Answering difficult questions: a day in the life of a data analyst
In this digital world, data is key to your business decisions. No more finger-in-the-air planning, data should be at the core of all business decision making, as it offers definitive answers to difficult questions that you couldn’t otherwise answer. Welcome to a day in my life: a day in the life of a data analyst…
8:50am I arrive at work, lucky enough to have left home unscathed from the feeding ritual of my 10-month-old son and triumphed over the Monday morning traffic. Today, I’ll be drinking the warm nectar of a caffeine-rich dark roast – essential for the recovery from the baby’s midnight teething pains.
Daily Anomaly Checker – finding out what’s wrong
8:55am I open my emails and check our automated reports to ensure all our clients’ campaigns are functioning as they should.
The Daily Anomaly Checker is the first port of call for identifying any issues on our clients’ sites that could affect marketing activity. The Checker is an automated process that compares metrics gathered from the preceding 24 hours, to the average for that day of the week, and flags when there is a statistical difference.
It seems that the Daily Anomaly Checker has flagged that a client’s site sessions have fallen significantly compared to an average Sunday. This tells me that something’s wrong – but it doesn’t tell me what or why. I check Google Analytics to investigate.
9:12am I check individual channels to make sure paid ads are still working and that no potential rankings have dropped for organic traffic. Everything looks fine.
9:24am I check the device and browser traffic to make sure the site is functioning as it should. Still no answers.
9:31am I check the data by country. The US is fine, but all the Asian countries have been affected. Aha! I discover that yesterday was a Chinese day of celebration. By interrogating analytics data, I have answered what’s wrong. In this case, luckily, it was a false alarm and traffic returned to normal.
Keyword research – finding out what people want to know
Keyword research is one of the most insightful activities within digital marketing – particularly for new clients, as it’s a window into their customers’ needs and wants. It’s the process of collating the words that people type or say into a search engine. Data is then gathered on those keywords and calculations are made to help identify marketing opportunities.
For example, keyword research can help to identify areas of improvement in organic or paid search. It also guides content creation, because you can write about what people want to know – the answers they’re searching for.
9:50am I collate and categorise the keywords by gathering the search volume data and current rankings for the potential client. My calculations are made and I send the spreadsheet to the account strategist with an email explaining the findings.
Reporting platform – finding out what’s working
Reporting and analysing the performance of a campaign is just as important as campaign implementation. Without performance statistics, there’s no way of knowing whether or not your marketing activity has been successful – and to what extent.
To report on the performance of a campaign, you typically have to go to multiple sources, download the data from each into a spreadsheet, then arrange the data to produce graphs and metrics that are easily digestible. This can be a time-consuming and costly process.
However, Further’s own reporting platform gives us the ability to automatically collate website, ranking, paid search, social and sales data into one report. There’s no need to have the Paid Digital team downloading data from AdWords and the organic search team checking various Google Analytics views – with the reporting platform, they simply log in and have all the information they need at the click of a button.
11:17am The next task on my list is to modify a widget in one of our client’s monthly reports to show the performance of a new Google Analytics goal. I open the reporting platform, locate the widget in editing mode, and make the required changes.
12:30pm It’s time for a tea round and a bite to eat before the next task. I also take the opportunity to look at the news headlines to see what’s happening in the world.
1:30pm A new report is needed for our Paid Digital team to help them manage their spending for one of our clients. The report will need to draw on historical data to forecast the number of leads that will be created that week. This will help the team know if they need to increase or decrease their bids to ensure that they hit their campaign target. I set up the report and an automated daily email containing all the necessary data the team needs.
Customer profiling – finding your audience
Customer profiling is a way of understanding your customers in more detail by identifying characteristics that are unique to distinct customer groups. This is achieved by drawing data from a variety of demographics and dimensions, such as age, gender, interests and hobbies. Personas are created from the findings to help put a face to the customer data. Knowing to whom you’re marketing means that you can tailor your messaging and tactics appropriately to increase conversion and secure a positive return-on-investment.
3:58pm I receive one of our clients’ customer data files on an encrypted drive. This data will be used to create customer personas for different product purchase groups. I write a script to upload the data to our database. The file contains millions of rows of data, so I leave it to run overnight, ready for the morning.
5:10pm I have a catch up with the Planning Team to make them aware of my progress today, and to discuss tomorrow’s tasks.
5:30pm It’s time to go home and answer today’s final question: how much sleep will my son let me have tonight?
The above is just a fraction of what a data analyst does. Data analysis is varied – one morning I’ll be doing keyword research, the next morning I’ll be analysing data from a dating app.
At the core of each task is answering a difficult question: what do people want from a certain brand? Who is a typical customer on an eCommerce site? How many people will sign up to a certain newsletter next month? How successful is current link-building activity? etc. The list of questions is endless – and data analysis can provide an answer for each of them. Having that eureka moment when you find the answer you’re looking for is what keeps data analysis interesting – it’s why I love my job.
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