home : chapter 1 : chapter 2 : chapter 3 : chapter 4 : chapter 5 : chapter 6 : chapter 7 : chapter 8
chapter 9 Metrics and Analytics
further reading ...
Note that I’ve included some articles that are a couple of years old ...
don't let their publication date put you off - they are still relevant now.
The most recent posts are at end of each section.
This book covers only the essentials – for links to wider coverage of the
subjects take a look at the web pages for Digital Marketing; a Practical Approach.
Metrics and Analytics
A beginner’s guide to building a data science team. You might also want to read Here’s why so many data scientists are leaving their jobs as it will give you an insight into what a data scientist thinks of his job. I particularly like the line "The data scientist likely came in to write smart machine learning algorithms" ... that - to me - sums up what they do. They produce data, they do not analyse it. Marketers analyse date, they don't produce it.
In general, I share the views of the author of Big data is just a crutch for unimaginative marketers to lean on - and he knows a lot more about the subject than I do.
The Case Against Google Analytics for Organizations Collecting Personal Data.
Attribution
Why marketing attribution hasn’t lived up to the hype—yet.
Data gathering (data mining)
Vanity Metrics: Add Context to Add Meaning.
86% of websites using Google Analytics are not anonymizing their users’ full IP addresses could also be in the privacy section in chapter 1 - but I put it here because it is relevant to collecting data.
Analytic skills
Better known for other things ... Adobe [as in Photoshop] collects data as a business model.
Adobe Advertising Cloud Health Segments 2019 is just one 'segment' of the data that the company offers for sale. Note that this is not illegal, and not covert. Each list will have a 'personal identifier' [not necessarily a name] referring to individuals and will have been gathered by Adobe from numerous sources. Third-party data is the company's sales pitch
and Buy, sell, share: A marketer's guide to the data trade is a ppt slideshow about the same which - as the title suggests - is actually an excellent introduction to data gathering and use.
I have included Using Google Analytics to Track On-site Promotions purely to give you an idea of what else is out there - and in this case, it's on Google Analytics. And just when you get used to one analytics platform ...
Google Data Studio now known as Looker Studio.
17 Free Tools for Social Media Analytics is included not to promote the brands listed, but to make students aware of what is out there to help digital marketers.
Gaining Meaningful Insights from Data is Still Hard. Why?
GSK’s Jerry Daykin on how to avoid the ‘slippery slope’ of digital KPIs.
What is being measured?
Some of the ideas presented in Analyze Competitors for High-traffic Content Ideas are pretty basic – but well worth a look.
Using clickstream data to know your customer's entire online journey.
Identifying users on different devices is important for marketers, so What is identity resolution?
6 ways CPG brands can reach their best audiences is an excellent summary of how data should be used.
Although Buying a pre-owned domain? Check these 10 things first is about checking the history of a domain name, I have included it here to show the range of analytics available and from where. Essentially, this research can be conducted on any domain name.
Although Demystifying Google’s guide to clicks, impressions and position in Google Search Console is based on SEO, it is actually about SEO analytics.
The vital role of ‘slow data’ in e-commerce offers a basic - and short - introduction to slow data. Note also that this article could be part of content marketing - you'll see a 'find out more' link to the organization's web page where a free demo is offered. In other words; this piece has not been written as an educational article - it's part of the organization's marketing.
How to Measure “Hard-to-Measure” Marketing Channels.
Limitations of online data
Data doesn’t need to be big or creepy to shed light on consumer psychology is rather 'heavy' - but well worth the effort to read it. I particularly like that its author expresses that most collected data tells us what people did - not what they will/might do in the future.
Data Managers Feel Overwhelmed by Abundance of Tools.
We need to talk about digital dashboards actually addresses analytics in a wider context than just dashboards.
Is data good for the environment? read the opinion of campaigner Gerry McGovern.
'Anonymized' Data Is Meaningless Bullshit is an interesting commentary on the subject -m which I think makes a lot of sense.
Gartner Survey Reveals Marketing Analytics are Only Influencing 53% of Decisions reflects some aspects of what I say in the book.
How much of the internet is fake?
Is everything on the internet fake?
Problems with metrics
Your marketing dashboard is too full of s**t offers a wider perspective of the subject.
Does Your Analytics Platform Have Cybersecurity Built-In? is a little deep - but if nothing else, it provides some good issues for you to pose questions at potential analytics service providers.