The data sites you would need to extract data from is a pointer to the type of information you need. Many websites have security that prevents the extraction of data using blocking techniques. These techniques make use of geolocation-based restrictions, IP rate limitations, and fingerprinting. To go around this, you will need to make use of a proxy and your choice of a proxy would be determined by the sophistication of the site and the blocking technique employed by the target site.

1. GEO-LOCATION BASED RESTRICTIONS

Your IP address bears your location and websites make use of this to determine the location of a request. As product pricing and some other information vary based on location, websites use the IP information on the location to provide the relevant product pricing and other information to the visitor.

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A request from an IP that originates from a country that has been blocked by the site owner would not be given access to the site. Also, a request from a competitor IP could be blocked, or fed false information like increased product price. To get around this block, or prevent being fed with false data you need to make use of location-targeted IPs.

2. IP RATE LIMITATIONS

Rate limiting is used to distinguish human users from bots. It’s an anti-bot mechanism that recognizes bot activity and blocks the IP. They work by measuring the rate of requests from every IP in requests per minute and block IPs that send in too many requests quickly. With rotating proxies, you can rotate the IP address after every number of requests from your crawler. This rate isn’t fixed and depends on the target site and by working with the minimum rate of requests per IP, you can obtain data with speed without getting blocked due to IP rate limitations.

3. FINGERPRINTING

Fingerprinting makes use of techniques that utilize a lot of information about your device like the types of software installed, the languages used, screen resolution, type of protocols, HTTPS/TLS protocols, and a lot more. To overcome this limitation to data collection, you need to understand the target site and know the particular fingerprint technique they make use of. Different fingerprinting techniques require different approaches to overcome and here are types and ways to avoid blocks due to the different types of fingerprinting:

A . IP FINGERPRINTING

IP fingerprinting is the most common form of blocking technique used by websites. Limitations that make use of this technique include allowing only requests from certain geolocation to have access to the site, limiting IP actions by allowing only one account per IP and one purchase per IP. These restrictions are made by tracking the IP history which provides a lot of information including other requests that have been made using the IP.

Rate limiting is another way of blocking IP based on history. This bock is mostly to prevent crawlers from collecting data from the site and works by restricting the number of requests per IP in a given time frame.

To bypass IP fingerprint blocking, make use of a rotating proxy. This way your IP address gets rotated after several requests have been sent.

B. HEADER FINGERPRINTING

When using a crawler to send a request, your scraping code may sometimes send headers in an order that doesn’t mimic a real browser. This is usually the case especially when some techniques are employed as requests are sent to overcome some specific blocking methods used by the site. Websites check that browser header information is the same as that gotten during previous sessions. The most common way of using header fingerprinting is to check that the headers meet up to criteria set for user agent which includes the header case and order.

To overcome blocks by header fingerprinting, make sure that the headers and header case of the crawler match with the intended browser.

C. TLS/HTTP PROTOCOL FINGERPRINTING

Specific protocols and protocol versions are used by different browsers, and sites check if the right protocols and versions are being used. Doing this allows the target site to differentiate between requests from human users and requests from bots. For example, scrapers use HTTP/1.1, while human browsers use HTTP/2.2.

To overcome blocks due to this fingerprinting technique, make sure the protocol version you use is the same as that of your browser so that your requests will appear real.

D. CLIENT-SIDE FINGERPRINTING

This fingerprinting method takes note of the information in the user’s device. This information includes the set time zone, operating system, screen resolution, type of device, and other aspects of the browser. Put together, these data create a unique identity for the user and can be likened to the user’s fingerprint.

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Browsers like google chrome, Mozilla Firefox, and opera utilize webRTC to communicate between APIs. If not properly configured to send UDP traffic through the proxy you use, webRTC can leak your data and your real identity would be discovered. Completely disabling webRTC is suspicious and some sites would not let you in. in most cases, using a virtual machine can help you overcome this block, but as sites are different, overcoming client-side fingerprinting is different for each.

E. BEHAVIOR FINGERPRINTING

The security of sites inspects the actions of your browsing session for any abnormality. Normal behavior is human actions like cursor movements in a curve like way towards a button. The curve is important and a distinguishing feature between human users and bots because bots would go directly to the buttons and click. Other actions that are considered normal include scrolling through a page as machines do not scroll to get the required information but rather capture it directly.

