As organizations creep toward a common standard of customer data collection through marketing automation, CRMs, and a host of attribution and other pinpoint marketing technologies, the bar is raised for staying ahead of the curve, and marketing looks to IT to solve it. This collaboration has led to two primary options:
- Develop an in-house solution using data warehouses and business intelligence tools, which can be costly and time-consuming.
- Implement a Customer Data Platform (CDP), offering a more cost-effective and rapid solution.
The explosion of CDPs addresses a critical need in enterprise marketing: the ability to consolidate and analyze disparate data sources effectively. With 52% of marketers citing integration as their biggest MarTech challenge, CDPs offer a promising solution.
Understanding Data Management Solutions
To make informed decisions about data management, it’s crucial to understand the differences between key solutions:
- Data Warehouse: A centralized repository for structured data, designed for specific reporting needs.
- Data Lake: A storage system for raw, unstructured data.
- Customer Data Platform (CDP): A purpose-built solution for customer data, offering pre-built integrations, advanced analytics, and marketing-specific functionalities.
CDPs stand out by providing a comprehensive view of the customer journey, something traditional CRMs and Marketing Automation Platforms (MAPs) often struggle to deliver.
The Business Case for CDPs
When IT is tasked with solving marketing problems, they must understand the core business problems that drive the need for change. When considering a CDP implementation, organizations should focus on three key areas:
1. There is a need for significant improvement in marketing campaign effectiveness.
Let’s be honest: Marketing managers have been through the wringer. An onslaught of tools and shifting priorities have left them with more information, yes, but also without clear conviction about what to do with it, or how to measure its impact.
A CDP increases your visibility into how effective your campaigns and content have been across the entire customer journey, from unknown visitors to paid customers. With that information, a marketing manager can confidently report on overall campaign effectiveness and not lose her sanity over it.
2. There is a need for deep insights into marketing spending and ROI.
The disconnect between spend and ROI is glaring and painful. With a comprehensive view of performance that’s tied directly back to your budget, you can better understand the return on your marketing investments to improve quarter over quarter.
3. There is a need for more efficient analytics processes and automation.
Most marketing teams miss the mark because they stop at the dashboard and either don’t or cannot take the actions necessary to change what the dashboard shows them.
A CDP not only automates reports but can also automate many of the marketing actions between systems. From fixing data in Salesforce to segmenting a Smart List in Marketo to matching an ABM audience for a LinkedIn campaign, CDPs can write data back to other systems. This is not something a homegrown data warehouse can do.
“Insights with no action is an academic exercise and a waste of money.”
– Allison Snow, Senior Analyst, Forrester
What it Takes to Build & Maintain an In-House System
If the primary goal of your project is to be able to support deep marketing analytics, then we should begin by defining exactly which types of reports would be required. For this exercise, let’s assume that the focus is on showing these:
- Data Management
- Marketing Analytics & Attribution
- Return On Ad Spend
- Customer Engagement
- Funnel Performance
For attribution, the system needs the ability to handle multi-touch attribution models and optionally support deeper machine learning models downstream (Chain-Based Attribution). The second goal is to orchestrate and push segments back out to the systems of engagement. To simplify things, let’s assume there is a requirement to push segments of users into the marketing automation platform and CRM based on receiving intent signals.
Your build-out would look something like this:
The devils are in the details of each of these. Remember that IT teams aren’t made up of marketers (for good reason). AI’s ongoing analysis, maintenance, and fluid nature are paramount to an effective CDP. Maintaining constant API changes from your CRM, MAP, Web Analytics systems, and other vendors presents persistent challenges and demands dedication.
In addition to the IT team, you’ll need several resources to bring it all together at various points:
- Marketing Ops team
- Data Analyst
- Javascript/Python developer
- Database/SQL developer
- Marketing Demand team
- Business Analyst
- BI tool expert
- Marketing Leadership
Where does machine learning fit in? The holy grail of having all this data is to get insights and understandings about the behavior of your customers and prospects and act upon it quickly and efficiently. Machine Learning is the next evolution of marketing analytics and promises to allow you to turn that data into activities and actions.
To support these algorithms, you need to have your data set up in a way in which the algorithms can learn from and that supports meaningful outcomes.
If you are building your own platform and wish to do machine learning down the line, there are requirements over and above what I just listed that would expand the project’s scope and require additional resources that understand machine learning and data pipelining.
Build vs. Buy: Evaluating Your Options
When deciding between building an in-house solution or implementing a CDP, consider the following factors:
- Resource Requirements: In-house solutions demand diverse expertise, including IT, marketing ops, data analysis, and more.
- Time to Value: CDPs offer faster implementation and quicker insights than custom-built solutions.
- Scalability and Flexibility: CDPs are designed to adapt to changing marketing needs and technologies.
- Ongoing Maintenance: In-house solutions require continuous updates and maintenance, while CDPs are managed by vendors.
Refer to our comprehensive CDP Build or Buy Guide for a detailed comparison.
Final Thoughts
A CDP positions the business for revenue acceleration. It is the data and analytics bridge between marketing and business and between the CMO and the CFO/CEO and the board.
Data is power only if you can make sense of it. Marketing’s time has come to prove itself as the function toward that end.
