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Data Enrichment explained

Accurate informed decisions in your business involve enhancing, improving and organising the existing data. You can optimize this data governance process through data enrichment.

Nabler is a pure play digital analytics consulting company and we provide enterprise level data governance consulting through data enrichment services. We have experience working and consulting on the top data enrichment tools like Adobe 360, Google 360, Optimizely and Alteryx. Talk to our consultants for your data governance requirement. Read more about our services Data Infrastructure | Digital Analytics Audit | Tag Manager implementation | Data lake consulting | Customer data platform consulting

The success of any enterprise is data-driven. But this data needs to be secure, intact, and easily accessible daily for operations. Data Governance maintains the usability, availability, security, and integrity of data. And to save your efforts from being wasted on unqualified data, you need to tap into data enrichment which is one of the most crucial components of data governance.

Let’s understand the concept of what is data enrichment and why do you need data enrichment in your organisation.

As the name suggests, data enrichment services means enriching data through refinement, improvement, and enhancement. For example, the information in your raw data may consist of minimal details such as the names of your target audience. To make this data richer, information like demographics and geographics should be added to the existing database. Furthermore, income levels as well as addresses can be weaved in to enhance the quality of the data. This enriched, complete and comprehensive data serves as a better pipeline to reach out to all your customers and prospects. In other words, data enrichment adds value by helping you analyse huge amount of information and extracting insights to boost your productivity.


It is also necessary to differentiate data enrichment from data cleansing. Very often, the two are confused to be the same. Data cleansing is checking data for errors and correcting them for accuracy whereas enrichment is adding more relevant facts to the cleansed information for better results.

But to get it right you need to be mindful of these data enrichment best practices


Though it may sound easy, it is a continuous process that should take place daily. It is quite challenging for any firm to sustain the pace. And so, multiple data enrichment best practices involving data enrichment tools which use complex algorithms are put in place to ensure its consistency.


Among the many data enrichment best practices,

  • Identify your ideal customer profiles- Instead of chasing unprofitable prospects and clients. Investing your resources in finding your ideal customers is a wise decision that proves to be beneficial in the long term. After the ideal customer is identified, choosing the next steps and tools becomes easier.
  • Locate the right data enrichment tools- When it comes to data enrichment tools, there are robust platforms available in the market. However, the one that works best for your requirements is what you should be searching for. Another best practice is referring to use cases, which assists you in finding the appropriate data enrichment tools. Popular use cases are lead generation, customer segmentation, customer experience, personalization, etc. A data enrichment tool that scrutinizes the data based on your requirements will work miracles for your sales team.
  • Set your objectives- What are your goals that you need to achieve through the data enrichment process.
  • Employ the right team- Delegate the task to an experienced team of data engineers who are on the same page as you are as far as the goals of the organisation are concerned.

The simple takeaway from all of this is that high quality data obtained through data governance and data enrichment is a big business advantage. The right data enrichment practices with the best data enrichment tools are the most trusted assets as components of the data governance module and a force to reckon with to stay on top of what you strive for.

With Nabler you can wisely invest in an efficient data governance model that will help you maximize your data collection efforts through a reliable tag implementation, Implementation audit, data lake and data pipe system.

So, what is data enrichment example? Read here – The ultimate guide to Data Governance

Drive better results by understanding customer data