Executive summary

A common challenge to effective decision making in digital is the misconception that organisations need more data, or that having access to more data will solve the strategic and organisational challenges that limit decision making and hold back commercial impact.

But in truth, a lack of data is rarely, if ever, the real challenge holding back decision making and commercial growth.

In 2025, the E-Commerce data industry is estimated to be worth $25 Billion and expected to grow to $97 Billion by 2035 (1) with hundreds of software solutions available to organisations across data warehouses, BI suites and customer insight platforms (to name a few). Given the sheer size of the data landscape, it is extremely unlikely that a lack of available data is a genuine challenge facing organisations.

This begs the question; why do organisations believe they need more data and what are the real challenges they are struggling with?

The real challenge is not a lack of data – the understanding of what is happening, but the lack of understanding as to why it is happening – a lack of insight.

In this article, we examine how organisations conflate data with insight, and how a lack of insight limits effective decision making and investment in digital channels.

This article concludes by recommending that organisations stop focusing on the 'data' and rather focus on better defining the, customer-centric, questions that will allow for more effective decision making. This necessitates a shift in mindset from “organisation-first” to “customer-first”, but one that, if adopted, will lead to better decision making and greater commercial impact of digital investments.

The challenge

Organisations invest vast amounts of time, money and resources in data warehouses, visualisation and BI suites, marketing analytics, customer insight and experimentation platforms to name a few.

This is driving substantial growth in the E-Commerce analytics market with the value of the market estimated to grow from $25Bn in 2025 to £83Bn by 2023 (1).

But when we compare the expected rate of growth of E-Commerce data to the rate of growth in E-Commerce customer spending, we find that whilst the analytics market is expected to growth 200% to 2033 the E-Commerce market (i.e. customer spending) is only expected to growth by 75% in the same period (2, 3).

The rate of growth in the cost of data outstrips the rate of growth of the market it supports.

This highlights the challenge facing digital organisations; that the ever-increasing level of investment required by “data” is not delivering the promised commercial impact and is, paradoxically, limiting decision making in marketing investment and digital transformation programmes with organisations investing in 'more data' for the sake of having 'more data'

In reality however, the challenge is not that organisations are unable to measure what is happening (the data) but struggle to understand why it is happening (the insight).

Data vs Insight

Already we are encountering an important nuance in e-commerce analytics; that of the difference between data and insight.

These terms are often used interchangeably but they have different meanings, and it is essential for organisations and teams remain aware of the difference.

Data

The understanding of what is happening

The following are examples of data:

• The website receives 100K visits per month

• The website makes £250K per month in online sales

• We spend £25K per month in pay-per-click advertising

Insight

The understanding of why it is happening

The following are examples of insight:

• Website traffic has decreased 5% compared to last year due to an increase in cost per click for paid marketing on desktop devices that is reducing click volumes despite a consistent level of investment and click through rate.

• Online revenue has increased 3% compared to last year despite a consistent conversion rate, rather we have seen a 3% uplift in average order value driven through a 5% uplift in average item value but a 2% decline in average basket size; the increase in price due to cost pressures has increased revenue but at the cost of a reduction in basket size

• Our paid marketing spend is unchanged year on year but due to an increase in cost per click as a result of competitor activity we are seeing lower levels of traffic through paid channels

In each of the above examples, whilst data is a necessary description of what is happening, it is the insight that contextualises this data and informs subsequent decision making.

It is through the combination of both what (data) and why (insight) that commercially impactful decisions are made – in this case an increased focus on encouraging visitors to return.

The cost of failing to act

A perceived lack of data causes organisations to invest more time and money in closing the “gaps” in data, often through the acquisition and implementation of additional software solutions or substantial increases to investment in existing data architecture.

But the implementation of new software in and of itself does not create insight (as we will explore in our next article) and so the additional time and financial investments fail to deliver the expected commercial impact. This in turns results in the organisation losing faith in their data and degrades the value placed on data, this pressures decision makers to identify a need for “more, better data” and the cycle repeats again.

By failing to address this challenge, organisations enter a negative feedback loop that limits effective decision making, reduces impact and degrades the perceived value, and utilisation, of data within the organisation. Whilst placing ever growing commercial pressure on digital teams to deliver growth.

Organisations find themselves having to make ever-increasing investments in their data but never see the promised return on investment.

