Data has moved on but businesses still need “old skool” understanding to build commercial success
Updated: Oct 2, 2019
It’s a run of the mill statement to say that the world of data has moved on. We all know it has, from the sheer data volumes and sources that surround us, the breadth and variety that these volumes and sources provide giving the ability for greater insights and applications to a business hypothesis.
Techniques have also moved on. The analytical techniques to unpick data and uncover insights are expanding as experts find new ways of working with the vastness of data available.
The platform evolution has supported this development, with many predefined libraries enabling marketing scientists to perform analysis quicker and more flexibly than ever before. This speed of processing and flexibility in solutions enables more hypothesis to be explored, and insights to be generated quicker - gone are the limitations of the OLAP cube!
And last but not least, ambitions have moved on – rarely does a conversation around data not involve AI, real-time marketing orchestration and skills availability. I am yet to meet a business who does not want to be data driven to some extent. It has become common sense for businesses to use insight grounded in fact to shape their products and services and ultimately succeed.
However, the foundations of customer insight to drive commercial success are the same as they have been for the 2 decades I have been working - who are my valuable customers, how can I attract more of them, how can I keep them for longer and make them more valuable.
Enterprise clients typically know the answer to these questions, but they have deeper pockets for more tech and in-house data resources to investigate, answer and monitor such questions.
However, in the 4 months since we launched, we have asked these questions many times in conversations with SMEs and the answer is often unknown. These foundation questions are essential to businesses of all sizes, but SME’s usually have more limited data resources and these customer focussed questions are overlooked in place of financial BI. I’m not disputing that financial BI is critical to a business, but we need to be building layers of knowledge and demonstrating how these foundation questions can drive the strategy for business performance, improvements and growth which is then visible in BI metrics.
Combined with this, it is also beneficial to identify where a brand is on its own data journey. Now the concept of a data maturity curve can be overwhelming - just google the term and many variations of the theme will be served to you (infrastructure, analytics, use of data in the organisation etc).
I particularly like the Forrester’s research commissioned by Tealium “Customer Data Maturity Powers The Modern Enterprise” which addresses how an organisation’s customer data maturity powers their modern businesses. They identify six dimensions of customer data maturity which enables a businesses data capabilities and applications to be measured, forming a benchmark against what is possible which growth strategies can be developed. The six dimensions are shown in the visual below:
Understanding a business’s data maturity across these pillars, its depth of knowledge in the “old skool” customer measures, the potential in a business and its ambitions are the logical steps in using data to drive commercial impact for businesses of all shapes and sizes.