Unwrapping a Customer Data Architecture
How do you use all the data you capture to gain a competitive advantage? It’s not always about capturing the most data or using the latest technologies. In this post, we explore how a carefully designed customer data architecture can help you shape exceptional customer experiences.
Customer Data: the big differentiator in building great customer experiences
Companies are continuing to collect data at an exponential rate, despite ever more stringent data privacy regulations. While the total amount of data created, captured, copied, and consumed globally was estimated at 64 zettabytes in 2020, it is expected to surpass 180 zettabytes in 2025 (source).
And even though Tech news in 2023 has been dominated by Generative AI, experts predict AI will not be the ultimate differentiator for companies. Even OpenAI staff have proclaimed that access to data is the key to building the best performing model, not the technology itself.
At MultiMinds, we believe that going forward, the ability of brands to effectively use data to deliver great online and offline customer experiences will be the real differentiator for success. To succeed, you need to think about the end-to-end data lifecycle, from data capture to activation and archival. Queue customer data architecture.
Data Architecture: make the pieces of your customer data puzzle fit together
When talking data to business leaders, people typically only discuss the data consumption layer.
Beautifully designed management dashboards with well thought through KPIs.
A Customer Data Platform allowing personalised communication with customers
The reduced churn rate thanks to an effective churn prediction model.
However, as data professionals know, this is just the tip of the proverbial iceberg. What looks beautiful on the surface, can be a messy combination of duct tape and rubber bands under the hood. Often depending on a few key people to keep everything up and running.
Data architecture is about defining the technology, processes, and roles to keep the data organisation running smooth and efficient. While IT architects may only look at the best of breed technical components to make data flow from source to destination, and marketers on the other hand might not look beyond conversion numbers in ad platforms, MultiMinds brings a holistic framework to go from a business vision to data capabilities. This framework starts from an organisation’s vision, its North Star. Next, relevant objectives are defined and the required business capabilities to deliver on those objectives are defined. Based on those, we determine together how data and analytics can contribute to these objectives within new or existing business capabilities.
For the New Year, I wish…
It’s easy to fill your wishlist with the latest tools and technologies to collect and manage your data assets (more on that in our next blog post). However, chances are your management will not approve a big investment taking years to “fix the basics” or “build the data fundamentals”.
However, crafting your ideal customer data architecture is not a game of bingo, where your goal is to tick all the boxes. Figure out where you want to go based on specific business goals and objectives. Next, identify the building blocks that provide the highest return on investment. Instead of trying to capture all data, focus on the data you need to deliver your actual use cases and collect that data well. In other areas, keep track of your technical debt (the implied cost of future reworking required when choosing an easy but limited solution instead of a better approach that would take more time and money now) to also keep your (future) costs under control.
