Digital Marketing - Study Notes:
What is the Average Trap?
The Average Trap is a statistical term whereby using an average may misguide the real situation or circumstances of an event. In other words, using averages may result in misleading predictions or forecasts. When you have large data sets, it’s an easy mistake to focus on what the average of that data is telling you. The problem with constantly going back to the average is that you might miss out on vital insights, or you might miss out on what the data is actually telling you.
This commonly occurs with metrics such as site conversion rate. The site conversion rate is the average conversion rate of all the traffic on your site in relation to conversions. However, if you investigate the individual channel data, you might see that paid search has a very high conversion rate, , while display has a very low conversion rate for example. Focusing just on the average conversion rate of all traffic wouldn’t give you this insight and if you use it in your forecasts, you’ll get inaccurate results.
For example, if display drives a lot of traffic and has a low conversion rate, this distorts the average conversion rate for the site. If you were to only look at the average conversion rate, you wouldn’t see that some channels are performing very well and that non-conversion-focused channels such as display are bringing down the average.
As a result, you shouldn’t use averages across data sets if individual metrics are available as they will provide a much more reliable story than the average will.
Avoiding the Average Trap
To ensure you don’t fall into the Average Trap:
Avoid using an average as a goal.
If an average is a goal, check how far above or below the actual goal performance is and report on this.
Report on the frequency of goal misses rather than the average performance.
Not only are averages sometimes misleading, but they can also result in false negative or false positive reporting and recommendations. So, it’s essential that you don’t fall into the Average Trap when analyzing data!
Cathal Melinn
Cathal Melinn is a well-known Digital Marketing Director, commercial analyst, and eommerce specialist with over 15 years’ experience.
Cathal is a respected international conference speaker, course lecturer, and digital trainer. He specializes in driving complete understanding from students across a number of digital marketing disciplines including: paid and organic search (PPC and SEO), analytics, strategy and planning, social media, reporting, and optimization. Cathal works with digital professionals in over 80 countries and teaches at all levels of experience from beginner to advanced.
Alongside his training and course work, Cathal runs his own digital marketing agency and is considered an analytics and revenue-generating guru - at enterprise level. He has extensive local and international experience working with top B2B and B2C brands across multiple industries.
Over his career, Cathal has worked client-side too, with digital marketing agencies and media owners, for brands including HSBC, Amazon, Apple, Red Bull, Dell, Vodafone, Compare the Market, Aer Lingus, and Expedia.
He can be reached on LinkedIn here.
Kevin Reid
Kevin is a Senior Training Consultant and the Owner of Personal Skills Training and the Owner and Lead Coach of Kevin J Reid Communications Coaching and the Communications Director of The Counsel.
With over twenty years of experience in Irish and International business with an emphasis on business communications training and coaching, he is a much in demand trainer and clients include CEO’s, general managers, sales teams, individuals and entire organisations.
With deep expertise in interpersonal communication through training and coaching and in a nurturing yet challenging environment, Kevin supports teams and individuals through facilitation and theory instruction to empower themselves to achieve their communication objectives. This empowerment results in creativity, confidence building and the generation of a learning culture of continuous self-improvement.
By the end of this topic, you should be able to:
- Critically analyse the process of using analytics tools to create insights
- Critically evaluate the role of Artificial Intelligence (AI) and Machine Learning (ML) tools in enhancing marketing strategy
- Evaluate Customer Relationship Management (CRM) data and its use in informing business decisions
