Marketing Decision Making: Use of Data versus Intuition

Marketing people rely more on their intuition than they think, however they describe this decision-making as data-driven. This raises all sorts of questions such as: Do marketing people realise they are as irrational as their consumers are and for which types of marketing decisions do they use their intuition? Using interviews with 13 executives representing several business sectors in the Netherlands I looked at how data and intuition are applied in marketing tasks.

Data without numbers or facts

There is no doubt among the interviewees about the effectiveness of data-driven decision making (DDDM). This is also supported in academic research, for example an often cited academic study (1) concludes that DDDM generates higher market value and productivity. However, what is a data-driven decision? And how can you ascertain that you just made a data-driven one? Unsurprisingly, when asked for a definition they refer to DDDM as making each decision based on facts and numbers.

At the same time, this is not the complete picture. The executives say that you do not need data to describe your decision as data-driven. Huh?! The executives refer to circumstances without any quantitative data. Observations of consumers in a UX lab or the views of a small group of colleagues are equally considered as data. As one marketing executive puts it: “I learnt that if you speak with 5 people in an unbiased way, test, engage people, present them a solution to a problem, then with 80 to 90% certainty you get the same outcome as in case of a quantitative research”. Also, when several scenarios are discussed for example the impact of a price increase on consumer demand, the structured trade-off of these scenarios is viewed as data-driven. And if everyone in the meeting room has agreed with the assumptions underlining the scenario executives think they are doing things in a data-driven manner. Making the decision without data does not disqualify decision makers. Instead, marketing executives rely often on their experience and intuition. DDDM mirrors the transformation of experience and intuition into data. One analytics executive said: “What always was in the heads of people, is now entered into systems and used to improve management of business”.

Definition DDDM

There is no clear answer in academia either what DDDM entails. The above mentioned study references to DDDM as “business practices surrounding the collection and analysis of external and internal data”. They rely on 3 survey questions measuring the availability of and dependency on data. However, the availability of data does not explain why one organisation is using more of the data and is more successful than another one. McKinsey estimates that while 90% of the digital data ever generated in a period of 2 years, only 1% of these data were analysed (2). DDDM is not about having or actually using data, but the awareness that you should use data for marketing decisions and make an attempt to leverage IT systems.

DDDM can be defined as a mindset where one uses data and where data’s importance is reflected in the culture and processes.

One interviewed CEO said: “There are all sorts of approaches, but it really is in particular about the awareness, no, being aware that you base your decisions solely or almost completely on well-grounded material.” It is difficult to determine which data was used for a marketing decision. Instead, I suggest to define DDDM as a mindset in which you intend to use data and look at specific behaviours that describe how marketing managers searched for data to support their decision. In an article together with academics from the Universities of Alabama and North Texas I formulated a range of behaviours that mirror the mindset of marketing decision makers for DDDM (3):

1. posing critical questions;
2. asking where the data / facts / numbers are;
3. urging others to use data for decisions;
4. conducting research;
5. letting the relevant data lead oneself to a specific topic;
6. and having the will to understand that data may lead to different conclusions than a priori assumptions.

Marketing decisions are not made in isolation. First of all, they depend on the data and information systems that are available. But these do not explain all of the performance. In my interviews and academic literature I found many aspects that drive the level of data-driven decision making that will then result in all sorts of consequences. In summary, IT systems, data availability, the external environment and organisational factors influence the way the marketing department interacts with other departments. The marketing decision is further influenced by characteristics of the individual decision maker and will depend on the marketing task at hand.

Accepting that a decision could be data-driven without any data at hand opens up a scala of situations when making marketing decisions based on intuition and experience is a good thing, and maybe even better. In the interviews executives indicated several marketing areas when making decisions based on intuition or experience is seen as effective. Said differently, these are moments that marketing people do not search for data but rely more on their intuition instead:

To introduce a new, bold proposition

The new proposition is very different from others on the market. These are moments that define true marketing leaders that build a vision and dare to create something new. When existing methods and data cannot demonstrate that there is a consumer need for a product, but the marketing function believes they can serve consumers well. An analytics executive phrased this: ”Data may say A, but if you think B will give a disruptive position, you do not let data make the decision”. A marketing director added: “As a human being you can see all kind of connections. The end goal is to understand human behaviour, sometimes you need a conversation rather than data.”

