud server without database required.

Kimono

Produced by Kimono labs this tool lets you convert data to into apis for automated export.   Benjamin Spiegel did a great Youmoz post on how to build a custom ranking tool with Kimono, well worth checking out!

Mozenda [Commercial]

This is a unique tool for web data extraction or web scarping.Designed for easiest and fastest way of getting data from the web for everyone. It has a point & click interface and with the power of the cloud you can scrape, store, and manage your data all with Mozenda’s incredible back-end hardware. More advance, you can automate your data extraction leaving without a trace using Mozenda’s  anonymous proxy feature that could rotate tons of IP’s .

Need that data on a schedule? Every day? Each hour? Mozenda takes the hassle out of automating and publishing extracted data. Tell Mozenda what data you want once, and then get it however frequently you need it. Plus it allows advanced programming using REST API the user can connect directly Mozenda account.

Mozenda’s Data Mining Software is packed full of useful applications especially for sales people. You can do things such as “lead generation, forecasting, acquiring information for establishing budgets, competitor pricing analysis. This software is a great companion for marketing plan & sales plan creating.

Using Refine Capture tetx tool, Mozenda is smart enough to filter the text you want stays clean or get  the specific text or split them into pieces.

80Legs [Commercial]

The first time I heard about 80Legs my mind really got confused of what really this software does. 80Legs like Mozenda is a web-based data extraction  tool with customizable features:

•    Select which websites to crawl by entering URLs or uploading a seed list
•    Specify what data to extract by using a pre-built extractor or creating your own
•    Run a directed or general web crawler
•    Select how many web pages you want to crawl
•    Choose specific file types to analyze

80 legs offers customized web crawling that lets you get very specific about your crawling parameters, which tell 80legs what web pages you want to crawl and what data to collect from those web pages and also the general web crawling which can collect data like web page content, outgoing links and other data. Large web crawls take advantage of 80legs’ ability to run massively parallel crawls.

Also crawls data feeds and offers web extraction design services. (No installation needed)

ScrapeBox [Commercial]

ScrapeBox are most popular web scraping tools to SEO experts, online marketers and even spammers with its very user-friendly interface you can easily harvest data from a website;

•    Grab Emails
•    Check page rank
•    Checked high value backlinks
•    Export URLS
•    Checked Index
•    Verify working proxies
•    Powerful RSS Submission

Using thousands of rotating proxies you will be able to sneak on the competitor’s site keywords, do research on .gov sites, harvesting data, and commenting without getting blocked.

The latest updates allow the users to spin comments and anchor text to avoid getting detected by search engines.

You can also check out my guide to using Scrapebox for finding guest posting opportunities:

Scrape.it [Commercial]

Using a simple point & click Chrome Extension tool, you can extract data from websites that render in javascript. You can automate filling out forms, extract data from popups, navigate and crawl links across multiple pages, extract images from even the most complex websites with very little learning curve. Schedule jobs to run at regular intervals.

When a website changes layout or your web scraper stops working, scrape.it  will fix it automatically so that you can continue to receive data uninterrupted and without the need for you to recreate or edit it yourself.

They work with enterprises using our own tool that we built to deliver fully managed solutions for competitive pricing analysis, business intelligence, market research, lead generation, process automation and compliance & risk management requirements.

Features:

    Very easy web date extraction with Windows like Explorer interface

    Allowing you to extract text, images and files from modern Web 2.0 and HTML5 websites which uses Javascript & AJAX.

    The user could select what features they’re going to pay with

    lifetime upgrade and support at no extra charge on premium license

Scrapy [Free Open Source]

Off course the list would not be cool without Scrapy, it is a fast high-level screen scraping and web crawling framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing.

Features:

•         Design with simplicity- Just writes the rules to extract the data from web pages and let Scrapy crawl the entire web site. It can crawl 500 retailers’ sites daily.

•         Ability to attach new code for extensibility without having to touch the framework core

•         Portable, open-source, 100% Python- Scrapy is completely written in Python and runs on Linux, Windows, Mac and BSD

•         Scrapy comes with lots of functionality built in.

