Data Use Cases

Customer Data Enrichment, Why Should I Do It?

Customer Data Enrichment, Why Should I Do It?

As the world continues to become more and more customer-centric, most businesses are harnessing the most out of customer data to shape their solutions and products and enhance customer journeys.

Rightly so, because this whole exercise is yielding visible results. According to a study by McKinsey, organizations that make the most out of customer behavioral insights tend to outperform their competitors by around 85 percent in terms of sales growth, and by more than 25 percent in terms of gross margin.

This sounds interesting.

But here’s the catch: despite knowing the benefits that customer data can offer, most companies are still sticking to traditional ways of possessing data, including legacy systems, sporadic automation, and siloed databases. Perhaps they are unaware of the solution.

The solution? Customer data enrichment.

What is Customer Data Enrichment, Anyway?

Quite predictably, customer data enrichment is the process of enriching first-party customer data obtained from internal sources with third-party data procured from various external sources.

Enriched data is far better than data stored in traditional systems as it is more insightful and useful. It can tell you things about your customers you would have not found out based solely on your own data.

This is the reason that most businesses enrich their raw data to make educated decisions. In fact, according to Ascend2, 51% of marketers say enriching contact data quality is their most significant barrier to achieving email marketing success. Customer contact data enrichment will help you personalize your messaging within your campaigns and gain better click through rates.

How Does Customer Data Enrichment Work?

More often than not, customer data is extracted in raw form, irrespective of the source it is obtained from. Whether the data is collected from social media, or site traffic, or resides in the form of email lists – it is raw by nature and is generally stored in a central database. This whole scenario is useless.

This raw data is then made fit to use by structuring it properly and conducting thorough cleansing mechanisms.

Once done, this raw data is then enriched with external data and useful information is added.

Enriched customer data reveals hidden details, and helps companies in fuelling their strategies. Wondering how?

Let’s explore this in more depth.

Four major benefits of customer data enrichment.

Benefits of Customer Data Enrichment

  • Enhanced cost savings

Most companies spend a huge amount every year to store all kinds of data that they have. According to a report by Global Databerg, an organization with one petabyte of data ends up spending as much as $650,000 per year to manage the data. What is even more interesting is the fact that in spite of so much investment, they only use a small part of this data for real benefit.

Given the huge cost of data management, it would only make sense to make the most out of your existing investments in the data field. Data enrichment can do this for you. Organizations no longer need to store all kinds of data with them; instead, they only need to focus on existing data that is beneficial, then enrich it with external sources.

  • Easy customer nurturing

Data enrichment enables you to identify the segments of your customer base that need nurturing. With proper analytics and strategies in place, organizations can make use of cross-referencing techniques to classify customers based on attributes related to consumer interests and lifestyles. This would help the businesses understand which group of users is more likely to make a purchase, for instance. All these insights are therefore used to nurture the related segment, and bring results.

  • Meaningful customer relationships

Undoubtedly, data enrichment makes way for personalized communications, which translates to better customer relationships and business opportunities.

With high-quality customer data, you can have a deeper look into what your customers’ needs are. These critical insights can be utilized to provide your users with the right experience – one that they will look forward to having.

By combining internal data with brand affinity and social media data obtained from third party providers, you can strategize customer retention. For instance, you can keep an eye on how customers are perceiving your brand, understand their pain areas, and improve your services accordingly.

  • Better targeted marketing

It is high time that businesses realize that a one-size-fits-all marketing approach is simply non-functional. There is an urgent need to implement targeted marketing.

Have you ever received a gift coupon when your birthday is around the corner? Or product suggestions after liking a facebook page? This is nothing but target marketing, and a lot of organizations are already implementing it with the help of data enrichment.

For instance, with data enrichment, you can take your existing customer profile based on your internal data and multiply that with matching profiles in the external world. Given that the external profiles are based on your already happy customers, they should resonate with your messaging with promising results.

Data Enrichment is an Ongoing Process

As is evident, data enrichment has emerged as a necessity for organizations.  However, it is important to mention here that data enrichment is not a one-time effort; it is a continuous process since customer data is always changing.

For example, the marital statuses of customers change their spending habits fluctuate, or their income levels may rise and fall. Not to forget, the physical addresses of customers change as well. Not only this, but the data sampling and collection methods evolve as well. All these events make your existing data outdated, thus inducing the need for data enrichment.

Therefore, you must ensure that your customer data is fresh, accurate, and reliable. How?

Common means to assuring external data quality include:

  • Researching and understanding your data provider’s raw data sources and collection methods.
  • Requesting a sample set which can be used to test the data for its intended use case and environment.

For more information about specific data types, their use cases and quality assessment, see our data categories and guides.

What are your views on this? How often do you enrich data?

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