A skills shortage in the marketing sector is seeing brands playing catch-up as they look to find candidates with both brand marketing and data skills to reflect new realities in the industry. Here’s some tips from Dr Shorful Islam for brand marketers looking to upskill in data.
Data professionals find it interesting to see the relationship that marketers, especially brand marketers, have with data. Marketing agencies will explain that data is critical to how they operate. However, most marketers are not equipped with the relevant skills to be data-driven, according to a 2022 report from Treasure Data.
Most marketers want things simplified: brushing complexity over with a neat graphic, a number rounded or selected to prove a point. Many show an uneasiness using data to inform campaigns, and focus more on measurement which seems much easier to understand and grasp.
However, modern marketers need to rethink their relationship with numbers. It is not, as many state, the ‘opposite’ of creativity. In fact, many data analysts are extremely creative people.
If marketers with a brand background want to grow their career, they need to prioritise building data skills.
So, how should they go about doing this?
- Learn the basics of statistics
In the modern world of marketing, numbers are an integral part of a marketers’ tool kit. The need to understand how campaigns perform or their ROI becomes more important the ranks are climbed. It’s not enough to simply state a spend of X on marketing, accountability is a must. Also, with the wealth of data available, using data to inform the execution of marketing, from what to create to who to target, is a competitive advantage.
Marketers need to understand how percentage growth is calculated, how to correctly interpret ratios, and become familiar with how a mean calculation with skewed data can be misleading.
There are plenty of introductory statistics courses available – from a series of short courses over several weeks run by universities, to self-taught statistics courses through Coursera or Udemy for example. No one is expecting an A-level exam pass, more knowing the mean from the median.
- Understand the foundations of data collection
Another area that marketers need to be aware of is how data is collected, from customer touchpoints, but also more generally. Basing marketing on metrics such as website visits, customer footfall, sales, registrations, likes or video views seems easy when a number is presented seemingly accurate.
But biases and the methodologies developed to create and collect these data points can be misleading. This is a known phenomenon when collecting data through surveys. The way questions are asked, and to whom, determine the results.
The same is also true from so called ‘big data’ – where decisions have been made how data is collected and presented. Marketers need to be aware of flawed or biased data or wrong decisions can be made.
In 2016 Facebook apologised for an error in how it measured video viewership, a miscalculation that greatly overstated how much time, on average, users were spending watching videos. This lack of insight led many marketers to prioritising Facebook videos over TV advertising assuming a greater reach. Something that clearly was not correct.
Instances like these are not uncommon. Being familiar with how data is collected can ensure the data used reflects the reality.
- Know how to analyse data in Excel
An analyst's favourite tool, Excel, should also be a marketer’s favourite tool. It’s unlikely macros and pivots tables will be created or an xlookup formula will be used, however, it should still be an essential part of a marketer’s tool kit.
Often receiving multiple reports across differing sources can lead to misinterpretation. Having the ability to copy and paste numbers in Excel to conduct the relevant calculations will not only make life much easier, a marketer will then have the analysis needed.
Learning Excel however, should never be done with a course – the best way is to self-learn through practical, relevant tasks. This makes remembering that much easier. It helps to have an Excel savvy colleague. Analysts do love to show a good Excel tip and trick.
Being able to manipulate data and doing (basic) analysis or calculations means marketers can look at data in their own way and validate hypotheses or hunches. It can be treated like a big calculator. It will also win kudos from the data analytics team.
- Get to know the language of analysts
When marketers need to ask analysts for data, it is important to know the language analysts speak. Instead of asking how a campaign performed for example, its use to performance is not a metric which analysts can run a query on. Being specific in requests can only help.
Is performance related to the number of people clicking, people visiting, people buying or people just browsing? The same with engagement – it is also not a number analysts can query. The more specific the query, the more likely marketers will get what’s needed and in a timely manner.
The use of words is also important. An analyst will use terms like transposing or pivoting data for switching columns to rows, and vice versa, or feature engineering when referring to the attributes of any data set. If marketers use their own terms for requests, they might end up with something that’s not quite expected.
Finally, conversing, both with analysts and fellow marketers, about what the data means and how it can be used will make better and more effective brand marketing campaigns.