•         Scrapy is extensively documented and has an comprehensive test suite with very good code coverage

•         Good community and commercial support

 Cons: The installation process is hard to perfect especially for beginners

Needlebase [Commercial]

Many organizations, from private companies to government agencies, store their info in a searchable database that requires you navigate a list page listing results, and a detail page with more information about each result.  Grabbing all this information could result in thousands of clicks, but as long as it fits the same formula, Needlebase can do it for you.  Point and click on example data from one page once to show Needlebase how your site is structured, and it will use that pattern to extract the information you’re looking for into a dataset.  You can query the data through Needle’s site, or you can output it as a CSV or other file format of your choice.  Needlebase can also rerun your scraper every day to continuously update your dataset.

OutwitHub [Free]

This Firefox extension is one of the more robust free products that exists Write your own formula to help it find information you’re looking for, or just tell it to download all the PDFs listed on a given page.  It will suggest certain pieces of information it can extract easily, but it’s flexible enough for you to be very specific in directing it.  The documentation for Outwit is especially well written, they even have a number of tutorials for what you might be looking to do.  So if you can’t easily figure out how to accomplish what you want, investing a little time to push it further can go a long way.

Best use: more text

irobotsoft [Free}

This is a free program that is essentially a GUI for web scraping. There’s a pretty steep learning curve to figure out how to work it, and the documentation appears to reference an old version of the software. It’s the latest in a long tradition of tools that lets a user click through the logic of web scraping. Generally, these are a good way to wrap your head around the moving parts of a scrape, but the products have drawbacks of their own that makes them little easier than doing the same thing with scripts.

Cons: The documentation seems outdated

Best use: Slightly complex scrapes involving multiple layers.

iMacros [Free]

The  same ethos on how microsoft macros works, iMacros automates repetitive task.Whether you choose the website, Firefox extension, or Internet Explorer add-on flavor of this tool, it can automate navigating through the structure of a website to get to the piece of info you care about. Record your actions once, navigating to a specific page, and entering a search term or username where appropriate.  Especially useful for navigating to a specific stock you care about, or campaign contribution data that’s mired deep in an agency website and lacks a unique Web address.  Extract that key piece (pieces) of info into a usable form.  Can also help convert Web tables into usable data, but OutwitHub is really more suited to that purpose.  Helpful video and text tutorials enable you to get up to speed quickly.

Best use: Eliminate repetition in navigating to a particular datapoint in a website that you’re checking up on often by recording a repeatable action that pulls the datapoint out of the clutter it’s naturally surrounded by.

InfoExtractor [Commercial]

This is a neat little web service that generates all sorts of information given a list of urls. Currently, it only works for YouTube video pages, YouTube user profile pages, Wikipedia entries, Huffingtonpost posts, Blogcatalog blog posts and The Heritage Foundation blog (The Foundry). Given a url, the tool will return structured information including title, tags, view count, comments and so on.

Google Web Scraper [Free]

A browser-based web scraper works like Firefox’s Outwit Hub, it’s designed for plain text extraction from any online pages and export to spreadsheets via Google docs. Google Web Scraper can be downloaded as an extension and you can install it in your Chrome browser without seconds. To use it: highlight a part of the webpage you’d like to scrape, right-click and choose “Scrape similar…”. Anything that’s similar to what you highlighted will be rendered in a table ready for export, compatible with Google Docs™. The latest version still had some bugs on spreadsheets.

Cons: It doesn’t work for images and sometimes it can’t perform well on huge volume of text but it’s easy and fast to use.


Tutorials:

Scraping Website Images Manually using Google Inspect Elements

The main purpose of Google Inspect Elements is for debugging like the Firefox Firebug however, if you’re flexible you can use this tool also for harvesting images in a website. Your main goal is to get the specific images like web backgrounds, buttons, banners, header images and product images which is very useful for web designers.

Now, this is a very easy task. First, you will definitely need to download and install the Google Chrome browser in your computer. After the installation do the following:

1. Open the desired webpage in Google Chrome

2. Highlight any part of the website and right click > choose Google Inspect Elements

3. In the Google Inspect Elements, go to Resources tab

4. Under Resources tab, expand all folders. You will eventually see script folders and IMAGES folders

5. In the Images folders, just use arrow keys to find the images you need to have (see the screenshot above)

6. Next, right click the images and choose Open the Image in New Tab

7. Finally, right click the image > choose Save Image As… . (save to your local folder)

You’re done!

How to Extract Links from a Web Page with OutWit Hub

In this tutorial we are going to learn how to extract links from a webpage with OutWit Hub.

Sometimes it can be useful to extract all links from a given web page. OutWit Hub is the easiest way to achieve this goal.

