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The art of generating data insights (from an analyst/marketer point of view)

Hicham is the Head of Analytics at Algorytme, previously having worked as Director of Analytics and Reporting at The Economist.

Whilst the most advanced machines/tools will help gather, organize and visualize large datasets, they are incapable of highlighting the behavior that will lead to a marketing opportunity. Only an experienced person with advanced knowledge about a specific industry could generate this piece of truth.

Companies are collecting by the truckload and the rate of data growth is now exponential. In 2021, it was estimated that more data has been created in the last 2 years alone than in the entire previous history of humanity. Most experts agree that only about 5% of data is being used in a meaningful way. In other words, analysts and marketers have access to a plethora of information but find it challenging to generate insights.

Early on in my data analytics journey, I was not equipped to distinguish between data commentary and insight. I was adamant that making relevant, smart observations and writing about them was sufficient enough to understand what makes a target audience tick. I could not be more wrong! 

Gaining experience and working on multiple integrated marketing programs with different objectives and stakeholders with diverse skill sets led to questioning what factors affect the overall performance of a campaign. The accumulation of advanced knowledge within a specific industry made me realize that describing the data was only the first step to delivering actionable results. It's years later when interviewing for analyst roles that I realize that only a handful of candidates knew what insight really means. Most thought they understood the concept but when asked to define it and provide an example, they fell into the same trap I once did. 

So, what is an insight?

We know it's not a trend (sales increased last month compared to the previous month), nor a simple observation (click-through rate dropped by 15% in Q4). It's also not contextual data (our social campaign, leading to the back-to-school season in the US had helped drive additional revenue, exceeding the target by 8%) or a group of metrics put together (the bounce rate and time on site both exceeded industry benchmarks). 

A solid definition is offered by Oxford where it defines it as “the capacity to gain an accurate and deep intuitive understanding of a person or thing”. Applied to marketing, it's how marketers analyze and dissect an audience to comprehend how their habits, core values and rituals could lead to new strategic opportunities for an .

Thus, insight follows a comprehensive analysis and discovery phase. It's that golden nugget that will allow an organization to shift their messaging and/or lead to new strategic tactics. This combination only happens in the person's head. In fact, whilst the most advanced machines/tools will help gather, organize and visualize large datasets, they are incapable of highlighting the behavior that will lead to a marketing opportunity. Only an experienced person with advanced knowledge about a specific industry could generate this piece of truth.

In my experience as an analyst, generating an insight follows a 3 step process.

First, we need to describe and interpret the raw data we captured and organized. The goal here is to find outliers, anomalies and patterns we can use to support our insights (for example, users have consumed on average 3.7 page views per session, exceeding industry benchmarks by 38%).

Second, we need to understand what led this audience to show this level of interest. One way to do this is to identify the causes and relationships between the media strategy and excess content consumption (for example, tailoring and using different messaging over time in our social media campaign, particularly for female desktop users aged from 34 to 45 years old, has resonated well with this audience leading them to higher and rate).

Finally, we need to connect this behavior to a marketing opportunity (for example, the subscription rate increased by 3 percentage points when targeting this audience 3 times with 3 tailored consecutive messages on Instagram over a month period of time). Thus, we can build an audience with a similar profile and apply the same strategy on other marketing channels to see if it leads to the same or better results.

In conclusion, to make a difference as a marketer, you need access to organized data, develop the ability to follow paths and patterns and, finally, be able to use this advanced knowledge to make the right link between the findings and actionable recommendations.

This process, as simple as it sounds, requires a certain level of experience, a skill that is earned over time.