CDP vs. Data Warehouse: What’s Best for Your Business?

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Your business learns more and more about each customer at every touchpoint. The vastness of this knowledge can be overwhelming without a strategy to utilize it. Moreover, data management solutions can present a puzzle as you parse out different options.  

Data warehousing is an information storage option that’s been around for decades. A customer data platform (CDP), on the other hand, represents a new way to act upon warehoused data that’s growing in demand. In fact, Research and Markets estimates a 34 percent annual increase in CDP market size growth

The difference between data warehouses and CDPs is significant and poses an opportunity for you to make a choice about how to approach data management at your company. 

Differences Between a Data Warehouse and a Customer Data Platform

Data warehouses can be thought of like all your memories stored in your brain: every interaction and experience you’ve ever filed away. You can organize them in different ways. You can access them in different situations. Lots of memories. Lots of data points.

In contrast, a customer data platform (CDP) is your cortex. It’s the executive planning station of your brain, where you decide how to use your memories as you move throughout the world. Like your cortex, a CDP empowers your business to interpret people’s needs, analyze interactions, strategize partnerships, and predict success.

Defining Features That Make CDPs Stand Out

CDP integration within your company’s MarTech stack makes data actionable. A key way a CDP does this is by unifying customer profiles. Once a customer’s disparate information is combined, a CDP offers insights into customer behaviors. 

In turn, these analytics enable your marketing team to build target audiences and launch campaigns. A CDP can forecast a campaign’s effectiveness using machine learning to analyze prior customer interactions. 

A CDP acts in concert with data storage architecture to turn information into plans that can grow your business.

Typical Data Warehouse Architecture

Data warehouses on their own are less flexible. Like physical warehouses, their rigid structure serves narrowly defined purposes.

Effective data warehouses can receive large amounts of information from databases. Using a process called extract, transform, and load (ETL), data warehouses clean, summarize, and shelve data in a frozen state. 

In a data warehouse, data is organized and secure in that it can’t be deleted, but without a CDP’s actionable capabilities, it’s less usable. A data warehouse’s rigidity means your business may find itself conforming to a data collection system rather than vice versa.

Most data warehouses traditionally are limited to structured data transactions because they’re built for financial analysis at the end of the day. The CDP is going to deal with unstructured and semi-structured data. So they’re gonna have a broader breadth of data than you would store in a traditional data warehouse. They’re also going to be more flexible, because they’re designed to bring in any kind of data.

– David Raab, founder, CDP Institute, on Customer Data Perspectives

CDPs and Data Lakes

A CDP can integrate with traditional data warehouse architecture, as well as data lake storage models. 

A data lake accepts every kind of data in its original form, including unstructured or semistructured data, like videos, PDFs, recordings, and online reviews. Given a data lake’s extract, load, transform (ELT) process, your business can use a data lake as a depository, defining organizing criteria after storing. Purposes for data lakes include using machine learning to create predictive models and forecast trends.

Whether using data warehouse or data lake infrastructure, CDP’s executive functioning can ensure flexibility in the data that is future friendly. 

Data lakes are a great source of data for your CDP. It saves the developers having to go out and gather the data from all these systems because it’s already being dumped into the data lake. But that’s what data lakes are….they just take the data in the original format, and just puts it in a copy of it so the analysts can play with it without interrupting the operation of the original source system. 

– David Raab, founder, CDP Institute, on Customer Data Perspectives

Capabilities of Customer Data Platforms and Data Warehouses

If your company isn’t using a customer data platform, CDP industry data suggests that your competitors might be. In fact, 63 percent of marketers say they use a CDP for mapping out customer journeys and personalizing digital campaigns. Options for CDPs are abundant, but effective CDPs have a number of core features.

Features You Need in a CDP

1. Single Customer View

Every time one of your customers accesses a department of your business, you glean data about them. An in-store associate runs the client’s credit card; your website logs their purchase of an accessory; a helpline staffer assists them with a refund. At each channel, your business has learned new information about the person interacting with your brand.

A CDP’s essential function is to bind together a single client’s disparate information into one unified customer account, or single customer view (SCV). The CDP unites a customer’s credit card, emails, address, phone number, product purchase history, and so on. After that, the client can be fully seen and heard by each sector of your business. 

Having a single source of truth for each client provides immediate and long-term potential for your company to impact the customer journey.

On the practical side, if a customer calls your helpline about an issue they’re having with a product, the helpline staffer can see their purchase history. The staffer can then offer relevant updates, accessories, or discounts. With identity resolution capabilities, company representatives in store and online can offer customers a tailored experience. In each interaction, the client can feel known, and trust in your brand can solidify in their memory.

A CDP’s analytics capture customer behavior, such as their purchasing frequency, preferred shopping times, and online interaction patterns. With these customer insights, your marketing teams can devise productive campaigns.

2. Target Audience Building

A CDP empowers your marketing teams to utilize unified client profiles at scale through target audience building. For example, a marketing team could form an audience of VIP customers who have spent above a certain amount in the last year. The team can draft a campaign offering the VIP customers a discount. After closing the loop with knowledge from the SCV, the marketing team can send their campaign via their preferred communication mode at the time of day each person is most likely to respond.

