What is data enrichment? All you need to know
What is data enrichment? All you need to know
Today every business organization is taking advantage of the vast pool of customer data available to stay ahead and beat the competition. But utilizing the same set of data in the same manner and sticking to the traditional strategies as your rivals can result in fierce competition. Collecting and utilizing first-party, volunteered data is one technique to gain the upper hand over them. Surprisingly, first-party data alone might not be sufficient if it is unreliable or erroneous.
In organizations where even the leads give you enough details to conduct a focused marketing campaign, stakeholders must recognise this as an opportunity to implement Data Enrichment tools & strategies.Organisations probably have a whole lot of customers treasure data that includes your clients' email, name, age, etc. But this data lacks the potential to deliver more pertinent messages & content that can effectively convert leads and ultimately boost sales. One can refer to this data as ‘un-enriched data’.
Data enrichment is a technique that can help organizations to create a precise client profile from the data which is already available to the organization. These concretely defined precise profiles can assist the stakeholders of the organization in better mapping the demands of the clients. This helps the organizations to know how to effectively serve their clients across all channels with pertinent content, offers, and other personalized experiences.
Data enrichment is a sometimes disregarded yet vital step in creating datasets that are suitable for analytics. This frequently occurs when the data stakeholders do not consider the data requirements for downstream analytics when deciding what data to capture.
Therefore, having a well developed, user-friendly data enrichment tool that enables the data stakeholders across all the levels in hierarchy to modify, alter or enrich data to their unique needs can be very helpful. This can allow the data stakeholders of the analytics teams to generate highly accurate insights, promote broader analytics adoption, and be more responsive to the clients demands that further leads to the organization’s growth.
What is Data Enrichment?
Data Enrichment is nothing but aggregating and consolidating the organization-wide first-party data which may be gathered from numerous internal sources or can even be found via any external sources like any third-party.
There are many instances where data cleaning or data enrichment are used interchangeably but they do differ. Both the terms hold separate meanings and aso have quite unique applicability. Data cleansing refers to the process of removing erroneous or out-of-date information from datasets, whereas data enrichment entails augmenting pre-existing first-party data sets utilizing third-party data sources. Both these methods serve different purposes. In simple words you can understand Data Enrichment as the process of enhancing the quality of available data by aggregating data available in new forms.
Importance of data enrichment for businesses
Modern organizations rely heavily on data, which can then be utilized to strategically tailor marketing, sales, and customer service plans. Majority of the decisions taken by the stakeholders to grow & expand profitably are backed up by religiously following the practice of performing Data Enrichment on the company wide data. Availability of reliable data makes it easier for the stakeholders to make informed decisions that can evidently boost the profitability of the organization rather than creating a false dependability on any random or gut-based speculation.
Thriving organizations of today’s time are investing their human capital to clean, organize, and enrich data that can further be analyzed to empower decision-making processes. Many forward-thinking businesses are realizing that the necessity for data wrangling is due to the fact that data has grown to be diverse and unstructured. Just to let you know that there are six steps of data wrangling including discovery, structure, cleaning, enriching, validating, and publication.
Data enrichment has become a very crucial step for organizations because of the fact that it enables the data stakeholders to learn more about their existing users without having to ask them for additional details.
For instance, let's consider a very basic scenario where by simply asking for a user's email address, the organization can confirm their identity. In a matter of minutes and without creating any user friction, or delayed response or even delaying the user experience, Data Enrichment (if practiced) can assist the organization in risk reduction and evidently make sure about taking the integrity of the candidate for real transactions and eradicate the scope of fraudsters.
When the organizations are igniting their journey of growth & expansion, the more data the organization has access to, the more informed judgments the organizations can make. This is particularly true for organizations that lack essential customer data, when they are planning to land in a new market, upskilling to stay abreast of the current market trends, launching new products or even expanding their physical presence to become globally available online, etc. Data enrichment also catalyzes the learning about any risk that might occur to the organization due to fraudsters.
Types Of Data Enrichment
There are many different types of data enrichment, however the following are the most popular ones:
- Socio-demographic Data Enrichment
- Geographic Data Enrichment
- Purchase Intent ( Behavioral ) Data Enrichment
- Data Enrichment based on application usage
Socio-demographic Data Enrichment
Demographic Data Enrichment refers to the process that involves addition of demographic data to an existing dataset. The examples of such demographic data includes marital status, family size, etc. The data researchers may even gather a wide range of demographic information, such as the number of children and the type of vehicle driven, etc. But before the data collection, one must make sure of the purpose of carrying out this research.
Learning about the final deliverables of the study before enriching with demographic data can help ensure that the data that is collected is relevant and desirable for carrying out the study. For instance, the organizations dealing in insurance might consider the credit scores or even net worth of the house or the property that the client owns for calculating homeowner insurance premiums. By providing customized messaging, data enriched with demographic information can considerably enhance targeted marketing efforts.
