Sizing Up WebTrends' Maturity Model

  |  May 26, 2009   |  Comments

Maturity models help organizations identify where they are and where they're going. Some feedback on one designed for digital marketers.

Maturity models seem to be all the rage these days. These models help organizations identify where they are on the road map of whatever discipline or capability the model is about and where they need to be. They help describe the journey to world-class status or best practice.

I've used a simple maturity model for a few years to help organizations identify where they are in terms of developing their digital marketing optimization capabilities. It's a useful device to help people understand the journey they're on and a sense of the ultimate destination.

At eMetrics in San Jose, WebTrends launched its own maturity model, the Digital Marketing Maturity Model, or DM3. It's a useful contribution to the debate.

WebTrends is clearly hoping DM3 will be adopted as an industry standard and that, over time, organizations will be able to benchmark themselves against others. There's even a survey you can take based on the model that will help to build industry norms.

The model seeks to help organizations assess the development of their digital marketing measurement capability on six main dimensions:

  • Measurement strategy

  • Analytics resources and domain expertise

  • Data integration and visualization

  • Data analysis and insight

  • Adoption and governance

  • Ongoing optimization

These dimensions cover the bases and reflect that an organization's maturity isn't based only on what technologies they've invested in but also on the infrastructure they have in place to support them and how they use them. The model recognizes that one key criteria is an organization needs to have a coherent measurement strategy. Too often, organizations still invest in measurement technologies without a clear idea of which problems they want to solve or with little recognition as to where the technology fits into an overall plan.

DM3's other useful aspect is the recognition that adoption and governance are another important component. This section is essentially about business processes around the measurement technologies.

Do organizations have procedures around some key processes, such as campaign tracking, content tagging, or user support? If they have those procedures, are they actually being followed? Again, too often analytics and measurement technologies are implemented without the necessary rigor of the business processes around them, leading to disappointment and poor quality data.

WebTrends stresses that DM3 is a work in progress and is looking for feedback. My own feedback is in some of the details of the model constructs in the different dimensions.

For example, one component within the Data Analysis and Insight dimension is called Social Media and Competitive Analysis. These two elements are completely different and need to be separated. You can have good benchmarking capabilities and spend a lot of time monitoring your competitors while doing absolutely nothing about monitoring or measuring social media activity.

One notable exclusion in DM3 is mobile measurement. Given all the attention mobile is getting at the moment and the challenges in getting decent mobile metrics, it's important to have mobile in the model somewhere. It probably highlights one of the challenges DM3 might face: keeping current with emerging digital marketing channels, such as mobile.

Also, the model is too orientated toward site-centric measurement systems. Any digital measurement strategy needs to incorporate "voice of the customer" type programs to some extent. While it's implicit in some of the dimensions around data integration and data analysis, it needs to be a more explicit competency that an organization needs to display.

It's early days for the model and I'm sure it will evolve, but I think DM3 is a useful tool by which organizations can look at themselves and make an assessment about where they are on the learning curve. The model also gives some guidance about what needs to be done to move to the next level. On the basis of this type of formalized process and scoring, organizations can be better informed about how and where they need to invest their efforts next.

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ABOUT THE AUTHOR

Neil Mason

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.

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