Build or Buy a CDP solution?
In the ever-evolving domain of modern marketing, the Customer Data Platform (CDP) has emerged as an indispensable tool, especially within the bustling ecosystem of a large, marketplace-type business. As we confine our discussion to the marketing use cases inherent to such a marketplace, we aim to unravel the burgeoning question: why should businesses opt for constructing their own CDP as opposed to investing in proprietary software? At its core, a CDP is a forward-thinking technology that seamlessly integrates and systematizes customer data into a single, unified repository, paving the way for an intricate understanding of each customer.
But why is a CDP critical for any business? As we traverse the ever-expanding universe of customer data, the need for a CDP transitions from being merely beneficial to utterly crucial. Through a CDP, businesses gain the capability to meticulously craft marketing initiatives, elevate customer engagement, and, ultimately, fortify business growth. This article endeavors to probe the salient influence of a CDP in the marketing landscape as it pioneers a seismic shift towards a profoundly customer-centric business model.
Marketplaces have thrived through the annals of time, dovetailing with our cultural, innovative, and civilizational advancements — from the ancient bazaars to the modern, Uber-style digital platforms. Despite this evolution, the vibrant interplay of sellers and buyers remains the steadfast indicator of a marketplace’s success. Consequently, marketing teams within these marketplace businesses are ever ambitious to both entice and maintain buyers and sellers on their platforms. Beyond the buzzwords often paraded by CDP vendors, what does the stark reality look like for these marketing departments?
Marketing teams deploy various outreach tactics to engage customers and prospects, including:
- Dispatching emails to highlight new features or offerings in the marketplaces.
- Issuing notifications to edge devices with timely updates.
- Investing in paid displays or banners to showcase relevant marketing content on 3rd party platforms.
- Customizing ads per advertiser’s preferences on 1st party platforms.
- And the list continues.
Each outreach channel signifies a distinct marketing strategy with its own set of costs and intended targets. Employing these channels in isolation won’t yield significant results unless there is a strategic plan in place from the outset. This is where omni-channel marketing segmentation comes into play, a critical application of CDPs that relies on a strong underlying data foundation. From a data perspective, a CDP can furnish accurate customer profiles and recommend optimal outreach channels and timing. Furthermore, for seamless execution, a CDP ought to integrate natively with all these channels to enable automated workflows.
However, this represents the ideal scenario. For a platform serving millions, like ours, it’s likely that multiple engineering teams with distinct technology stacks have contributed to its development, thus introducing challenges in data collection and uniformity essential for downstream applications, including marketing. To capture the entirety of a customer’s interaction with the business, data collection spans various organizational segments, vendors, and legacy systems. For an establishment of our scale, this is no trivial task, and integrating all these elements requires significant efforts even with an operational CDP platform.
To achieve a comprehensive 360-degree view of our customers, we must assimilate data from both the front and back ends. It’s unrealistic to expect a single tracking tool from a CDP vendor to function flawlessly straight out of the box.
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Moreover, advanced data analytics, ML, and AI capabilities offered by a CDP may not work flawlessly due to issues with data literacy and explainability. Mature businesses with advanced data teams will swiftly surpass built-in ML functionalities of these platforms.
Thus far, we’ve delved into the technical aspects. What other factors could tip the scales in this decision-making process?
- Time to market: If the business has operated smoothly without a CDP for years, this shouldn’t suddenly become a key factor.
- Leadership sponsorship: Launching a CDP is costly and resource-intensive. Without leadership buy-in, the initiative is likely to fail.
- Data security: With increasing concerns around data security, businesses must consider the risks of storing sensitive customer data on a third-party platform that competitors might also use.
- Regulatory compliance: With privacy laws like GDPR and the shift away from third-party cookies, building a CDP can enhance a company’s first-party cookie strategy.
- Data semantics and processing: Often overlooked, this consideration involves deciding where to process your data, which can affect scalability and vendor dependence, including integration with downstream applications.
In a Reforge program, four critical factors were identified for the Build or Buy Decision:
- Strategic value: For a marketplace, customer data is paramount, and its importance is only likely to grow.
- Available resources: With senior leadership support, my team is actively developing a CDP prototype, and continuing this development seems feasible.
- Cost: The true total cost of ownership can be indeterminate with most vendor-provided solutions due to unforeseen integration and maintenance expenses.
- Vendor reliability: Service reliability should be taken in context of the businesses’ needs and not just the vendor’s reputation. Given the breadth of a CDP project, vendors become more of business partners than mere providers.
In light of these insights, developing an in-house CDP solution appears to be a logical step for us, enhancing our business use cases. Nevertheless, this should not discourage ongoing exploration of available market solutions. In the subsequent article, I plan to delve deeper into how we assessed various off-the-shelf CDP options.
