What is the difference between ETL and CDP?
15 years ago, marketer Clive Humby proclaimed that "data is the new oil." And while that may have been a bit of an overstatement at the time, data is certainly the lifeblood of business today. In order to make informed decisions and competitive moves, companies need to collect data from a variety of sources, clean and process it, and then use it to power their analytics and business intelligence (BI) applications.
Businesses use various data solutions to collect, clean, process, and analyze data. Let’s focus on two major solutions: Extract, transform, and load (ETL) tools, and customer data platforms (CDP).
The terms ETL (Extract, Transform, Load) and CDP (Customer Data Platform) are often used interchangeably, but there is actually a big distinction between the two. ETL is a process that extracts data from a source, cleans and prepares it for analysis, and then loads it into a data warehouse or data mart for reporting and analysis. A CDP, on the other hand, is a system specifically designed to collect customer data, for real-time access and use by sales and marketing.
Both of these solutions have their own strengths and limitations.
What Exactly is ETL?
To better understand ETL, imagine your company has a data warehouse that stores information about customers, orders, and products. Your marketing team wants to analyze customer purchase data to figure out what product lines are selling well. To do this, they need to access data from the data warehouse as well as data from your order management system and your product catalog.
The ETL process would involve extracting data from the order management system and the product catalog and loading it into the data warehouse or a CDP. The marketing team could then use this data to create reports and graphs about customer purchase behavior.
ETL tools are commonly used to cleanse and consolidate data from disparate sources before loading it into a centralized data store. This allows businesses to more easily analyze the data and make better decisions.
These include tools like Xplenty, Talend, Hevo Data, and Informatica. They can be used to extract data from a variety of sources, including the web, social media, CRM systems, ERP systems, and data lakes. The extracted data can then be cleansed and processed using a variety of methods, including SQL, standard transforms, and machine learning algorithms.
The point of ETL is ultimately to break down data silos and make the data more usable, whether for data scientists, business analysts, or marketing professionals, which is a crucial step to gain value from raw data.
What Exactly is a Customer Data Platform (CDP)?
CDPs are used to analyze customer data from a variety of customer data sources, including web traffic, social media, CRM systems, purchase histories, and more. They then clean and process the data to create a single customer profile for each individual. This profile can then be used to power BI applications and drive marketing decisions.
CDPs are a great tool for businesses that want to better understand their customers. They provide a single view of the customer, which can be used to create targeted marketing campaigns and personalized customer experiences.
These tools centralize data from multiple sources, which can be difficult and time-consuming to do on your own. Additionally, they make collected data more accessible and easier to use in any department.
Why Use Both ETL and CDP?
There are several reasons that businesses might choose to use both ETL and CDP.
For one, ETL tools are great for data preprocessing. They can be used to clean and process data from a variety of sources before it is loaded into a data warehouse or data mart. This allows businesses to more easily analyze the data and make better decisions. Meanwhile, CDPs are great for consolidating data from multiple sources into a single database.
ETL tools and CDPs can be used together to create a more complete view of the customer. For instance, ETL tools and CDPs can be used to target customers with more relevant ads.
What's Missing from ETL & CDP: Unstructured Data
Although, traditional data infrastructure has significantly evolved to current sophistication, it falls short when it comes to unstructured data. Data such as text, voice, video, and images now account for 90% of the world's data and it is not utilized due to lack of tooling needed to convert it to a structured format. We have set out to do just that. Coming back to ETL tools, they can be enhanced by using Commerce.AI.
How Commerce.AI Can Enhance ETL Tools
First, Commerce.AI can be used to extract data from sources that ETL tools cannot access on their own. This includes data from unstructured sources like the web and social media.
Second, Commerce.AI can be used to augment the functionality of ETL tools. For example, Commerce.AI can be used to identify relationships between data sets that ETL tools cannot detect on their own.
Third, Commerce.AI can help to improve the performance of ETL tools. By using Commerce.AI to analyze data from a variety of sources, ETL users can minimize the amount of time they spend on data preprocessing or collection.
How Commerce.AI Enhances CDPs
The goal of a CDP is ultimately to gain a deeper understanding of the customer. Commerce.AI can help businesses do this by augmenting CDPs with its massive data engine, which has scanned over a trillion unstructured data points.
This data can be used to improve customer profiles and create more targeted marketing campaigns. Additionally, Commerce.AI can help identify opportunities and trends that may not have been visible before.
For example, if a business is only looking at purchase data from their own website, they may not be aware of market opportunities with complementary products or services. However, by incorporating Commerce.AI's data into their CDP, they may be able to identify these opportunities and increase their sales.
Important Considerations for Powerful CX
Given the importance of data in business, it’s no wonder that both ETL and CDP platforms are in high demand. But before you rush out and buy either one, there are a few things you need to consider.
One important consideration is the source of your data. Most businesses have a variety of data sources, from internal systems like ERP and CRM to public sources like social media and government data. Not all ETL or CDP platforms are created equal when it comes to sourcing data.
ETL tools are generally designed for extracting data from internal systems. They can handle some public data sources, but they are not as well equipped to handle the variety and volume of data found in social media and other public sources. CDPs, on the other hand, are designed to ingest external data as well. This often makes them a better choice for businesses that want to use public data to power their customer experience initiatives.
Supercharge Each Platform with Unstructured Data using Commerce.AI
Both ETL and CDP platforms are essential for businesses looking to collect, clean, process, and analyze data. But which platform is best for your business depends on your needs.
If you need a platform that can extract data from internal systems and some public data sources, then ETL is the better choice. If you need a platform that can ingest all customer data in its original form, from any source, then CDP is the better choice.
But even if you have already decided on an ETL or CDP platform, you can still supercharge your CX initiatives by using unstructured data. Unstructured data is data that is not organized in a pre-determined way. It includes data like text, images, and videos.
Unstructured data is difficult to handle and process, but it is also very powerful. It can be used to improve customer understanding, personalize customer interactions, and optimize customer journeys.
Fortunately, there is a solution that can help you to supercharge your ETL or CDP platform with unstructured data: Commerce.AI. Commerce.AI is a machine learning platform that can handle all types of unstructured data. It can be used to improve customer understanding, personalize customer interactions, and optimize your business processes.
Takeaways
Data fuels modern commerce. The more high-quality data companies have, the better they can understand their customers, products, and markets. However, collecting and managing data is challenging. Data must be cleansed, normalized, and transformed before it can be used for analysis or machine learning.
Commerce.AI’s massive data engine helps companies overcome these challenges. Our engine ingests and cleanses data from a wide variety of sources, including websites, social media, and ecommerce platforms. It then normalizes and transforms the data into a format that is ready for analysis and AI.
The Commerce.AI engine can also enhance other data solutions like CDPs and ETL tools. Our engine combines data from many different sources, allowing companies to get a more complete understanding of their customers and markets. The engine can also improve the accuracy of machine learning models by using more data to train the models.
Commerce.AI is the perfect solution for companies that want to take their data-enabled product and service innovation to the next level.
