Your sales and marketing efforts are only as good as your data. Pinning your KPI-driven dreams on tainted or disorganized data is about as useful as trying to squeeze blood from a turnip. Just ask anyone in sales or marketing.
For your efforts to truly succeed, you need to make decisions based on what your customers and prospects want and need. But the only way you can understand what that is is with clean, high-quality data that tells a cohesive story.
Once you master your data, you’ll find a marked increase in its usability and value. Harmonizing data into a simple-to-use organizational tool is the fastest way to turn your data into better sales and marketing performance.
What is data harmonization?
Harmonization is a crucial part of master data management. It’s the process of unifying data from multiple databases or structures into one single source of truth. It also bridges any knowledge gaps that may exist between departments or users due to formatting differences, duplicates, or other inaccuracies. In short, harmonization turns raw data into easily digestible, functional insights.
Without harmonized data, you won’t have an accurate picture of your key performance indicators, making your marketing efforts haphazard at best. Without the ability to properly analyze your data, you also risk making incredibly costly mistakes. In fact, we surveyed 600+ organizations around the world and found that nearly half of the respondents lost over 10 percent in annual revenue due to low-quality CRM data.
How does data harmonization work?
Data harmonization doesn’t happen in a vacuum. Simply sharing a master spreadsheet packed with raw data is unlikely to help anyone. After all, what information is being shown? Where did it come from? Is it up to date? What’s it telling you? These are all questions that can be answered through effectively harmonized data, a key component of CRM data management. Here are the key components of proper harmonization.
Data mapping (aligning with master data)
First things first: disparate data is unlikely to be organized in the exact same way every time. Data mapping is the process of bringing in data from all your different sources (spreadsheets, data gained via acquisitions, etc.) and matching fields from one set to another. Standardizing data this way helps you start every query with a clean slate, so to speak.
Think about it. Ever tried to migrate data from spreadsheets into your CRM only to find nothing matches up because the fields are all out of order? Or that the values are the same but the fields are named differently? This step of data management is crucial not just for your sanity—it also sets you up to successfully determine how to transform that data.
Data transformation changes the format, structure, or values of your information and makes for more efficient data processing. Aligning raw data in this way not only helps improve the quality of your business intelligence—it also makes it easier for you to analyze it in any way you’d like.
Examples of data transformation include:
- Data cleaning: the process of identifying and correcting data issues. These issues may include incorrect, misformatted, corrupt, duplicate, or incomplete data. Initiating an active and consistent data cleaning plan will help your organization maintain accurate, reliable data and useful data analysis.
- Aggregation helps you synthesize, contrast, and compare your data any way you choose. This becomes especially handy when trying to digest high-level information at a glance.
- Filtering helps you home in on just the information you need. It’s also a way to ensure that anyone accessing the data only sees what they need to see, minimizing the risk of data breaches.
- Validation is the process of confirming the integrity (and accuracy) of the data you’ve collected. After all, invalid data, like email addresses with typos, will do you no good.
- Integration is crucial if your organization uses more than one method of collecting data. Similarly to mapping, it unifies information into one, easy-to-read structure and/or interface. This is especially important for sales and marketing teams whose priorities and data often overlap.
- Data splitting occurs when users break down large datasets into smaller subsets. It also works for dividing your data into two groups, one of them a designated “training” set. A training set is the initial data used to train machine learning models. If you’re responsible for more complex segmentation techniques (like customer scoring), you’ll likely need machine learning automation to help analyze key data points.
Speaking of machine learning, if you’ve broken out into a cold sweat at this point, remember that data harmonization is usually a combined effort between artificially intelligent automation and manual measures. Put simply, you don’t have to go it alone!
3 ways tech helps with data harmonization
If yours is a thriving company with a growing clientele, data management is likely too big a project for just one person. Investing in data management software saves your company time and money, and encourages users to prioritize data quality.
Leveraging solutions like DemandTools, from Validity, means you can resolve data quality issues at a much faster pace and with higher accuracy. That said, there are a number of other benefits to leveraging tech for data harmonization. Namely…
It makes implementation easier
Having the right tech tools makes the data harmonization process scalable because it doesn’t rely on individuals within the company to perform repeatable tasks. Data management software steps in where humans can’t due to time or resource constraints. A robust data management platform can process substantially larger volumes of data, centralize data so that it can be accessed at a global scale, and clean your database without overloading your tech stack’s storage.
It reduces the likelihood of errors
It’s called human error for a reason, right? While not necessarily infallible (after all, we humans are the ones setting up the tech), Using software tools to automate repetitive workflows and queries makes for far more efficient data processing. Leaving such tasks to tech makes it unlikely that mistakes will be made due to not enough sleep, for example.
It creates a single source of truth for all business units
Harmonization makes it easier to process and analyze your business intelligence by standardizing your raw data in a way that is easier to digest. If you’re working with large volumes of raw data that need to be viewed by users on a global scale, for example, consistency becomes crucial. When you’re not worried about omissions, inaccuracies, or resource constraints, it’s easier to focus on the information at hand.
Another benefit of picking the right tool to manage your data is unifying how information is presented from a UI/UX perspective. Data management software levels the playing field for all departments by synthesizing the information they need on an interface everyone can understand. No complicated formulas or digging through different Excel sheets. Whether each department has a designated view or the search function is just that much more intuitive, your data management tech should make finding information a breeze.
It keeps your data safe and secure
According to IBM’s Cost of a Data Breach report, the average cost of a data breach increased from 4.24 million USD in 2021 to 4.35 million USD in 2022. Data management software helps organizations secure customer data against unlawful processing and helps ensure compliance with regulations like GDPR. It also offers a way for companies to set the level of access any given user can have to organizational data to prevent internal misuse.
It helps you leverage real-time data
Make no mistake: When talking about data processing, management, and analysis, we’re not just talking about historical data. Leveraging tech means your sales and marketing teams can work from ever-changing, real-time data to make key decisions based on current customer attitudes.
The idea of adding to your tech stack as a growing business may seem daunting. But rest assured, there are ample tools available with integrations to match any company’s needs. You may just have to do some shopping around.
What harmonized data means for your sales and marketing performance
The better your organization understands your data, the better decisions you’ll make. The more unified your data, the easier it is for sales and marketing to get on the same page. Everyone gets the same story, making it easier to steer the company ship based on the facts presented.
Data harmonization is about giving your business the gift of clear, valuable, and above all, actionable data insights.
To learn more about the impact of data on your business and how to implement a foolproof data management program, read our report, The State of CRM Data Management in 2022.
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