Organizations must ensure they do their due diligence if a direct data connection, data flexibility, and data management are essential to a company. It’s possible that a CDP isn’t the best fit for them, which can be a time-consuming and costly mistake. Businesses can do whatever they want in their own data warehouse – while maintaining control and flexibility – if they employ the right technologies and put them at the heart of their marketing universe.
The number of customer touchpoints is increasing, fragmenting data collecting. The possibility of a muddled customer view is also rising. Organizations struggle to provide personalized customer interactions due to a lack of a joined-up data solution. Businesses have been looking for a solution to store, manage, and extract insights from data due to the increased focus on improving the customer experience. Therefore, businesses are increasingly turning to Customer Data Platforms (CDPs).
The right customer data platform can boost the efficiency and effectiveness of data-driven marketing initiatives, and its benefits can be used across the company and beyond marketing to departments like customer support and sales. Replacing a technology infrastructure decision is no minor task if organizations rush into it and select the wrong platform for their requirements or one that doesn’t scale.
Businesses can consider the following three factors before making a costly and time-consuming commitment.
Lack of Direct Data Connection
The first reason to rethink whether a CDP is appropriate for the martech stack is simple: data. Almost every CDP will demand that companies send their consumer data to the vendor. Businesses must, however, copy and transfer their sensitive data to another provider, where it will be stored outside their firewall in a separate siloed environment. For them to be able to see their data in that UI, this is a mandatory requirement.
Brands that are already frustrated with doing this with their Email Service Provider (ESP) – copying and shipping data to the ESP’s cloud – are effectively signing up for the same process with a CDP.
That also means they’re paying to store their data three times: once in their own database, then in their ESP’s cloud, and finally in their CDP. They’re paying for the same data to be stored in three separate ways, in three distinct places, none of which are directly connected.
Data Management Challenges Remain the Same
Companies deal with data silos, stale data, and other common challenges as they reach that inflection point in their growth curve.
They seek help from a CDP in the hopes of resolving the concerns, but they subsequently discover that the same problems exist. Because they still have to copy and send their data outside of their own firewall and into the CDP’s environment, this is the case.
Businesses discover that they can do all of these things with the CDP’s features and UI. However, they still have stale data, data lag issues, and so on – the bidirectional sync isn’t well enough or fast enough to overcome the challenges of creating yet another copy of the customer data and storing it in yet another environment.
Most CDPs are based on a rigid data model that will not work well with a company’s data architecture. Their schema is their schema, and if businesses want to utilize them, they must follow it.
This will almost certainly result in many late nights for the data team, as they will have to re-architect their data to meet the CDP’s specific model. They’re asking their team to cram their data into the CDP and make it function, which could lead to issues such as an overworked and irritated crew.
If businesses have their own hierarchy or proprietary objects within their data set, they may have difficulty reconciling that with a CDP. It’s a conversation that must be held with the data team well ahead of time.