A life in the day of Rajesh Rajendran, Campaign Manager, Blis Asia

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A life in the day of Rajesh Rajendran, Campaign Manager, Blis Asia
Patricia Reyes


The Blis team is growing across APAC. As pioneers of the power of location data, we’re on the lookout for people who can interpret deeper brand and consumer insights from our campaign data, and tell then these stories. This blog series digs into life at Blis, kicking off with a one-on-one with Campaign Manager and all around nice guy, Rajesh Rajendran.

It’s a busy week at Blis Singapore and the Ann Siang Street office is buzzing with activity. Desks are being shuffled around to accommodate a batch of joiners shadowing their new line managers. Hunkered down on their laptops, Team Ad Ops remains a focused, reserved bunch amidst the noise. There are campaigns to run, clients to satisfy, reports to bang out and these guys waste no time.

The daily grind

Rajesh peels himself from his desk and takes a precious hour off his day to talk through his role. Hailing from South India, he relocated to Singapore for Blis two years ago and loves the autonomy. As a Campaign Manager, he is responsible for all phases of an online campaign.

“I collaborate with the Sales Team the most,” he shares. “Sales bring in the projects, then Ops execute, manage and optimise. We report the results which typically share how their campaigns are performing.”

Sounds simple? Hardly. These campaigns are complex by nature, coupled with Blis’ high standards for accuracy, precision and scale. Raj is one of three Campaign Ops Managers in this office that serves as the regional hub for Asia. Between them, they are running 10-20 campaigns every day. Rajesh monitors up to 15 active client campaigns at any given day running at various stages, which means he’s very much in the asking line of all departments. Optimising the campaigns, that is, managing the various platform functions for them to perform better, takes up the biggest chunk of his day given the scale of work.

Comfort in complexity

Despite this, Rajesh appears unfazed by the demands of the job and seems absolutely comfortable with complexity. If you want to see his eyes light up like a kid at a candy store – talk spreadsheets, code and analytics. Not surprising for a guy who carved his niche by being the go-to Excel whiz.

“When I first started, I was initially interest in typing code…In my first company, which had almost two hundred people working on digital marketing, everyone was doing the same work…I applied my knowledge and ability to code into Excel and it became something that made me unique. There should be something unique to show, otherwise, we’d all be the same.”

As we nod our heads in agreement, he recounts a moment of career kismet:

“I was first interested in programming, software development and IT, but in 2006-2008 and it was difficult to find a job. So, I thought this (digital marketing) would be six months temporarily and I would try finding IT jobs in the meantime. But I got interested, so it went like this *points up* and it’s been eight years since.”

The future of adops

Why the stickiness? Why would anyone get into Ad Operations in the first place? Typically, this job attracts number-savvy problem solvers. Their analytical inclinations bode well for a satisfying career in digital marketing. Aside from the fact that digital ad spend is surging year on year in the SEA region, the role is a prime spot for constantly upgrading skills.

It takes patience, talent and mental tenacity to analyse data in its most granular form to manipulate parameters and reach campaign objectives. It’s safe to assume that numbers and data are like crack to these guys. However, moving along the trajectory, Ops people are encouraged to take on a more consultative role and be proactive with their clients.

“Clients are very different, especially across various countries and based on their moods, asking for information at any given time. Aside from managing campaigns, a lot of my work is also managing clients – but it’s fun. It’s a learning experience, at the same time it’s two-way. It takes a lot of patience. We can take it in a funny way or a negative way, but it’s important to have a good attitude about things,” shares Rajesh.

Sage advice from this accidental digital marketer who cites LinkedIn and Quora as his go-to sources for community discussion, industry updates and lots of humour. Aside from reading the latest updates, he entertains himself with random queries such as: “What are some things that airline pilots won’t tell you?” (A LOT.) or “Can I restrain a wolf with my bare hands?” (You can’t!)

The hour is almost up, and as Raj pauses in between questions to scan his phone for requests, we sense the day is just beginning for him. We leave him to it, and ask if he’s got any tips for aspiring marketers. With a sly smile, he laughs and says, “It’s a very easy job, very easy. Just start. When people start to do it, they’ll get an idea how to do it. If they have questions, I’m there to help them and let’s learn more together.”

Interested in joining Blis? See our website for current openings www.blis.com/career/

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Patricia Reyes

Patricia is part of the marketing team and operates out of Singapore helping to oversee SEA and ANZ marketing and communications.

Prior to Blis, she’s worked at both sides of the coin as editorial, project and account management before finding her sweetspot in marketing and adtech.

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When Blis became one of the first tech partners to offer the CPV model earlier this year, we sent a critical message to both retailers and the wider industry: We’re ushering in a new era of transparency and accountability in advertising.

Check back again next week when we switch gears to discuss how retailers can use mobile to boost engagement, retention and acquisition.

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Mobile devices provide the answer. By revealing where consumers go, mobile location data can tell brands which consumers spend their time browsing similar products at a competitor’s store. Let’s say Target wants to reach out to consumers who usually shop at Walmart. They can use location data to identify—then target—those who frequently visit the competitor yet still live near a Target store.

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