Data from Statista shows that there were almost 7 billion smartphone mobile network subscriptions in 2023. Most people on this planet have access to the internet right now. In a world where massive amounts of data are being created daily, it's only natural that businesses want to utilize it to improve their operations and chances of success.
However, in order to utilize data, you first need to determine what kind of data you need. There are many categories, ranging from satellite data to various types of business data.
In this article, you will learn all there is to know about B2B data and how to select and buy it.
How to buy data?
First and foremost, it's important to note that it's almost never sensible to buy a one-time list of business data that is not continuously monitored and refreshed with new data.
Data loses relevance fairly quickly and becomes inaccurate over time, therefore, one-time purchases might do more harm than good. In turn, inaccurate data can cost your business a fortune instead of giving an advantage. Unless you simply need a list of specific companies that exist now and it doesn’t matter to you whether new ones are founded or some of the existing ones go bankrupt.
What you should opt for instead is a data provider that updates and keeps the data fresh at all times. That way, you will be sure to have accurate data that you can use to conduct market research or use it in other ways to improve your business operations.
Statistics about buying data
The market is huge for high-quality data, and the statistics are here to back it up:
- 79% of businesses that surpass their revenue goals use customer data for enhanced marketing strategies;
- 91.6% of executives are investing in both big data and artificial intelligence to improve decision-making;
- 97.2% of companies invest in big data and AI, but only 24% use the data to inform decision-making.
The use of artificial intelligence (AI) and machine learning (ML) is becoming increasingly prevalent in data buying and analysis. These technologies enable businesses to analyze large amounts of data and identify patterns and insights that would be difficult or impossible to uncover using traditional methods.
Where to buy data?
To buy data, you can either:
- Browse a data marketplace
- Utilize web data collection services
- Find a data provider directly
Browse a data marketplace
Data marketplaces such as Datarade usually advertise many different data providers or datasets. You can find a list of options there and select the one that fits your needs the most. Usually, the platform provides information about data features, freshness, a description of the company, and more information that allows you to select a vendor.
Once you pick a dataset that meets your needs, you can purchase it directly from the marketplace or contact the vendor for more information.
Utilize web data collection services
If you don’t need loads of data and you don’t want to pay for an entire dataset, you can opt for APIs instead. With Coresignal’s Company API, Employee API, and Jobs API, your spend is based on the number of credits you use.
Web data collection is a difficult and resource-intensive process that requires a dedicated experienced team. Also, it should be mentioned that the most popular sources of business data are notoriously difficult to collect from.
Find a data provider directly
Another option is finding a data provider directly. One public web data provider that can help you build your data product or extract deep insights into investment opportunities is Coresignal. We can offer you broad coverage of over 3B public web data records from 20 sources, such as Indeed, Owler, and more. Talking about more, the data is always fresh so you won't have to worry about inaccuracies.
Also, we believe in data collection ethics and collect only publicly available data and only personal data that is related to businesses. We also do not gather contact data to prevent spam emails to the data subjects in our databases
One of the main issues with buying raw data is that you need to have an in-house data team to process and analyze it properly. In case you'd like to learn more, we have prepared a guide explaining how to prepare for working with public web data.
How to choose the right data solution for your business?
- Determine business goals. Define how the data would help you achieve your target goals, put a data strategy in place and identify high-impact areas that require data.
- Check competition. Research the tools and solutions that your competitors are using. It could help you better navigate the proverbial data waters and create new opportunities.
- Identify the end-user. Make sure that the data is relevant to the people in your business who will end up using it for analysis.
- Consider the costs. Data solutions vary greatly in price, quality, deliverability, and other aspects. Make sure that the data you get is the data you need. If you only need company data, then you shouldn't go for a large dataset that consists of companies, employees, and jobs. It will only boost your expenses. Look for a separate and cheaper dataset, instead.
All in all, choosing the right data solution for your business shouldn't be taken lightly. Not only is it going to cost you some money, but it will also affect your future business decisions. Therefore, take your time and analyze all your data needs and business goals related to them.
Advantages and disadvantages of data-buying
Scraping the data and buying it have their strengths and weaknesses. Overall, it all comes down to your project. Generally, scraping data provides more flexibility in the long run but will require a lot of resources upfront. While buying data might look like a larger investment, it ensures you will receive a high-quality dataset collected following all the regulatory guidelines.
Here is a quick comparison:
What is high-quality data?
High-quality data is clean, fresh, accurate, and deduplicated data that is ready to use for business operations. However, data changes all the time, therefore it's difficult to maintain its quality, especially if you're collecting the data on your own. It can be easy to get lost in duplicated, corrupted, and outdated data over time.
Clean data, without any corrupt or inaccurate records, will ensure that your decision-making is not impaired by low-quality, compromised data records.
If you're looking to buy data, you should always ask the data provider to give you a data sample at the very least. This way, you'll be able to see exactly what you're going to get, determine its potential, and see how it fits with your business goals.
Overall, it's better to rely on a data provider if you're looking for high-quality data. Otherwise, your decision-making will be prone to errors and may cost you a fortune in the long run. After all, business decisions based on low-quality data will be a lot less likely to return the results you expected. On the contrary, it may cause you to lose even more money and opportunities.
How do companies use purchased data?
