Top secrets of digital marketing analytics

Marketing practitioners are in touch with digital analytics all the time. But there are a few secrets in digital marketing analytics that they need to know. Some of these may need the disclosure. Others may just be so common that they are left in blind spots.

Secret 1: Before marketers ask for it, analytics has already started

Analytics relies on data. Creation of data does not wait for marketers’ command to go ahead. Neither do processing and analysis of data. In the era of Big Data, data come from everywhere and all the time. They appear in both quantitative and qualitative forms, structured and unstructured, in big volume or in small batches. Analytics happens in real-time as data emerge, or more precisely when things happen.

For example, when one started to create a campaign plan the first question was always about what the situation was. The description of the situation was a result of some analytics that had taken place before the need to know arose. At this point, the marketer just opened the dashboard to look for some analytics to confirm the situation.

What markets need to do is to treat analytics as an on-going process and know where to hunt for the needed data. This requires them to be sensitive as well as informed. Remember, when Mike Bloomberg asks that everyone else bring data, he knows they should already have them.

Secret 2: The APIs are making all these to happen

When using digital analytics, not knowing about APIs is like opening a website without knowing the Internet. Whereas the analytics dashboards are like websites, the APIs are equivalent to the world-wide-web protocols to enable the exchanges of data and information.

API is the application programming interface, which is a group of computer codes to ask computers to exchange data with other computers. Clicademy has another reading to focus on this topic. Today all digital analytics tools use APIs. Scroll down their websites to read their documentation. Here is an example from Ahrefs about its API offerings.

Marketers do not need to deal with APIs directly, just like website users do not need to know what the www protocols are. However, marketers need to know how to discuss APIs and their capabilities with computer engineering teammates and those in partner companies. They need to have a say in what data are exchanged between the data owners and the fetchers.

Secret 3: What you see is mostly vanity

Pageviews, sessions durations, returning users, new users… how do these metrics matter? Sadly, among the several hundreds of measurements that marketing analytics tools show us, most of them are more for vanity than usefulness.

Not fearing to critically analyse our own data, your Clicademist acknowledges that we are in such a situation said above. We are yet to roll out our search engine marketing programmes, so the hits and views we get are the leaves without connections to the roots. What concerns our most is the sign-up rate, with very few site visitor’s journeys ending at the Goal Page.

Then what is not for vanity? The answer is to choose the correct KPI(s) which should correctly measure the current marketing performances of your organisation. Once set, the KPI metrics are the analytics that is useful. Others are just good to have but non-essential. For example, the current performance for Clicademy hinges on building site traffic and signing up members. The visitor-to-member conversion rate, measured by the visits to the Goal Page versus the total traffic is our focus.

Secret 4: Analytics are most useful when helping to create solutions to digital marketing problems

Good numbers and upgoing darts just tell a partial story. Digital analytics is more useful when it shows problems. Being able to see these problems and to make difficult choices to solve these problems make a good decision-maker.

Marketers constantly need to set objectives. After doing this many times enough, setting marketing objectives becomes the second nature. Digital analytics enables the so-called data-driven objectives. Marketing managers should build it into a habit to consider setting marketing objectives means to solve some problems. And they are able to see the problems because of analytics data.

It is a tough call when faced with the choice of to see problems or to see vanity from data analytics. So when next time your boss asked you to bring data, would you bring in problems or good news?


How do marketers stay relevant to marketing today

Marketing professionals need to adapt to the New Marketing driven by data and technology. Else, they would risk losing their relevance to this profession. These words are not dramatics.

Let us reflect on what happens when we hear or talk about marketing today. Before long the narratives would run into words such as the Big Data, artificial intelligence, the Internet of Things, marketing automation, etc. Marketing practitioners today not only have to talk and hear about these phrases constantly, but also deal and work with them on daily basis.

What’s your strength?

Obviously, these concepts do not traditionally belong to marketing. It is a challenge for marketers to take ownership of them. Marketing professionals’ strength has been in creativity, communications, and strategy. They are less comfortable working with computer codes and statistics. Likewise, marketing students tend to be more interested in Adobe Creative Cloud than SPSS, R, Python, and GitHub. Some of them still do not think they would ever need to touch them.

In a field with the ideal division of labour, statisticians and software engineers should take up the number crunching and coding jobs. But what if the labour now is about numbers and coding? Look again at those marketing buzzwords. They all require data and coding skills.

Contested field

For marketers, marketing has become a contested field. The increasing adoption of and reliance on data and software skills see jobs going to statisticians, data analysts, and software coders and engineers. It does not mean that creative and communication skillsets are not essential. However, marketing job seekers have seen recruitment ads noting analytics as essential skills and software literacy as preferred ones.

Marketing today has become technology-driven. To fuel its engine, data and computing have joined creativity, communications and strategy to be the core career assets. For the marketers who are strong in the latter set of expertise, their working relationships with the number and code persons are mutual supplementary in general. But peer-to-peer competition is looming.

In this wave of the New Marketing (We do not call it digital marketing and there will be a post to explain why), marketers should consider any or all of the three suggested approaches to handle the working relationships with colleagues who possess data and coding skills: to work with them, to work like them, and to lead them.

Relevant learning

To achieve any of these, one needs to learn how data analysts and software engineers work. Such learning will build up data analytics and software project development knowledge and skills. They can benefit multiple aspects of marketing. For example, data-driven agile marketing management, consumer understanding using data analytics, AI-assisted customer journey optimisation, new product development, automated customer relationship management, to name a few.

Building such knowledge requires a journey but is feasible within a manageable period of time. Clicademy in its next few series of posts will introduce concepts, tools and approaches that for our site visitors to learn data analytics and the New Marketing practices.

Clicademy links learning with reality. The site provides live traffic data to provide you with the first-hand analytic insights. You will need to register a membership to access the data analytics.