Geographic Data Enrichment
Geographic Data Enrichment refers to the process that involves addition of geographic data to an existing dataset. The examples of such geographic data can be the Postal codes, learning about the geographical boundaries of the states, villages, cities, towns, etc.
All of this data can be gleaned via geographic data enrichment, which involves adding geographic data to an already existing dataset. Geographic information can be helpful in a variety of situations. For instance- let us consider the scenario where an organization wants to select among multiple locations for launching a new store or even to determine the footfall of customers in a particular area.
Purchase Intent ( Behavioral ) Data Enrichment
Purchase Intent ( Behavioral ) Data Enrichment refers to the process that involves addition of data that precisely assess a potential customer's propensity to purchase to an existing dataset. Because of Purchase Intent ( Behavioral ) Data Enrichment brands are able to make more informed decisions which are based on purchase interest and previous purchasing activity of the customer.
Organizations may even run targeted, performance-focused marketing campaigns that target the relevant consumers and influence them toward making a purchase decision by acquiring real shopping data and product view frequencies.
Data Enrichment based on application usage
Data Enrichment based on application usage refers to the process that involves addition of Application usage data to an existing dataset. Application usage information provides organizations with knowledge of the applications that their customers use, the operating systems they use to access the application, and also enables the organization to learn about the devices consumers use to access the application.
This technique of data Enrichment enables the organizations to more accurately identify user preferences that can improve the overall customer experience, and also help them determine which applications they should be targeting while running any marketing campaigns. This method also redirects the personalization efforts to become more effective when datasets are enriched with information about application usage.
How to Choose Data Enrichment for Your Business
For any organization to perform & practice Data Enrichment, must know that it cannot be completed in a single step. The client data seems to be always varying and even after being meticulously gathered from the beginning the data necessitates continuous attention and updation for the organization to stay current with customer demands. Organizations that might not be implementing data enrichment are definitely missing out on chances to add value to their business through pertinent offerings and interactions with clients based on the collected client data.
The gathered Data must be useful, actionable, and simple to comprehend, safeguarding privacy and compliance is a crucial component of data enrichment which should never be overlooked. It's essential that the third-party data utilized to enrich data assets is completely consented and compliant, particularly in some regions where there is strict enforcement of privacy laws. This might seem to look like a challenge for many industry providers to guarantee and work within the boundaries of such privacy laws.
Though there are many Data Enrichment tools ( such as Fivetran ) available in the market today, that guarantees that all third-party data sources are supported by unparalleled security and compliance. The good news is that more businesses have emerged than ever which offer complete automated data enrichment for the data sets. But finding one that truly matches the needs & purpose of the organization might seem to be a challenging task. But nevertheless, we’ve got you covered like always! Before diving deep into the search for the right tool, here are some things that require your attention:
- Manual or Automated DE tool: Data stakeholders must decide on what type of tool they would likely be keen on investing based on the needs & purpose. Also, this selection will be based on the amount of data set that is involved. Automated tools will be a desired choice if the organization has enormous data to enrich. Manual tools can serve well when dealing with comparatively smaller data sets.
- Integration: Do you wish to use an API to work? or get the database yourself and run the search yourself? Answering such questions will concretely carve your path to reach the end stop for your search for an appropriate tool. Though,it might be simple for developers to create bespoke integrations, but it's not always accessible and also might not be an effective thing to invest on when there are tools that can do it for you.
- Legality and Data Quality: How recent is the information you're gathering? And does the business providing it adhere to laws like data protection or privacy? Organization must look out for the three key concepts of Data protection i.e. Confidential, Integrity, and Availability.
- Pricing: Pricing is another key aspect that one must look into. Most of the third party data enrichment providers charge a small cost for each check but before finalizing any tool have a quick chat with the provider to discuss any hidden charges that might arise later.
Examples Of Data Enrichment
- Make lead generation forms smaller: Initially the aim must only be to capture the information, and then enrich that gathered information. Because who do you think will complete a form with numerous informational fields? The conversion rate is higher when the shorter and simpler the contact form is. It is only because of Data enrichment that organizations now have the option to keep forms as straightforward as possible. It is a good practice to ask the bare minimum like- name, email address, and company. Once you have the lead, you may complete the profile by adding information.
- Identify and eliminate form fields that discourage users: Did you know that requesting a phone number reduces the conversion rate of lead generation forms by 5%? Leads frequently show reluctance when asked for too much personal information like turnover, addresses, etc. However, with data enrichment, you can convince them later rather than immediately. You can get it on your own. Simply eliminate the form fields that have a detrimental effect on conversion to increase leads.
- Segment and arrange your data by using data enrichment to give meaning to the jumbled data. This can be done by putting an emphasis on data quality and concentrating on the data that is most important to the organization. Once the information is handy, divide leads into segments based on traits that they have in common. Create email lists and ad target audiences using the segments to then launch focused outreach initiatives.
- Enhanced personalization: The success rate of personalized email messages is 46% greater than that of generic emails. Customizing email outreach with the knowledge and insights provided by enriched company data can speak wonders and is a more tailored and pertinent way of doing things.