1. Launch OutWit Hub

If you haven’t installed OutWit Hub yet, please refer to the Getting Started with OutWit Hub tutorial.

Begin by launching OutWit Hub from Firefox. Open Firefox then click on the OutWit Button in the toolbar.

If the icon is not visible go to the menu bar and select Tools -> OutWit -> OutWit Hub

OutWit Hub will open displaying the Web page currently loaded on Firefox.


2. Go to the Desired Web Page

In the address bar, type the URL of the Website.

Go to the Page view where you can see the Web page as it would appear in a traditional browser.

Now, select “Links” from the view list.

In the “Links” widget, OutWit Hub displays all the links from the current page.

If you want to export results to Excel, just select all links using ctrl/cmd + A, then copy using ctrl/cmd + C and paste it in Excel (ctrl/cmd + V).

Source: http://www.garethjames.net/a-guide-to-web-scrapping-tools/

Sunday, 26 April 2015

I Don’t Need No Stinking API: Web Scraping For Fun and Profit

If you’ve ever needed to pull data from a third party website, chances are you started by checking to see if they had an official API. But did you know that there’s a source of structured data that virtually every website on the internet supports automatically, by default?

scraper toolThat’s right, we’re talking about pulling our data straight out of HTML — otherwise known as web scraping. Here’s why web scraping is awesome:

Any content that can be viewed on a webpage can be scraped. Period.

If a website provides a way for a visitor’s browser to download content and render that content in a structured way, then almost by definition, that content can be accessed programmatically. In this article, I’ll show you how.

Over the past few years, I’ve scraped dozens of websites — from music blogs and fashion retailers to the USPTO and undocumented JSON endpoints I found by inspecting network traffic in my browser.

There are some tricks that site owners will use to thwart this type of access — which we’ll dive into later — but they almost all have simple work-arounds.

Why You Should Scrape

But first we’ll start with some great reasons why you should consider web scraping first, before you start looking for APIs or RSS feeds or other, more traditional forms of structured data.

Websites are More Important Than APIs

The biggest one is that site owners generally care way more about maintaining their public-facing visitor website than they do about their structured data feeds.

We’ve seen it very publicly with Twitter clamping down on their developer ecosystem, and I’ve seen it multiple times in my projects where APIs change or feeds move without warning.

Sometimes it’s deliberate, but most of the time these sorts of problems happen because no one at the organization really cares or maintains the structured data. If it goes offline or gets horribly mangled, no one really notices.

Whereas if the website goes down or is having issues, that’s a more of an in-your-face, drop-everything-until-this-is-fixed kind of problem, and gets dealt with quickly.

No Rate-Limiting

Another thing to think about is that the concept of rate-limiting is virtually non-existent for public websites.

Aside from the occasional captchas on sign up pages, most businesses generally don’t build a lot of defenses against automated access. I’ve scraped a single site for over 4 hours at a time and not seen any issues.

Unless you’re making concurrent requests, you probably won’t be viewed as a DDOS attack, you’ll just show up as a super-avid visitor in the logs, in case anyone’s looking.

Anonymous Access

There are also fewer ways for the website’s administrators to track your behavior, which can be useful if you want gather data more privately.

With APIs, you often have to register to get a key and then send along that key with every request. But with simple HTTP requests, you’re basically anonymous besides your IP address and cookies, which can be easily spoofed.

The Data’s Already in Your Face

Web scraping is also universally available, as I mentioned earlier. You don’t have to wait for a site to open up an API or even contact anyone at the organization. Just spend some time browsing the site until you find the data you need and figure out some basic access patterns — which we’ll talk about next.

Let’s Get to Scraping

So you’ve decided you want to dive in and start grabbing data like a true hacker. Awesome.

Just like reading API docs, it takes a bit of work up front to figure out how the data is structured and how you can access it. Unlike APIs however, there’s really no documentation so you have to be a little clever about it.

I’ll share some of the tips I’ve learned along the way.

Fetching the Data

So the first thing you’re going to need to do is fetch the data. You’ll need to start by finding your “endpoints” — the URL or URLs that return the data you need.

If you know you need your information organized in a certain way — or only need a specific subset of it — you can browse through the site using their navigation. Pay attention to the URLs and how they change as you click between sections and drill down into sub-sections.

The other option for getting started is to go straight to the site’s search functionality. Try typing in a few different terms and again, pay attention to the URL and how it changes depending on what you search for. You’ll probably see a GET parameter like q= that always changes based on you search term.

