Ahead of her session at VMF South Africa, Marketing Science expert Dimple Dinesh talks about the importance of data culture and measurement techniques
“It is essential for marketers today to determine the success of their business based on the right business KPI, such as return on investment, as opposed to using proxy metrics, such as social media likes, comments, or shares. The critical aspect here is to understand the difference between causation and not just correlation between two variables,” said Dimple Dinesh, Marketing Science Partner, Meta.
Having worked with a wide spectrum of clients across big and small industries, Dinesh discusses how marketers must measure impact and optimise their media mix. She also talks about the importance of data-driven decision-making and how marketers should encourage that culture.
Excerpts from the interview
Tell us about your role at Meta and what it entails.
My core job is to consult clients and determine the effectiveness of their business performance, such as driving revenue or profits.
I’ve had the opportunity to work with a wide range of clients across different industries, assisting them in making the right business decisions based on data. For example, it is essential for marketers today to determine the success of their business based on the right business KPI, such as return on investment, as opposed to using proxy metrics, such as social media likes, comments, or shares.
The critical aspect here is understanding the difference between causation and not just correlation between two variables.
How can marketers measure impact and optimise their media mix?
While advertisers measure for different reasons and utilise various tools, marketers use AB testing or attribution to estimate a channel’s impact.
But to understand the causation, which is the real incremental impact driven by a channel, marketers should use a brand lift study or a conversion lift study. The core idea should be to determine the incremental impact that a channel drives for a business. A mature advertiser would use a measurement technique, such as econometrics, to understand every channel’s impact and optimise its media.
Advertisers must realise which measurement study helps them to determine their key KPI of success. I recommend optimising the marketing mix and using the same technique across the board instead of running this analysis in silos for every channel. Every business would want to be profitable overall and not just for one channel.
How can marketing teams encourage a culture of data-driven decision-making?
Data is essential in decision-making and is the golden rule for all businesses. In the past year, due to signal loss, we have seen advertisers move towards building their first-party data infrastructure and utilising it to measure better data. It helps clients make informed decisions and increase profitability based on facts rather than guesswork.
However, data-driven decision-making should not end with running an analysis once or twice. It should be a continuous cycle. We should keep experimenting, learning, and applying knowledge on an ongoing basis. Econometrics is one such study that helps make decisions based on data.
It has been in the industry for years and is now modernised to run continuously and provide insights more frequently. Furthermore, it is also privacy-friendly and uses aggregated data. In the future, I would love to see many more advertisers embracing the culture of data-driven decision-making on an ongoing basis and utilising the advanced measurement techniques available to drive marketing effectiveness based on data and science.
And, of course, it’s always a good idea to set measurable decision-making goals to ensure that you’re moving in the right direction; after all, data is the king.
Tell us about your session at VMF ZA. What can delegates expect?
I’m going to speak about embracing the art of marketing science. It’s learning the keys to developing modern marketing mix models that accurately capture the value of your digital efforts and what the future holds for marketers, especially after the ads ecosystem changes and because the attributing value has become more difficult today.