Jim Sterne, author and the chairman of Emetrics, was in London last week, and I had the opportunity to catch up with him at our offices. Our conversation included discussion about the way the market is developing and what the differences were (if any) between what's happening in the digital marketing optimization space on my side of the Atlantic compared to his.
As we talked, I kept thinking back to a simple model I developed many years ago to describe where organizations are in the development of their digital marketing measurement and optimization capabilities. These days it would be fashionable to call it a maturity model.
My simple maturity model has three main stages:
In the first stage of their development, organizations are focused on performance tracking. The challenge here is to get the right numbers right, laying the foundations for further capabilities to be developed.
The main activities revolve around defining the business needs, setting success criteria, such as key performance indicators, and getting the right measurement technologies in place and getting them working properly. These steps will involve a lot of effort with specification and configuration issues.
At this stage, organizations might wonder whether it's all worth it. The effort-to-insight ratio is high. The amount of value being gained from the data may seem low compared to the amount of heavy lifting required to get it. However, it's vital to get this right. Otherwise, it's hard to move from this stage of the maturity model to the next.
Once the right numbers are right, organizations can start to use the data to make better decisions. Applying insight to the business creates an opportunity to optimize processes and create some ROI (define) by putting the measurement capabilities in place. So the focus shifts from tracking to optimizing the core digital marking processes, such as acquisition and conversion.
The optimization process is driven by the "test, learn, and adjust" approach and requires more than just good data and some smart technology. It also needs the right organizational culture backed up by sound business processes.
These processes must be embedded into the organization during the performance-tracking phase to guarantee data integrity. Nobody likes making decisions on dodgy data, and you can't optimize marketing processes without making decisions about what's working and what's not.
During process optimization, organizations still tend to be quite site-centric. They're focused on optimizing a series of processes, tweaking conversion rates, improving satisfaction scores, and so on. The next stage in the model is moving from being site-centric to being customer-centric.
The main difference is between asking what the conversion ratio was last week and asking how many new customers there were last week and what their expected future value is. Customer centricity is about looking at the digital channel in the context of an organization's overall relationship with the customer rather than the other way around.
The main challenge here is to be able to get a multichannel perspective on the customer. You need multichannel data that brings together, where possible, data from offline systems and online systems.
The conclusion I came to from my conversation with Sterne was that the difference between what's happening over here versus what's happening in the U.S. essentially boils down to the distribution of where organizations are in the maturity model. Some companies in the U.K. and the rest of Europe are doing some really interesting stuff, it's just that there are more of them in the U.S. But that's OK. Sometimes it's best to go second, you can learn quicker that way!
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Neil Mason is SVP, Customer Engagement at iJento. He is responsible for providing iJento clients with the most valuable customer insights and business benefits from iJento's digital and multichannel customer intelligence solutions.
Neil has been at the forefront of marketing analytics for over 25 years. Prior to joining iJento, Neil was Consultancy Director at Foviance, the UK's leading user experience and analytics consultancy, heading up the user experience design, research, and digital analytics practices. For the last 12 years Neil has worked predominantly in digital channels both as a marketer and as a consultant, combining a strong blend of commercial and technical understanding in the application of consumer insight to help major brands improve digital marketing performance. During this time he also served as a Director of the Web Analytics Association (DAA) for two years and currently serves as a Director Emeritus of the DAA. Neil is also a frequent speaker at conferences and events.
Neil's expertise ranges from advanced analytical techniques such as segmentation, predictive analytics, and modelling through to quantitative and qualitative customer research. Neil has a BA in Engineering from Cambridge University and an MBA and a postgraduate diploma in business and economic forecasting.