Melissa MacGregor
What’s the one thing you wish you’d known when you started in social listening?
Rigor is your friend, rigidity is not.
As practitioners in this field, it’s imperative to stay nimble, creative and open – as the world of social data is moving and morphing fast. Methodology, processes and platforms that unlocked so much for one project or one stakeholder set, might be entirely insufficient the next. Sources change. Interests change. Keep the rigor in your work + methods, but stay flexible to meet the next moment.
To do so, IMO, always go back to your north star - the business question.
Have you had any experiences that have made you want to quit? What made you keep going?
There have been tough periods for sure – but late nights, messy data, systems crashing, dynamic business needs… all come with the territory of any research field.
However, I think Microsoft’s growth mindset culture plays a major part in reducing burnout. There is an incredible emphasis within all levels of the company to cultivate a ‘learn-it-all’ mentality rather than a ‘know-it-all’ one.
For me, this mindset –paired with the ever-evolving social intelligence space– fuels my curiosity every day and encourages me to hold space every day for discovery, experimentation, innovation and storytelling. It also creates an environment of great colleagues, stakeholders and suppliers who are open to this newer research discipline and who are eager to learn –and do– more.
Additionally, I enjoy my role because of:
- People. The people I work with, the people who use Microsoft products and the people who share their perspectives, creativity and ideas online. I love that social intelligence allows me to collaborate with great colleagues to elevate insights or spotlight emerging needs so Microsoft can iterate and help people achieve more. I feel close to the users, close to the strategists and fully part of Microsoft’s mission.
- The fast, ever-changing nature of social media. Social, in my experience, is never dull. Platforms ebb + flow, how people express themselves to do too. Shifts to Threads, shifts in emoji usage, rapidly shifting memes – we work hard to uncover, interpret, and contextualize. It’s forever a moving target – and it’s one worth going after. There is always a cool question, topic or technique to dig in on which helps us get a little closer.
What role does tech play in your social intelligence process? Where to people contribute?
Tech and people are interdependent forces in social intelligence. Both are incredibly important and, in my opinion, both will continue to be so. I’m glad we are far beyond hand-coding verbatims or manually sourcing tweets; I’m also glad we have analysts that help guide, fine tune and vet our tech. Technology empowers us, but it’s the human touch that adds nuance, elevates insight and infuses thoughtful, strategic direction.
Today, instead of sinking days and days into manually cleaning data or scoring verbatims for tone, we rely on our tech stack, spam detection and QA processes – which allows us to spend more time focusing on the insights, strategy and impact. Artificial intelligence (or Systematic Approaches to Learning Algorithms and Machine Inferences (SALAMI) as I like to remind myself now and then) will likely thoroughly and fully uplevel our existing processes, but our final outputs –in my opinion– will be stronger when we include people who can guide tech’s methods, cleaning, insights, visuals, narrative and recommendations.
We need analysts, engineers and strategists’ critical thinking to shape and refine our implementation and interpretation. People provide context, interpret results, ensure ethical considerations and so much more than tech alone.
I am hopeful that products like Copilot will make insight generation and data cleaning easier– and social intelligence practitioners will be able to focus our efforts on impact, execute a wider-range of research to more people and broadly achieve more. However, I believe we will need to always be part of the full process – providing expertise, creativity and guidance to deliver strongest social intelligence insights.
Who have you seen as a mentor in your career?
So many! A few alphabetic shout-outs include Angie Aldape, Bernard Brenner, Kelly Holland, Justin Schoen and Eryn Taylor.
Most embarrassing mistake you made in a social listening project - what did you learn from it?
As a junior analyst years ago, I raised my hand to take on a daily social media round-up report that had high visibility.
This report went out at the same time every morning – and, a few weeks in, I had my morning routine honed and my reporting process fully in place. All my dashboards, stories + stats were ready to go and finely tuned; I felt like I was nailing this assignment. I’d received great feedback and I felt proud to have my name prominently attached to the project.
Well, one April morning –about five or so minutes before that day’s report went out– news broke that Facebook (now Meta) bought Instagram for $1 billion. It was an unprecedented business move for the industry for an unheard of amount of money for the time.
The acquisition instantly became the lead story everywhere!
Well, except my morning round-up. This news wasn’t in my report. I’d missed the acquisition story because I was looking at semi-stale data. Minutes after hitting send, I received a flood of mostly well-meaning folks emailing me that I had missed it. Everything turned out fine in the aftermath, but I can still feel myself sinking deep into my office chair after I refreshed my browser.
That feeling still haunts me!
But in a good way.
To this day, whenever I do a quickturn analysis or nonroutine reporting, I always always always refresh my feeds before sending a report out to ensure I’m sharing the fullest, strongest and freshest insights possible.
How do you see the future of social listening evolving?
Social intelligence has the rightful reputation for being on the bleeding edge.
In SIP, we refer to this as the “speed of social.”
I see this research discipline getting better at making sense out of images, audio and video at scale. Social intelligence practitioners tend to gravitate to where the action is online – and so meeting the moment in these arenas is where we are angling the most, especially as research techniques + computing power become more economical, scalable and speedy.
What’s the most useful data source? Are there any you find useless? Why?
<boring answer>
It totally + completely depends. IMO, source usefulness (and source uselessness) greatly hinges on the business question driving the research.
One researcher’s trash is another one’s treasure.
/boring answer
How have you been able to win over ney-sayers throughout your career?
My motto is “bring others along the journey.” Stakeholders, colleagues, managers, suppliers, social veterans, social newbies and even ney-sayers – social insights + recommendations are always stronger when other folks come along for the research ride. It takes energy, pro-activity and a lot of intentionality, but it’s worth it.
I find the benefits are fourfold:
- A more diverse range of expertise is leveraged from around the company – sharpening our business questions, queries, data cleaning, insight curation and storytelling
- In turn, more people have awareness of and learn firsthand the power of social research methods, which amplifies our discipline’s impact
- It forces us researchers to not slip into social jargon, default thinking or assumptions – saying what we truly mean, tailoring the best approach for the work, documenting clearly and producing meaningful research that lands with a wide range of audiences
- It also sparks ideas for future projects – such as supporting brand strategy around Pride Month, Societal Impact or Sustainability as well as method development like general population audience modeling, lifecycle product mapping or custom emotion classifiers
Okay and a fifth:
- It’s energizing! Doing strong, effective cross-functional work is incredibly motivating and, IMO, contagious; When we model this behavior with social intelligence projects, it begets other research teams and stakeholders wanting to emulate a similar process of integrity and inclusion – and our whole org thrives! We all get smarter, sharper and a fuller understanding of our customers’ needs
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