I started my career in a financial securities company working in data processing automation for securities trading for institutional clients. Around 2005 when the blog was taking off, Google Analytics was launched. It was a game-changing event for me.
I had been thinking about what I wanted to do next with my career. One of the things that came up was wanting to get into marketing and analytics. I believe at that time, with server costs expected to decline, more data will become available for anyone.
I truly thought that digital businesses would eventually take off, and data will become one of the most important parts of running such businesses.
Digital Analytics seemed like a perfect fit for me, given my expertise in data processing automation, data query language SQL, and writing scripts. It just so happened Google launched their new web analytics tool, “Google Analytics,” in 2005 and made it available for free to anyone that owned a website.
What is Digital Analytics
Digital Analytics is the process of measuring, collecting, and analyzing data about user behavior to improve engagement.
There are many different types of analytics, but all share a common goal: understanding what’s happening on your site or app to make informed decisions that will positively impact user experience. Digital Marketing Analytics is an emerging discipline in marketing with its own set of tools and techniques.
In 2005, the common terminology that described tracking and measuring the website was referred to as web analytics. However, it was also considered a subset of the larger discipline, referred to as Digital Analytics.
Web analytics consists of many different types of tracking and analysis around:
- Content engagement tracking: Understand what content visitors are viewed
- Traffic source and campaign tracking: Where visitors came from to access your website and landing pages.
- Conversion tracking: Understand where the visitor came from and purchased a specific product at a certain price.
Digital Analytics has evolved since the early 2000s. Today, it is the primary discipline of marketing and management that focuses on understanding user behavior online to improve engagement with your company or product.
Digital analytics has helped businesses of all sizes grow. For example, by using technology to collect data from our online marketing activity, we can better understand what resonates with customers and how they engage with content through the different devices they use throughout their day.
The goal here is to grow customer experience and convert more consumers into paying customers by understanding which digital channels work best for them and when (morning vs. night) or where (mobile vs. desktop).
How I got started with analytics for marketing
I started my marketing career in 2006 as a marketing analyst at a digital agency, where I got the chance to learn about analytics and the optimization process on websites for clients in the CPG industry.
At that time, there weren’t many job openings for marketing analytics. Instead, it was geared towards IT or some technical role that supports marketers enabling tracking and building reports.
Many enterprise companies are now investing heavily in the digital marketing space, but only a few large companies have invested in enterprise-grade web analytics platforms.
Having Google Analytics experience on the resume didn’t help much, as many marketing managers were looking for specific experience with certain tools on a resume.
What helped me get a marketing job was making a strong case around my data engineering skill-set and tying it back to my projects building blogs. Getting my foot into the door on the agency side was a great choice when I had zero experience in marketing.
The foundation of skills that help me get analytics jobs
My marketing foundation was built in the first few years of my career in the agency world, when I was reading and studying as much as possible about tracking and data integration.
The hands-on deployment was probably the most important part of the job to build the experience and track record working with large enterprises’ websites. Eventually, those skills helped me get a better job on the client-side.
It’s been an amazing ride since then!
As you can imagine, the analytics world has changed a lot in the last decade. It’s no longer just about tracking visitor behavior and web traffic, but also audience growth, social media marketing with advertising for performance-driven campaigns on Facebook, and many other SNS and ad channels.
Following the exposure to enterprise-grade web analytics tools, was getting the experience working with a large e-commerce site. Having that exposure to a business that grew tremendously was an important part of building the foundation for data-driven marketing. In addition, that experience to tie data back to business growth and to deploy marketing strategies with large marketing spend was valuable.
Another phase in my analytics career that built a firm foundation is adopting Tableau, a BI tool that many companies and marketers use today to find insights from their data. Learning Tableau and applying it in practice was a game-changer. It allowed me to be free from excel and, most importantly, do more with analytics and insights discovery.
Three important lessons I learned to become a data-driven marketer
1) Set the right expectations by interpreting the data according to the stakeholder
This means asking, “What is this data telling me?” and what would the key stakeholders who would see the data or reporting would take away from the insight?
As a marketer working with data, you will find many bad results or marketing outcomes that aren’t living up to the goal. It’s up to you how you tell the story, but it is important to set the right expectations for stakeholders, so your data don’t mislead them.
2) Avoid vanity metrics
There are many KPIs that marketers obsess over but don’t correlate with customer acquisition or retention. A great example of this is social media likes and followers. As a marketer who will need to bring results to the business, it is important to focus on metrics that bring value.
Use data trends and analysis to determine how that impacts the KPI and the business’s bottom line. And know what the objective of the data asks is since it is very common for management to ask marketers with different intent, depending on the business they’re in.
On one day, asking for conversion rate means a CEO is trying to prepare a comment for a board meeting, and on another day, the question’s intent could be to learn what the team should be working on to improve the sales. But if you as a marketer understand the difference between vanity metrics and KPIs, you can prepare yourself to answer questions quickly and efficiently.
3) Understand how the data is tracked and avoid bad data
I’m sure you’ve heard “Garbage In Garbage Out,” which is the idea that bad data will result in a distorted analysis. With analytics, it’s true!
You have to be very careful when choosing what data you want to collect. It is also important to know how the information you’re tracking and reporting is being collected and processed within the data tool from which you pull the data.
I’ve come across many situations where marketers refer to the term conversion rates, but the numbers and math used to define the conversion rate make it a very different metric.
It would be best to be extremely careful, especially when you encounter a situation where the collection and methodology change for data representing the business’s KPI. Executives never enjoy the case when their KPI’s definition varies because the last thing they want is an unpredictable measure of their success or progress.
What you can learn from my path to become a data-driven marketer
I learned that data is a powerful weapon in the marketing arsenal, but it also requires experts who understand how and when to use it for different purposes.
It’s easy to be seduced by vanity metrics or without understanding what stakeholders ask about KPIs. However, you can become a valuable asset in any company when you know how to interpret the data and what tools are better for certain KPIs.
A successfully seasoned marketer who is data-savvy could reap the benefit of a higher salary, promotions, etc.
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