To drive an objective that is complex to measure

An analytics executive gave the example of an activation event at a pop concert. There was a belief that the activation would attract a new, younger target group. However, it was a difficult to proof in advance how this activation would contribute to the main goal of strengthening the brand image.

To perform operational marketing tasks

These are tasks that people carry out efficiently without data or systems. It is efficient in terms in time and budget to perform these routine tasks provided there is limited risk. Interviewees give the examples of deciding on the look and feel of a magazine advertisement or judging if the packaging colour communicates the flavour of the new product well.

To set firm objectives and strategy

Many interviewees say that decision making at the top of the organisation is less data-driven because topics on the board table call for a diversity of criteria. Strategy setting is challenging in highly dynamic and ambiguous environments. As a result, it could be based on personal perspectives as opposed to consumer research. Executives feel such situations cannot be avoided as they think consumers cannot express their deeper needs accurately. There seems to be an inverted U-curve of DDDM against a horizontal axis that runs from operational to strategic marketing decisions.

To make a judgement call between conflicting data points

An analytics executive explained that when different data are in conflict with each other, their organisation spends too much time trying to explain differences. The data may come from different data sources for example, internal financial data versus consumer research report. In the end, a conclusion needs to be made. Though data are used, it is diffuse how one reaches a conclusion.

To maintain the profit level for the proposition

One executive explained that a significant minority of their organisation revenue is derived from undifferentiated services in a non-strategic business unit. The organisation decided to take an opportunistic approach and run the business without investing in research and data. In this manner the organisation remains profitable and operates successfully on the short term.

To launch on the market rapidly

Sometimes it is more important to get the product to the consumer fast than getting the proposition right. A marketing executive prefers a minimum viable product rather than knowing everything in advance while attempting to mitigate all kinds of possible risks. Competitive pressure might be high. Or executives feel so uncertain about how consumers respond that no further agile experiment or research will bring the data they need.

To give people the feeling they are being heard

In these situations obtaining commitment is more important than being right based on data. A marketing executive said that being right is not so much based on data but on human interaction. Data may be less important than giving people influence and building a relationship.

In summary

In this article I explored the balance between data and intuition in marketing decision making. Although marketers claim to make data-driven decisions, they often rely on intuition and experience. Interviews with 13 Dutch executives reveal that what is labelled as "data" frequently includes informal inputs like their personal observations or team discussions, not just quantitative data. My suggestion is to define data-driven decision making (DDDM) as a mindset where one uses data and where data’s importance is reflected in the culture and processes. Such a mindset is reflected in behaviours such as posing critical questions, urging others to use data for decisions, and letting the relevant data lead oneself to a specific topic. DDDM in marketing occurs in a context of the external environment and organisation factors, but is also driven by characteristics of the individual decision maker and the marketing task at hand. There are a number marketing tasks when executives find intuition more valuable than DDDM. Human judgment may outperform DDDM especially when speed, ambiguity or creativity are key.

Sources

1. Brynjolfsson, Hitt and Kim, Strength in numbers: How does data-driven decision making affect firm performance? (2011)
2. McKinsey, Straight talk about big data (2016)
3. Berkhout, Bhattacharya, Bauer and Johnson, Revisiting the construct of data‑driven decision making: antecedents, scope, and boundaries (2024)

About the author

Constant Berkhout works at the crossroads of Shopper Psychology, Data Analytics and Retail Strategy and is author of three books:

Retail Marketing Strategy, Delivering shopper delight

Assortment and Merchandising Strategy, Building a retail plan to improve shopper experience

The Retail Innovation Toolkit, 42 category management tools for growth