Data entry work has been consistently searched for and outsourced for many decades. But it's only in the latter half of 2017 that data enrichment rose prominently online. That's around the same time that machine learning technology made leaps in research and development. Thus, data entry and analytics may ultimately become AI-enabled services, but data enrichment work can only be done by humans who turn that data into meaningful information for businesses like yours.
Still unconvinced? Here are 3 reasons why it's better for you to outsource data enrichment work that's more complex than data entry or data mining jobs.
#1 Humans are needed to sift through the data, identify which ones are incorrect or useless, and either remove or replace them.
Data enrichment work involves processes that enhance, refine or improve raw data. And, a team of human workers can do that better than a machine no matter how "intelligent" it may be. Humans can simultaneously assign meaning to data and re-organize it based on that label.
Agents may use software to speed up the search process and filter the results, but unless data has been correctly tagged or labeled, you can't glean any accurate and significant information from it. After all, incorrect labeling or adding the wrong numbers can have dire consequences, especially in data-related work for the healthcare and pharmaceutical industries.
#2 Data enrichment means you'll need agents who have research and analytical skills.
Outsourcing your data-related tasks is a good idea when you're in the business of managing big data, manipulating it, and extracting as much useful information from it as you can. With a team of skilled agents under your supervision, you'll cut your research work by half and discover sooner new information to add to your database. This is especially true for projects that update customer databases and contact information.
While AI may have a better chance of verifying that information has been created or modified recently, humans have the upper hand when verifying which information is correctly associated with whom. Many people have the same first and last names. Some of them may even live in the same country or city. But, it's only through investigative work that you can qualify a customer's personal data as true and correct.
#3 Data enrichment, when done right, can produce meaningful results.
Through machine learning, any AI-enabled technology can look at a grocery receipt and identify which items match the list of ingredients for a popular dish. But only humans can figure out that the buyer chose to buy those ingredients because he or she was going to cook a loved one's favorite dish because it's their birthday the next day.
This is the kind of information that only a team of human workers can produce for real estate agencies, offline and online retailers, and even healthcare and pharmaceutical companies. Imagination, insight, and creativity are qualities that only humans possess. And, these qualities help these data workers perform better than any technology can.