Try removing other unnecessary GET parameters from the URL, until you’re left with only the ones you need to load your data. Make sure that there’s always a beginning ? to start the query string and a & between each key/value pair.

Dealing with Pagination

At this point, you should be starting to see the data you want access to, but there’s usually some sort of pagination issue keeping you from seeing all of it at once. Most regular APIs do this as well, to keep single requests from slamming the database.

Usually, clicking to page 2 adds some sort of offset= parameter to the URL, which is usually either the page number or else the number of items displayed on the page. Try changing this to some really high number and see what response you get when you “fall off the end” of the data.

With this information, you can now iterate over every page of results, incrementing the offset parameter as necessary, until you hit that “end of data” condition.

The other thing you can try doing is changing the “Display X Per Page” which most pagination UIs now have. Again, look for a new GET parameter to be appended to the URL which indicates how many items are on the page.

Try setting this to some arbitrarily large number to see if the server will return all the information you need in a single request. Sometimes there’ll be some limits enforced server-side that you can’t get around by tampering with this, but it’s still worth a shot since it can cut down on the number of pages you must paginate through to get all the data you need.

AJAX Isn’t That Bad!

Sometimes people see web pages with URL fragments # and AJAX content loading and think a site can’t be scraped. On the contrary! If a site is using AJAX to load the data, that probably makes it even easier to pull the information you need.

The AJAX response is probably coming back in some nicely-structured way (probably JSON!) in order to be rendered on the page with Javscript.

All you have to do is pull up the network tab in Web Inspector or Firebug and look through the XHR requests for the ones that seem to be pulling in your data.

Once you find it, you can leave the crufty HTML behind and focus instead on this endpoint, which is essentially an undocumented API.

(Un)structured Data?

Now that you’ve figured out how to get the data you need from the server, the somewhat tricky part is getting the data you need out of the page’s markup.

Use CSS Hooks

In my experience, this is usually straightforward since most web designers litter the markup with tons of classes and ids to provide hooks for their CSS.

You can piggyback on these to jump to the parts of the markup that contain the data you need.

Just right click on a section of information you need and pull up the Web Inspector or Firebug to look at it. Zoom up and down through the DOM tree until you find the outermost <div> around the item you want.

This <div> should be the outer wrapper around a single item you want access to. It probably has some class attribute which you can use to easily pull out all of the other wrapper elements on the page. You can then iterate over these just as you would iterate over the items returned by an API response.

A note here though: the DOM tree that is presented by the inspector isn’t always the same as the DOM tree represented by the HTML sent back by the website. It’s possible that the DOM you see in the inspector has been modified by Javascript — or sometime even the browser, if it’s in quirks mode.

Once you find the right node in the DOM tree, you should always view the source of the page (“right click” > “View Source”) to make sure the elements you need are actually showing up in the raw HTML.

This issue has caused me a number of head-scratchers.

Get a Good HTML Parsing Library

It is probably a horrible idea to try parsing the HTML of the page as a long string (although there are times I’ve needed to fall back on that). Spend some time doing research for a good HTML parsing library in your language of choice.

Most of the code I write is in Python, and I love BeautifulSoup for its error handling and super-simple API. I also love its motto:

    You didn’t write that awful page. You’re just trying to get some data out of it. Beautiful Soup is here to help. :)

You’re going to have a bad time if you try to use an XML parser since most websites out there don’t actually validate as properly formed XML (sorry XHTML!) and will give you a ton of errors.

A good library will read in the HTML that you pull in using some HTTP library (hat tip to the Requests library if you’re writing Python) and turn it into an object that you can traverse and iterate over to your heart’s content, similar to a JSON object.

Some Traps To Know About

I should mention that some websites explicitly prohibit the use of automated scraping, so it’s a good idea to read your target site’s Terms of Use to see if you’re going to make anyone upset by scraping.

For two-thirds of the website I’ve scraped, the above steps are all you need. Just fire off a request to your “endpoint” and parse the returned data.

But sometimes, you’ll find that the response you get when scraping isn’t what you saw when you visited the site yourself.

When In Doubt, Spoof Headers

Some websites require that your User Agent string is set to something they allow, or you need to set certain cookies or other headers in order to get a proper response.

Depending on the HTTP library you’re using to make requests, this is usually pretty straightforward. I just browse the site in my web browser and then grab all of the headers that my browser is automatically sending. Then I put those in a dictionary and send them along with my request.

