I came across the above illustration by Gapingvoid a while ago. The more I think of it the more I’m able to relate it with some of the ways brands and agencies are going wrong with collecting and using data sets.
Data is usually piled up on DMPs without having a defined set of tactics on why it is being collected in the first place.
Below is my take at trying to visualize the Gapingvoid model step by step with a typical problem a brand selling both online and offline would face on an everyday basis:
Data: Customers in certain demographics are keen on buying my brand’s product.
Information: Customers are more likely to buy my products online on the brand.com than offline.
Knowledge: Customers are landing on brand.com when shown display ads.
Insight: Customers are more likely to buy my products online when exposed to a remarketed display ad.
Wisdom: Most likely display ads are probably not the only medium customers are exposed to. Hence, we need to identify all the channels that are having an impact on the website sale.
Impact: Offline and online data sources combined now provide a better view of the channel impact on sales.
With every step in the above scenario, the marketer was a bit more informed about the consumer’s transition towards a sale. This information would have been in-correct if the marketer had only looked at website data as a single source of truth.
This is where building insights teams will prove beneficial for brands and agencies alike in the long run.
Why does building an insights team help?
Investing in identifying the problem:
Usually, companies invest in building data teams and technologies as the first step. This first investment should ideally first towards building a team that defines the strategy and problems that data models would help solve.
This can generally be achieved by upskilling the team members who have a keen interest in data and insights, who are keen on taking cross-team function and are clear communicators.
Not having fragmented teams:
Different teams are usually working in silos without really being aware or provided enough information on why and what data sets are important to help them achieve their goals.
Having an insights team will help provide clear tactics to all the relevant teams where a data set can add value. This value can be achieved by communicating only data sets and insights which are relevant for a certain team.
Not having fragmented team goals:
And finally, different teams are working on reaching independent goals, whereas the data should ideally help identify a common thread.
This common thread would be the insights team that would essentially help synchronize the efforts and provide required data, insights, and tactics which are relevant for respective teams.
Consumption of data sets can be simplified within brands and agencies when you have a dedicated insights team providing key value to different teams internally. This in return will help avert all the confusion that generally arises around data sets.
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