In this era of data-driven everything, the need for high-quality marketing analytics has never been greater.
Yet for many companies, marketing analytics still consists of a weekly report and perhaps a dashboard or two.
It’s been a big year for data-driven marketing. Gone, mostly, are the dry aphorisms about ‘data as the new oil’, and in their place are marketers actually talking about data science.
The catalyst for this has arguably been the ‘AI summer’, but there’s much more to consider. Let’s ask the experts what 2018 will have in store…
Nearly every business now has a company-wide programme to help it capitalize on recent advances in digital technology.
Commonly known as ‘digital transformation‘, this process could (and perhaps should) be thought of as ‘data-driven transformation’ considering how important data is to the whole process.
Few would argue that two of the most important marketing topics at the moment are customer experience (CX) and data analytics.
Which is interesting as CX and analytics seem worlds apart. CX tends to be a soft, holistic study of how to make customers happier and analytics consists of the cold, hard numbers which fuel return on investment (ROI) calculations.
The world’s largest marketers and media companies have strongly embraced data management technology to provide personalization for customers that demand Amazon-like experiences.
As a single, smart hub for all of their owned data (CRM, email, etc)—and acquired data, such as 3rd party demographic data —DMPs go a long way towards building a sustainable, modern marketing strategy that accounts for massively fragmented digital audiences.
Although most brands confine their analysis of social sharing to share buttons and email newsletter tracking, our latest experiment shows that 87% of all shares are made through copy-and-paste direct from the address bar.
Unfortunately, there hasn’t been an easy way to track this data, until now.
One of the vast, underexplored opportunities of digital marketing is that, with the right data, marketing performance can be improved automatically in ways which marketers cannot foresee.
To make this happen, though, marketers need to use analytics, specifically prescriptive analytics, which we discuss in our fourth and final post in the series.
In the first post in our series on analytics, we discussed descriptive analytics which you can use to keep others informed about what has happened.
The next step on your analytics journey is to discover why something has happened, and for that you need diagnostic analytics. Here’s an overview of the practices including an example, a step-by-step guide and some best practices.
The term analytics is rooted in the ancient Greek word for ‘breaking up’ or ‘setting free’ and was intended to indicate a transformation of something complex into something simple which everyone could understand.
With that in mind, it’s funny that analytics itself is now widely regarded as complex, difficult and something best left to the experts.
Data from ad campaigns has, in some ways, never been so important.
Data has become the way marketers know whether the brand messaging is right, what drives customers to purchase and where they should advertise in the future.
Nowadays, marketers need to know so many systems, platforms, formats, and channels that it can be tough to keep up.
As we can’t be researching everything all the time, it is important to ‘park’ some skills while training up on others. As an example, a marketing team may decide to hold steady with their AdWords strategy while spending time and effort on improving how they approach social media.
Now do you think we’re sexy?
Let’s be honest, digital website or media campaigns audits don’t sound all that sexy.