Note that this might mean grabbing some login or other session cookie, which might identify you and make your scraping less anonymous. It’s up to you how serious of a risk that is.

Content Behind A Login

Sometimes you might need to create an account and login to access the information you need. If you have a good HTTP library that handles logins and automatically sending session cookies (did I mention how awesome Requests is?), then you just need your scraper login before it gets to work.

Note that this obviously makes you totally non-anonymous to the third party website so all of your scraping behavior is probably pretty easy to trace back to you if anyone on their side cared to look.

Rate Limiting

I’ve never actually run into this issue myself, although I did have to plan for it one time. I was using a web service that had a strict rate limit that I knew I’d exceed fairly quickly.

Since the third party service conducted rate-limiting based on IP address (stated in their docs), my solution was to put the code that hit their service into some client-side Javascript, and then send the results back to my server from each of the clients.

This way, the requests would appear to come from thousands of different places, since each client would presumably have their own unique IP address, and none of them would individually be going over the rate limit.

Depending on your application, this could work for you.

Poorly Formed Markup

Sadly, this is the one condition that there really is no cure for. If the markup doesn’t come close to validating, then the site is not only keeping you out, but also serving a degraded browsing experience to all of their visitors.

It’s worth digging into your HTML parsing library to see if there’s any setting for error tolerance. Sometimes this can help.

If not, you can always try falling back on treating the entire HTML document as a long string and do all of your parsing as string splitting or — God forbid — a giant regex.

Source: https://blog.hartleybrody.com/web-scraping/

Wednesday, 22 April 2015

Hand Scraped Flooring For a Natural and Unique Look

An option in hardwood flooring that is being increasingly adopted by those looking for something new, innovative and unique for their homes is hand scraped flooring. This type of wood flooring helps one achieve a distinct natural look on one's floor and also has a couple of advantages.

There are three types of scraping that you can get done on your wooden flooring: light, medium and hard. Preferably, if you have a light colored woodwork, then you should go for light scraping and if your floor has a darker shade, then you should opt for hard scraping. But, irrespective of the type of scraping you go for, you must ensure that the laborers doing the scraping are very skilled and impeccable in their job as hand scraping floors is an art that demands patience, time, talent and hard work.

Nowadays, many people tend to go for machine scraping, attracted by the lower investment involved in it. But such people are unable to achieve the requisite natural effect on their floors as machines create patterns on the floors that are easily detectable. These patterns do not emerge with hand scraping and the consequent look is as random and unique as it gets.

Though such scraped flooring is a costly option in flooring, it demands little maintenance. While with perfectly smooth surfaces, you will be always on the edge ensuring that there are no scratches, with hand scraped floors, you will not have to be concerned about this as any new scratches will only add to the already distressed appearance of the flooring.

Prefinished hand scraped wood flooring is also available in the market nowadays. These eliminate the need of any on-site scraping. But this option is of course unsuitable for those who have already got their floors installed. As it is, if you get on-site scraping done, you will have more control over things as you would be able to see the scraping as it develops and would be therefore in a position to exercise your preferences more.

Source: http://ezinearticles.com/?Hand-Scraped-Flooring-For-a-Natural-and-Unique-Look&id=4581623

Saturday, 18 April 2015

Data Mining and Predictive Analysis

Data collection and curing is the core foundation of most businesses. Database building thus is an important function and activity where enterprises invest heavily. With information now available on the Internet and easily obtained, it raises the importance of having professionals who crawl data and offer web scraping services.

Once the data is accessed, though, it is important to filter out the relevant data based on the business need. Although Many DaaS provider convert the unstructured web data into meaningful structured data it is recommended to be internally equipped to use the data to its maximum.

This understanding has given rise to the field of Data Mining. Data Mining is designed to explore large amounts of data in search of consistent patterns and connections between the variables and validate the findings by applying the detected patterns to the new sets of the data. Once these connections are established and understood, the end goal is to be able to predict the possible outcomes using predictive analysis techniques.

Together, both Data Mining and predictive analysis aid in making marketing campaigns more efficient. While predictive analysis helps simulate and understand what may happen, data mining helps identify exciting data patterns and connections.

