What is data enrichment?
Data enrichment is the process of using multiple data sources to create a more complete picture of the customer. This can be done by combining information from different data sources or using different types of data (such as text and images).
For example, if you’re a restaurant and want to know which dishes your customers like best, you could ask them for their email addresses in order to send them coupons or discounts on future visits. If they don’t have a smartphone or tablet yet but are willing to sign up to receive these offers via text message (usually cheaper than email), this would be a good way to get more customers into your restaurant!
The goal is to build profiles that provide you with insight into your customers so that you can better serve them. The result will be comprehensive profiles containing all the necessary details about each customer: their interests, behaviours and preferences—everything needed for a successful marketing campaign or product launch. Here are some examples of how data enrichment is helping businesses generate value
Customer experience
Customer experience is what drives business success in today’s highly data-driven world. As such, it’s an important factor in driving loyalty which can be measured by how much time consumers spend on average interacting with particular brands and how often they return.
Data enrichment can be used to improve the customer experience. For example, a business might want to know where its customers live so that it can provide them with local information about restaurants and entertainment options.
Targeted marketing campaigns
Data enrichment is a powerful tool that allows you to find out what customers like, what they buy, and how often they purchase from your brand. It also helps you target those customers with relevant content or offers based on their preferences in order to increase engagement with your brand and drive sales. Data enrichment can help you identify the right audience for your campaign. It also helps you target those customers with relevant content or offers based on their preferences in order to increase engagement with your brand and drive sales.
For example, if you know that your target audience lives in the North East of England, you could use this information when designing an ad campaign targeting people who work in tech companies there—it will mean more sales!
Personalisation
Personalisation is a great example of how data enrichment can help businesses generate value. It’s used to target customers with the right product or service, improve customer experience, make more informed decisions on behalf of their customers and also for targeted marketing campaigns. Personalisation can be used to personalize offers based on their preferences. This allows you to provide tailored content they would want to receive, increasing the chances of converting them into loyal customers and building a strong brand image in their mind. For example, if someone buys something online but doesn’t want it shipped directly to their home address, then this person might need some assistance getting their package sent back safely through customs—and data enrichment could help them figure out how much extra money they’ll need before making another purchase!
Data enrichment and predictive analytics
Predictive analytics is a type of data mining that uses statistical techniques to predict future events. In order to use predictive analytics, you first need a sufficient amount of historical information about your customers or products. This can be obtained through web analytics, customer surveys or other means (such as analysing sales orders). Once you have access to this historical data set, it’s possible for you to apply predictive algorithms on top of it using machine learning techniques like neural networks or deep learning.
The goal here isn’t necessarily just predicting what will happen next rather than simply detecting patterns in the past—which could lead us down unsophisticated paths toward false conclusions. Instead, it will be finding patterns where none existed before (or at least not easily). For example, if I were planning to purchase something online tomorrow morning, then my purchase history would likely show me purchasing items similar throughout past purchases. This could be useful information if we knew anyone who did this regularly enough so that we could potentially predict their future purchases accurately based on past ones.
Enriched data can lead to valuable insights and improve your business.
Enriched data can lead to valuable insights and improve your business. The more information you have about your customers, the better your marketing campaigns will be. The customer journey is also critical, especially in the digital space. If a customer has purchased your product and had a good experience, chances are they will buy again—but this time with an improved experience because of enriched data in their purchase records.
Data enrichment helps you target customers better by giving them a personalised experience based on what they have done before (or not done). For example, if someone visits your website but doesn’t buy anything because there is no reason for them to do so yet, enriching their purchase history might help encourage them to return later after deciding on something else.
Conclusion
As we’ve seen, data enrichment can be a powerful tool for helping companies make better decisions. Your business may already have some information that can be used to improve your operating model, and you could use data enrichment as a way to enhance it. There are many ways to get started with data enrichment, so start today!