The biggest challenge when implementing marketing clouds centers around accessing customer data and maintaining it.
In my blog, Marketing Cloud Solutions Fall Short of Expectations, I covered analyst research showing that marketing clouds often don’t meet the expectations of their customers. The root cause is that organizations unrealistically expect their marketing data will magically appear in the cloud. Marketers soon find out this requires integration work, and though cloud products offer open APIs, these APIs don’t program or maintain themselves.
There are other data problems with marketing clouds that gradually reduce marketing efficiency beyond moving the data. In this blog, I will examine the other cloud data problems and how enterprise data warehousing best practices and Campaign Management applications can combine to solve them and supplement your marketing cloud.
Problem #1: Prepackaged “canned” data models that don’t match the business
Your marketing data model should match your business. Its terms, organization of attributes, hierarchies, and relationships should be designed to custom fit your business.
In contrast, most Marketing Clouds offer a one-size-fits-all approach with a canned application data model and a few data extension features. Some of the challenges with this “canned” approach include:
Generic attribute names that don’t match your business terms
Flattened business hierarchies and relationships (e.g. eliminated or drastically simplified site to account maps, territory maps, or product hierarchies), with data no more than a few levels deep
Limited ability to support multiple business units from a single instance when each uses different terms, metrics, and customer relationships
What does this mean to an enterprise deploying these solutions? It means their marketers must change how they create target lists. It also reduces the depth and richness of the marketing data they can use for selection. Finally, this canned approach forces large enterprises with a number of business units to deploy multiple instances of the marketing cloud.
Problem #2: Proliferation of data silos
The centralized 360-degree view of the customer across all touchpoints and operations has been the goal for most organizations. However, it hasn’t always been practical or possible for various reasons, but it’s getting much worse now.
That’s because data silos have snuck back into organizations in a bigger way with the growth of marketing clouds and digital channels. Every new marketing cloud, digital channel, or MarTech solution adds another customer data silo. This is multiplied as you add business units, each with its own marketing cloud instance or set of marketing technology. In this digital age, the single view of the customer has fractured and is broken into a variety of tiny little data silos.
Problem #3: Deteriorating data quality
To drive better marketing decisions and generate high performing marketing promotion lists, you must have clean, consistent, and understandable customer data. Your marketers must trust and understand the available data. Remember, the number one factor to better marketing and higher marketing response rates is good, quality data.
Relying on multiple Marketing Cloud or MarTech data silos to self-maintain marketing data is a problem. Over time marketing clouds start to collect bad contacts, companies, and addresses. With little to no cleansing and no consolidation beyond a simple email address match, duplicate individuals and companies start to appear. This bad data and duplicates make trusting cloud siloed data difficult and will eventually force organizations to load marketing lists from their own internal, trusted sources instead.
In addition, marketing cloud data silos tend to grow out of control. For example, marketing clouds allow for custom attributes to be added very easily. This is a good feature that can turn bad very quickly. As attributes are added, the list of attributes becomes very long often with duplicates of the same attribute loaded at different times. These added attributes are often partially populated, and contain out-of-date data, with no way for the user to know what is good and what is bad data. Then there are ghost attributes – those attributes loaded for a single purpose but remain as an un-exercisable ghost of marketing programs past. All these problem attributes grow like weeds and can soon overwhelm your marketing team, forcing them to return to requesting lists from their own trusted in-house data sources.
Solution: Keep your data and don’t abandon your own marketing list generation – expand it!
To address these and other problems of marketing cloud data silos, don’t keep copying data to multiple cloud systems. Adopt a centralized marketing data warehouse approach with good, clean, and business relevant data in your model. Bring response data from the clouds and digital systems back to your database instead of leaving it scattered in the cloud.
Next, ask yourself what is the good of having great, centralized, and organized marketing data under your control when only a few technical analysts can access it? This technical bottleneck strangles marketing efficiency.
Campaign Management products like Aprimo Campaign can help. Aprimo Campaign maps to your existing clean and trusted data sources, exposes only the attributes needed for different business units, and allows mere marketers as well as data analysts the ability to generate highly targeted marketing lists. Campaign Management products like Aprimo Campaign can be the bridge between your on-premise, managed customer data and the marketing cloud.
Go to the Aprimo Campaign page to find out how it can help you keep control of your marketing data and connect it to the marketing cloud.
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