3. Predictive Models

With machine learning, your business can forecast a campaign’s success, predicting clicks, purchases, conversions, and churn. More robust use of a CDP’s predictive power would involve data scientists building their own models through artificial intelligence’s synthesis of company data.

4. First-Party Data Management

The data a CDP uses comes from your company’s first-party data, meaning that your customers have willingly provided you with the information that you’re analyzing. Your CDP allows you to do analytics in house, reducing risk of exposing your customer’s personally identifiable information. In fact, 92 percent consider a CDP important to their privacy and compliance efforts.

Furthermore, the analytics possible with CDPs are available only to your company because you have information about your individual customers no third party can purchase. This allows your business to keep a competitive edge while sampling third-party data as needed to supplement discoveries made from your own data. 

Data Warehouse vs. CDP Capabilities

When it comes to a customer data platform versus a data warehouse, there’s no question that a CDP has more capabilities.

A data warehouse can employ recent data quickly for a limited range of functions. These include reports or basic analyses of performance as well as identifying your most valuable customers. However, these operations must be agreed upon by all stakeholders ahead of implementation.

Because of their fixed architecture, data warehouses require careful planning. Your team must identify what its goals are to inform what data is collected and decide on how the data warehouse will store the information. With a data warehouse, these processes stay static.

However, data warehouses’ track record is under scrutiny. According to SnapLogic and Vanson Bourne, around 88 percent of industry thought leaders report having issues with their data warehouses’ data storage and data use capabilities.

Customer Data Platform vs. Data Warehouse Implementation Time

Within a few weeks, you could purchase a data warehouse and begin feeding it information from your company’s databases. However, an impact data storage project is best seen as a collaboration, with some back-and-forth between your company’s IT specialists and the data storage architects you’re purchasing from.

The same is true for purchasing and implementing CDP. A CDP vendor with a streamlined process can guide you through CDP implementation between eight and fourteen weeks, on average. This depends upon the length of your company’s data record and the scope of data management goals.

Both options take time and coordination. Because the best data management systems can produce bad data, companies must have troubleshooting procedures in place to remedy issues that arise.

How CDPs and Data Warehouses Can Work Together

An issue with the debate over customer data platforms versus data warehouses is that it assumes you have to select one over the other. To return to the brain analogy, a CDP works with a data warehouse or data lake the way your cortex works with your memory, using stored information for higher planning purposes.

A business leader can ensure synergy between a CDP and a data warehouse through teamwork. Research suggests that companywide buy-in to your data management is key. The more uniform each company department is in understanding and using CDP capabilities, the more optimistic the overall company tends to feel about using data to enrich customer experience (CX).

Connections between CDPs, Data Warehouses, and Databases

Many CDPs include pre-existing data warehouses as a part of their applications. As a CDP user, you stream data from your data warehouse into your CDP. This includes data from external and internal databases. 

Companies have internal databases for information gleaned through daily operations, such as purchase orders and customer feedback. This type of data falls into the first-party data category mentioned earlier. 

Increasingly, companies have been utilizing third-party data from external databases to inform their business strategy. Third-party data is data collected in an aggregated form by another company to describe general customer behaviors. For example, by analyzing third-party data, you might conclude that customers buy your type of product in winter more than in summer. A company can purchase lists of this type of data which can then be shared via an external database. A CDP can integrate data from these external sources, as well as internal ones. 

With data needing to be piped seamlessly between these elements of your data infrastructure, experts consider data streams and pipelines an expanding market in data warehousing.

Determining whether Data Warehouse or Customer Data Platform Works Best for You 

A CDP empowers marketing teams to be more involved in using a company’s data to grow and enhance CX. However, there are several factors to consider before investing.

Considerations to Make before Deciding on a Customer Data Platform or a Data Warehouse

1. Business Size and Complexity

If your company is mid-market or smaller, with only one or two ways a customer interacts with your business, a data warehouse may suffice. With a data engineer, you can store company data in overview form and access it to run simple analytics and reports. Because data warehouses have been around a long time, many data scientists have experience using them.

However, expanding mid-market businesses likely will find themselves wanting to invest in business intelligence. How long do customers stay on certain webpages over others? What kind of ads would be compelling views for them? These questions and more can be answered with a CDP’s ability to create unified customer profiles and run predictive models through machine learning. 

2. Business Readiness

According to the 2021 CDP Institute User Survey, a quarter of unsatisfied CDP users cited “lack of organizational preparedness” as the reason why their business was unhappy with their CDP.

Because a CDP can offer insights into how customers access each channel of your business, implementing a CDP requires involvement from each department, not just marketing. Whatever your decision, data management must be seen as a process with cycles of feedback and implementation between your teams and your CDP vendor. 

Building vs. Buying a CDP

The debate over customer data platforms versus data warehouses is an apples-to-oranges comparison. If you’re interested in creating a unified customer experience through customer data orchestration, the choice is clear. CDP’s smart hub can get you there. 

Of course, if your company hosts a large development team that can code applications from scratch and create their own analytics, you could theoretically build your own CDP. In terms of actual costs, the difference between building your own CDP compared with buying one is likely in the millions of dollars. The process would also be lengthier and more intensive than buying from a vendor who could meet your needs and free up your developers to work on other projects. 

Check out our guide to choosing the right CDP vendor to learn about other factors to consider when choosing the right technology for you. Staff Staff
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