Solution Design for Marketers
The Solution Design is a working document to be updated as we go. It goes into further detail and is used by the implementation and data teams to understand the structure and reasoning behind the overall solution.
Like the project plan, the level of complexity for a solution design will be determined by the scale and complexity of your project. Larger organisations may even need to hire a Solutions Architect to create detailed drawings of all the tools in the stack and the various stages of data flow between the multiple pieces of hardware and software. A solution design for the Analytics Maturity Curve can also be drafted in phases. To break up the task, we might decide to create a simple solution design with very few connections for our planned move from level 1 to level 3 but then have separate future drafts for our setup for the much more complex and challenging levels 4 and 5.
Here is a simple and effective visualisation from Ruben Ugarte, author of Bulletproof Decisions. He argues that our marketing stacks should be modular, where we focus on choosing tools that are ‘good enough’ for now, without worrying whether we will be able to scale with a specific vendor or getting locked into solutions that end up not working as promised. More on this in Let’s Go Tool Shopping – Chapter 8.
A basic solution design could look like this, in this case using Segment as the CDP of choice:
Source: https://rubenugarte.com/marketing-stack/
Continuing our shoe-in.com example, our solution could look like this.
Source: MckTui Consulting.
We can plan out our project phases, at least initially, in a simple table. In this example, I’ve also noted at what points we would have hoped to have levelled up, once everything needed for that level is in place (for a full breakdown for the stages and phases, please see Appendix 4).
Customer Touchpoint Planning
We can also plan our implementation by focusing on who our customers are and visualising what information we intend to collect (with permission) and when. This can allow us also to plan our value exchange, offering more and more personalisation in exchange for the additive data required to provide the additional service or product.
