Marketers across industries share a common pain point: marketing data management.

Poor marketing data management holds them back from reaching their marketing goals and delivering great omnichannel customer experiences.

The result is disjointed customer experiences, a lack of visibility into the end-to-end customer journey, slow action times when new types of data are introduced and failure to hit the all-important right message, for the right audience at the right time. 

Using marketing data management to your advantage connects fragmented customer data, providing a single view of the customer — but many marketers don't know where to start when choosing a solution.

3 Choices for Managing Customer Data 

These three marketing data management solutions each tackle a specific challenge: 

  1. customer data hub (CDH)
  2. data management platform (DMP) 
  3. marketing data lake (MDL)

All three help you better manage marketing data. But that’s where the similarities end. 

Some organizations may find they need all three, as each delivers unique — and complementary — value.

uses, users and characteristics of marketing data management solutions

Manage Prospect Data with Data Management Platforms

Data management platforms have the most limited scope, in that they are used solely for managing prospect data for digital advertising. They can send hyper-targeted digital ads via display, search, video, mobile or even social media. 

If you’ve ever noticed a product you searched for on one website is suddenly appearing in banner ads in other places you browse to, you’ve been targeted by a retailer using a DMP. 

DMPs are very effective at helping marketers optimize their media spend and improve campaign ROI. 

But they won’t give you a true single view of the customer, which includes all customer interactions across channels and functions. That’s where a customer data hub comes in. 

Here’s where DMPs fall short: 

  • Focus only on digital channels and activity
  • Does not provide a total view of customer across all channels and functions
  • DMP analytics are purpose-built for ad campaign reach and funnel
  • Offline data must conform to DMP structure
  • DMPs are owned by third parties, giving users less control of data

Get a Single View of the Customer with a Customer Data Hub

Managing the end-to-end customer experience means you need a single view of your customer across all touchpoints. You need to manage data across your whole enterprise. 

A customer data hub includes all of the core customer data that can be found across your marketing, sales, customer service and finance teams; across your lines of business; and across your regions and channels. 

In addition to data management, a CDH ensures the high quality of your data by:

  • identifying and resolving duplicate customer profiles across applications and data sources 
  • validating the accuracy of contact information (email, phone and address) 
  • enriching customer profiles with other data sources 
  • managing relationships between: 
    • customers and their households, family members or influencers
    • customers and company employees or sales channel partners 
    • customers and the products, services or assets they purchase or rent
    • a customer’s profile in marketing apps, the CRM app and their social profile. 

A CDH delivers clean, safe, consistent data, making it a powerful tool for improving marketing results and customer experience. Because its data is shared across the whole organization, every customer interaction can be based on consistent, accurate and up-to-date customer data.

how a customer data hub fits within customer data management ecosystem

A CDH delivers all of the following: 

  • A single view of customer (SVOC) across touchpoints 
  • A 360 degree view of valuable relationships
  • A complete view of all customer interactions across channels and functions 

Unlike a DMP, a CDH lets you improve customer experience beyond the marketing function. 

Benefits of a CDH:

  • Fuels MarTech, sales and service applications, as well as analytics
  • Performs data quality tasks to maintain data trustworthiness and consistency
  • Pulls data from the applications you use today, including your marketing automation, CRM and more, and fuels those applications with great customer data 
  • Aligns the customer experience across the company
  • Recognizes customers any time they interact with you

Capture Big Data with a Marketing Data Lake

A CDH is perfect for managing all the customer data within your enterprise, but big data creates different challenges. 

Big data includes many data types that are unstructured or lie beyond your enterprise footprint: things like web clickstream data, call logs, social media, sensors connected to the Internet of Things (IoT), location and mobile device data. 

Marketers know they must begin to take this data into account to improve their marketing results and deliver great customer experiences across channels. 

To capture, manage and gain meaningful insights from big data, either you need to structure the data to make it usable (a lot of heavy lifting which increases cost and takes up a lot of time) or use a new technology designed specifically for this unstructured or semi-structured data. 

Enter the marketing data lake (MDL).

In a recent poll, one in five marketers didn’t know what an MDL was. An MDL is a one-stop-shop for any type of customer related data for analytical purposes, such as web clickstream, social media, sensor, location and entire third party data files as well as traditional data types from CRM and the marketing automation platform (MAP). 

There are no strict requirements on the type of data it houses. It helps you be more agile. It allows you to ask new questions and run new reports and analyses on data you couldn’t use before. 

For example, only an MDL lets you add context to your customer data so you can answer questions like: What things did this customer look at before buying? Or: What else do we know about this customer that would help us serve the right offer? 

An MDL brings islands of data together so you can see the end-to-end customer journey and take action on it. 

Who Doesn't Need an MDL

An MDL isn’t the answer for everything. Who should not build an MDL?

  • People who need penny-perfect data
  • People who only work with structured data
  • People with zero IT support
  • People who aren’t into analytics
  • People with messy data or core marketing systems

Tackle Your Data Management Challenges

Once you understand the unique capabilities provided by each marketing data management solution, you can envision using them together in a holistic marketing data strategy. 

You can use a DMP to do targeted ad campaign management. You can use a CDH to get a single view of the customer across channels and functions. You can use an MDL to connect data from disconnected marketing and sales applications to see the end-to-end customer journey and gain valuable customer and marketing insights. 

Still confused about the differences? Take a deeper dive into these three solutions.

How do you plan to tackle your most pressing marketing data management challenges? 

Title image Hannah Wei