Understanding and Utilizing the Ideal Customer Data Model
What's worse than your marketing team pouring countless resources into campaigns that just don't seem to be yielding any results? Nothing, right?! We have all been there. To increase our chances of success and ensure that we exhaust every possible avenue in marketing our products, we must understand and utilize an effective Customer Data Model.
The Ideal Customer Data Model: Its Importance and Benefits
Modern-day business has become reliant on data, so it's no surprise that Customer Data Models (CDM) have become indispensable for successful businesses. But what exactly is a CDM, and how can it help your organization?
A Customer Data Model (CDM)is a powerful tool used to organize and analyze data points on customers, helping businesses better understand customer preferences and guide them through purchasing decisions. So, let's dive into the importance of CDMs, their benefits, and how you can get started.
First off, why are CDMs important? Because they serve as the foundation for informed decision-making and sound customer relationships. A comprehensive, well-structured data model allows businesses to make better financial investments, save resources both in terms of capital and manpower, track customer behavior more effectively, and streamline selling processes.
By understanding customer needs and preferences through the CDM, you can create a tailored shopping experience that results in higher ROI and increased customer satisfaction.
Improved Human Resource & Capital Efficiency
CDMs are essential for businesses looking to optimize their manpower and capital investments. Usually, a Customer Data Model requires some upfront monetary outlay, but the rewards far outweigh these costs.
A well-structured solution allows you to centralize customer data, creating comprehensive rules and guidelines that make the whole process much more efficient.
Streamlined Selling Processes
Are you unable to keep up with customer buying trends and preferences? No worries! A Customer Data Model can help you get the insights you need so your selling processes become more streamlined.
This data structure can be used to track customer behavior, giving you expanded knowledge of your target audience and their needs. With this knowledge, you can simplify the customer's experience — reducing purchase abandonment rates — and diversify tactics for increased ROI.
Reduced Communication Complexities
Customer Data Models not only help marketers make better decisions, but they can boost team collaboration too. Since teams can share customer insights with ease, communication between departments becomes much simpler.
In addition to helping the team understand their customer better, it also provides a platform for sales staff to have easier access to technical teams, leading to better customer service.
Enhanced Team Collaboration
The ability to understand customers' data and preferences creates enhanced team collaboration, as it helps marketers make more accurate decisions with less effort. Marketers can update one another quickly on customer information and share insight a lot easier — making sure everyone involved is on the same page.
This improved collaboration will lead to better marketing campaigns and promotion strategies, ultimately increasing ROI and customer satisfaction rates.
Improved Decision Making
The ultimate goal of a CDM is to improve decision-making, and it certainly delivers. Through data analysis, marketers can gain quicker insights into customer actions and preferences — meaning they are able to make better decisions quickly and easily.
With this, businesses can measure customer behavior across multiple channels, monitor changing customer preferences in real-time, and adjust their strategies to meet their customers' needs — leading to higher ROI.
Strategy Overview for Developing an Ideal Customer Data Model
If you're looking to take full advantage of CDMs, here's a brief overview of what your strategies should look like. To put it simply, you want to leverage web analytics by creating three tables: Interactions Table (who did it), Cycle Table (how often they did it), and Entity Table (what's their personality).
The Interactions Table: It captures customer interactions in terms of page views, impressions, email opens, transactions, and campaigns.
The Cycle Table: It stores information detailing user behavior over time, such as session and course completions.
The Entity Table: It captures information about individual users — like age, gender, and location.
Best Practices When Creating an Ideal Customer Data Model
When crafting the ideal Customer Data Model, there are three simple best practices to keep in mind:
1. Identify the Grain
When developing processes, it is important to precisely identify the data grain in fact tables. Too much detail, and our team may get overwhelmed.
So define the grain of your relationship and make sure that columns are accurately named so that their meaning is crystal clear (e.g., user_age should not be used when referring to orders). If you are not sure what grain to use, look at existing processes and try to match the grain.
2. Always Materialize
Also known as "caching" in software engineering, materializing a relationship can be defined as either a table or a view. Approach this decision based on query response times and up-to-the-minute data obligations. While a view might be faster to query and more up-to-date, a table can be used when data is older or requires heavy querying.
3. Respect Data Governance
It is important always to remember the importance of data security and privacy! Make sure to follow all applicable regional regulations (such as GDPR) when creating relationships based on customer data.
Bringing it All Together
The ideal customer data model is a powerful tool that can give organizations unprecedented insight into the customer's preferences and behavior. When crafted correctly, this data structure will yield valuable insights that will help marketers adjust their strategies for more effective campaigns with higher return-on-investment (ROI).
Following the traditional web analytics best practices, understanding customer needs through mapping interactions, cycles, and entities and becoming fluent in SQL skills while still blazing the trail towards agile performance analysis upon consolidating CDMs becomes a breeze for any business.
VisitIQ™ is a CDP dedicated to helping you track, optimize, and analyze your customer data in an effort to boost ROI. With its powerful features, VisitIQ™ can help you build an ideal customer data model that will let your business understand, assess and interact with customers more effectively.
Final Words
At the end of the day, an effective customer data model can be a game-changer for any organization. All it takes is slightly more effort on your part to ensure that you're optimizing the process and getting the most out of it.
