I was recently asked to put together a workshop session on data-driven marketing for a class of digital marketing students. While pulling the material together for the workshop, I came to the conclusion that there are four key components for successful data-driven marketing, some of which are obvious, some perhaps less so.
The four components are:
This is the most important component. To be successful at data-driven marketing, an organization must have the right culture and philosophy.
At its heart, data-driven marketing is about continuous optimization and iterative improvement. It's the deployment of a test, learn, and adjust philosophy. Yet you can have the best data and technology in the world, but if there's no the desire to act and to change, then the data and technology only provide interest as opposed to insight. Organizations must have a desire to act.
At a Web Analytics conference I attended last week in Berlin, a lot of the talk in the networking session was not about metrics and systems, but about how to embed analytics within organizations. Often, the biggest challenge facing analysts is getting support for the development of their programs because, culturally, their organization doesn't have a philosophy of measurement and accountability.
If "philosophy" is about the desire to act, then "processes" is about the ability to act. More specifically, it's about the ability to execute, then to react. These processes involve the management of the technologies, and also management of the decision making.
Processes include building "measurement" into the marketing development process, for example, so there's no question that new campaign won't be tracked properly or new content on the Web site won't be tagged. It also involves ensuring a feedback mechanism is in place so trends can be identified and changes can be made in appropriate timescales.
An example of a potential desire to act that was inhibited by an inability to execute was once demonstrated to me. We did a piece of segmentation analysis for a retailer to feed into their e-mail marketing program. We identified a number of distinct customer groups with different purchasing behavior that could be marketed to in a more customized way.
We also identified some key timing mechanisms that could potentially double a customer's propensity to buy again. Despite these insights, the segments were never deployed operationally because the retailer didn't have the resources and processes in place to develop and deliver more targeted e-mail marketing programs.
Data is, of course, a vital ingredient in the mix, but the organizational culture and processes provide the recipe for success (or failure). Good quality data is important. Attention must be paid to getting the numbers right. People are reluctant to make decisions if they don't have faith in the data.
Data-driven marketing also requires integrated data rather than data residing in silos. Within organizations different types of data often sit in databases, and different functions may have ownership of different types of data. For data-driven marketing activities to be effective, different data sources must relate to one another.
To understand and optimize marketing across channels, data from different channels (PPC search, display ads, e-mail, etc.) must be in the same place, whether that place is a Web analytics systems, a campaign management system, or both. In addition, data needs to be managed across the customer life cycle, for example by ensuing data on how customers are acquired can be analyzed alongside customers' long-term value or profitability.
Finally, technology is the enabling component. Technology allows you to execute and react, either over the duration of a planning cycle or in real time. I don't think technology can make up for deficiencies in the philosophy and processes, though if you have the right approach and procedures you can make progress even if your technology isn't the most effective.
Good technology enables you to cycle through processes faster, even to the point where real-time optimization is possible. Like the data, the technologies should be integrated and allow the loop between insight and action to be closed.
So the core ingredient of data-driven marketing is high-quality integrated data. Technologies are tools. It's the right combination of organizational philosophy and strong processes that provide the foundation for success.
Neil is off today. This column was originally published Feb. 19, 2008 on ClickZ.
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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.
March 19, 2014