Digital analytics is the use of data and metrics to gauge the overall performance of a business in regards to their digital marketing efforts.
A good digital analyst needs three primary skills:
1. A sound comprehension of the data; where did the data come from and what it really depicts?
2. An understanding of the problem that needs solving. What insights are useful rather than just interesting?
3. An ability to communicate the actionable insights well. Valuable insights are insignificant if they are not shared credibly.
In order to be a good digital analyst, you must be good with numbers. Your job would be to analyse the effectiveness of any digital marketing channel such as social media, mobile, or even email. If you can’t figure out whether a channel is profitable for a company (calculate the ROI- Return on Investment) and you can’t predict how it will grow then unfortunately you aren’t cut out to be a digital analyst.
Other than being good with numbers, you must know how to use programmes such as Excel and PowerPoint so you can help create a marketing plan for your senior. Lastly, you need to be able to provide insights. Marketers already have enough reports so they are looking for individuals who can effectively convey the insights. As an analyst you need to help the company gauge it’s overall performance when it comes to digital marketing.
A lot of our clients also look out for certain core skills even in fresh out of University graduates with no experience. For example, during some interviews, candidates are given an Excel exercise and access to Adobe Analytics (formerly Omniture) or Google Analytics to do an analysis of the data from the website (sans training).
There is therefore an assumption that applicants already know how to navigate software and use the Internet and “Help” function. In terms of presentation, clients are always looking for people who can use the data to draw conclusions and not just read back reports! Inferences may not always be correct due to the complexity of digital data, but the concern is in the inclination to make those insights initially none-the-less.
A good analyst becomes a great analyst when they are able to creatively put all these three above mentioned points together. They understand the data and the problem well enough to learn how to make decisions based off the data versus inventing new ways of respectively using the data to solve it. A great analyst has a bold imagination and enjoys playing with ideas, as all of these factors affect how profitable a channel is and you need to determine if they are worth pursuing.
For example, if the marketing team of a company started email marketing campaigns and you know that they are losing the business money, you may want to cut the programme. But before you do so, you need to analyse the channel to get a good understanding of when the data shows it can break even and what your long term return on investment (ROI) will be.
The Evolution of Digital Analytics Tools
Software companies have long been focussing on providing much more detailed insights on each individual customer. For example at Kissmetrics, they have stopped their focus on tracking metrics such as bounce rates, and instead placed their focus on tracking people. This way you can get a better understanding of the lifetime value of your customers, or churn, or average time before a customer purchases. If tracking that was based on individual customers versus “visitors” didn’t exist, software companies would not be able to provide that sort of aforementioned data.
In digital analytics nothing is more impactful or ubiquitous than personalisation.
As for challenges, companies may run in data overload, where analysts will have to do a better job of crunching data for others within the company, especially as digital analytics crosses the borders of big data. Software solutions will need to do a better job of providing actionable insights too so that analysts have an easier job.
“You can’t manage what you can’t measure”.