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Discovering the Pure Play CDP Differences - CMSWire

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Companies are collecting more data from their customers now than ever before. As online consumer spending increases, companies have an opportunity to collect and unify their data sources to create robust customer profiles, which in turn can be used to increase customer engagement. This has led to a wealth of data sitting in data warehouses, data lakes and even data oceans. Some organizations can have their customer’s data stored in up to 50 different information systems. (1)

But collecting data isn’t done for its own sake — the data needs to have a purpose to be useful. “There was a time when everyone was chasing so-called big data, but now there’s a real “so what” moment surrounding customer data,” says Jonathan von Abo, head of business development for EMEA at Arm Treasure Data. “To best serve your customers, your data needs to be activated to help reach your customers quickly. Marketing to a potential customer even the next day might be too late; you need insights in real time to make strategic business decisions.”

With the proliferation of both the number of business lines capturing customer data as well as the different places throughout the enterprise where that data is stored, customer data platforms (CDPs) become an essential component of marketing technology. CDPs can unify the customer data view in an era where such data lives on many different systems. Without the ability to aggregate that disparate data, companies can’t translate that information into actionable insights.

The CDP market expanded in recent years, and companies have a lot of choices. with new players and options entering the market every year. (More than 20 new vendors entered the CDP market in the first half of 2020 alone. (2))

There are many ways to evaluate the CDP market and it’s important to judge the options against specific business needs. With so many options to choose from, how can companies decide which CDP is right for them?

Today’s CDP vendors can be loosely divided into two buckets: pure play systems and marketing cloud options. Both approach data collection in unique ways. When evaluating CDPs, it’s important to choose the one that’s right for your particular business situation.

Marketing Cloud CDPs Work Best Within Enclosed Systems

Several large firms entered the CDP market in 2020. Without fail, these CDP offerings are all part of the parent company’s larger marketing cloud and marketing strategy.

The biggest difference between marketing cloud and pure play CDPs is that marketing cloud CDPs are not standalone services. They’re usually offered by a large vendor as part of a greater martech package.

Marketing cloud CDPs tend to primarily focus on unifying their own data, and often need to rely on other technologies to bring in data outside of the suite. They might view customer analytics as features across several of their products, rather than standalone products. As a result, CDP capabilities might be spread across the entire marketing cloud. This means for companies that need strict CDP capabilities and nothing else, or who already have a martech strategy, going with a marketing cloud provider can be overkill, pushing them into systems or services they may not need or would ever use.

This may be the biggest drawback to a marketing cloud CDP. These solutions are designed to work within the vendors’ own product suite, and might not play well with other systems. Marketing cloud CDPs aren’t designed to stand alone, but rather complement other products and programs that are already in the parent company’s martech package. If companies have martech products they already use, then this advantage is wasted. “Selecting a marketing cloud CDP also means you’re locked in with that single vendor, and have to depend on their pace of innovation even thought solving CDP pain points may not be their top priority.” commented von Abo.

Another drawback with marketing clouds is that they aren’t purpose built. “Many marketing cloud solutions are made up of acquired technologies that are running different code bases,” von Abo points out. “This effectively eliminates the advantage of a marketing cloud solution as they are facing the same integration problems customers are. If solutions within the marketing cloud don’t talk to each other all that well, then the advantage of bringing all your platforms under one umbrella is lost.”

Pure Play Systems Address CDP Needs First

Growth-oriented companies with multiple data sources and silos to contend with need to make sure the CDP they pick can actually work in their environment. This brings us to pure play CDPs. These systems are purpose-built to support and address CDP use cases first, without needing to be integrated into a larger system.

A pure-play CDP that’s designed to work at enterprise scale considers the sheer variety, velocity and volume of enterprise data, making the platform flexible and scalable with business growth.

One differentiator is whether or not the CDP is schema agnostic. CDPs that must ensure incoming data is in the schema they can work with before they can ingest that data have more limited capabilities. The goal should be to fit the CDP to the current strategy rather than the other way around. “Treasure Data is completely platform, data and schema agnostic,” von Abo says. “We don’t care where your data comes from or what format it’s in. Our goal is to bring the data in, stitch it together, and make it available for activation on any of the customers chosen platforms. Marketers don’t need to be concerned about whether the CDP will interfere with their current martech stack. For us it's the data that is paramount.”

Bring Your Own AI

Companies use machine learning for targeting, analytics, conversion and other uses. As data grows in variety and volume, companies must rely on machine learning algorithms to help them draw insights from data — deciphering connections across channels, identifying patterns of behavior and predicting the likelihood to buy. All these insights allow marketers to build robust audience profiles with well-defined characteristics, which in turn enables targeting the right people with the right message on the right channel at the right time.

One of the advantages of a pure play CDP is the flexibility around machine learning capabilities. Many vendors — including marketing cloud providers — are now packaging AI or machine learning options into their CDPs, which allow for out-of-the-box capabilities. However, companies should look for a tool that can truly flex with their business. “Beyond pre-built models, Treasure Data’s CDP allows our customers to build their own machine learning and AI capabilities within the platform,” von Abo says. “This is a differentiator if you need custom algorithms and want to gather unique insights about your customers.”

Pure Play Systems Perform Best on Data Privacy and Security

Customer data platforms compete with each other in four key areas: architecture, compliance/privacy, data security and scalability. (3) In all four areas, pure play CDPs can outperform their marketing cloud counterparts. Pure play systems were built from the ground up with the goal of integrating and unifying data, whereas marketing cloud systems often prioritize working within their own clouds over maximizing privacy. In the age of compliance laws, CDPs must align with regulations such as GDPR and CCPA.

“Data security is one of the most important parts of a CDP,” von Abo says. “Data privacy laws vary wildly from country to country and are constantly changing. When choosing a CDP, you want one that’s put data security at the center of every approach to your customer’s data.”

Conclusion

Pure play CDPs are purpose-built and designed to integrate with existing systems, workflows and technologies. For companies that have already invested in martech platforms, pure play CDPs can integrate seamlessly with this strategy, making the technology work with the flow, not against it.

Learn how Arm Treasure Data’s pure play model puts your customers’ data first at treasuredata.com.

Sources

Arm Treasure Data is a global leader in Customer Data Platforms (CDP) and enterprise data management. Providing the ability to aggregate and translate massive volumes of scattered and siloed data.

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