- Make a mechanism for scoring leads: The practice of categorizing leads based on their worth and amount of interaction is known as lead scoring. Leads are given scores based on their activities and interactions with your brand, such as website views, email clicks, content downloads, etc. Typically, a marketing automation technology is used for this. Only a small percentage of leads are ever truly ready for sales. With more information about each lead, you'll be better able to design a lead scoring system.
- Watch for and recognize business signals: A business signal is any action that suggests a lead would be wise to make a purchase from you. You typically hear about timely, news-driven information from a company's social media accounts or other media sources. It can involve raising money, making management changes, conducting recruitment campaigns, or creating a new office. This kind of information can be directly downloaded from the internet into your contact database via data enrichment. It not only helps you pace your pitch, but it also gives you a chance to further customize your outreach.
- Give dead leads a second chance: It's time to clean off your "Lost Leads" file of dust. Budget, requirements, and decision-makers are all dynamic concepts. A lead may not always be uninterested or unprepared just because they weren't then. Even a dated prospect list is valuable. By incorporating new information and insights, data enrichment techniques can help it come to life again. It's the ideal approach to draw attention to fresh prospects.
Benefits Of Data Enrichment
- Enhanced consumer segmentation: Segmentation is a crucial marketing technique that aids in focusing advertising efforts on particular demographic groups. Marketers can build tailored messages that appeal to customers who may not have previously shown any interest by utilizing segmentation technique. Data enrichment gives advertisers the chance to segment based on data from third parties, frequently including factors like purchase intent or app usage. This gives marketers more tools to identify new clients and produce content that is especially suited to the preferences of those various groups.
- Increased conversion rates: Although manual lead scoring might be tiresome labor, it is essential for increasing conversion rates and creating a productive working relationship between the sales and marketing teams. Utilizing information from other sources, data enrichment can assist firms in automating the lead scoring process.
- Enhanced personalisation: Organizations are better able to seize opportunities with a customer-centric approach that is tailored to specific preferences and demands. You need more than just statistics; you also need enriched information from other sources if your company's efforts to understand clients' preferences are to be successful or not wasted in mass-market advertising campaigns rather than targeted ones.
- Savings from Data Enrichment: Data enrichment helps you save money by preventing the storage of data that is not pertinent to your company's operations. Instead, you add external data sources to the internal data to improve it for your firm. The money that would have been spent on databases is now put toward other projects that boost revenue.
- Developing strong customer relationships: Enriched data encourages personalized messaging. Your company may create communication strategies that cater to client preferences and wants if it has access to pertinent customer data. When a customer believes that your business is aware of their needs, they are more inclined to make a purchase.
- Increased Sales: Imagine spending a lot of money on your contact list in the hopes of attracting clients and prospects, only to find out that it is out-of-date. Such losses are unaffordable for businesses. In order to improve sales effectiveness and raise ROI, data enrichment makes sure you have a clean and correct contact list. Additionally, because a company has the correct data and is well acquainted with its clients, it presents potential for cross-sells and upsells.
Tools for Data Enrichment
With the help of a data enrichment tool, you can discover more about consumers using just a few data points. For instance, with merely an email address, it is possible to cross-reference the user's existence, the use of a free or temporary domain, and the existence of any related social media accounts.
Businesses can gather, organize, and prepare data from a number of sources with the aid of software or other services known as data enrichment tools. To make a dataset more complete and valuable, these methods can be used to add other data points, such as contact details, demographics, or behavior. Tools for data enrichment can be very helpful for boosting data analysis, personalizing user experiences and recommendations, and focusing marketing efforts.
The optimal data enrichment tool for you will rely on your unique demands and requirements. There are many different data enrichment technologies on the market. The optimal tool for your needs should be chosen after carefully comparing the features and capabilities of several tools.
How FiveTran helps in Data Enrichment?
With Fivetran, the data team can access the entire data at their fingertips. Automated enrichment creates powerful, precise lead scoring and routing, detailed customer segmentation, and results-driven reports. Bid adieu to incomplete records and outdated contact details. Fivetran interacts with your go-to tools to deliver the data you need where you need it & all thanks to its robust architecture.
Make data-backed decisions the norm, stop spending time on manual data entry, and unify your go-to-market teams. Utilizing Fivetran can swiftly combine various datasets from various source systems and evaluate the caliber of the enriched information. Organizations can also keep an eye on changes to the workflows they use for data enrichment which also makes sure that data security is prioritized and that customers' private information is not jeopardized.
The industry leader in data preparation, Fivetran, manages everything related to data, including data wrangling, data enrichment, and data cleansing. Fivetran emperors the organizations to quickly, accurately, and easily prepare the data for further analysis and helps the organization with all of the data enrichment needs.
So what are you waiting for?! Utilize Fivetran to enrich your data and increase the value of the existing data for the profitability of the organization.Set up a meeting with us to go over your data project. To learn more about how to combine your data efforts and uphold the highest level of privacy on one platform, get in touch with our team for a demo.
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