We live in a data economy. The explosion of data and the ability to use that data to make more informed decisions have drastically changed the way we do business—for the better.
But many organizations have found that even though they have all the data they want, putting it together and determining exactly how to use it still proves challenging.
That’s where data solutions come into play. But with so many options for different types of tools that manage, cleanse, transform, combine, and help you act on data, how do you know which one is right for your business? And what does each of those tools even do?
You’ve come to the right article.
Six Types of Data Solutions and What You Need to Know About Them
To better understand the various tools available to help your business unlock the power of its data, let’s take a look at six types of data tools, including the purpose they serve and the benefits they offer.
1. Customer Data Platform (CDP)
What is it? According to the CDP Institute, “a Customer Data Platform is packaged software that creates a persistent, unified customer database that is accessible to other systems.” Critically, a customer data platform not only offers a centralized place to house first-, second-, and third-party customer data but also makes it easy to take action based on that data.
Who uses it? Marketing and sales teams that focus on engaging and retaining prospects and customers can use a CDP to improve their understanding of customers and run more informed and efficient campaigns.
Do you need it? Any business with customer data sitting in multiple systems can benefit from a CDP. This type of platform brings together all that data to create a 360-degree view. In doing so, a CDP makes it easy for marketing and sales users to better understand customers and take action accordingly. A CDP also streamlines processes and simplifies reporting because it allows users to view and take action on data in one place.
What are some examples of a CDP? Hull, mParticle, Zaius
2. Customer Relationship Management (CRM)
What is it? A CRM system manages all of your business’s interactions with customers and prospects to give users insight into the customer relationship. As a result, a CRM acts as a system of record for points of engagement with customers and prospects.
Who uses it? Sales teams use CRM systems to manage their relationships with customers, making it something of a modern (and supercharged) rolodex. In some cases, marketing and customer service teams may also look at CRM data to manage their interactions with prospects and customers.
Do you need it? A CRM system is necessary to manage customer and prospect relationships at scale. By logging all customer interactions, a CRM system provides an important record of what actions customers (or prospects) have taken, what information has been shared with them, and when the last point of engagement took place. Having that information handy is critical for salespeople to do their jobs effectively and for reporting on sales activities. Moreover, that data is an essential component of creating a 360-degree view of customers, which you can do by combining it with customer data from other go-to-market platforms (e.g., marketing automation) through a CDP.
What are some examples of a CRM? Salesforce, Pipedrive, HubSpot
3. Data Management Platform (DMP)
What is it? A DMP aggregates and organizes second- and third-party data from a variety of systems. Although it sounds similar to a CDP, the two platforms are actually quite different. The key difference lies in that DMPs serve one core purpose: to segment data from different external sources to build intelligent groups of customers for use in advertising campaigns. Furthermore, a DMP holds data only for about 90 days (the lifetime of a cookie). A CDP, however, serves a variety of purposes for understanding and taking action based on data, and can act on historical first-party data from any point in time.
Who uses it? Marketers and marketing agencies can use a DMP to power advertising efforts, for example by using it to create a “lookalike” audience for customer acquisition.
Do you need it? In some cases, you can use a CDP and DMP together, with the DMP focusing on third-party data for paid advertising campaigns and the CDP focusing on all other marketing activities. However, if your goal is to focus primarily on your own, first-party customer data to develop long-term campaigns that engage prospects and customers over time, then you need a CDP—not a DMP.
What are some examples of a DMP? Adobe Audience Manager, Oracle BlueKai, Lotame
4. Data Integration & Workflow Tools
What is it? Data integration and workflow tools carry data between systems and perform actions like transforming, mapping, and cleansing data. These tools move and manipulate data and can then trigger actions based on selected criteria.
Who uses it? Business analysts, marketing, sales, and IT users can all use data integration and workflow tools in a variety of ways to move data across different systems.
Do you need it? Data integration and workflow tools play an important role in combining and standardizing data. Particularly if your organization has a CDP, these tools can be critical to carrying over data from other systems across the organization so that the information is available for reference and action within your CDP.
What are some examples of data integration and workflow tools? Zapier, Automate.io, Segment, Tray.io
5. Data Lake
What is it? A data lake stores both structured and unstructured data, all in its original form. Data lakes are highly scalable, so data never gets deleted, allowing data lakes to hold historical information for any length of time. However, a data lake does not handle any analysis of data.
Who uses it? Because a data lake stores such large volumes of data, all in its original form, it is best suited for data scientists who can handle such varying types of data at scale.
Do you need it? If you have a data-science team, a data lake can be extremely useful for storing all types of data for any length of time. Without a data science team to manage it, however, having a data lake—considering the complexity of these systems—can become much more challenging for your business.
What are some examples of data lakes? Amazon Web Services, Google Cloud Platform, Informatica
6. Data Warehouse
What is it? A data warehouse combines structured data from multiple sources for comparison and analysis. Data housed in data warehouses is typically cleansed and organized for specific purposes, and it’s used for business intelligence.
Who uses it? IT users and business analysts are the primary users of data warehouses because of this solution’s focus on data analysis and business intelligence.
Do you need it? When used correctly, data warehouses can arm executives with insight into performance across the entire business. But storage in data warehouses is typically limited and the data must be structured, which means data warehouses are useful only if you have the right resources to manage the storage and ensure you have enough structured data to feed the system. If you do, a data warehouse can also feed into other data systems, such as a CDP, to help supercharge the data available to nontechnical users in Marketing and Sales.
What are some examples of data warehouses? Amazon Redshift, Microsoft SQL Server, MySQL
Managing—and Using—Your Data at Scale
The rise of the data economy has had several iterations. A few years ago, simply being able to manage all of your business’s data was considered a win. But, today, the goal is to actually use that data by making it easy for people in all roles, regardless of technical ability, to take action based on that data. When you use data in this way, you allow for more informed decisions and more efficient processes—which come together to increase revenue for your business and simultaneously decrease costs.
So how do you reach that desired point? It’s all about having the right solutions to manage, cleanse, transform, combine, and act on data. Critically, you need tools that not only perform those tasks but also make it easy for all kinds of users to interact with and use data every day.
The mix of solutions that’s right for your business will depend on your data, your goals, and your team structure, as noted earlier; but some solutions—such as a CRM to act as a system of record and a CDP to combine data from different sources and make a full view of data actionable—are essential to just about any organization’s success in the data economy.
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