Analytics Practices: Connecting Consumers and Companies Alike

Posted by Alex Avitabile from Ogilvy CommonHealth Worldwide — North America on December 18, 2017

As a recent college graduate who has begun his career in Marketing Analytics, I have already learned so much! Learning new skills, however, always poses new challenges. From creating presentations to pulling and analyzing data from multiple sources, things have been far from easy. But that’s okay! I never expected it to be easy, and I always like a challenge. Through the trials and tribulations of starting my career I have reached a point where I feel comfortable taking on the challenges I face at work. Since starting my career I have picked up some important practices that have helped me build my analytics skills immensely. I believe the following habits can be applied to make Marketing Analytics more easily understood, more interesting, and more applicable to a wide variety of scenarios.

1. Keep Your Data Clean


“Bad data kills marketing effectiveness. Period.” – Justin Gray, CEO of LeadMD


Making sure your data is clean is one of those housekeeping tasks that seems trivial enough to overlook, but is in fact important enough to take a serious toll on a project. Keeping data sheets neat and understandable is important for multiple reasons: first, you never know when you are going to have to go back and pull something that you had previously worked on. Whether you are trying to find a previous metric or a set of numbers to compare to a current analysis, messy data sets can waste time and energy. Disorganized data is a huge source of frustration, and can truly impact the quality of the process and the output. Another good practice for clean and concise data is making sure that your data sets do not contain duplicates, which is two of the same variable being accounted for in the same data set. Duplicates can throw off numbers for reports and important metrics, such as customer loyalty programs and sales information. Making sure that a data-set’s integrity is intact is a key practice for valuable reports. 

2. Build a Story


“The goal is to turn data into information, and information into insight.” – Carly Fiorina, Former HP CEO


So, the data is clean, and you have run all necessary analyses on it. That’s great! But… what does it mean? Why should a client or internal team care about the correlation between variables? What is happening in the market and what should we do about it? You need to build a story around your findings. Providing the numbers and observations around them is simply not enough. Looking for a meaningful insight or implication makes the analysis worthwhile. Creating a story around your data is a building block to the brand’s identity and helps explain the way that the target audience interacts with it. Stories will help give a brand direction, and data can be applied to all aspects of a marketing mix. Data-driven stories can tell you who your brand’s message is resonating with most, who is or is not connecting with your brand, and why certain interactions take place. Most importantly, stories can tell you the best way to optimize and be more cost efficient moving forward.

3. Make It Human


“A story created by a robot is a story devoid of human emotion, which is one more reason why effective marketing, even in the data-driven era, will always need the human touch.” – Bryan Melmed, Vice President of Exponential Interactive Inc.


With all the numbers, metrics, insights, recommendations, takeaways, KPIs, etc., analytics can begin to feel monotonous, as if someone is reiterating something straight from the computer. This feeling of repetition and potential boredom is, in my very-fresh-to-the-industry opinion, the antithesis of how analytics should be handled. Emphasis on human interaction is extremely important.


An amazing thing about all this data is that we can make it more human by the sheer amount of data available. Most of my experience working with big data is leveraging it to understand consumer interaction with brands, whether it be with a website, an advertisement, or a sales promotion. And yes, big data is a scary thought to many—constantly being tracked with every email open, website click, and CRM program sign up. Account teams and clients can sometimes shy away from big data, fearing that hard numbers could prove certain campaigns or tactics to be unsuccessful. To all those with big data qualms I say, “Fear not!” Data and audience interactions are tracked to make the consumer experience more enjoyable or, at the very least, less painful. With data analytics, we can figure out things that consumers like and dislike about certain brands, websites, and advertisements, and adjust accordingly.


The beauty in numbers is having the ability to bridge the gap between countless amounts of statistics, ratios, metrics, and the human experience. We’re all human, and we should all be treated as such.



These practices of keeping data organized, building stories, and being relevant have truly made my job easier and, more importantly, worthwhile. The amount of data we have is growing every day and is vital for businesses to leverage to “break through the noise” and allow customers to understand their identity. With more data come more challenges and insights, and as famous statistician W. Edwards Deming once said, “Without data, you’re just another person with an opinion.” I implore you to take the right steps with your data for an efficient—and human—approach to marketing.