Lean Data Strategy: How Much is Too Much?

In the year 2010, an individual embarked on a journey as the ‘analytics guy’ for the Retail Practice team at Demandware, which later metamorphosed into Salesforce Commerce Cloud. Their role involved partnering with various brands and retailers to pinpoint areas of growth through the lens of data analysis.

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At this early stage, many of these organizations were just dipping their toes into the world of e-commerce, with traditional retail ideologies heavily influencing their outlook on business expansion, seeping into areas like analytics and data handling.

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A Wealth of Consumer Behavior Metrics
The digital domain, however, had a unique advantage that was widely acknowledged yet not fully harnessed – data. E-commerce platforms were bursting at the seams with a wealth of consumer behavior and transaction data, an area where brick-and-mortar retail always faced challenges.

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This led organizational leaders to resemble eager children in a candy store, frenziedly grabbing any and all data they could get their hands on with no thought given to risks, ethical personalization, or other facets of this goldrush.

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This resulted in the accumulation of ‘fat data’ cluttering dashboards, emails, and presentations, weighing leaders down in a murky pool of ‘data muck’. Rather than empowering them, the data often drained their energy.

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By the time 2023 rolled around, brands found themselves forced to transition over to Google Analytics 4 (GA4). This ‘capture everything possible’ mentality seemed to be making a resurgence, but with a slightly different flavor. Digital leaders were viewing this as an opportunity to revamp their data capture strategy and rectify past mistakes. A critical question arose – how could brands be guided in understanding what to track and feeling confident in their decision?

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Is Excessive Data Valuable?
In the current scenario, there appears to be a slight shift in attitude towards data, a change for the better. E-commerce teams are fond of data, sharing numbers, reports, and charts via emails and collaboration tools regularly. Accordingly, these organizations have given birth to internal ‘data factories’ that churn out charts for both one-off studies and scheduled reporting.

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Yet, the question remains – is some degree of data collection unnecessary, potentially causing confusion and adding unnecessary complexity? Digital leaders desire decisions rooted in substantial hard data. While some view data as a means to reinforce intuition, others welcome the challenge it poses. Managers ought to ask themselves four crucial questions about their data to ensure that it pushes the organization forward rather than creating a quagmire of ‘analysis muck’.

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Ask the Right Questions
Firstly, are they asking the right questions? Rather than indiscriminately collecting available data, managers should focus on gathering the information that will aid in decision-making and business operations. Secondly, does the data tell a story?

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Raw data is typically unusable and needs to be transformed into coherent information that can narrate the current business context. Thirdly, does the data aid in predicting probabilities and preparing for future events? Finally, can it answer the ‘why’ behind events, a question often requiring intuition, judgment, and qualitative data?

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As the collection and processing of data become easier, e-commerce leaders and managers must remain mindful of the operational burden and cognitive overload that data overload can bring. The mantra should be to stay lean and move quickly, avoiding the treacherous terrain of data muck.