Data is a crucial commodity, exceptionally so when it deals with the information of individuals who are a part of the best global professional networking platform: LinkedIn.
With over 850 million members, this professional social network is an asset for businesses. With proper execution, LinkedIn data mining services can help surface information on executives, managers, & decision-makers from different trades and aid multiple types of marketing campaigns through those insights. But, here’s the catch- LinkedIn does not openly support mining, there is a legal standpoint, and you need to maneuver that while adopting appropriate data mining techniques to get the data you want without risking a lawsuit or a big drop in your budget.
That’s where the need to outsource data mining for LinkedIn arises. Read on to know how LinkedIn scraping can benefit companies in improving marketing initiatives and why a business should turn to LinkedIn data mining companies for a sustainable, reasonable, and guarded data mining experience.
Table of Content
- Is LinkedIn Data Mining Legal?
- How Is LinkedIn Data Mining Beneficial For Business
- Advantages Of Outsourcing LinkedIn Data Mining Services
- How Is Outsourcing Better Than In-house Data Mining
- How To Find The Perfect LinkedIn Data Mining Company
- How Do Experts Mine Data On LinkedIn
- Leverage SunTec India’s Data Mining Services
Is LinkedIn Data Mining Legal?
According to LinkedIn’s user agreement, data mining or data scraping is prohibited for most of its data. However, the data that’s been made public by a user (or data that’s publicly accessible on LinkedIn) can be scraped.
It is important to note that despite having access to data in the public domain, LinkedIn does not make it easier to get insight-rich data. The network uses advanced tools to monitor APIs and crawlers, verify their identity, and prevent any response if it finds even a single aspect of the scraping tool suspicious. In such cases, inefficient or poorly designed data scraping bots may infringe on LinkedIn’s user agreement and invite legal action. That may be a risk even if you buy data from LinkedIn data scrapers.
Outsourcing LinkedIn data scraping services give businesses an advantage in this case. Professionals ensure that none of the rules get violated, the API designs are accurate, and they use a tested methodology that saves you from legal issues.
Leverage LinkedIn’s Professional Network’s Data for Your Business
How Is LinkedIn Data Mining Beneficial For Business
Data Mining can be crucial in business operations at different levels. It can reduce marketing investments and assist in sketching a focused sales plan. LinkedIn data mining can also help in predictive modeling, based on the analysis derived from the data. Companies can form strategies around growing market demands, user behavior, future trends, upcoming technologies, and such.
LinkedIn data mining can help you in the following ways.
1. Marketing Operations
It can provide specific leads for marketing initiatives, reducing time and investment on assumptions. This assists in coining effective campaigns. LinkedIn’s information on demography, occupation, spending capacity, hierarchy, etc, can be used to predict marketing strategies. This data can be crucial for market research, identifying new opportunities available.
2. Sales Operations
All major brands- be it Amazon, YouTube, Spotify, etc. -use data mining to deliver personalized sales pitches to users. Similarly for LinkedIn, the mined data can be analyzed to identify user preferences and needs. Once you have exact information on the requirement, decision-making, and spending capacity, it is fruitful to pitch sales offers.
3. Business Expansion
A clear strategy and vision are the key to any business expansion. LinkedIn data can assist in market analysis, identifying geographic regions for expansion, and also examine the grounds for any new launches. This data can provide insights into the market size, demographics, market share, industry dynamics, key competitors, etc,
Advantages Of Outsourcing LinkedIn Data Mining Services
Engaging a professional LinkedIn data mining company is the way to go (as compared to hiring in-house or freelance experts) because of many reasons. The following are the benefits of outsourcing data mining services.
1. Cost-Effective
Data scraping by an in-house team is a costly affair. It involves infrastructure and human resource costs. Contracting a LinkedIn data mining service company can save you from them. Outsourcing companies know the exact technicalities of this process and also have access to the latest technologies, tools, and practices used by the industry. Spending on the same in-house is expensive. On the other hand, while freelancers depend on fewer resources to save costs, their response time is long, and managing their performance and quality can become a nuisance.
2. Assured Security
LinkedIn data mining service companies are better equipped to keep your data safe as they follow multi-layer encryptions. Professional outsourcing firms follow strict protocols to keep client data secure. Maintaining data security in-house is an expensive task and requires strict monitoring too, but since data mining service providers are in the business, they already possess advanced systems for it. However, you must check data security certifications before handing over the task to any vendor.
3. Quick Turnaround
Outsourcing LinkedIn data mining saves a lot of time for businesses. The data service firms have all the necessary resources, infrastructure, and human resources to begin operations on the go. Most reputed service providers value deadlines and almost always deliver on or before time.
4. Quality Control
LinkedIn is a rich source of data. But, if the data experts are not clear on the objectives of the extraction and how it can meet business goals, all efforts will be in vain. In-house human resources need close monitoring for quality maintenance so that the goals are not missed, whereas if you outsource data mining for LinkedIn to professional firms, their focused process and dedicated manager can assist in easy quality control.
5. Multiple Format Output
LinkedIn data mining companies can offer you data outputs in a number of formats. Their skilled data professionals are equipped to present data in different formats or as desired by the client.
How Is Outsourcing Better Than In-house Data Mining
LinkedIn data mining can be managed in-house by hiring a team of professional data scientists, data analysts, and database experts. But, you will have to bear the cost of infrastructure, tools, software, and human resources.
