Comparing Customer Data Platforms vs. Marketing Automation For Improving the Customer Experience
Last updated June 1, 2022
Businesses regularly use marketing automation to perform repetitive daily tasks, such as sending emails, push notifications, or social media posts. Customer data platforms (CDPs), on the other hand, use customer insights to personalize engagement across all channels. Which is best for your customer experience strategy? Let’s take a closer look to compare the benefits of a customer data platform vs. marketing automation.
Customer Data Platform vs. Marketing Automation
Marketing automation platforms (MAPs) first developed around email campaigns. Over the last 20-30 years, they have improved capabilities to take on additional communication modes via mobile and social media. MAPs are designed to automate routine marketing tasks such as sending SMS (text messages), mobile notifications, and ads to reach out to customers. In comparison, CDPs became more popular in the marketing arena around 2013. Designed as an end-to-end data management solution for collecting omnichannel data and unifying customer profiles, CDPs have greater analytical and segmentation capabilities than traditional MAPs. A CDP leverages these capabilities to derive customer insights and personalize customer journeys at scale. This enables CDPs to target the right lead at the right channel and time.Here’s a quick comparative overview of the pros and cons of a customer data platform vs. marketing automation for business users:
Customer Data Platform |
Marketing Automation |
||
| Pros | Cons | Pros | Cons |
| Personalization: CDPs can personalize customer journeys for individuals and audience segments alike at scale | Total Cost: Some companies find initial costs of setting up a CDP too steep | Automation: MAPs free up time and staff resources by automating routine tasks | Inflexibility: MAPs can restrict marketing teams’ freedom through rigid structure and platform limitations |
| Scalable: CDPs can scale up or down according to business needs without significant data architecture overhaul | Cost of Storage: Some users choose to keep their original customer data and replicate it onto a CDP, doubling storage costs | Established Market: MAPs have an established market with numerous available providers | Inability to Scale: Not all MAPs are designed for complex marketing campaigns |
| In-depth Customer Insights: CDPs apply AI and machine learning to derive in-depth customer insights for marketing, sales, and service teams | Training: CDPs require minimal training for marketing teams and new/intermediate users | Lower Cost: Market competition lowers the cost of MAPs for small business users | Incomplete Insights: MAPs can miss nuanced behavior and small customer actions, limiting audience insights |
Personalized Approach
Customers have come to expect personalization from brands and businesses they patronize regularly. With MAPs, businesses can automate certain campaigns to deliver a level of personalization across predetermined channels. However, automated campaigns with no room for manual modification leave marketing teams with a singular “cookie-cutter” response, regardless of a lead’s place in the funnel. This creates an artificial personalization strategy based on templates instead of a customer’s profile and actions.CDPs offer a different approach. They use omnichannel data collection as well as identity resolution to unify customer profiles. Then, they segment audiences according to their behavior, demographic background, psychographic profile, and other data points to shape a personalization strategy. This strategy is then applied dynamically to the customer journey so that customers’ responses determine the Next Best Action (NBA) instead of prompting an automated template to reply.
In-depth Customer Insights
Because MAPs can be locked into a rigid workflow, they can miss subtle behavior cues, or ignore them altogether. For example, they might interpret repetitive behavior, like multiple visits to a product page within a single day, to have the same value as a single visit. This lapse in valuation can obscure critical opportunities and cause failures to cinch sales or secure commitments from interested leads. MAPs also rely heavily on customer relationship management (CRMs) for customer data, which makes them largely incapable of generating in-depth customer insights marketers can use in real time. CDPs have greater capability to interpret such actions, thanks to a richer pool of customer data from which to derive insights. Best-in-class CDPs wield AI and machine learning to find behavior patterns based on thousands to millions of data points. As trends emerge, CDPs are able to predict with greater accuracy what a customer will do in response to certain triggers. CDPs equip marketers with real-time insights along with NBA recommendations so they can orchestrate a customer’s journey toward conversion.
Scalability
When a company’s growing audience exceeds its current MAP’s capacity, it decreases the efficiency of running campaigns. Adding outside resources or tools to compensate for the lack of capacity might also impact efficacy. In addition, not all marketing automation platforms are built to handle complex marketing campaigns, or activate actions on channels outside its automated workflow. This limits how businesses can reach their growing user base and impedes customer data maturity. Best-in-class CDPs can scale data management and journey orchestration according to a company’s audience size and data maturity. Because CDPs are schema-flexible, they connect to most types of data sources and marketing technology without drastic system overhaul. This enables CDPs to create actionable insights and activate personalized campaigns based on a business’s current scale.In conclusion, businesses gain deeper insight into the customer journey using a customer data platform v.s marketing automation tools. While MAPs can be locked within rigid workflows, CDPs use customizable campaigns and in-depth insights that empower marketers to personalize customer experience. Lastly, a CDP offers scalability with relative ease for growing businesses according to their needs, compared to MAPs that lack the capacity to handle complex marketing campaigns.
Maximize Your CX Strategy With Treasure Data CDP
Treasure Data enterprise CDP leverages customer data to produce a winning customer experience (CX) strategy. Our AI and machine-learning capabilities provide deep insights to personalize customer journeys at individual and segment levels. With Treasure Data CDP, you can visualize data insights and respond quickly to critical trends for maximum impact. To learn how you can win at CX strategy using a customer data platform vs. marketing automation, consult an expert today. Want to learn more? Request a demo, call 1.866.899.5386, or contact us for more information.