The process of Data Mining and Predictive analysis consists of 3 steps

Exploration


Once a database is compiled, it needs to be cleaned, analysed and potential connections need to be built. This process involves filtering the relevant data and identifying the possible predictors. Data Exploration also sets a premise for preliminary feature selection to manage number of variables. This data is then prepared for statistical analysis using a wide variety of graphical and statistical parameters. This helps identify the most relevant variables and setups the predictive models to be built.

Data mining process

Validation


Next comes building various models and choosing the most relevant ones. This decision is based on their possible predictive performance and of being able to produce stable results across all the samples. Simple as it sounds, to truly get the results, all possible models must be treated with data to simulate scenarios. The model with most stable statistical feature is validated.

Application

Once the relevant models are finalised, the same is applied to new data to understand and predict the estimated outcomes. Application of data models is an ongoing and complex process since every new dataset needs to be configured in the model.

Data Mining and predictive analysis essentially involves blending statistical methodology where the traditional statistics machine learning and complex algorithms. This greatly increases the need for efficient and skilled data handlers. This could include data analysts and scientists.

See how you can become data scientist here:

Data crunchers use data mining and predictive analysis actively to get an edge in the big data management. Database platforms like Hadoop assist in database management and large-scale distribution. But the costs involved in setting up data centres and big data management capacity are high. Budgets allocated within the enterprise are more project-focussed and analytics budgets are usually limited. Quite often, big data and analytics project fail to launch because of this problem! The other problem is that to run effective predictive models, data requires to be handled by scientists with experience. Finding and setting together a technologically-advanced team is a daunting task most enterprises face outside the tech domain.

Predictive Analysis model

A predictive analysis model is essentially predicting the all possible outcomes from a given set of data. Here are a few steps that can be taken to help build and identify the “ideal” predictive analysis model. These steps more or less mirror the usual statistical methodology of building a test model.

Defining an objective

This is the first and a critical step. Unless the objective is identified and defined there can be no concrete results since there wouldn’t be clarity to compare the final outcome to the expected result. It also helps understand the scope of the project.

Preparing the data

This is more to do with data mining. Historic data used for training the model is scattered across multiple platforms and sources. To compound the problem, data can be unstructured with possible duplicate accounts and missing values! Data quality determines the quality of the model, and thus it becomes imperative that data is healthy and relevant.

Data Sampling

Once mined, Data is essentially split into 2 parts. One set is for training that is used to build the model and the second is the ‘test’ set that is used to verify the accuracy of the final output. This also helps identify and filter the noise component.

Model Building

Sampling cam equally result in a single algorithm or parallel & connected algorithms. In such a case the data goes through multiple testing and a decision is based on the final output.

Execution

Once a model gets finalised, the other teams in the organization need to be involved to build a deployable model and understand its impact on the overall business.

The possibilities with Data mining & Predictive analysis are huge. It also gives a huge room for learning and experimenting. There are several tools available in the industry to aid through all the steps of data mining and predictive analysis. The combination of human expertise and intellect along with the help of the available tools and the overall cooperation within the multiple channels within the organization essentially ensures a stronger grip on the ability to build a solid predictive model.

When used together, predictive analytics and data mining help marketing professionals anticipate and get ready for customer needs, rather than just reacting to them.

Source: https://www.promptcloud.com/blog/data-mining-and-predictive-analysis/

Tuesday, 7 April 2015

rvest: easy web scraping with R

rvest is new package that makes it easy to scrape (or harvest) data from html web pages, inspired by libraries like beautiful soup. It is designed to work with magrittr so that you can express complex operations as elegant pipelines composed of simple, easily understood pieces. Install it with:

install.packages("rvest")

rvest in action

To see rvest in action, imagine we’d like to scrape some information about The Lego Movie from IMDB. We start by downloading and parsing the file with html():

library(rvest)

lego_movie <- html("http://www.imdb.com/title/tt1490017/")

To extract the rating, we start with selectorgadget to figure out which css selector matches the data we want: strong span. (If you haven’t heard of selectorgadget, make sure to read vignette("selectorgadget") – it’s the easiest way to determine which selector extracts the data that you’re interested in.) We use html_node() to find the first node that matches that selector, extract its contents with html_text(), and convert it to numeric with as.numeric():

lego_movie %>%

  html_node("strong span") %>%

  html_text() %>%

  as.numeric()

#> [1] 7.9

We use a similar process to extract the cast, using html_nodes() to find all nodes that match the selector:

lego_movie %>%

  html_nodes("#titleCast .itemprop span") %>%

  html_text()

#>  [1] "Will Arnett"     "Elizabeth Banks" "Craig Berry"   

