A businessman peering through a magnifying glass at his PC's monitor. CDP Evaluation Concept
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This is part 2 of a 4 part article series on customer experience and CDPs sponsored by Arm Treasure Data.

Want to find a competitive advantage in your marketplace? If you are, you’re probably already thinking about leveraging customer data to guide your decision making. But there are some hurdles to overcome before you can use customer data as business intelligence to support data-driven decisions. According to a survey from Arm Treasure Data and Forbes Insights, challenges that are impeding the ability of marketers to make better use of customer intelligence include outdated technology, siloed applications and data, and a lack of clean, quality data.

This type of enterprise data management challenge is a demanding one that goes beyond the capabilities of other, highly specialized customer data solutions like customer relationship management (CRM) or data management platforms (DMP). (Full-featured CDPs do, however, use data from CRM and DMP systems.)

CDPs are specifically designed to help marketers address the needs of the modern digital consumer by understanding customer behavior, helping marketers to design and deliver personalized customer experience. CDPs unify data from multiple, disparate organizational silos and merge them together into a single central repository while creating unified profiles around known customers.

A CDP is a must-have for any company that takes data-driven customer-centric programs seriously. But which CDP is right for your organization? There are a lot of different types of CDPs out there, each handling a different subset of customer data management. So depending on your particular use cases and applications, you may have special needs from a CDP that require some good pre-planning and thought on your part.

Here is a list of the top considerations to think about when evaluating a CDP for your particular organization and applications.

Related Article: An Overview of Customer Data Platforms (CDPs)

Consideration #1: What are Your Primary Use Cases?

A key step in the CDP decision process is to document your most important use cases, so you can find the right vendor with the specific features and support your business needs. Look for low-hanging fruit to start with, such as outbound marketing applications and web (e.g. email, personalization, SMS), as your initial use cases. And while you may have many use cases, use the top two or three to model your software choice.

Each CDP handles several types of tasks extremely well. That’s why your best bet is to find one that aligns with your primary use cases, rather than trying to “boil the ocean” right from the start. Is omnichannel personalization your primary use case? Make sure the vendor and platform you choose handles near real-time data from mobile shopping apps, CRM, email, and social media. Or, if you’re focused on B2B sales, make sure your CDP handles multiple attribution models, so you can figure out which customer journeys typically result in closing sales.

Consideration #2: What Type of Data Handling Do You Need?

Different CDPs handle the data they take in from multiple sources in a variety of ways. All CDPs should ingest data from silos like Facebook, Google and Salesforce and storing it indefinitely in a centralized data repository. But more robust, enterprise-grade CDPs like ARM Treasure Data’s CDP solution ensure you can future-proof your CDP investment by providing the scale and flexibility to grow with your business and data needs.

One of the ARM Treasure Data’s platforms core strength is advanced, schema-less data lake technology, which allows organizations to bring in large amounts of raw data in its native format to be used later. Also, traditional data warehouses have to be specifically designed to store and retrieve certain types of data, in a particular configuration. If your business needs or data formats change, traditional data warehouses are notoriously inflexible, often requiring re-engineering your schema. Schema-less data lakes, on the other hand, do not require re-engineering just to add new data or data types. This ability to store large amounts of raw data before processing gives ARM solutions the ability to scale and handle whatever data challenges may be thrown at you in the future.

Consideration #3: What Type of Integration Work Needs to Be Done?

Integration is always a top consideration, regardless of the CDP or particular use cases you face. How many sources of customer data need to be consolidated to get a single view of your customers? What type of integration needs to be done beyond low-hanging fruit like web integration and standard outbound marketing applications like email? If you have a robust enterprise-grade CDP, it should have built-in connectors and APIs that allow you to collect data from a variety of solutions. Without them, expect lots of custom development and support to connect your CDP to the rest of your martech stack.

Heavy-duty CDPs like the ARM Treasure Data solution, used by huge e-commerce companies like Wish have decided to focus on building flexible data pipelines and personalization engines that give them a competitive advantage. This focus highlights the data lake and analytics capabilities the ARM platform is based on.

Consideration #4: What Level of Support and Staffing is Needed?

As with any software solution, knowing what capabilities the vendor offers and what you have in-house are of key concern. Is the CDP on premise or SaaS? Will you need tech support beyond installation? The whole idea of a CDP is that they are marketer-managed, meaning a marketing department should be able to do day-to-day operations without having to rely on internal or external IT support. But the definition of marketer-managed is up to your company. It can mean that marketers own the software, but have assistance to do daily operations, or that marketers do it all, with data analytics support to configure integrations and adjust data workflows. The level of your internal staffing and ongoing support will also determine how much and what kind of training is required from the vendor.

Conclusion

Large enterprises that have demanding use cases such as delivering omnichannel personalized experiences to millions of customers in real time need a data management solution that will be scalable and future-proof. An enterprise-grade CDP is the go-to solution for companies who have to connect different disparate channels together so customer data can be mined, combined and analyzed in order to inform personalized digital experiences across the full buying journey. Choosing the right CDP for your organization and particular use cases is crucial as it needs to be able to scale and have the data management and integration capabilities that will allow the CDP to grow with your company, and not be a hindrance to it.

Good planning and modeling of primary use cases, integration complexity, data management staffing and support needs will help you pick the right package and the right vendor for your company and customers.