Also, many companies that need LinkedIn data mining are not necessarily associated with data operations. In that case, recruiting and managing data experts can be challenging. In such cases, businesses have the option of outsourcing LinkedIn data mining services. Here are the major differences:
| In-house Data Mining | Outsourcing |
|---|---|
| Better control over data mining operations. | Experienced supervision of data mining operations. |
| Set data security level as desired. | Outsourcing companies follow a multi-layered encrypted data security system. |
| Ability to scale the team & operations up and down. | Professional data mining companies can upscale projects as desired. |
| Cost of managing infrastructure, human resources, software, and tools. | The Outsource agency bears the cost of infrastructure, human resources, software, and tools. |
| Less quality control. | The team consists of professionals to keep a check on the quality. |
| Involves supervision and management responsibility. | Supervision and management responsibility is on the hired agency. |
How To Find The Perfect LinkedIn Data Mining Company
Searching for the right outsourcing partner for LinkedIn data mining can be challenging. An inexperienced agency might lead the objectives to remain unfulfilled. The following steps will help you choose the best option:
1. Plan Your Data Demands And Its Goals
According to your company’s requirements, list your data mining goals. Based on these goals, also take note of the type of data you need from LinkedIn. For instance, if you are a corporate gift manufacturing company, your demand would be finding data on purchase officers of different companies and decision-makers. Your goal will be to pitch sales offers and packages to these contacts.
2. Search For Data Mining Companies
You can find LinkedIn data mining companies in online searches and advertisements. Look for reviews and client feedback. Review their ratings in company journals. It would be better to look for companies that have an experienced team of professional data mining experts that fit your demand area. Based on the findings, short-list the company names.
3. Analyze Their Capabilities
Next step will be to research the shortlisted company’s data mining capabilities. Identify what their team can do and what they need to do when looking for a suitable solution to your data needs. Also, determine if any tools or software provide a value proposition to help you meet this need. Read the company’s client reviews.
4. Discuss The Plan And Budget
Once you are done with the above steps, discuss packages and services with the companies in the final list. The goal should be to find the LinkedIn data mining services that suit you economically and meet your data demands at the same time. Check whether the plan is scalable and customizable, as you might have to improvise the demands with time.
How Do Experts Mine Data On LinkedIn
The data mining process involves using advanced analytics technology to find useful information in datasets. It involves collecting, filtering, deduplicating, and analyzing data. Professional LinkedIn data mining companies usually follow the following process for relevant and useful results:
1. Data Extraction
Relevant data is assembled from different LinkedIn accounts. All structured and unstructured data is collected in a data pool, through extraction. This process is also called data scraping. A number of tools are available to extract data from LinkedIn.
2. Data Filtering
The gathered data is refined by removing irrelevant information. To maintain the quality, data exploration, profiling, and pre-processing happen in this step. Then, the errors are fixed through data cleansing.
3. Data Indexing
It is the process of distributing data in segments as per the requirement and type of information. For instance, email and phone numbers in contact segments; and qualifications in education.
As these data sets are ready, the final mining process is initiated through the chosen relevant technology. The algorithms designed as per the requirement are applied to these data sets. The results obtained from that analysis are used in marketing and other business operations.
Post Data Mining, the following steps are carried out:
4. Data Archive
The analyzed and indexed data sets are then archived. This assures the availability of this information whenever required. The archived data sets are tagged as per their segments or time period or any unique identity, for the sake of recalling the requirement.
5. Database Set Up
These archived datasets can be used to set up a large database library, where all the archived data is stored. This is helpful in the case of big data storage.
Case Study
The Client
Client is an American corporate gift and accessories manufacturing company, based in California.
The Requirement
The client wanted to create a database from LinkedIn data. The client required the data to include contacts, qualifications, and hierarchy details. An analysis that could form the basis for a solid marketing plan was also needed.
Project Challenges
To assist the client in the development of a robust marketing strategy through the LinkedIn data, the following challenges were observed:
- Extract data of corporate employees in and around California, filter that data for decision-makers, and index it in the segments of contacts, qualification, and hierarchy.
- Extract data for events monthly, quarterly, and yearly corporate events in respective companies.
- Analyze the data to create a focused marketing strategy.
The Proposal
SunTec India offered this client a dedicated team of data experts and analysts. A dedicated project manager was also assigned to supervise, report, and take feedback from the client.
The Result
The client was extremely satisfied with the outcome. The database helped in the creation of a focused marketing plan and pitch contacts for sales.
Leverage SunTec India’s Data Mining Services
SunTec India has been a leading IT outsourcing company serving businesses from various trades and specializing in data services. Our team of skilled data experts has assisted firms from all around the globe with factual analysis of data that shaped marketing strategies.
Outsourcing LinkedIn data scraping services to SunTec India offer several advantages.
- Our data experts possess professional data extraction, analysis, and management skills.
- Our data mining team has experience in handling projects for varied clients from different industrial backgrounds all around the globe.
- We provide 24*7 assistance with data mining services
- Our data mining system is a fusion of automated and manual processes that gives an error-free output.
- Our customized data extraction services and solutions can save up to 60% of costs.
- Our professional data experts create exclusive and customized data extraction and analysis solutions.
- We provide a hundred percent data accuracy through dual validation and quality control.
- We have an excellent track record of meeting deadlines. As per the client’s requirement, we have even delivered projects in 24 hours.
- Our teams are led by dedicated project managers to ensure consistent monitoring, feedback, and support.
- We follow strict data security guidelines. Client data is encrypted to provide double-layered security.