#>  [4] "Alison Brie"     "David Burrows"   "Anthony Daniels"

#>  [7] "Charlie Day"     "Amanda Farinos"  "Keith Ferguson"

#> [10] "Will Ferrell"    "Will Forte"      "Dave Franco"   

#> [13] "Morgan Freeman"  "Todd Hansen"     "Jonah Hill"

The titles and authors of recent message board postings are stored in a the third table on the page. We can use html_node() and [[ to find it, then coerce it to a data frame with html_table():

lego_movie %>%

  html_nodes("table") %>%

  .[[3]] %>%

  html_table()

#>                                              X 1            NA

#> 1 this movie is very very deep and philosophical   mrdoctor524

#> 2 This got an 8.0 and Wizard of Oz got an 8.1...  marr-justinm

#> 3                         Discouraging Building?       Laestig

#> 4                              LEGO - the plural      neil-476

#> 5                                 Academy Awards   browncoatjw

#> 6                    what was the funniest part? actionjacksin

Other important functions

•    If you prefer, you can use xpath selectors instead of css: html_nodes(doc, xpath = "//table//td")).

•    Extract the tag names with html_tag(), text with html_text(), a single attribute with html_attr() or all attributes with html_attrs().

•    Detect and repair text encoding problems with guess_encoding() and repair_encoding().

•    Navigate around a website as if you’re in a browser with html_session(), jump_to(), follow_link(), back(), and forward(). Extract, modify and submit forms with html_form(), set_values() and submit_form(). (This is still a work in progress, so I’d love your feedback.)

To see these functions in action, check out package demos with demo(package = "rvest").

Source: http://blog.rstudio.org/2014/11/24/rvest-easy-web-scraping-with-r/

Sunday, 5 April 2015

How to Generate Sales Leads Using Web Scraping Services

The first stage of any selling process is what is popularly known as “lead generation”. This phase is what most businesses place at the apex of their sales concerns. It is a driving force that governs decision-making at its highest levels, and influences business strategy and planning. If you are about to embark on an outbound sales campaign and are in the process of looking for leads, you would acknowledge the fact that lead generation process is of extreme importance for any business.

Different lead generation techniques have been used over and over again by companies around the world to satiate this growing business need. Newer, more innovative methods have also emerged to help marketers in this process. One such method of lead generation that is fast catching on, and is poised to play a big role for businesses in the coming years, is web scraping. With web scraping, you can easily get access to multiple relevant and highly customized leads – a perfect starting point for any marketing, promotional or sales campaign.

The prominence of Web Scraping in overall marketing strategy

At present, levels of competition have risen sky high for most businesses. For success, lead generation and gaining insight about customer behavior and preferences is an essential business requirement. Web scraping is the process of scraping or mining the internet for information. Different tools and techniques can be used to harvest information from multiple internet sources based on relevance, and the structured and organized in a way that makes sense to your business. Companies that provide web scraping services essentially use web scrapers to generate a targeted lead database that your company can then integrate into its marketing and sales strategies and plans.

The actual process of web scraping involves creating scraping scripts or algorithms which crawl the web for information based on certain preset parameters and options. The scraping process can be customized and tuned towards finding the kind of data that your business needs. The script can extract data from websites automatically, collate and put together a meaningful collection of leads for business development.

Lead Generation Basics

At a very high level, any person who has the resources and the intent to purchase your product or service qualifies as a lead. In the present scenario, you need to go far deeper than that. Marketers need to observe behavior patterns and purchasing trends to ensure that a particular person qualifies as a lead. If you have a group of people you are targeting, you need to decide who the viable leads will be, acquire their contact information and store it in a database for further action.

List buying used to be a popular way to get leads, but their efficacy has dwindled over time. Web scraping is the fast coming up as a feasible lead generation technique, allowing you to find highly focused and targeted leads in short amounts of time. All you need is a service provider that would carry out the data mining necessary for lead generation, and you end up with a list of actionable leads that you can try selling to.

