A Behavioral-First Mindset

Changing the way brands understand consumers

14 min read


The most successful brands build their marketing strategies from a deep understanding of the people they are trying to resonate with and reach. And for years, marketing research has provided brands with answers to their questions about what consumers are doing in order to gain this deep understanding of people. When this understanding is truly met, brands grow and innovate and remain relevant to their customers. But on the flip side, not all market research has been successful. And thus, some brands have made decisions based on market research that were ultimately fails. For example, did Colgate really think expanding into the Frozen Entrees was acceptable for its brand?1

Market research has been around for over one hundred years now. It started out with a desire to ask consumers questions. And today, consumer research still mainly relies on consumers to tell us answers to questions we have about their lives, their behaviors, and their actions. This type of insight is still very valuable, but it must be done right. And we believe asking consumers to recall their behaviors should be secondary to leveraging their actual behavioral data

With consumers’ busy lives paired with the complexity of the world we live in we can’t expect consumers to accurately recall what they did. Not because they don’t want to tell us the truth, but because with everything someone is doing, it would be hard for any of us to recall exactly what we did yesterday, let alone last week or last month, with precise detail. 

Fortunately, with the explosion of technology and the connected world we live in today, consumer behavior can be recorded in real-time, providing actual consumer behavior versus recalled behaviors. 

Table of Contents

What is Behavioral Data and Specifically Digital Behavioral Data:

Behavioral data could be described as any data set that describes consumer behaviors, which could include stated behaviors based on recall and collected through surveys. However, I’d argue that type of data is still survey data on behaviors, not behavioral data. 

True behavioral data is captured in real-time when consumers are doing it, without any recall or reliance on their memory of what was happening. Behavioral data is being captured all around you – think about smart devices, GPS/map software, loyalty programs, connected vehicles, and more. 

The type of behavioral data that I am focusing on today is digital behavioral data. There are various panels out there that capture consumers’ digital behaviors, tracking everything they are doing online, where they are going, what they are searching for, how much time they are spending, sites they are shopping, and what they are purchasing – ultimately painting a picture of the online journey and path that consumers are taking. Some provide more than others, and some even provide cross-device, in-person location data, or social advertising data. 

True behavioral data sets are permission-based, meaning consumers have chosen to opt-in and allow for their data to be shared. They do not rely on cookies, meaning it is future-proof. The data is longitudinal, capturing every click, every app open, and every search a consumer is making. 

These data sets are extremely large (terabytes and terabytes), they are unwieldy, and for the average marketer or researcher, may seem impossible to analyze and make sense of. Each line of the data represents a separate consumer event that was captured – a search, a click, a website visit, an app open, an in-person location visit, an ad they saw. 

In addition to just the digital events collected, the data often has many descriptive variables that accompany it. An event timestamp provides the order of events and how long someone spent in an app or looking at a specific page. When someone agrees to share their data, often a short sign-up survey collects key demographics or attitudinal statements that can be appended to the behavioral data. 

The data itself, while it may not seem insightful at first, provides a digital footprint for consumers which when analyzed, can help brands understand who these consumers really are. Not just what they are doing online but who they are as humans. What are their interests, what hobbies do they have, what keeps them up at night, what things are they buying online for use offline, and more? Behavioral data ultimately provides brands with a leg up on being truly consumer-centric and getting to know consumers better than anyone else.

Why Behavioral Data:

The average person spends 6 hours online every day. And today, there are over 200 million active websites and over 3 million apps available in the app store. And it does not stop there… over 2000 new apps and 250,000 websites are released each day!

We live in a digital world; everyone is online all the time. Traditional primary research would ask people to tell us about everything they are doing. While they may try, it would be hard to accurately recall everything they did even if it was just 5 minutes ago. 

Additionally, traditional panels continue to see an increase in bad data – whether that be bots, people rushing through surveys and not really reading them, or even the creation of the survey itself being poor. However, consumers are increasingly interested in signing up for panels that are easy and have a fair exchange. In the case of behavioral data panels, consumers are rewarded with fair incentives or other types of rewards like promotions and coupons in exchange for providing access to their data. The details of what they are sharing are very transparent, and most find it to be a very fair exchange. 

