Data enrichment is an important process of data analytics for any business. It’s not enough, after all, to simply collect some data on your customers. You need to gather as much data as possible, plus ensure that all gathered data feeds into itself, forming a comprehensive and robust picture of your target consumers.

Today, let’s explore five key ways to enrich your data like never before.

Keep Your Data Up to Date

For starters, you must ensure that your data is kept up to date. Out-of-date consumer data is almost as useless as no data at all. If, for example, you only collected data on your customers once every quarter, you can’t expect your marketing campaigns to resonate with your target consumers. After all, that data effectively leads you to market to people who existed one quarter ago!


  • Use multiple tools to gather data all the time
  • Ensure that any gathered data is up-to-date or brought to your data warehouse/data center in real-time
  • Use data analytics tools to cross-reference captured data with other data sets to ensure accuracy and validity

The more real-time data you have to work with, the more enriched your data will be, and the better your marketing efforts will succeed.

Try Web Scraping

You can also practice data enrichment by using web scraping. Put simply, web scraping means extracting tons of data automatically from across the web. This is one of the most cost-effective, affordable, and scalable ways to enrich a B2B or business-to-business database.

For example, you can practice web scraping by importing publicly available data into a spreadsheet or, ideally, a CRM/customer relationship management software app. Fortunately, you don’t have to be a programmer or have software experience to perform web scraping.

Instead, you can use various data scraping tools to extract data from websites or public databases without any technical knowledge. Web scraping is the best way to enrich your databases by adding a lot of data quickly and easily, thereby allowing your other data collection efforts to be more accurate and precise relative to your target audience.

Perform Manual Research

Of course, manual research always has a place in data enrichment efforts. You can enrich customer or client leads using manual research, such as by:

  • Looking up client company websites
  • Looking up your leads on LinkedIn
  • Using Google to check out leads or companies
  • And so on

Once you have your data from your manual research efforts, you can add the information to a database, spreadsheet, or CRM platform. Regardless, manual research can enrich your data directly and progressively, even though it takes a lot of time and effort on your part.

You may wish to enrich your data periodically through manual research rather than relying on it as your primary method of data enrichment. Try to do some manual research for particularly high-value clients or once in a while to bolster your automatic/web scraping efforts.

Use Reverse ETL

Reverse ETL processes may also help you enrich your data. Standard detail means replicating data from a data source and putting it in a data warehouse. Thus, reverse ETL is the exact opposite. It means copying data you’ve already gathered from a central data warehouse or repository, then bringing it into operational tools such as CRM platforms and so on.

Why is this effective? Many companies, particularly large enterprises, have tons of data they don’t do much with. Through reverse ETL, you can enrich your active or practical data sets even though you don’t add any new data to the mix. Reverse ETL is, therefore, one of the most cost-effective means of data enrichment available to you.

Reverse ETL is effective if you have a large, well-organized data warehouse, but your CRM and other software platforms are constantly in need of new data to make accurate predictions or analyze leads. Reverse ETL enables those tools to get the data they need ASAP, while also leveraging data resources your enterprise already has.

Use the Right Data Enrichment Tools

Last but not least are data enrichment tools. A good data enrichment tool can gather third-party data from the Internet, plus clean and organize the data for further analysis. Most importantly, some data enrichment tools can aggregate data from several different sources using automated and machine learning processes. Some good examples of these tools include Clearbit, Dropcontct, and Zoominfo.

Regardless, use data enrichment tools to accelerate the data-gathering and analytics processes so you can build up your data sets – and learn more about your target leads – faster than humanly possible.

As you can see, these strategies and tools can help you enrich your data and get more value out of all your data collection efforts. For the best results, use each of these strategies together – that way, your data is as descriptive and comprehensive as it can be!


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