PII: For Carat's Patricio Jaramillo, Business And Analytical Skills Are A Career ‘Killer Combo’
Patricio Jaramillo is in a serious relationship with data. “My relationship with my wife is first, and then with data,” the SVP of analytics at Carat told AdExchanger.
Jaramillo has built a career in digital marketing analytics, from working in ecommerce for Zappos to shopper marketing data company Dunnhumby. Before Carat, he worked in retail ad tech at HookLogic.
Now, he’s landed at media agency Carat to move its analytics practice beyond reporting and into what he calls “statistical analysis.”
“A lot of people think statistical analysts should be in the back, not talking to anyone, developing algorithms,” he said. “I’m looking for people who can actually talk to a client and have a good [business] conversation with somebody who is not technical.”
Jaramillo spoke with AdExchanger about his career as a data guy across the marketing landscape.
AdExchanger: Why did you move to the agency world?
JARAMILLO: At the time I was applying to Carat, I had offers from Amazon to take over marketing analytics in Europe or Seattle. If I went to Amazon, it would be what I did at Zappos on a bigger scale.
If it’s monotonous, I get bored. I care more about the challenges of the data and infrastructure, and I saw there was a lot that could be done agency-side.
Zappos changed the way I think about my career. I really consider culture important. I didn’t have any knowledge on how agencies worked, but I enjoyed the culture and people at Carat. I’ve worked in financial services for MasterCard, in pharma on the retail side for Kroger and on the CPG side with retailers and brands. I had a lot of expertise in digital and ecommerce.
What was it about Zappos that changed your mindset about your career?
It’s by far the best place I’ve worked because it’s where I met my wife. It becomes a part of your life, but in not a typical work way. It's not all about revenue; it's about delivering what the customer needs. You have the full freedom to decide what you want to do. There’s no need to go up the chain. There’s collaboration across all teams without too much bureaucracy. I’ve seen that here at Carat, too. Everyone helps each other and collaborates.
How do you use data in your daily life?
If I see an article, I don’t believe it until I see the data behind it. If somebody is talking about polls, I have to look at who actually did them. How did the data evolve?
I look at numbers to see if they have correlations and pairs. It [comes from] older Chinese and Indian cultures. Certain numbers represent something better. It's like numerology.
So you like to play number games.
Kind of, but there’s a natural distribution of numbers zero through nine, proven by a mathematician called Bernoulli. It’s used for fraud purposes, which I used in financial services.
When I look at things from a financial perspective, I take the emotional part of my brain out — even though I’m South American.
At Carat, I put a lot of emphasis on the percentage of people doing reporting vs. analytics and how we could push to more analytics-driven opportunities.
Do you ever find data-driven advertising creepy?
You haven’t worked in financial services if you think ads are creepy. The information they know about you when you open a bank account, all of the probably 5,000 variables they put into a model to give you a score, that’s creepier. That's why banks make relationships with phone carriers and cable companies. You can know specific income, what a person does and whether or not they are receiving a check. Tracking in terms of an ad is not as intrusive.
Companies [like Google] have that information, but there is still hesitancy. Machine learning is not as advanced as it should be. You have to make decisions in milliseconds to make sure there’s no latency. There’s a lot more that people can use from data.
What advice would you give someone looking for a career as a digital advertising analyst?
A data analyst can no longer just pull data. They need to create a demo to convince an executive about an idea, to make sense of numbers from millions and millions of rows.
The most important thing is knowing about the business. Pulling numbers for Pfizer is totally different than for MasterCard. You need to know the strategy. That’s the killer combination — willingness to learn not only the data side, but about the business and the agency.