In my next life I’m coming back as a marketing analyst. They are in such demand right now. Virtually every agency I work with has multiple openings. It may be a result of the Internet and social channels providing new models to measure engagement and response. Or that marketers have more data on their customers than ever before, or can negotiate more efficient media buys. Whatever the case, the ability to flip content, channel and cost in real time demands that you’re actually reading and interpreting all that data you’re collecting. That’s why this year is the year of the analyst.
So What Do Analysts Do?
In ad agency settings, Analytics can take on a variety of formats. At the most basic level, it’s about measurement strategy, e.g. defining KPIs, figuring out how to track and report on them, testing and optimizing to achieve the best results. When I started recruiting for Analytics roles, this is the skill set that first came to mind. Turns out it’s only the tip of the iceberg.
The next tier is marketing mix modeling, which has to do with attributing response to media channel, identifying which ones offer the best ROI, then recommending a budget allocation. There’s also response projections, proformas and predictive modeling, which forecast results at different uptake and spend scenarios.
Analysts are also the keepers of customer and business intelligence. They track demographic, behavioral, transactional and self-reported data captured on customers, and use it to drive segmentation and customer profiles. They get involved with database and survey design, and modeling activities aimed as teasing out most lucrative customer segments and finding more like them.
Here’s one you wouldn’t expect: A member of the Analytics team at R/GA is working on product development and user interface based on data gathered at in-store kiosks.
An analyst at Citigroup developed several new trading strategies/algorithms based on consumer and credit card data. These strategies tell stock & bond traders how to manage investment funds and inform buy/sell decisions.
A Razorfish analyst introduced a new retargeting model and CPM pricing strategy anticipated to save clients millions on online media buys.
Challenges Analysts Face
The two main challenges mentioned consistently are: 1) Educating clients and winning more sophisticated analytics assignments for the agency, and 2) Being engaged early enough in a project to add value.
Phil Castoro, Director/Data Solutions Group at Merkle puts it this way: “We’re not going to be the first people to get invited to the party. We need to have a compelling enough presentation and rapport that people want to have us around and get our advice.”
Phil’s team often uses “snapshot reports” as a conversation starter. These reports give an overview of marketing activities and results, customer profiles and competitive environment. They provide clients with new insights into how to improve marketing effectiveness and ROI. “Once you’ve demonstrated you have the tools to make them more successful in their jobs, it’s easier to sell in everyday analytics work and consulting.”
Esther Kang, Director of Digital Analytics at mcgarrybowen says: “Clients are always interested in learnings – ways to achieve bigger results with smaller dollars. We have to be looking for ways to achieve this economy early in the game.”
To truly optimize marketing performance, Esther recommends that her team is engaged at the creative briefing stage. “Learnings from previous marketing activities have to be considered and embedded in iterative work, KPIs must be defined and we need to ensure we’re capturing the data to effectively report on them.”
What Makes a Good Analyst
It’s not what you might think. Aptitude with quantitative data is a given. Analysts typically spring from academic disciplines like Economics, Math, Statistics, Finance and Engineering. They have an innate ability to spot trends in data. They’re the Jedi Masters of Excel.
But beyond fun with math, the more elusive skill – and the one that’s difficult to teach – is relaying insights and implications in a way that’s actionable. Says Esther Kang: “It’s the capacity to communicate difficult concepts. Analysts must be able to translate math to English and back again. That’s my rule with my team: If you do work, you’re going to present it. It gets my group into the practice of explaining analysis and interpretations to lay audiences.”
I’ve enjoyed recruiting analysts and getting to know the skill set. (This is a good thing because it doesn’t look like demand is going away any time soon!) Besides respecting their mathematical aptitude, I dig that they are keyed into a stream of minutiae that most of us don’t notice or understand. This often leads to both astute and hilarious observations. For example, one analyst I talked to – I won’t say who – insisted that 5K race time is “one of the most reliable predictors of how hot a girl is.” Another anaIyst uses the analogy of points and assists scored during a basketball game to explain the channel attribution model. These are terrific proof points of how a good analyst can make data approachable, meaningful and fun!
With many of the analysts I talked to, there was also an efficiency of communication… simplicity and directness that I can only attribute to someone who reads data versus expressing impressions or hypotheses. The very best analysts are riveting conversationalists and persuasive presenters.
Advice for Employers
Not surprisingly, people who have this aptitude with numbers and language – right brain/left brain stuff – advance quickly. Ability and demand pull them along, so it’s not unusual to see director-levels 4-5 years out of undergrad making over $100K+. I’ve ridden out some extreme bidding wars with employers who have to compete with multiple job offers. My best advice to client companies is to keep pace with the market by interviewing and making offers quickly. And when you can’t compete with salary or diversity of work, establishing a personal connection and demonstrating professional development opportunities are successful ways to woo candidates. I’ve encouraged the Analytics department head to personally call candidates after we extend an offer – to convey the vision and opportunity new hires will have to make a meaningful contribution.
Finally: If reading this article has made you want an analyst of your very own, call me. I’ve met a lot of great ones recently.