Koen Pauwels
Professor, Ozyegin University, Koen Pauwels

Slow brand evolution versus quick online interest – what does it mean for brand marketers? A 2013 study by Koen Pauwels and Bernadette van Ewijk, Do Online Behavior Tracking or Attitude Survey Metrics Drive Brand Sales? An Integrative Model of Attitudes and Actions on the Consumer Boulevard offered revolutionary insight to answering that question. The study focused on data collected from six brands in over 15 categories throughout an eight-month period. It provided a new understanding to the consumer journey in the digital age. Co-author of the study, Koen Pauwels of Turkey’s Ozyegin University, talks to Content Science Review about consumers’ habits, the volatility of online behavior, and brand loyalty.

We were fascinated to read in your study that the pace of the Internet and online interest is so quick, yet brand attitudes evolve slowly. Do you predict this duality pattern will change?

It all depends on where consumers’ habits were formed, which are typically early in life. My own (and earlier) generations formed our habits offline and migrated them online. I firmly believe that we will continue to only slowly change our mind (and heart), while we have learned to quickly click on new links online. In contrast, the new generations of digital natives are forming their habits online. This can very well mean a faster change in attitudes. For instance, my kids get exposed to a new videogame online, download it right away and devour it within days, and then move on to a new challenge. What does this mean for brand loyalty in future generations?

Where do you think online content comes into the decision-making process for consumers? Did your findings evaluate social platforms and whether the medium where the information is gathered plays a factor?

Most definitely online content matters for some consumers in some categories. In mature markets, most people look at online content for high involvement products such as cars and smartphones. However, a few also do this for products that induce less involvement in the general population: e.g., cherries or yogurt. This means that online content is generated by only a small fraction of the (potential) consumer population – so it is important to realize it is non-representative and likely biased (that is, the opinion of these online content providers does not represent the average opinion). However, our research finds that even in grocery market categories, the online activity of this small fraction explains and predicts brand sales changes in the full country. We give two explanations:

  • A substantial number of consumers may not actively post stuff online but get exposed to the online activity of the small fraction (e.g., online reviews, complaints).
  • Changes in the online activity of the small fraction represent similar changes in the wider population (just as online word-of-mouth can act as a proxy for offline word-of-mouth).

We did not split out results by online platform. I can speculate that people rather use Twitter to complain (as they might expect a response from the company), Facebook to boast about purchases, and Instagram to integrate brand visuals.

What is the one thing that surprised you the most about the study results?

I did not expect that online metrics would explain sales for mundane grocery items such as dairy and salty snacks. Survey-based attitudes are very powerful in explaining brand sales in these categories, but the online activity of a few consumers still added different information that helped us explain sales changes.

In your study, you propose a model of consumer interaction as a “boulevard” of fast consumer actions (measured by behavioral analytics) and slower moving attitudes (measured by surveys) and quantify how specific marketing actions can improve both types of metrics. Is there a universal consumer boulevard?

No, we should design the consumer boulevard for every category and even every brand – even if the metrics are the same, their impact on brand sales will differ. The socioeconomics of consumers probably matter when it comes to Internet access, for example. But we can also investigate more subtle changes. In another study, we find much higher sales effects for brand love in a mature market where the product is cheap compared to average income than in an emerging market. When you are rich, it is easier to act on your love for the brand.

Please explain your profound finding that overall, online behavior metrics excel in sales explanation, while attitude survey metrics excel in sales prediction.

Online behavior is very volatile, with attention growing and waning fast for specific memes (e.g., the black/blue or white/gold dress) and for brand’s social media campaigns. One week you are up, one week you are down (e.g., because your competitor did something cool online), and this does explain weekly sales changes. However, unless these online activity changes translate into attitude changes in the broader population, they are mostly noise and don’t help you predict brand fortunes several months out. Attitudes change slower, but have more predictive power. It appears we are fast to click on new stuff, but slow to change our hearts and minds.

How do you think content marketers can apply the data from your study to a client’s needs? Could these behaviors be applied to other industries?

The study helps them show how online shared content can increase sales performance and get reflected over time on offline (survey-based) metrics of brand health. Yes, I see no reason why this would not apply to other industries.

Explain to me your notion of content metrics as “toll booths” and what that means within the online customer journey?

Social media experts are often reluctant to have the results of their activity measured in sales numbers. Their mantra: the brand should not ask what the consumers could do for it (e.g., buy more, refer to friends) but it can do for consumers (e.g., excite and connect consumers to engage with and about your brand). That is partially correct, but if you are going to spend a lot of time (and even money) on such engagement, the outcomes should be tracked to compare campaigns and learn what can be done better. Metrics are ‘toll booths’ that indicate the content’s effect is in the right direction, months or even years before you see sales increase. In other words, ask both what you can do for your customers and what your customers can do for you … and increasingly for each other. Co-create and share content that helps customers connect with each other and the brand, and also track the effects on this on your brand’s performance

Based on your research, when a brand begins to map out their customer boulevard, what’s the first thing they should do?

Think through how (segments of) consumers get exposed to and interact with communication about the brand. Think like a person interested in your category, try getting information online and try buying your brand! Google gave us the ‘Zero Moment of Truth’ where people get exposed to your brand and its content before they are even in the market (e.g., by hearing social media buzz or watching BMW Films). Procter & Gamble gave us the ‘First Moment of Truth’ where potential customers observe you in a buying situation (e.g., on the retail shelf). Finally, the ‘Second Moment of Truth’ (also coined by P&G) is when you experience the quality, get (dis)satisfied and express your opinion – now increasingly online.

Key Takeaways:

Based on the online behavior metrics that came out of your study, what is one content action item you would you recommend to a brand wanting to increase their online presence?

Think about how to increase the net effect of your content. For example, in integrated marketing communication, the interplay between the metrics is key:

  • Online and Offline – Aim for content that is not just shared online but also easy to remember and discuss offline.
  • Within Online – Aim for synergies between earned, owned and paid media; create and share content that gets people to your website, have them click through more on your paid ads, and so on.

The Authors

Content Science is a growing content strategy and intelligence company and the publisher of Content Science Review. We empower digital enterprises for the content era by taking their content approach to the next level. Customers of our professional services and one-of-a-kind products (such as ContentWRX and Content Science Academy) include the Fortune 50, the world’s largest nonprofits, and the most trusted government agencies.

Koen Pauwels is a Professor of Marketing at Ozyegin University in Istanbul, Turkey. He is also the co-author of the study, Do Online Behavior Tracking or Attitude Survey Metrics Drive Brand Sales? An Integrative Model of Attitudes and Actions on the Consumer Boulevard

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One thought on “What Drives Brand Sales? A Q&A with Marketing Researcher Koen Pauwels

  1. Extremely useful insights. For me, these findings stress the importance using the right data (behavior analytics, social analytics, surveys, etc.) in the right way at the right time. If you’re trying to change brand attitudes, it’s not going to happen overnight. If you’re trying to boost incremental sales, social data can be more useful than we once thought. Great stuff.

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