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Blog / Data Reliability: Importance and Benefits

Data Reliability: Importance and Benefits

If you’re involved in the world of online marketing, you’ll be no stranger to how competitive things are, and how important it is to have accurate and reliable analytics for optimizing performance.

The effective use of business and marketing data has actually emerged as one of the most important factors in achieving marketing success.


Yet, despite the importance of data in marketing, 34% of Chief Marketing Officers confirmed that they didn't trust their business data.

And without that trust in business data, it's almost impossible to embrace a data-driven culture or make effective marketing optimization decisions.

In this post, we're going to take a look at the importance of data reliability and how the right approach to data integration can help you ensure that your data is reliable and trusted by users across the business.

What is data reliability?

Data reliability refers to the extent to which your data is complete and accurate and can be trusted by the business for making important decisions.

Without reliable data, marketing teams risk missing opportunities, or even worse - basing optimizations and strategies on erroneous insights, leading to poor marketing performance.

For businesses that invest in the time and technology to ensure their data is reliable, there are a number of benefits;

  • Increased trust in data

Data reliability can lead to stakeholders across the business having more trust in your data, leading to a data-driven culture that has significant competitive benefits.

  • Increased efficiency and productivity

When your business data is reliable, marketing teams don't need to spend time double-checking it against the original data sources, saving valuable time. Having reliable data also saves businesses the time of analyzing the poor performance of campaigns and strategies that have been made from erroneous data insights.

  • Better analytics and reporting

Accurate, reliable data allows marketing teams to get a true picture of how their campaigns are performing, and spot any emerging trends. This empowers them with the insight to make meaningful, impactful optimizations.

  • Improved decision-making

With the compound effect of increased trust in data, improved efficiency, and better analytics - data reliability can ultimately lead to better decision-making across the business.


Data reliability Vs. data validity

Within the field of data management, it's common for some phrases to be used interchangeably when they really shouldn’t be!

One example is the use of the terms data reliability and data validity, which are interrelated but distinct areas of data management.

We’ve already covered that data reliability relates to the extent to which your overall data can be trusted and relied upon by the business. Data validity on the other hand is more about the accuracy and integrity of the data that is being taken from your data sources, transformed, and loaded into your centralized data destination.

To illustrate data validity in action, assume you want to consolidate marketing data from a dozen different marketing sources, all of which have a slightly different date format. 

Some are using MM/DD/YY, others DD/MM/YYYY, and others MM/DD/YY. 

During the data transformation process, these values can all be standardized into the format that is most useful for the business - for this example let's say DD/MM/YYYY.

This date field will only be considered ‘valid’ if it meets the agreed standardized format of DD/MM/YYYY. 

And that is where data validation comes into play,  ensuring the accuracy and integrity of the data that is being transformed and consolidated against the predefined rules. 

So how are data reliability and data validity linked? Quite simply, data cannot be classed as reliable if you don't have the confidence that it's valid.

What causes data to be unreliable?

We've already established the importance of having accurate, reliable data to make important marketing and business decisions, and we’ll shortly come on to some ways you can improve your data reliability. 

But before we do that, it's important to get an understanding of some of the factors that cause data to be unreliable, so you’re in the best position to address them. 

  • Inconsistent data collection methods

If your marketing team is working across a number of different channels, it's likely that each platform is going to report metrics slightly differently.

If this data is combined without the right transformation and data validation, it's likely to be difficult to compare and analyze consistently, which can lead to inaccurate analysis and inefficient optimizations.

  • Human error

The consolidation and integration of data is a complex task. It always surprises us how many businesses are still attempting data integration manually, as it can be incredibly time intensive and opens up the process to human error.

Even the smallest of errors, like missing a row when copy and pasting, or adding an extra zero on manual data entry, can have a major impact on the accuracy and reliability of data and the optimization decisions that are made from it. 

  • Outdated data

If marking performance data isn't updated regularly, marketing teams may be making optimization decisions on data that doesn’t accurately reflect the current performance of their campaigns.

Outdated data is a common issue for businesses that rely on manual data integration, simply because of the sheer amount of time it can take to bring disparate data sources together. 

Our recent survey really highlighted the extent of this issue, with 43% of CMO’s stating that they spent more time getting their data in one place than they did actually making decisions from it.


Quicker response time to events and changesHaving up-to-date data is critical to respond to risks and opportunities in good time.