To overcome a block due to behavior fingerprint, make sure your browser behavior during browsing sessions are normal. Abnormal behaviors trigger a captcha to prove that you are human, or could get your IP blocked from the site.

Overcoming blocking techniques used by websites is mostly easy but some sites make use of sophisticated methods and in such cases, a third party may be required to be sure a thorough job is done.

The type of data to be collected and the purpose of data collection are a major determinant of the type of IPs that would be required. Below are some of the common types of IPs and their uses:

1 .DATA CENTER IPS

Datacenter IPs are machine-generated from a data server or data farm. They are the cheapest types of proxies and can have location targeting. These types of IPs are useful for extracting web data and for market research.

2. RESIDENTIAL IPS

A residential IP is owned by a person who has volunteered to let a proxy network make use of their IP when it's idle. Using such IPs have all the features of a regular customer visiting a site. If accuracy is very important, residential proxies are used and such situations are in ads verification, accumulating price comparison information, and travel aggregation. Residential IPs are a great solution to blocks by IP rates as they come in pools and are charged per GB, giving you unlimited rotation.

3. MOBILE IPS

Mobile IPs are similar to residential IPs and are the 3G and 4G connections mobile IP owners make use of when they choose a network. Mobile IPs are needed for the verification of direct billing campaigns and app promotions. Mobile IPs come in pools and allow continuous rotation and a payment plan per GB.

1 . OUTSOURCING FOR THE REQUIRED DATA

The services of a third-party company that gathers intelligence can be employed to obtain the data for you. What you need to make available to them are the target sites and the data sets you are looking at. The disadvantage of collecting data this way is that the same data you are given may be the same data that is sold to other companies, including your competitors.

2. IN-HOUSE TEAM AND PROXY INFRASTRUCTURE

This is another method of data collection that requires a data extraction team to set up a proxy infrastructure, develop the crawlers, and maintain the collection of required data. This is an expensive method and not a very easy one to manage because it has a lot going on that all have to work at the same time while adapting to changes that occur on the web.

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3. IN-HOUSE TEAM USING AN EXTERNAL PROXY NETWORK

Instead of having to set up and maintain their proxies, a data extraction team could pay for proxy services. These proxy services will provide the team with tools that will make the process of extracting data highly successful even if the target sites are sophisticated.

4. USING THE SERVICES OF A PROXY NETWORK THAT ALSO PROVIDES DATA COLLECTION SERVICES

Many available proxy service providers also provide data collection services which include providing a crawler, and the proxy infrastructure. Collecting data this way provides you with the most accurate available data by utilizing various networks and IPs.

5. AUTOMATED DATA COLLECTION

The data collection automation tool was produced in response to the high rise in the need to easily collect a large amount of accurate data from the web. The automation tool takes into consideration, the target site and the type of blocking technique it uses, and this information in combination with an advanced proxy infrastructure overcomes any hindrance to your collection of accurate data. All users have to do is send an API that contains the information they need and they will receive that information in the format they want.

Accurate data is very important in businesses. The best way to satisfy your customers is by having good information about them that lets you understand their needs and interests. Having this understanding allows you to create products and services that they need and that also exceeds their expectations. To do this, data has to be first collected, but what are the data collection methods that provide you with accurate information?

One of the important collection tools is the data management platform (DMP). It goes further to help with organizing, analyzing, and also activating data. With DMP, you have tools at your disposal that will help you get the best out of your collected data.

Primary data refers to data that you source for by yourself rather than that which was collected by a third party. This means you are the first to come in contact with such data, as you are getting it directly from the source. First-party data is a form of primary data and is the type businesses collect about their customers. First-party data is gotten directly from the customers and could include data from online properties, data in relationship management systems belonging to your customers, or offline data you get through surveys and others.

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First-party data is different from the second and third part data second-party data is another company’s first-party data. It can be purchased so you must know that you may not be the only one making use of it. Third-party data is that which data collection services have obtained from various sources and typically has a large number of data points. No other type of data is as accurate and trustworthy as first-party data because you collected that yourself.