There are a lot of ways that companies can use purchased data. For example, some industries that benefit the most from buying external data are investing, HR tech, and lead generation companies.
- Investors use external data to identify new investment opportunities, track company performance, identify expansion opportunities, and more.
- HR tech companies use external data to improve talent sourcing, enhance talent intelligence, build recruitment platforms, conduct labor market research, and more.
- Lead generation companies use external data to discover potential customers and personalize sales and marketing messages.
These are just a few examples of how companies in different industries can leverage external data for their benefit. Yours might be different, depending on your business goals.
Types of data you can buy
Business data breaks down into many different categories, some of which are:
- Firmographic data. Consists exclusively of company-related data, such as its name, size, website, location, industry, revenue, and more. You can use it to generate investment signals and conduct market research.
- Employee data. Consists of employee-related data, such as name, location, connections, job title, company name, education, and more. You can use it to source talent more efficiently and find the best-fit talent.
- Job posting data. Consists of job ad data, such as job title, location, employment type, job description, skills required, and more. You can use it to see where certain companies intend to expand, conduct labor market research, and more.
- Sentiment data. Consists of company employee reviews and tech product reviews. You can see how employees rate the company they work in and how the market responds to a certain tech product. You can use it to enhance investment and product intelligence, respectively.
- Community data. Consists of developer community-related data. You can use it to find the best developers and also research state-of-the-art software products.
- Funding data. Consists of funding-related data, such as funding rounds, amounts, last funding date, acquisition data, and more. You can use it to find a company that is hungry for the next investment.
- Technographic data. Consists of technographic-related data, such as stack lists, tool features, pros, cons, and more. You can use it to find businesses that might want to buy your product or for market research.
You can select and buy a database that reflects your needs the best. Or you can buy several and generate actionable insights from multiple data sources and categories.
How to identify your data needs?
Before buying data, it's imperative to establish what you're going to use the data for. It will narrow down the scope of the search significantly.
For example, if you want to build a data product, such as a recruiting platform, you will need a lot of employee data to enable the platform. Afterward, you can use job posting data to add extra features to your product that may attract more clients.
If your goal is to discover new companies to invest in, then firmographic data would be your best choice. With it, you could generate a list of target companies based on selected criteria, such as location, headcount, founding date, and more. After generating the list, you can narrow down the list even more and select companies that fit your investment criteria the most. Also, you could use company employee review data to see if the people working there are happy with the job environment.
Buying data from a reliable data provider - how to choose one?
There are many companies selling data nowadays and it might be challenging to select one. Each of them differs in data quality, delivery format, delivery frequency, price, service, and more. Some might offer a single dataset, while others could be providing multiple databases.
In short, the best data provider is the one that offers exceptional data quality, freshness, convenient delivery, and finds new ways to overcome web data challenges. These qualities will define the value of the data. For example, if the data is not fresh, it will most likely be inaccurate and might lead to bad business decisions.
Top big data sellers
Coresignal is the leader of the market in terms of data freshness. We also have a large coverage of over 1 billion records in total and historical data on top of this. Our parsed and ready-to-use data is tailored for investors, HR tech, and sales tech clients. Each of our clients gets a dedicated account manager for quick communication and problem resolution.
Coresignal also offers 4 different APIs - Company API, Employee API, Jobs API, and Historical headcount API, which you can use to extract records without paying for the entire dataset. Our credit-based system allows you to search for free and use credits only to collect the data.
Some other big players in the web data industry, such as People Data Labs, Thinknum, and Operia, also offer similar datasets and services. Compared to Coresignal, the scope of their coverage and focus areas varies. However, in terms of data freshness and updates, which is one of the most important data qualities, Coresignal provides an advantage with regular and large-scale record updates, refreshing millions of company and employee records monthly, focusing on the most relevant profiles.
Stay ahead of the game with fresh web data
Coresignal's data helps companies achieve their goals
What are the main data formats?
There are several main data formats: SQL, JSON, CSV, XML, and HTML. The main difference between them is their structure.
- Structured data is SQL. This data format is usually sourced from online relational and tabular forms and stored in data warehouses. It's not flexible but demands less storage than unstructured data.
- Unstructured data includes formats such as JPEG, DOC, PDF, MOV, and more. This type of data is undefined and non-relational. It's used for natural language processing, text mining, and can be sourced from video files, emails, online documents, social media platforms, and more. Unstructured data is flexible, requires a lot of storage space, and is stored in data lakes.
- Semi-structured data includes formats such as JSON, CSV, XML, HTML, and more. This type of data is semi-defined, tagged, and semi-relational. Just like unstructured data, it's used for natural language processing and text mining. It's usually sourced from online documents, JSON files, and XML files. Semi-structured data can be stored in both data warehouses and data lakes. It's semi-flexible and demands a medium amount of storage space.
To wrap up: Data-buying best practices
To summarize the topic, let's examine the best practices for buying your first dataset. Feel free to come back to this article any time you want, and for now – here is a list of practices to keep in mind:
- Define your business goals
- Identify data needs to reach those goals
- Decide on your budget
- Research data providers online, and request data samples
- Discuss your data needs with the sales team/data experts for optimal packages and costs
- Proceed with providers that only sell high-quality data
- Maintain communication with the selected data provider
