Community and coding: Women in STEM are not alone

Aimy Le; image supplied by Meta.

The struggles that women in tech face are significant, and as marketing and technology grow ever closer, it is now a shared responsibility to break down the barriers. Aimy Le, Marketing Science Partner at Meta, reveals how their partnership with She Loves Data is helping to address these challenges.

If you’re a woman in tech, chances are you may feel as if you need at least 90% of the qualifications listed in a job description in order to qualify for the role.

As She Loves Data’s ANZ Region Lead and Global Head of Analytics, Eva Taase explains, in her experience, most men feel they only need about 60%.

It is this discrepancy that led to the birth of She Loves Data, a non-profit social enterprise aiming to inspire women around the world to upskill and network in analytics, coding and data. This cause is also special to Meta – in 2019, we committed to doubling the number of women in our workforce by 2024, with internal Women@ groups facilitating positive changes for women in our community.

Meta’s latest Diversity Report revealed we met our workforce goal ahead of time, but there is still work to be done. The ultimate goal is to create a more diverse and inclusive industry – and we can achieve that by training women in skills that will increase their chances of attaining new jobs or promotions. Marketing mix modelling (MMM) is one of these crucial skills.

That’s why Meta’s Marketing Science team recently partnered with She Loves Data for a collaborative bootcamp with some of Sydney’s brightest minds.

Attendees, who were primarily women, were able to both discover and upskill on all there is to know about MMM, and Meta’s open source MMM code, Robyn. This was an in depth training with Meta Marketing Science, with each participant getting first-hand, valuable experience in how to run a MMM and deal with more complex statistics.

This workshop revealed just how integral community building is to anyone looking to develop their personal skills.

All marketers must try to ride the wave of evolving tech

As marketers continue to grapple with ongoing privacy concerns and increasing scrutiny over budgets, MMM has appeared as a solution to help resolve these tensions.

Put simply, MMM is statistical analysis of sales and marketing data that can help measure the effectiveness of marketing tactics. It has also seen a significant evolution – MMM is now more agile, automated, and machine-learning driven than in the past. It provides valuable insights that marketers can leverage in order to protect budgets and prove the value of their work.

Andy Ford, Head of Marketing Science at Meta Australia and New Zealand believes MMM is crucial for marketers to understand, and has increased in importance over recent years.

“MMM is probably the most robust and useful cross-channel attribution tool that you can measure and use,” he said in his opening speech at the She Loves Data bootcamp. “The world has changed, privacy has changed and marketing analytics has changed. This all requires a slightly different way of thinking.”

However, “MMM” as a term can sometimes sound intimidating, particularly to those who perhaps don’t have much experience in sophisticated statistical analysis. Historically, marketers may not have been trained in data analysis or coding.. To be a marketer now requires a more complex understanding of technology, measurement and data than before.

In Australia’s She Loves Data community, it’s women who are employed in senior positions and looking for new roles, or who want a career change, that are in need of support to ensure they’re not being locked out of jobs with no way to rectify the situation. Women who have taken a break to raise children before re-entering the workforce also often face challenges when it comes to learning new technologies.

As the saying goes, you don’t know what you don’t know. But building a foundational knowledge in the latest developments in technology is increasingly essential for any women in this space.

No one can afford to be an island anymore

Meta’s Robyn bootcamp was an all-day affair, where attendees were able to connect, collaborate and learn with like-minded professionals.

Attendees learnt how to run an MMM from start to finish, including collecting and reviewing data inputs, using Robyn to produce models, and experimenting with Robyn’s Budget Allocator tool to identify optimal budget allocations. It was a hands-on, intensive training experience, where the goal was to enable everyone, including those from non-analytics backgrounds, to run MMM themselves.

If that sounds like a heavy learning load for a single day, it was made possible via the collaborative nature of the bootcamp, which saw attendees network and learn not only from Meta’s Marketing Science team, but from each other.

She Loves Data’s Taase explains that this is completely intentional.

“One part of our in-person workshops is networking, where beginners can ask those in more senior roles for advice,” she says. “The workshops are tailored to empower women, and give them more support and courage.”

A community-based environment is crucial, ensuring attendees not only finished the day with in-depth knowledge on running complex MMMs, but also made connections that can resonate throughout the rest of their careers.

These workshops and training sessions also show that the links between personal and professional development are shrinking. Helping women be more confident or bold in a workshop one day may translate into their personal lives the next. When attendees finish a bootcamp and can add, “Marketing Mix Modelling,” or “Coding,” to their resumes, they can also take that deeper level of critical thinking into their daily lives.

Aside from dedicated workshops run by Meta and She Loves Data, professionals can turn to other peak industry bodies which provide training and courses, such as the  Interactive Advertising Bureau (IAB) and Association for Data-Driven Advertising (ADMA).

So while it may seem as if the ratios of power in this industry may never change, or that there are certain technologies too difficult to learn, it will always start with one step. Whether that be a networking event or bootcamp, it’s clear that it’s a step worth taking.

MMM, and in a broader sense, complex stats, are more accessible than you think, and are increasingly important in the evolution of advertising measurement. You can discover more about Meta’s Robyn model here.

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