Second-party data can also be trusted in its accuracy because it comes from a source and you can benefit from the additional insights it brings that are absent in first-party data. The benefit of third party data is the large scale it has compared to the others.

Different types of data can be used in different situations, and they can also be used together. In any analysis, first-party data of course would be the base of your dataset. If the first-party data is however limited, then you can make up for the inadequacies with second or third party data. Merging all types of data allows you to deal with a larger scale of audience, and makes it possible to meet new audiences.

Primary data can be further divided into quantitative data, and qualitative data.

1. QUANTITATIVE DATA

Quantitative data is in number form, and also comes as quantities and values. It describes entities in measurable terms and examples include the number of passengers that booked a flight, the time a visitor spent on your webpage, and also the customer rating for your product out of 5 stars.

Quantitative data is easily analyzed due to its measurable and numeric nature. During the analysis of quantitative data, you may find some information that gives you a better understanding of your customers. In terms of reliability, you can count on quantitative data as it’s very objective.

2. QUALITATIVE DATA

Unlike quantitative data that’s numeric, qualitative data is rather a description. It’s not easily measurable and less concrete, and may also have some opinions and descriptive phrases in it. Some examples of qualitative data include online reviews from customers about a product and a conversation between a customer and a customer service agent.

Qualitative data helps a company understand the ‘why’ behind the information gotten from the quantitative data. And so quantitative data must act as the base of your dataset.

Since quantitative data is foundational, the steps discussed here will focus more on how to collect quantitative data. Even though there are different methods for collecting the different types of quantitative data, there’s a fundamental process that must be followed despite the data that is to be collected and it includes:

1. DETERMINE THE TYPE OF INFORMATION TO BE COLLECTED

Before collecting any data, you need to first decide on what you would be collecting. You need to be straight on the topics that would be relevant to you, the source of the data, and how much data you would have to collect. The purpose of the data collection will help you in answering the above questions.

2. SET A TIMEFRAME FOR DATA COLLECTION

After you have made up your mind on the type of data to collect and the details it would contain, you need to make a plan on how to collect it. Part of your plan should include a timeframe to collect the data. Depending on the data, you may want to collect continuously or set up a tracking method for collecting data over a long time. If data racking is for a specific campaign, then it would be over a set period, and in cases like this, you will need time to begin and a time to end.

3. CHOOSE THE APPROPRIATE METHOD FOR COLLECTING DATA

Choosing the data collection method is important and it will be your data gathering strategy. As they are a lot of methods to choose from, choosing the right one comes down to the type of data you intend to collect, the duration you have in mind to collect it, and other factors you have considered.

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4. COLLECT THE DATA

After all, plans have been made, what’s left is the collection proper. In this stage you will need to follow your plan and work based on your laid-out strategy. Collected data can be organized and stored in your DMP and always check for your progress intermittently as you move forward. You may want to include a schedule in your plan for checking your progress and this is especially important if you are continuously collecting data. Even though you have to stick to your strategy, it’s not unwise to make updates and some alteration to the plan depending on the conditions you meet.

5. ANALYZE COLLECTED DATA

After all, data have been collected, it’s time to analyze and organize the information you have gathered. This is a very important step as this phase turns the raw collected data into valuable insights for all decisions to be made including marketing strategies. The DMP has analytics tools that can help you and once patterns have been uncovered and decisions made, you can implement them to improve the standing of your company.

You have goals to be met and you need data to help achieve these goals, but how do you go about the data collection? Different methods exist to help you collect primary quantitative data and some involve a direct conversation with customers, monitoring customers as you have conversations with them, and also observing their behaviors. There is no one perfect method to use in data collection and the one you choose would depend on the type of data you are collecting and what you wish to use it for.

1 . SURVEYS

If you are considering collecting information directly from customers, you can ask them to take a survey and this way obtain the information you need. A survey is a method that can be used to collect either quantitative or qualitative data or even both. With surveys, the respondent answers in one or two words, and the answer options are often provided by you. Surveys are very convenient and can be conducted online, over the phone, and even via email.