  • Poor data integration practices

We're not going to delve too deep into the topic of data governance here. But, if you don't have the correct guidelines and processes established for the management of your business data, it can make the process of data integration more challenging than it needs to be.

For example, if there isn't a clear strategy or understanding of how marketing data should be consolidated, it can lead to incorrect data mapping, which can in turn result in inconsistencies in the database and erroneous analysis of marketing performance.

  • Lack of data validation

Data validation helps to ensure that all your consolidated data aligns with your agreed structure and format. 

If there isn't a clear data validation process in place for your data integration, you run the risk of inaccurate or inconsistent data making its way to your database, which can compromise your data reliability



How to improve your data validity and reliability  

If you're reading this post and it's making you realize that there's more that could be done to improve your data reliability and data validity, there’s help at hand. 

There are plenty of tools and techniques that you can implement to help enhance the reliability of your data and improve the trust in it for marketing decision-making. 

Establish a unified view of data

The first thing to do is to eliminate any data silos and disparate data sources, consolidating everything into one single source of truth.

Effective data integration is the cornerstone of successful data-driven marketing, and there are plenty of ETL tools and integrated data platforms that can automate the process. Choosing technology over a manual integration process is critical for data reliability as it reduces the likelihood of human error. 

Data cleaning and transformation

A key part of effective data integration is data transformation, which takes all your disparate data sources and makes sure everything is in a consistent format in your centralized database. Having this consistency across your data is critical for data reliability and trust. 

Some ETL and data integration solutions also include advanced enrichments, such as allowing you to convert currency and languages during the transformation stage - going one step further in the pursuit of consistency and data reliability. 



Cleaning data is an important step to create data reliability and trust. 

Comprehensive data validation

As we touched on earlier, data validation helps ensure that all your transformed data adheres to the correct format.

This is a tough job to complete manually. 

Some automated data integration tools have features that can alert you to any inconsistencies in formatting, and can even prevent the data from being uploaded if it doesn't meet your validation criteria, helping you retain data reliability.

Real-time data updates

The majority of marketing teams would see it as unreliable to be making optimization decisions on consolidated data that is a few weeks old.

The fresher your data is, the more marketing teams are able to react quickly to market trends or changes in performance to improve the effectiveness of their marketing campaigns. 

Some data integration platforms offer near real-time data fetches, which can empower marketing teams with the fresh data they need to gain a real competitive advantage.

Improved data governance

If you don’t have established rules and guidelines for how your business processes, manages, and controls data - you should consider implementing a data governance strategy. 

From a marketing perspective, data governance can help ensure the quality, reliability, security, and accessibility of the data that is used for optimizing marketing activity. 

Implementing a data governance strategy and putting guidelines in place for what data should be processed and how it should be managed - helps maintain the consistency and reliability of data across your business. 

However, data governance is an area of data management that can be challenging to implement effectively without the right supporting tools and technology. 



How data integration platforms can help ensure the reliability and validity of data

Working with the right data integration platform can help you simplify the process of consolidating your marketing data, ensuring its reliability and reducing the likelihood of human error. 

By connecting with all your various data sources, transforming and standardizing your data, monitoring data quality and validity, and loading it into a destination of your choice - a data integration platform can automate the complex task of bringing all your marketing data into one centralized location. 

Some data integration platforms have specific features and functionality that are designed to help you maintain confidence in data validity and reliability.  

For example, Adverity includes: 

  • Smart Naming Conventions, which helps ensure data reliability by enforcing consistent naming conventions in your database.

  • Anomaly Detection, which uses AI to provide automated alerts whenever any of your important measures of performance on each of your marketing channels deviates from their expected range. This helps you address the issue early, and determine if it’s a genuine issue with performance or an issue with data.

  • Activity monitor, which gives you peace of mind by enabling you to see the status of all your different data feeds and spot any errors that need to be addressed.

  • Powerful data transformations and enrichments allow you to improve the quality of your data with ease. There’s a wide range of ‘out the box’ enrichments available, and the ability to code your own custom scripts. 


The reliability and validity of your data are critical for making effective marketing campaign optimizations and achieving business success. 

With data integration platforms like Adverity, maintaining data validity and reliability is easier than ever. 

Want to learn more about optimizing your data management, and how to ensure your data is reliable and valid? Sign up for our webinar or schedule a demo today.


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