Businesses across all industries are discovering new ways to use data they have collected over the years. This data could be derived from a variety of sources such as sales records, customer data from marketing campaigns, websites, and other databases.
Traditional data analysis methods provided marketers with an understanding of market trends, customer behavior, and marketing campaigns in the past. However, modern data mining methods can provide organizations with deeper insight than ever before.
What is data mining?
Data mining refers to the process of extracting knowledge from databases. In this process, data is searched, collected, filtered, and analyzed using advanced data mining tools.
These tools can identify patterns and relationships between variables in databases. This information can then be used to predict future trends and plan long-term business strategies.
Data mining tools are effective at analyzing large amounts of data, but many businesses fail to perform data mining effectively.
Here are some tips to mine your database for valuable business insights.
Start with a goal in mind
More often than not, organizations analyze data without a clear end goal in mind. They may be under the impression that any knowledge gained from analyzing complex data banks could be useful. However, there’s no point in spending time analyzing large groups of data if you don’t know what to do with the knowledge gained.
Data mining is most useful when it is performed to solve a predefined business problem. Once you have defined your problem, you can implement the most suitable data mining method to tackle the issue.
For example, a company that is analyzing their customer demographic data may not have much use for the knowledge that their customers are scattered across the country. However, if data mining is performed with the goal of identifying the regions in which their products are underperforming, the company could plan future marketing activities to target these areas.
Get different organization departments involved
To make the most of the data they have mined, organizations should get employees from different departments involved in the mining process. This means database experts, data mining analysts, and marketing managers should all be involved to ensure that the information gained through data analysis is useful and can be utilized to fill important gaps in knowledge.
Organizations should also consider making their data easier for employees to access. Data scientists can upload their results to a shared database where the organization’s business-side employees can access them. These other employees may find better uses for this data than the employees performing the data analysis.
Check the quality of your data
The quality of the data being mined will carry over to the quality of your results. If your database is riddled with missing attributes, blank fields, duplicates or multiple spellings, your results will be poor quality and may not be suitable for use in the decision making process.
Data analysts should comb through their databases looking for any deviations or discrepancies that could negatively impact the quality of results. This process may be time consuming if your organization has collected large amounts of data over the years.
However, some modern business analytics solutions automatically identify this data “noise” during the analysis process and filter it out so it does not affect results.
Translate the results as needed
Employees who are not familiar with data analysis may be tasked with using data mining results in their activities. These employees will have an easier time understanding the data if it is translated and/or simplified before it is provided to them. If the results are being shared with a wide range of employees, they may need to be translated to multiple different levels.
The data mining process may be complicated, but the results don’t need to be. However, organizations should ensure that critical details are not omitted or erased during the translation process, as it could compromise the quality and usefulness of the results.
Use a flexible data mining tool
Data can be analyzed in an infinite number of ways. Each of these ways could produce results that are useful to a different business function. Due to this reason, your data mining tool should be flexible enough to accommodate the many data analysis needs of your organization.
A good data mining software allows you to construct data according to your requirements, and lets you add new fields as needed. It’s hard to guess what your future data requirements will be, so it’s wise to select a flexible data mining tool in the present.
Select the right modeling techniques
Effective data mining involves matching your data with the right modeling techniques. To do this correctly, data scientists need to understand the various assumptions each modeling technique uses before it used to perform analysis.
Different models may also produce results with varying levels of understandability. This consideration should be taken into account before selecting a particular modeling technique as your results will be useless if employees can’t understand them.
You may have to try several different models before finding the one that is suitable for you. Data analysts should try adding or removing different fields and experimenting with various features to test out a model and determine its suitability.
These data mining tips can provide your business with insight into its operations and market trends. However, this data mining process can be challenging for smaller businesses that do not have dedicated research departments. These businesses could have data mining needs carried out by a marketing automation agency.
Hong Kong has many marketing agencies that are experienced with collecting and analyzing customer data from various industries. They can provide your business with valuable insight on customer behaviour and market trends so that you can plan your future activities with confidence.
Information is critical for businesses in competitive industries, so you should start implementing effective data mining practices at your organization as soon as possible.
Xen Chia is the Strategic Marketing Director of an award winning digital marketing company, with more than 15 years of experience in digital marketing strategies, brand development, CRM data analytics and business transformation. By combining digital marketing solutions with customer lifecycle approach, he has successfully transformed CRM marketing for many leading brands to deliver proven business results.