2. ONLINE TRACKING

Your website and app can be very helpful in tracking customer’s online activity and in collecting data. For instance, when someone visits your site, you get 40 data points. Such data allows you to know the number of site visitors you’ve had, how long they spend on your site, what they clicked on, and others. Your hosting service provider can collect this information for you, and you can also make use of analytics software to collect the data. Another way to track customer behavior is by placing pixels on your site and read cookies.

3. TRANSACTIONAL DATA TRACKING

It doesn’t matter the location of your market place, having transactional data can provide useful insights about your business and customers by extension. Transactional data gives you information on things like the number of sold products, the most popular and most sold products, the frequency of purchases you get, and others like this.

4. ONLINE MARKETING ANALYTICS

Valuable data can also be gotten from marketing campaigns like ads. The ads software will provide you with information like who clicked your ads, the number of times they clicked, the devices they used, and more. You can even obtain data from offline marketing campaigns like asking your customers how they got to know about your brand.

5. SOCIAL MEDIA MONITORING

Another way to collect data is by monitoring your business pages on social media platforms. By checking your list of followers for instance, you can figure out what they all share in common and this will help you to determine your target audience. You can also monitor the number of times your brand was mentioned in posts. Many social media platforms will provide you with posts analytics, but using third party software tools will give you deeper insights.

6. BY COLLECTING SUBSCRIPTION AND REGISTRATION DATA

Asking for data as you offer your customers something in return is an effective way to collect data that will help you improve your brand. An example of this is by asking for some information to customers or visitors to your site as they sign up for your email list, rewards program, or something similar.

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This method is particularly beneficial because most leads here are highly likely to convert. When creating the forms meant to collect the information however, know just how far to go without scaring off your customers. Asking for too much may discourage any form of participation, and asking for too little will provide you with inadequate data for your analysis.

7. MONITOR IN-STORE TRAFFIC

If yours is a brick and mortar store, you can also monitor the traffic there to help you with useful insights. Keeping track of the number of people who come into your store will let you know your busiest day and busiest time of the day too. It may also tell you what it is that brings in customers the most at such times. Installing cameras is another way of gathering information as you will get to know the most popular part of your store.

Data collection is a very important process in the growth of your business and brand. It helps you in the decision-making process, and the more high-quality and relevant the data you collect is, the more intelligent the choices you make will be especially when it concerns product development, sales, marketing, customer service, and more. Uses of data collection include the following:

1. IT IMPROVES YOUR UNDERSTANDING OF YOUR TARGET AUDIENCE

Understanding your customers will help you tailor your services in a way that will satisfy their needs, and meet their expectations. This is not easy especially if you have a large company and deal with a lot of customers. By collecting data from every customer, you can have a better understanding of your target audience and use it to improve your brand. By directly getting information from your customers, you can find out who your customers are and what their interest in your company is.

2. IT ALLOWS YOU TO IDENTIFY AREAS THAT REQUIRE IMPROVEMENT

By collecting the right information and analyzing the data you have, you can identify the areas where your business is doing well, and areas that need improvement. For example, transactional data can point out which of your products are most popular and sell out quickly, and which ones do not sell much. With such information, you can focus more on your best selling products and improve on it. You can even go further to produce similar products. Data collection also gives you insights on customer complaints about products and allows you to improve on them.

You can also productively expand your business by collecting data. If you run an online store for example and are considering opening a physical store, the data you collect will guide your choice of location based on where most of your customers reside.

3. PREDICT PATTERNS

With proper analysis of collected data, you can predict upcoming trends and better prepare for them. For example, if you own a website and you study the data, you may find that videos are becoming more popular as compared to articles. This pointer to the upcoming trend will trigger you to put in more resources into making more videos and fewer articles. You can also take note of what people tend to prefer at different times and make provision for those at the appropriate time. For instance, you may discover that people love bright colors in the summer and springtime, and prefer dark colors during winter and fall. This information will guide you to make the right choice of clothes available at those times.

4. IMPROVES PERSONALIZATION

Having good information about target audience allows you to tailor the messages you send to them to their specific needs and interests. In marketing products, data collection can be useful to design ads that are specific to your target audience. For instance, you intend to advertise a new brand of cereal from your company. Your customer data can show the age range of people who consume cereals the most and if that age range falls between 20 and 30, actors within that age range could be used for the ads for best results.