What is Enriched Data and How Can Marketers Effectively Leverage it?

Let us begin with a simple analogy: You are at a fine dining restaurant, you place your orders, and the waiter brings you the order, dramatically lifts the lid and you find all the ingredients raw and uncooked.

That, dear reader, is an example of raw data.

Now let’s revisit the analogy: You are at a fine dining restaurant, you place your orders, and the waiter dramatically lifts the lid, with each dish meticulously crafted to transport you to culinary nirvana.

That, dear reader, is enriched data.

ENRICHED DATA

Enriched data in the world of data science is essentially data that has been enhanced, augmented, and overall spruced up with additional information from several sources. Similar to giving your raw data a makeover, complete with a new wardrobe, a fresh haircut and a completely new look that makes it ready for processing.

But why go through all the trouble of serving up a gourmet meal? Why not just serve up the raw ingredients? That is because enriched data is the secret sauce in the process of Data Driven Decision Making. It makes all the difference between the fine dining experience and the data-drive through junkies at a street corner food stall. Enriched data empowers marketers to target customers and create campaigns that are more targeted than a heat-signature seeking missile – More personalized that an average consumer would think at the outset, and more effective than a laser guided weapon. So let’s embark on the journey through the wild and wacky world of enriched data. .

The Alchemy of Data Enrichment: Turning Raw Data Lead into Marketing Gold

Let’s start with a story of a lonely little data point called John. John was a simple fellow – a customer ID number, living in an old and messy database, along with millions of other data points just like him. But John had a dream – he wanted more – having a purpose, making a difference in the world of data science. However, till now, he was just a data point- a number living in obscurity.

But change is the only constant in this world, and one day, everything changed. A brilliant data scientist waved his magic wand (on his keyboard, of course), and, suddenly, John was transformed from being just a data point number to an enriched data entity. Now he had a name, age, a location, a job title, an income bracket, a list of recent purchases, a web browsing history, social media activities, and even his food and beverage preferences.

John was now…. enriched data!

Our second analogy explains the nuances and resultant alchemy of data enrichment. It’s the process of taking raw, basic data and turning it into a goldmine of customer or business insights. But how does this magical transformation happen? It’s not as simple as you might think. Data enrichment comprises of gathering data from multiple sources, internal and external, to create a more comprehensive and insightful dataset on which data driven decision making can be based. It also comprises context and depth of each data point. It’s a lot like upgrading your data from economy to first class. By enriching data, businesses can uncover hidden patterns, preferences, and behaviors that help data scientists and marketers create targeted, personalized, and highly effective marketing strategies.

INGREDIENTS OF ENRICHED DATA

The potent aspects of enrichment include the following ingredients:

• Internal Data – The data that the business already has – customer information, transaction history, website interactions, etc.
• Third Party Data – This is the interesting part if you’re following carefully. Third party data providers can offer a wealth of additional information – demographic data, firmographics (which comprises the characteristics of customers that businesses can use to segment their consumer base and create laser sharp targeted marketing and sales campaigns), technographics, you name it.
• Public Data – The treasure trove of public data is easily and freely available and doesn’t need any data provider or vendor. Public data is freely available in the public domain and includes features like – census information, social media data, government records, and more.
• Behavioral Data – This is the online data science sleuth that follows you around and studies your behavior as you browse along and make your online purchases across various touch points.
• Predictive Analytics – Predictive Analytics is crucial for making recommendations when using recommendation engines in data science. This applies machine learning algorithms to enriched data so that businesses can start predicting future behavior of the customer.

SO, WHAT DOES IT ADD UP TO?

The result of this somewhat alchemical process is that it produces a dataset that is probably richer than most billionaires in terms of data and actionable items for marketers to use, more insightful than investigative agencies and more valuable than a large vault full of bitcoin (depending on the day’s price!)

THE OTHER FACTOR

Data scientists could have a warehouse full of enriched data and yet not be able to leverage it fully. The other crucial factor here is the quality of data enrichment. Piling on more and more information is just hoarding possible insights to win a hoarding competition. The fundamental functions that data enrichment must provide include relevant, accurate and actionable insights.

In the world of data science, this means carefully selecting and validating data sources, ensuring constant quality metrics and consistency of the dataset, and keeping it enriched with useful information.

WIELDING ENRICHED DATA LIKE A BOSS

So, data mavericks, let’s roll up our sleeves, get our hands dirty and actually understand the different machinations of turning raw data into enriched insights. Here goes

• Segmentation – Customer Segmentation is the first stop on our enrichment journey. Enriched data gives you the power to slice and dice the entire customer base more precisely than a scalpel. This allows you to create highly targeted marketing campaigns that speak directly to your audience’s needs, interests and online behavior.
• Personalization – Personalization is the special ingredient in the data driven marketing mix that ensures ever marketing message was crafted specifically for that customer, offering highly tailored marketing messages, product and service recommendations, and even dynamic pricing based on the customer’s buying habits.
• Predictive Power – As a brief explanation, enriched datasets offer invaluable insights into customer behavior, which is a given. What separates the average data scientist from the superlative ones is that with enriched data, businesses can predict a customer’s future buying probabilities and patterns with surgical precision. This predictive power enables marketers to proactively reach out to prospects with the right offer at the right time, potentially even before they know they want to make the purchase. This uncanny accuracy increases sales volumes and business growth at exponential speed.
• Customer Mapping Journey – Enriched data enables businesses to create detailed maps of customer interactions with the business or e-commerce store across all touchpoints including product queries. It also helps understand the pain points, optimize the customer experience, and find opportunities to delight and retain them.
• ROI – With enriched data, businesses can track and measure the performance of your marketing dollars and efforts with pinpoint accuracy. These insights give you the power to minimize spend and, maximize your return on marketing investments, all the while tracking them with maximum precision.

THE FUTURE OF ENRICHED DATA: (CRYSTAL BALL NOT INCLUDED)

The future of data enrichment is not very different from emerging and prevalent technologies undergoing optimizations in Data Science. For example,

• AI and Machine Learning – According to almost every technology publication, artificial intelligence, machine learning and data enrichment will become inseparable in the near future, leading to accelerated and even more accurate data enrichment. AI algorithms that can predict customer behavior with pinpoint accuracy, or machine learning models that can automatically segment your audience into groups at the drop of a hat.
• Real-Time Enrichment – How about data enrichment without the wait? According to industry experts, in the very near future, data enrichment will not have to wait till a data scientist is available or hired to enrich the data. In the future, every click, every interaction will instantly trigger a cascade of data collection for enrichment automatically and instantaneously, constantly updating customer profiles and their buying habits.

CONCLUSION

As we stand on the brink of this revolution, it is up to the marketers and the data scientists and business leaders, to shape the future usage of these technologies. Now, before you move ahead with your browsing, a critical aspect to keep in mind if you are to be successful in the world of data science is professional certifications. It may sound boring and obvious, but in the fast-paced, ever-evolving landscape of enriched data and data science platforms, having the right certifications isn't just a nice-to-have – it's as essential as knowing how to turn on your computer. So go forth, get certified and stay relevant, credible, and employable in the wild world of data science.