Since marketing analytics continues to be the topic of the day, I decided to take a look at how organizations are recruiting analytic talent today and what they have determined to be the most important skills for their candidates to possess. My comments are based on discussions with digital marketing executives and practitioners as well as an extensive review of job postings for the role of digital analyst.
Given the urgency that exists within organizations to be able to leverage the vast amount of data at their fingertips, I am not surprised that I found that many companies may in fact be neglecting to focus on what I would consider some of the most important characteristics of a strong analyst.
Let’s start by discussing the laundry list of technical skills included in most digital analyst job descriptions. Requirements can range being an advanced SQL and SPSS skills to having years of experience with a marketing automation platform or third-party analytics tagging.
Having access to resources with a high level of technical expertise is absolutely vital for an organization. I would suggest, though, that those individuals who possess the high level of technical expertise required to program, tag or implement are not necessarily the same individuals who possess the ability to provide insights that will ultimately lead to increased customer engagement, conversions and an optimal ROI.
In fact, I have found in my own experience that it may be these softer skills that are the real hallmark of a successful analyst. And, it is those softer skills that I found were often missing from job descriptions for digital analysts. Here are six of them that I found to be particularly valuable in a solid analyst:
Listening
Stakeholders pose questions to an analyst that they think they want answered but in the end their questions are often rather tactical and not the question they really need to have answered at all. It’s up to the analyst to listen to the requestor and to gain an understanding of how the request can be tied to a strategic business goal.
Problem Solving
Once the business goal of a project is defined, creative problem-solving skills are an absolute necessity for an analyst to possess. It is their responsibility to figure out what is required in order to tackle the project. Discovery or scoping questions might include:
- What metrics or KPIs will be used?
- Do you have the necessary data? If not, how and when will you get it?
- If the data is coming from multiple data sources, what is the effort required for integration?
- What type of segmentation will provide the best view into the data?
Intellectual Curiosity
The analyst needs to be passionate about research and investigation. Their ability to drill down into the data to the level where they can identify the drivers of the KPIs and define actions that will impact them is crucial to their providing value. Potentially valuable research includes having an understanding of:
- Industry trends
- Search demand changes
- Competitor growth strategies and tactics
- Emerging competitors
- Emerging markets
Storytelling
The customer insights manager of a global multichannel merchant recently shared with me, “CMOs are no longer looking for dashboards and scorecards – they are looking for wisdom.” I believe he summed it up perfectly. The days of dashboards and scorecards are over. An analyst needs to share numbers as an easy to read story – one that is very short and direct as opposed to a long novel. The story might follow this organizational structure:
- Here’s the question we are answering
- This is what the data says
- Here’s what it means
- Here are the actions we should take based on the findings
Discerning
With access to so much data a good analyst must be able to discern what is valuable and what is not. You may be working with six different data sources, each with ten data points. They are not all necessarily valuable or relevant to the business question at hand. After looking at all of their data options an analyst should be able to determine:
- Which data points are going to add value to the story and then ignore the rest
- The extent of data normalization or cleanup required to account for data anomalies caused by events like site outages and tagging issues
- That the research and analysis methodology and data sources can be defended
Partnering
While an analyst does not need to be a coder, developer, merchandiser or marketing strategist, they do need to be able to speak the language of all of these partners and others who are involved in implementing the strategies and tactics they are recommending. Here are examples of some of the more vital partnerships they should strive to build:
- IT – To assure data hygiene, accuracy of campaign tracking and changes made to the web site
- Marketing – To stay abreast of branding changes and initiatives
- Channel Strategist – To stay up to date on campaign schedules and optimization efforts
- Product Marketing – To understand product launch schedules
In truth, these are two-way partnerships. The analyst needs information from his or her partners to add the necessary context to what they are delivering, and the partners need the insights from the analyst to drive what they are doing.
In summary, my recommendation is that if you are building an analytics discipline within your organization, find an analyst with the softer skills first who can be an educator, storyteller and advocate.
Then add on to that foundation by adding the technical expertise. If you do not have the luxury of being in a position to hire a second or third analyst, engage an agency or contractor to fill the technical gap. By all means – please do not recruit one person to do it all.
Janice Smithers is a digital marketing analytic consultant/researcher.