How Web Scraping makes a substantial difference

With web scraping, you can extract valuable predictive information from websites. Web scraping facilitates high quality data collection and allows you to structure marketing and sales campaigns better. To drive sales and maximize revenue, you need strong, viable leads. To facilitate this, you need critical data which encompasses customer behavior, contact details, buying patterns and trends, willingness and ability to spend resources, and a myriad of other aspects critical to ascertain the potential of an entity as a rewarding lead. Data mining through web scraping can be a great way to get to these factors and identifying the leads that would make a difference for your business.

web-scraping-service

Crawling through many different web locales using different techniques, web scraping services pick up a wealth of information. This highly relevant and specialized information instantly provides your business with actionable leads. Furthermore, this exercise allows you to fine-tune your data management processes, make more accurate and reliable predictions and projections, arrive at more effective, strategic and marketing decisions and customize your workflow and business development to better suit the current market.

The Process and the Tools

Lead generation, being one of the most important processes for any business, can prove to be an expensive proposition if not handled strategically. Companies spend large amounts of their resources acquiring viable leads they can sell to. With web scraping, you can dramatically cut down the costs involved in lead generation and take your business forward with speed and efficiency. Here are some of the time-tested web scraping tools which can come in handy for lead generation –

•    Website download software – Used to copy entire websites to local storage. All website pages are downloaded and the hierarchy of navigation and internal links preserve. The stored pages can then be viewed and scoured for information at any later time.     Web scraper – Tools that crawl through bulk information on the internet, extracting specific, relevant data using a set of pre-defined parameters.

•    Data grabber – Sifts through websites and databases fast and extracts all the information, which can be sorted and classified later.

•    Text extractor – Can be used to scrape multiple websites or locations for acquiring text content from websites and web documents. It can mine data from a variety of text file formats and platforms.

With these tools, web scraping services scrape websites for lead generation and provide your business with a set of strong, actionable leads that can make a difference.

Covering all Bases

The strength of web scraping and web crawling lies in the fact that it covers all the necessary bases when it comes to lead generation. Data is harvested, structured, categorized and organized in such a way that businesses can easily use the data provided for their sales leads. As discussed earlier, cold and detached lists no longer provide you with enough actionable leads. You need to look at various factors and consider them during your lead generation efforts –

•    Contact details of the prospect

•    Purchasing power and purchasing history of the prospect

•    Past purchasing trends, willingness to purchase and history of buying preferences of the prospect

•    Social markers that are indicative of behavioral patterns

•    Commercial and business markers that are indicative of behavioral patterns

•    Transactional details

•    Other factors including age, gender, demography, social circles, language and interests

All these factors need to be taken into account and considered in detail if you have to ensure whether a lead is viable and actionable, or not. With web scraping you can get enough data about every single prospect, connect all the data collected with the help of onboarding, and ascertain with conviction whether a particular prospect will be viable for your business.

Let us take a look at how web scraping addresses these different factors –

1. Scraping website’s


During the scraping process, all websites where a particular prospect has some participation are crawled for data. Seemingly disjointed data can be made into a sensible unit by the use of onboarding- linking user activities with their online entities with the help of user IDs. Documents can be scanned for participation. E-commerce portals can be scanned to find comments and ratings a prospect might have delivered to certain products. Service providers’ websites can be scraped to find if the prospect has given a testimonial to any particular service. All these details can then be accumulated into a meaningful data collection that is indicative of the purchasing power and intent of the prospect, along with important data about buying preferences and tastes.

2. Social scraping

According to a study, most internet users spend upwards of two hours every day on social networks. Therefore, scraping social networks is a great way to explore prospects in detail. Initially, you can get important identification markers like names, addresses, contact numbers and email addresses. Further, social networks can also supply information about age, gender, demography and language choices. From this basic starting point, further details can be added by scraping social activity over long periods of time and looking for activities which indicate purchasing preferences, trends and interests. This exercise provides highly relevant and targeted information about prospects can be constructively used while designing sales campaigns.

Check out How to use Twitter data for your business

3. Transaction scraping


Through the scraping of transactions, you get a clear idea about the purchasing power of prospects. If you are looking for certain income groups or leads that invest in certain market sectors or during certain specific periods of time, transaction scraping is the best way to harvest meaningful information. This also helps you with competition analysis and provides you with pointers to fine-tune your marketing and sales strategies.

get-results-from-your-lead-generation-campaign

Using these varied lead generation techniques and finding the right balance and combination is key to securing the right leads for your business. Overall, signing up for web scraping services can be a make or break factor for your business going forward. With a steady supply of valuable leads, you can supercharge your sales, maximize returns and craft the perfect marketing maneuvers to take your business to an altogether new dimension.

Source: https://www.promptcloud.com/blog/how-to-generate-sales-leads-using-web-scraping-services/