By Expected reading time 4 min read

Outsourcing is one of the best ways to run a company in 2017.

Given that you can find almost any product or service through your web browser, there is no need to do things in-house. Furthermore, the quality of services like data mining is usually high.

Even though outsourcing companies usually work online avoiding strict regulations, that doesn’t mean they use bad solutions or technology. The very fact they do business on the Internet places them in a very competitive market where only the best organizations manage to survive.

Still that doesn’t mean that if you do data mining outsourcing, the data you get will be according to your needs. There are a lot of things that clients need to know beforehand and a lot of things that can go wrong.

Here are all the facts that a management team needs to know before outsourcing data mining.

What are the risks and benefits of data mining?

First of all, let’s run down the general risks and benefits.

Data mining is a process of finding patterns within large data sets. These data sets can be found through social media, government resources, various registers, databases.

It is a marketing tool that can help you with customer and industry analysis, cost reduction, client relationships, to increase sales and improve blog content, etc.

When processing data, focus is placed on discovery and extraction of patterns.

We cannot simply extract data without putting them into a context. Instead, we try to group this data and find various interrelationships turning them into actionable information.

The greatest benefit of mining is that it saves time and money.

In this new business era, you need to focus on statistics and predictions. With data mining all your processes are becoming more efficient and effective.

On the other hand, the main issue is the applicability of data.

You can mine all you want but if this data is not applicable for your business, you are just wasting time.

Another potential issue is the fact that some companies do not act according to these results but instead try to go with their “hunch”. This is common for organizations that haven’t fully changed their business approach. Those who wish to implement modern technologies but still haven’t fully committed to results.

Benefits of data mining outsourcing

  1. You can avoid creating an in-house team

Data mining is a process that is valuable for any type of a commercial company. At the same time, it isn’t something you will do on a daily basis unless you’re a big company.

Due to this fact, creating your own in-house team can be a waste of time and money.

It probably wouldn’t be efficient for you and there won’t be enough work to go around.

This is precisely why it is much more efficient to order data mining outsourcing services when you have need for them.

  1. Helps managerial processes

Like with any outsourcing, you simply pay for a service and stop thinking about it.

If you’re running a small or medium-sized team, you probably try to remain involved as much as you can. For better or worse, when you outsource something, you are unable to have as much impact as you would with your own team.

This approach allows you to get the results without thinking about the process. It reduces management time and stress allowing you to focus on other things.

  1. Experts are there to assist you

As I already mentioned, one of the biggest issues with data mining is applicability.

There are several techniques that can be used showing you different patterns. Although it may seem obvious as to what you need, you probably don’t know how to get there.

Professionals working for an outsourced company will not only provide the service but can also provide consulting. This is especially important for people who never did mining of data but wish to incorporate it as a part of planning process or for their own database creation.

  1. Flexible market

When it comes to this particular process, most of the work is done online.

This might be troublesome for you as you don’t have enough control or legal support but it also helps you find the best service provider.

Traditionally, industries that are online-based are much more competitive which gives more options to potential clients. You can pick a company from any part of the world, from Canada to India. You can easily find any quality of service for various price ranges.

This is one of the main reasons why in-house data mining is inefficient as you need to create your own team, find space in office and integrate it into your company.

Risks of data mining outsourcing

  1. Inherent risks of outsourcing

Like with any outsourcing process, there are a lot of unknowns when it comes to outsourcing data mining.

Although based on algorithms and software, there is always a chance for something to go wrong. In fact, the issues don’t even have to be service-related. Culture, language, customs can all play a part when communicating with organizations from other countries and even continents.

Even though this happens rarely, you might not even receive the service that you wanted or you might receive incoherent data.

Best way to reduce this risk is by working with a reputable data mining company.

  1. False advertising

A lot of companies that are doing data scraping and data entry present themselves as data mining companies.

Have in mind that these two are not the same.

While mining is based on sophisticated algorithms, scraping is a process where a person takes data from a web page and copies it into a sheet.

Based on this alone it is easy to see that mining for data is much more precise. Also, it is much better for discovering relationships.

Before you decide to pay for a service, make sure you’re getting the thing you need.


Even with all the risks, data mining outsourcing is a common practice nowadays.

Given everything that I’ve said so far, the benefits outweigh the risks. Unless you need a data mining team on a permanent basis, there is no real reason not to outsource.

Have you ever outsourced data mining services? What is your experience? Share it in the comment section below!

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