This is an issue made worse by the introduction of artificial intelligence which, rather than cutting through the data to produce insights, simply cause the negative feedback loop to spin faster; more data, more dashboards, more reporting but never providing the necessary insight to support effective decision making.

What you can do about it

A good rule for the creation of actionable, commercially impactful, insight is to shift your focus from producing data to asking the right questions.

In practical terms, organisations and teams should not focus on “knee-jerk” or short-term responses to challenges or commercial pressures, for example launching half a dozen changes to the PDP based on “best practice” or investing in more data for the sake of having more data. Rather, teams should slow down and evolve the need for more data into a focus on reaching actionable insights.

These insights must be customer centric i.e. focused on explaining a particular customer behaviour and should provide a foundation of understanding which can inform experimentation. A good framework for producing insight is to focus on answering a specific question, for example “why do 50% of users on the PDP not engage with product images? (see ’a practical example’ for more detail)

This will feel counterproductive as it is a slower process than simply changing elements of the customer experience or marketing strategy and hoping these changes drive value, but over time this approach – of building and responding to measurable customer insights – generates greater impacts in revenue and delivers a higher return on investment than short term “quick fix and hope” activity.

Outsee Analytics works with organisations to support this change from measuring what to understanding why and through the migration to this approach, organisations can move themselves out of the data tailspin and towards an always on, scientific, programme of commercial impactful experimentation; that we call the Growth Engine.

A practical example

Imagine a team tasked with increasing PDP conversion by 1%, perhaps due to rising PPC costs or stronger competitor activity. The team recognises the need for both data (what is happening) and insight (why it is happening). But without clear, customer-centric questions, they risk defaulting to “we need more data” and failing to generate impact

Instead, they should define the questions that genuinely shape PDP behaviour, such as:

• How does PDP abandonment vary by channel, device and customer segment?

• How much abandonment is driven by factors outside our control (price, delivery cost, stock availability)?

• What are the main sources of customer frustration on the PDP?

• To what extent do product characteristics (price, category, attributes) influence abandonment?

• How do competitors execute their PDPs, and where do they outperform us?

These questions focus on understanding customer behaviour rather than gathering more metrics. Most can be answered by combining standard analytics, heatmapping and survey tools.

• Take the question of abandonment caused by factors outside the team’s control. Insight here might require:

• Analysing how product price affects add-to-cart or conversion rates

• Surveying users to quantify abandonment linked to delivery or stock

• Reviewing lateral browsing when items are out of stock

• Examining PDP interactions in low-stock states

Through this analysis, the team may discover that low availability of key sizes drives around 15% of PDP abandonment. If products with less than 75% size availability show significantly higher exits, a targeted solution—such as prompting users to explore similar in-stock products—could recover even a small portion of this loss. Addressing just 1% of this issue would deliver a 0.15% uplift in PDP conversion, representing 15% of the total 1% target.

This simplified example shows how growth comes from targeted insight, not more data. By asking the right questions, organisations uncover specific, testable opportunities that drive measurable impact.

Conclusion

To summarise, organisations often lament a perceived lack of data as being the barrier to effective decision making and commercial growth, but rarely is this the case. Rather, these organisations are limited by a lack of insight; a focus on the customer that brings an understanding of “why” to the measurement of “what”.

Organisations that fall into this challenge find themselves in a negative feedback loop whereby no level of investment in data is ever enough, resulting in ever increasing investments in data but no measurable commercial impact. Over time this degrades trust and the of value of data in the organisation which results in loss of ground to competitors who always seem to be one step ahead.

Addressing this challenge is inexpensive but requires a change in mindset.

Organisations must learn to work slow and think fast, evolving the questions of “what is happening” into an understanding of “why it is happening”, making time for the necessary interrogation and analysis of customer intent and behaviour to produce detailed, and actionable, insights that deliver real commercial impacts.

This is where Outsee Analytics specialises, bringing the scientific method to digital analytics to empower organisations with a deeper understanding of why, to inform and lead action to deliver real, verifiable, commercial impact.

References

1. www.businessresearchinsights.com/market-reports/e-commerce-analytics-market-102447

2. www.businesswire.com/news/home/20250528045768/en/E-Commerce-Market-Growth-Trends-and-Forecast-Report-2025-2033-AI-Enhancements-and-Virtual-Fitting-Rooms-Revolutionize-Online-Shopping-Experience---ResearchAndMarkets.com

3. www.researchandmarkets.com/report/e-commerce