Average-based metrics to measure digital marketing effectiveness or understand consumer behavior simply aren't good enough. Columnist Neil Mason explains why you must segment or die!
I've noticed a lot of chatter in publications and whitepapers recently about something I think about a lot: segmentation. Take this recent paper by McKinsey, which looks at shifts in media industries, for example. It observed, among of other things, that "averages hide incredible diversity in consumer behavior, making micro- segmentation necessary."
I couldn't agree more. I've long hated the use of average-based metrics to measure digital marking effectiveness or to understand consumer behaviour. They're at best sub-optimal, but at worst they are completely misleading. Typical digital behaviour is too diverse and skewed in different directions to make such metrics useful.
Let's assume that I'm a digital marketing executive in an ecommerce business and I'm measured by the overall conversion ratio. Currently, this is 4.1 percent. I decide to run a significant acquisition campaign to attract new visitors to the site. Many dollars later, the conversion ratio dropped to 3.2 percent and I got fired.
How did that happen?
Let's look at this in a bit more detail by doing some basic segmentation. What we have are two groups of distinct visitors, those who are new to the site and those who been there before. Their behaviours are different and importantly, their propensities to buy are very different. First time visitors are far less likely to convert than repeat visitors and purely because of the change of mix in the traffic, it looked like I hadn't done a good job.
Now, this example is slightly exaggerated, but we need to understand that segmentation is absolutely key to understanding both performance and execution. As Forrester put it recently:
Effective targeting, personalization, and campaign management depends on associating interactions to individuals or segments.
So the question, then, is what to segment and how?
Classical marketing segmentations tend to have been built on data such as demographics, product usage, and channel usage derived from transactional systems. Alternatively, needs-based segmentation approaches would be based on attitudinal data, gathered via survey research.
All of these are available to the digital (or omni-channel) marketer, plus rich behavioural data by the bucket load. We've never had it so good! The challenge is managing and being able to exploit all that data and for that we need the old trio: people, process and technology.
All of the above comes from organizations taking a strategic approach to segmentation and micro-targeting. McKinsey called out five key imperatives for executives operating in the digital world today:
Clearly, average just isn't good enough. In business today, you absolutely must segment or die!
Title image courtesy of Shutterstock.
Join the Industry's Leading eCommerce & Direct Marketing Experts in Chicago
ClickZ Live Chicago (Nov 3-6) will deliver over 50 sessions across 4 days and 10 individual tracks, including Data-Driven Marketing, Social, Mobile, Display, Search and Email. Check out the full agenda and register by Friday, Oct 3 to take advantage of Early Bird Rates!
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.
IBM Social Analytics: The Science Behind Social Media Marketing
80% of internet users say they prefer to connect with brands via Facebook. 65% of social media users say they use it to learn more about brands, products and services. Learn about how to find more about customers' attitudes, preferences and buying habits from what they say on social media channels.
An Introduction to Marketing Attribution: Selecting the Right Model for Search, Display & Social Advertising
If you're considering implementing a marketing attribution model to measure and optimize your programs, this paper is a great introduction. It also includes real-life tips from marketers who have successfully implemented attribution in their organizations.
September 23, 2014
September 30, 2014
1:00pm ET/10:00am PT
October 23, 2014
1:00pm ET/10:00am PT