Magic Numbers: Reframing the Story with Sathvy Reddy
Sathvy’s favourite question of all time is 'why?' Although this made her a very annoying child, it’s also what drove her to earn a bachelor's degree in business and psychology and ultimately what landed her in the analytics field. She loves dissecting human behaviour, looking at problems from different perspectives and understanding how we can find solutions to truly make an impact. Sathvy has experience working in the tourism, financial, higher education, retail and non-profit industries. Prior to A&G, Sathvy had a technical background where she built complicated data models and transformed them into digestible and beautiful dashboards that paved the way to strong insights. Today, she continues to build said beautiful dashboards but tries to bring a more humanistic approach when assessing what really drives business impact. She’s a team player that genuinely loves working with clients with different perspectives, and is always REDDY for a challenge!
LBB> Can you share with us any examples of projects you’ve worked on where the data really helped boost the creative output in a really exciting way?
Sathvy> Museum of Science Boston (MOS) is a perfect example. We’ve worked with them on campaigns for their Pixar exhibit, which was a limited time traveling exhibit rather than a permanent installation. What we found was that a sense of urgency and having limited time to experience the exhibit really helped boost ticket sales. We ended up using that sense of urgency for MOS’s summer campaign this year. The concept is that there’s so much summer, but so little time. I think that’s so brilliant because the idea that there is so much to do in the summer yet minimal time to take advantage resonates with so many people. Thus, we initiated this countdown concept of ‘100 Days of Summer’ and every single day, we displayed a new dynamic concept. It puts numbers to it, but really makes it even more actionable in a sense, because it evokes that sense of urgency in people where they will add MOS to their ‘must do’ list before the end of summer.
LBB> We talk about data driving creativity, but what are your thoughts about approaching the use of data in a creative way?
Sathvy> Personally, I think that the best, and most fun part about data analytics is the creativity aspect. It’s all about storytelling. To be a good data analyst, you have to embrace the creative side of the work and figure out how to take all this data that someone may not understand at first glance and actually create a story from it. If a client doesn’t understand what you’re saying, they are less likely to pay attention to your recommendation. One of our jobs is to showcase to the client why they should be paying attention in a digestible way, and how data supports your recommendation. I feel that people don’t often think of creativity beyond using numbers to tell the story, but then you’re left with “okay, what’s next? What can we do to improve upon this?” This showcases what we do at A&G, and why we’re different. A lot of data analysts might say “here’s the data, go run with it.” We take things to the next level by saying “okay, what do we do with it now? What if we tried this? How can we use these insights for the next project?”
LBB> What are your thoughts about trust in data - to what extent is uncertainty and a lack of trust in data (or data sources) an issue and what are your thoughts on that?
Sathvy> Trust in data is everything. If we don’t have data we can trust, we are making insights based upon a false story. One thing that’s challenging in the world of data analytics and in advertising specifically is understanding how much a campaign is driving success. When we show the client a revenue number, we emphasise that it’s a range and are honest with them that the real numbers are likely in between. There’s also this other concept of word attribution. Attribution is such a buzzword in the industry right now, describing the concept of understanding how much of your advertising is making an impact on sales. In reality, people might have seen an ad, and subconsciously, it might have had an impact on them. Then, at some point in the future, they might search up that brand. This is precisely why we still utilise out of home advertising, like billboards, even though they don’t drive direct revenue. The idea is that when you’re driving down the highway, and you see '100 Days of Summer Left,' it stands out to you. And then a week later, you might be thinking ‘what do I do with my kid today?’ You remember the billboard, and the Museum of Science comes to mind. When you go online and buy a ticket by Google searching 'MOS,' our data will attribute that ticket sale to Google, when in reality it should be attributed to the billboard. It’s very complex. There are so many ads being shown these days, so you really have to do something different and make yourself seen amongst millions and millions of ads that are shown to people every day.
LBB> What does a responsible data practice look like?
Sathvy> The most important thing for me as a responsible data analyst is to be transparent. A lot of times, people are afraid to show data that may show that the campaign was unsuccessful, or that there weren’t great results. The instinct to not show bad results is understandable, but it’s not really fair. Whatever the reality of the campaign, we have to be transparent. Clients are really grateful for that transparency, and that’s how you build trust with a client. You have to be able to discuss both the successes and the failures. Sometimes we’re so afraid of failure, but in reality, making mistakes actually helps improve future campaigns. This can be difficult because there’s a lot of sensitivity around an underperforming campaign. However, being able to acknowledge that, move forward and think about how to learn and do something differently next time is what helps us continuously improve.
LBB> In your view, what’s the biggest misconception people have around the use of data in marketing?
Sathvy> I’m going to answer this question a little bit differently, because I’d like to discuss the misconceptions around what a data analyst is. I often think that people think data analysts are all about numbers and that there’s really no creativity behind it. It’s actually the complete opposite. We have to really understand how audiences behave around those numbers and add that extra context. Nowadays, emotional connection and having an understanding of how emotions and human behaviour can impact data is critical. I think that’s often forgotten, but in our world, it’s all about human behaviour and human perception. Even when we talk about our own field of analytics, the goal is to really have a true impact on business. In order to achieve that, you not only need to change the behaviour of the audience, but also change the perception of the brand to get an audience to view them how they want to be seen. When you do that, that’s when you will really have an impact on behaviour. Those two factors in conjunction are what will create the largest impact for a brand.
