Audience data analyses require both quantitative and qualitative angles

I spend a lot of time thinking about all the KPIs that marketers and business leaders define for a company's success.

Businesses cannot depend solely on quantitative data. They need qualitative information to enhance and further understand the context.

The recent article published by Marcus Collins in Harvard Business Review reminded me of the importance of finding the right balance between quantitative and qualitative research.

I've encountered on multiple occasions when leaders look at marketing, sales or CRM data and see a particular product or customer doing well, they double down on that product or customer. They spend little-to-no time and effort understanding why that happened.

Quantitative numbers merely scratch the surface of behaviour; they're the consequence, not the full story. True understanding comes from delving into the how and why, empowering us to make insightful decisions. In the realm of business, quantitative analytics serves up hard data, like web traffic stats and product sales, offering a glimpse into patterns and trends. But it's the qualitative side that delves deep into the human psyche, tapping into subjective opinions and emotions that drive consumer behaviour. Yet, this side of the coin is often overlooked; it's where the real gold lies. From customer feedback to aesthetic preferences, qualitative analytics unveils the hidden gems that quantitative data can't touch.

From my experience, I've noticed that the biggest offenders and the team that ignores qualitative analytics the most is the e-commerce team. In e-commerce, decision-makers often prioritize numerical metrics, aiming for constant growth and setting goals based on hard numbers such as conversion rates, bounce rates, sessions, transactions, etc. Even when seeking assistance from external resources and other internal teams, the focus tends to revolve around boosting revenue, registrations, and user engagement metrics. However, qualitative data, which explores the underlying reasons for user behaviour, is frequently neglected in favour of quantitative measures, despite its capacity to provide richer insights. Questions such as why customers choose one product over another or why they abandon carts at the last minute require the collection and analysis of qualitative data.

I wish that more leaders spent time understanding the context of the data rather than just the results from the data.

Want to explore more examples highlighting the differences? Check this video.