5 Traits of the Analytically Empowered Organization

  |  July 19, 2011   |  Comments

Does your organization possess any of these characteristics?

Fifteen or so years after organizations first started to measure what was happening on their websites by parsing log file data, what does good look like? There are five characteristics that define an analytically empowered organization.

  • Clearly defined key performance indicators (KPIs)
  • Holistic approach to measurement
  • Integrated data strategy
  • Investment in "humanware"
  • Ability to execute

Clearly Defined KPIs

At analytically empowered organizations, considerable effort goes into defining digital key performance indicators. To do this, the digital strategy must be clear and coherent. If the strategy isn't clear, how can you possibly measure its success? In my experience, defining good, robust KPIs is not an easy task. As a result, KPIs are often not very good. Going through the process forces an organization to think hard about its strategy, define what success looks like, and make a commitment to measurement. If you can't measure it, then you can't manage it.

Holistic Approach to Measurement

The old saying goes, "If the only tool you have is a hammer, then every problem looks like a nail." Ever since the log file was developed, the digital marketing industry has been banging away with its web analytics hammer. The analytical empowered organization understands that it needs a whole toolbox. Web analytics provides some but not all of the answers about digital performance measurement. It's great for telling you what is going on but even a well-configured web analytics tool (itself a rarity) isn't very diagnostic. Organizations need to invest in additional quantitative and qualitative data sources to truly understand what is going on and why. Additional investment requirements include voice-of-the-customer feedback on a number of levels (based on visit, page level, and post-experience), ongoing user experience measurement and analysis, site performance tracking, and contextual information about trends in the marketplace.

Integrated Data Strategy

A holistic approach to measurement also requires a unified approach to data integration. An organization also needs to understand how all the pieces of the jigsaw fit together. This requires some effort around data definition (what the metrics actually mean) and where different types of data will be housed. In an ideal world, data is integrated around known users but this may not always be appropriate or possible. Different data types have different characteristics, so planning is needed to understand how the different components fit together. For example, some internal data may be on a customer level, but digital data is often based on cookie level data and one customer may use a number of different devices to interact with the organization resulting is a number of different cookie records.

One powerful outcome of data integration is the ability to match behavioral data with data around attitudes and opinions. By integrating web analytics data with voice-of-the-customer data, it's possible to look at the relationship between what people do in a digital channel and the experience they have. This type of integration gives the organization the ability to measure outputs (things that happen in the channel) and to understand outcomes, which are often the most important things to know.

Investment in Humanware

All the hardware and software in the world will get you nowhere without "humanware" to extract insight and value from data. Too often in the past, investments have been made in technology without appropriate investments in people. The result is often disappointment, if not failure.

Today, analytics teams are taking a more multi-disciplinary approach. As data becomes more integrated, an integrated approach to analysis and insight is needed as well. Web analysts must start working alongside customer insight specialists and user experience experts, sharing their knowledge and expertise.

Ability to Execute

Organizations gain a competitive advantage from the application of insight, not by the generation of insight. Insight has no value unless something happens as a result. So the analytically empowered organization has the ability to execute and make decisions. This has implications beyond the immediate concerns of analytical technologies; it also concerns a business's entire technology landscape. Often, a product or site development process and technology constrain an organization's ability to affect change. So the analytically empowered organization must develop strategies in technology and processes that enable it to act on its insights.

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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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