Deep Dive into Data Analytics with Global Digital Marketing Professional, Manuella Emerick! 🌐💻

Manuella Emerick is a highly analytical, self-starter, and dedicated professional with a passion for extracting relevant data-driven insights and providing data analytics solutions. Manuella has led projects in a variety of areas including digital marketing, growth & demand generation, data management (analysis, integration, and visualization), marketing automation, CRM management, etc. As a consultant, she has also established her skills and experience by partnering with several clients from small to medium-sized businesses to established global corporations.

Manuella is currently working as a Senior Data Analyst at Thermo Fisher Scientific within the biotechnology industry. The company is an American supplier of analytical instruments, life sciences solutions, specialty diagnostics, laboratory, pharmaceutical and biotechnology services.

Manuella: Hello, my name is Manuella Emerick, I’m a senior data analyst at Thermal Fisher Scientific in the biotechnology industry, and I actually recently started there but I’ve been a Senior Data Analyst in different industries before. Mostly in health insurance, hospitality for a little bit, and Consumer Finance so that is my role in where I’m at right now.

So, everyday on my role I work specifically in the global digital marketing in a global digital marketing team for one of our divisions. A lot of my day-to-day is either performing analysis that are needed for specific presentations or for just deep dives that we’re trying to do to determine improvements in our websites or our programs in our digital marketing programs. It may look like doing a lot of documentation, which a lot of times happens in corporate jobs where we just end up having to document a ton of processes and things like that. Every day looks a little bit different, but it’s obviously tons of cleaning data, going through data, putting data into graphs and visualizations to be able to present and find insights. Then, other days it’s just your usual business things where we’re trying to find efficiencies in the way that we do things.

I put it in a PowerPoint just so that because I had to make modifications to it but basically one of the tools that I’ve used the most because I’ve done a lot of web analytics in both e-commerce, but just overall digital is both Google analytics, Adobe analytics, which basically gathers all of our web data so any page traffic, visitors, all those metrics that come from our specific digital asset or specific website.

This specifically, I actually can show you the tools — so this is Adobe analytics. You’ll see a few things blurred because I can’t show much, but this is for example, like just a test workspace and a few dimensions, metrics that we have. The one that I’m going to show you is a specific analysis that I did on a specific site that we’re looking to sunset because it’s no longer serving our strategic focus. We’re looking to understand where traffic was coming from. It’s a global site — so what regions they’re coming from, what this traffic look like over time, what are the top referring domains. You can see that Google is the main one. There’s specific channels and specific URLs. I put together this here just so I could show you. For example, this was just the overall dashboard that I put together for us to be able to look at that. There is some, for example, digital funnel rates so awareness rate, conversion rate, maybe things that you guys are familiar with in digital marketing. Just overall web traffic, so I try to also put an example of what the analysis looked like with the information I could.

Basically this one was like I mentioned, we were trying to look for overall users of a site so that we could determine what are things that we need to account for when we were trying to sunset the site. So, we’re trying to get get it offline. We’re no longer going to use it so if certain regions were using it we had to account for that. If certain channels were being used like social media or paid search to drive traffic there we had to consider. Just a few things that I put together that I always recommend for any analysis that you do is always determine high level objectives. You can kind of lose track of the goal when you’re just focusing on putting data together and showing insights. So, it’s really important to always bring it back to the strategic objectives. What are we trying to accomplish? That’s just something that I always do — put together kind of like ‘here are the objectives of what this analysis is going to tell us’ and what you can expect out of it.

A few of the things that I had shown was just overall performance trends, this is how this experience has performed in comparison to last year or to a previous time, or to a different experience, or a different site. Specific benchmarking KPI’s that I could compare that would be interesting for the audience. Specific traffic sources just looking at this page specifically has accounts for 45 percent of the overall traffic for the site. The main source of traffic is the U.S. as a region, followed by the UK. Just overall metrics that tell us how a website’s being used. That’s the best way to put what this specific analysis was for and any kind of specific insights of how we can leverage the tool better. If that’s the goal that we have versus trying to sunset it, are there any insights or any any processes that we have right now, that we’re gonna lose if we sunset this website and just let go of it?

That’s something else like that’s kind of like an analysis that I’ve actually recently put together that I thought I could just share. I also just wanted to show you like an older Power BI dashboard. Power BI is mainly for data visualization, not necessarily hosting data in terms of the web analytics like Adobe or Google. It’s more your inputting data or you’re connecting it, integrating it with data, so that you can create reports and dashboards and it’s a great tool to combine different data sources. You can combine data from Google, from Adobe, from Google ads — from just tons of different sources and put it all together and be able to analyze them.

This one right here as you can see we were looking at overall registration rate. Both lines are registration — one is for this year, the other one is for previous years. As you can see right here we can see that in June, for example, registration for this year’s shoot up in comparison to the previous year. Same thing for cancellation rate, it’s always a good way, at least tons of times executives are really interested in ‘looking compared to last year’, ‘compared to same period last year’ or to a previous period. Kind of should give us an insight of how we’re doing compared to that how we’re doing better, are we not, and then we can investigate why. Same thing here with cancellation rate — this is for a specific consumer finance product. Then here is just a quick table which tons of times is not the prettiest way to show data, but sometimes it’s the way that most people prefer. So then, same here — overall daily cancellation units — this was a monitoring report done to kind of see by region and by client how many daily cancel units we’re having and having an overall trend and a trend line. So you can build out filters in Power BI, so then you can obviously play with the date and so on and so forth.

Rosa: Did you ever figure out why some people weren’t registering, or what was going on with the negative numbers?

Manuella: Yes, so for that specific project — it wasn’t a specific project, it’s just something that we always were trying to figure out. It was a membership subscription plan so we had to understand just all the overall lifetime value. We understood that people that registered had a higher lifetime value which executives are always interested in, obviously, because it means more revenue. So, we were able to identify specific digital barriers in the experience that were making people not sign up, we were able to identify or register, we were able to identify gaps in the email marketing program. We weren’t emailing them enough, reminding them to register or like even telling them this was a consumer finance product, so they could claim — let’s think of like a auto insurance — so they could do claims, and we were also observing that people will register only when they needed a service, so we wanted to drive away from that. So, those were all data insights that we were able to provide with the visualizations in this dashboard.

If I were to give just an advice on someone trying to break into data analytics in any industry or whatever, it would be focus less on tools because I think a lot of time people are more focused on: I have to learn SQL, I have to learn python and R, and all of these different coding languages. I think it’s a lot more important for you to know how to communicate effectively according to your business objectives and how to understand data and communicate it. The tools are just a resource — like it’s just a way for you to leverage that knowledge, but if you know the tools and you don’t know how to do that then there’s something missing in the — at least in the data analytics space. There’s different roles where it’s like data science, data scientists, data engineer, where you can be a lot more technical and focused on the tools. I think as a data analyst you have to be able to communicate effectively, understand the data and communicate it effectively. It’s not just about pretty pictures and graphs, it’s about the storytelling of it — like what is the data telling you, how can you communicate that to your audience, and know your audience because not everyone can understand the same. You can say the same thing in different ways and not everyone can understand the same way.