Top Data Enrichment Strategies to Maximize Business Values
In the digital world, where data comes from smart applications and electronic devices, it becomes a necessity to proactively manage and use it. However, it’s challenging to collect and refine their structure to easily get insights and drive informed decision-making. But it’s also true that where there is a will, there is a way.
Recently, sad news broke on the internet. A reputed ICICI bank had to bear massive losses and defamation. It reissued about 17,000 credit cards, which constitute about 0.1 percent of the overall credit card portfolio of the bank. Earlier, they were erroneously assigned in its digital channels to the wrong users.
Though the raw piece of information may not be in its ideal form, it requires enrichment. This very process of refining and augmenting its value is called data enrichment. Technically, this process is a typical way of making data refined, improved, and comprehensive. This is done by using external and internal sources. These sources carry demographic information, geographic data, behavioural insights, psychographics, or anything useful. This process gives an organization a stronger position through insights-driven decisions for customers, operations, or targeted marketing campaigns.
Wondering what strategies can help with effective data enrichment? Let’s figure it out below.
Strategies for Effective Data Enrichment
The following data enrichment solutions are proven and indeed helpful to make the most of enriched data. Let’s find out the most effective strategies.
1. Identify business objectives
The very first step in this process is to identify or discover the main objective of the corporate data. Since it’s for integrating valuable information, you need to discover what information is required and if it’s not in your existing datasets. In this case, the goal or objective can provide you with accurate hints. They can be helpful in improving customer segmentation, streamlining sales processes, enhancing product recommendations, etc. Or, you may think about what data would be most valuable to meet your objective.
Simply put, the objective says everything. It will guide you to enrich your database so that you can focus on the right sources of data.
2. Select relevant data sources
The next strategy is to select relevant data sources. Bring the best-fit data sources to enrich your existing database. For this purpose, internal CRM or external data providers, such as third-party data providers, can offer a pool of information to complete customer profiling. These providers collect precious data from various sources, like surveys, online polling, etc., to create comprehensive databases. Considering the value of third-party data, it is mostly accurate and up-to-date. This enables users to enrich datasets with the requisite details.
3. Ensure data quality and consistency
The next strategy is crucial because it makes data luxurious. It is to introduce quality on a consistent basis. Before integrating any new component into the data, ensure that the collected information is valuable, clean, and accurate. Data wrangling or cleansing, especially validation processes, can prove a milestone. Where wrangling takes care of its hygiene by removing duplicate entries and typos, data validation validates the authenticity of that data. This is how you can ensure that it meets quality protocols and standard data structures.
Always remember that bad data produces strategies that are inflexible and unreal. That’s why it is necessary to prevent unhygienic information from integrating.
4. Leverage automation and AI
With the advent of automation and artificial intelligence, businesses rely on them to significantly make data more comprehensive. These advanced technologies simplify progressive profiling, which means collecting critical information of customers through forms whenever they visit the website or online platform. You can integrate these tools with CRM or the touch points where the leads or inquiries generally come from.
You can also employ natural language processing and machine learning algorithms for this purpose. The chatbot, for example, can certainly handle and process a large volume of data quickly and accurately. This is how progressive profiling can be quickly done. It can enrich you with addition information and time to analyse and process inquiries and draw valuable insights. Later, these insights can prove a milestone, contributing to the success of marketing campaigns.
Also, you can gradually gather crucial customer details at diverse touchpoints online, which creates a positive user experience.
5. Integrate tools
Multiple tools, like Zoominfo, Full Contact, etc., and platforms for data enrichment are available these days. You can use them to streamline the enrichment process. The beauty of these tools is that they won’t solely rely on manual effort. These tools automatically keep the data up-to-date and verify the authenticity of the data. It refers to various resources to cross-check them with external sources.
6. Customer feedback and online
surveys
Nothing could be as authentic as survey data for collecting and enriching a database. You get information directly from customers. This is because surveys and feedback forms engage customers in a direct conversation with your target audience. These forms allow you to ask, gather authentic information so that it can be processed for valuable insights. Businesses can discover customer intent, pain points, demographics, or anything that can be helpful.
7. Implement privacy and security measures
The most important strategy is executing privacy and security measures. Because every data is helpful and consists of something meaningful, it becomes a necessity to secure it. Even the GDPR compliance are established for the same purpose, which ensures that businesses must make all arrangements to secure sensitive information. Also, these regulations make it necessary to get consent from the owner of the data if required, and reveal the purpose of its usage without hiding anything.
Conclusion
The aforementioned details shed light on how to strategize sources for data enrichment solutions, which can prove powerful in augmenting the value of data. These strategies can include selecting the right and relevant sources, ensuring premium quality, discovering insights, driving target marketing, optimizing operational efficiency, etc. It is true that data-driven decision-making continues to scale and adapt to changes. It is compulsory in the increasingly critical environment of a business that continues to change.
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