How to Implement Data Harmonization to Improve Your Sales and Marketing Performance

Your marketing and sales efforts are only as effective as your data. As beneficial as attempting to extract blood from a pumpkin is pinning your KPI-driven hopes on polluted or unorganized data. Just ask any sales or marketing professional.

For your efforts to be truly successful, you must base your decisions on the wants and needs of your consumers and prospects. However, the only way to comprehend this is through clean, high-quality data that offers a coherent story.

Once you grasp your data, its usability and value will grow significantly. Harmonizing data into an easy-to-use organizing tool is the quickest approach to improving sales and marketing performance with data.

What is the harmonization of data? :

Harmonization is an integral component of master data management. It is the process of combining data from multiple databases or structures into a single authoritative source. It also bridges any knowledge gaps between departments or users that may occur owing to discrepancies in formatting, duplicates, or other mistakes. In brief, harmonization transforms unprocessed data into easily consumable, actionable information.

Without harmonized data, you will not have an accurate picture of your key performance metrics, making your marketing efforts, at best haphazard. Without the ability to effectively examine your data, you risk making costly errors.

How is data harmonization accomplished? :

Data harmonization doesn't happen in a vacuum. For example, sharing a master spreadsheet with raw data is unlikely to be of assistance to anyone. Ultimately, what information is displayed? Where did it originate? Is it contemporary? What does it tell you? However, these questions can be answered by effectively harmonizing data, a crucial component of CRM data management.?

Here are the essential elements of effective harmonization:

1)Data mapping (aligning with master data):

Disparate data are unlikely to be grouped precisely like every time. Importing data from many sources (spreadsheets, collected data, etc.) and matching fields from one set to another constitutes data mapping. This method of standardizing data allows you to begin each query from scratch.

?Have you ever attempted to move data from spreadsheets to a CRM only to discover that nothing matches because the fields are in the wrong order? Or that the data are identical, but the areas have different names? This data management step is essential for your sanity and for determining how to transform the data.

2)Data transformation:

Data transformation modifies your data's format, structure, or values and improves data processing efficiency. Not only does this improve the quality of your business information, but it also makes it easy to examine the data in any way you see fit.

The following are examples of data transformation:

1)Data cleansing?is the procedure of finding and rectifying data errors. These difficulties may involve inaccurate, improperly formatted, corrupt, duplicate, or insufficient data. Your organization will be able to retain correct, reliable data and meaningful data analysis if an active and consistent data-cleaning process is implemented.

2)Filtering?allows you to zero in on the precise information required. In addition, it minimizes the risk of data breaches by ensuring that only authorized users have access to the data.

3)Aggregation?allows you to compare, contrast, and synthesize your data in any way you desire. This is especially useful when attempting to quickly process complex information.

4)Validation?verifies the data's integrity (and precision). Invalid information, such as email addresses with typos, serves no purpose.

5)Integration?is essential if your organization uses many data collection methods. Similar to mapping, it consolidates data into a single, readable structure and/or interface. This is particularly crucial for sales and marketing teams, whose agendas and data frequently overlap.

6)Data Splitting:?Users split data when they divide enormous datasets into smaller parts. It can also divide your data into two groups, one of which is a "training set." A training set consists of the initial data utilized to train machine learning models. If you are responsible for more advanced segmentation approaches (such as customer score), machine learning automation will likely be required to assist with analyzing critical data elements.

Typically, data harmonization requires a combination of artificially intelligent automation and manual processes.

How technology facilitates data harmonization? :

Data management is certainly too large for a single person if your business is developing and gaining customers. However, investing in data management software saves time and money for your business and motivates employees to prioritize data quality.

Utilizing solutions enables you to tackle data quality concerns more quickly and precisely. However, there are several additional benefits to using technology for data harmonization. Namely:

1)It facilitates the implementation:

The data harmonization process becomes scalable when it is not dependent on humans inside the organization to execute repetitive duties. Software for data management takes over where humans are unable to due to a lack of time or resources. A robust data management platform can process significantly higher volumes of data, consolidate data so that it can be accessed on a worldwide scale, and clean your database without exceeding the storage capacity of your technology stack.

2)It minimizes the likelihood of making mistakes:

A human error exists for a reason, correct? Using software tools to automate repetitive workflows and queries significantly improves the efficacy of data processing. While not infallible (after all, we humans are setting up the technology), these tools are not necessarily faulty. Leaving such jobs to technology reduces the likelihood of errors owing to factors such as lack of sleep.

3)It establishes a single truth source for all business units:

Harmonization simplifies the processing and analysis of your business intelligence by standardizing your raw data in a more digestible format. For instance, consistency becomes vital when working with massive amounts of unprocessed data that people on a worldwide scale must read. In addition, when you are not concerned with omissions, inaccuracies, or resource limitations, it is simpler to concentrate on the information at hand.

Another advantage of selecting the appropriate data management technology is integrating the UI/UX presentation of information. Data management software levels the playing field for all departments by synthesizing the information they require on a user interface that is intuitive for everyone. No complex formulas or searching through several Excel sheets. Whether each department has a specific view or the search function is intuitively designed, your data management technology should make it easy to locate information.

4)It keeps your information private and safe:

According to IBM's Cost of a Data Breach research, the average cost of a data breach will increase from $4.24 million in 2021 to $4.35 million by 2022.(https://www.ibm.com/reports/data-breach).

?Data management software assists enterprises in securing customer data from unlawful processing and ensuring GDPR compliance. It also allows businesses to specify each user's access to organizational data to prevent internal abuse.

5)It allows you to utilize real-time data:

Make no mistake:?When discussing data processing, administration, and analysis, historical data is not the only topic at hand. Technology enables your sales and marketing teams to utilize dynamic, real-time data to make critical decisions based on current client sentiments.

As a developing firm, expanding your technology stack may seem frightening. But rest assured, there are numerous tools with connectors to meet the demands of any business. You may need to do some comparison shopping.

Conclusion

The more your organization's data comprehension, the better decisions it will make. The more consolidated your data is, the simpler it is for sales and marketing to communicate effectively. Everyone receives the same information, making it easy to manoeuvre the ship depending on the supplied facts.

Data harmonization aims to provide your organization with clear, meaningful, and, most importantly, actionable data insights.