While traditional survey methods can provide a glimpse into consumers’ behaviors, it simply isn’t the most accurate way to understand behaviors. I’ve said it before, but at this point, it’s not really a choice. It’s our responsibility as an industry to stop asking consumers to recall behaviors that we know they can’t articulate. 

Leveraging this rich digital consumer behavior allows for a true understanding of consumers. It can help brands to extract insights to guide digital strategies, uncover how consumers are shopping and cross-shopping brands, keep a pulse on key competitors, and understand consumer research processes and shopping journeys. 

The ability to monitor consumers’ digital engagements with key brands and understand retention, loyalty, and social ad effectiveness in real-time presents unlimited opportunities. 

The Right Business Challenges for Behavioral Data:

Not all business questions are right for any one methodology. But many common business challenges brands come up against aim to understand consumers’ behaviors better. When this is the case, a behavioral-first mindset should be embraced. 

Some of the most common business challenges could be better answered and solved using digital behavioral data. 

Defining a competitive set and keeping a pulse on key competitors

Brand tracking has been around for many years and aims to track consumer perceptions and behaviors longitudinally. A typical brand tracking survey asks consumers about their awareness, current interactions, and future intentions with the brand and key competitors. It may also ask questions about brand perceptions and brand imagery. While consumers may not interact the same way digitally with all brands, ‘digital is not for me’, is no longer an excuse any brand should be using. 

Digital behavioral data can provide a glimpse into those who may be exploring a category or a specific brand but not admit that they are considering – the data provides upstream shopping and research that is happening, those touchpoints that are shaping and influencing future behaviors, that consumers don’t even realize are occurring. 

With digital behavioral data, a true competitive set can be revealed. You may not initially consider these other brands or categories competitors, but ultimately the behavioral data can show you they are competing for your customer’s share of wallet or time. Monitoring these brands, in addition to yours and your traditional key competitors, can ensure you keep a pulse on what is happening in real-time instead of waiting to see the impact happen in the market. You can observe overlap, switch, and even find new entrants before they make a splash in the market.

Digital behavioral data should not replace brand trackers but be sought to be the foundation of competitive and category insights. And when paired with a primary survey to capture those additional data points which cannot be derived from the behavioral data, a holistic picture of the consumer is gained. Connecting the behaviors that drive brand perceptions or connecting to some level of offline behavior can ensure your brand is showing up in the right place and resonating in the right way.

Define an audience

For years we’ve relied on survey data, asking consumers to tell us about their hobbies, their interests, and what things they like to do. But can you remember the last time someone asked you that? Did you know the answer right away or did you have to really think about it? Sometimes I feel like the things I like to do are not even the things I’m able to spend my time doing. So how does that help a brand know how to message directly to me?

The industry made a slight move to appending this type of information from third-party data sets. Much of which is modeled off where you live – assuming that you are like your neighbors. Maybe true, maybe not. These approaches increase lift by attempting to send messages to those who it will resonate with versus sending it out blindly to everyone. 

Profiling an audience based on behavioral data is mainly an untapped resource today. An individual’s behaviors are indicative of who they are as a person. Digital behavioral data analyzed in the right way can tell us what someone’s hobbies and interests are, what they are buying online to use offline, what types of media and advertising attracts them, and more. 

Knowing this type of information can guide messaging content and ad placement strategies. It can be appended to consumer segmentation and a brand’s target segments to better understand who they are, bringing them to life and revealing actionable strategies to reach them. 

Pinpoint how and where to reach your target customer

Ad agencies have access to many different sources of information guiding their digital ad placement recommendations. Many of these include the top websites overall or the top within a category. And many brands embrace an endemic digital marketing strategy placing ads in locations where consumers are engaging with their category. However, with the millions of things, consumers can do online, their engagement with your category might be so small that you’re actually missing them and ultimately wasting your media budget. 

With behavioral data, you can compare your target customer to a representative general population sample and understand those places online where your target is spending more time than the rest of the population. It also can guide strategy, uncovering lesser-known or hidden pockets where you can find your target customer. 

Uncover areas of confusion or opportunity areas where customers may be struggling to understand or find what they are looking for.

How many times have you gone online looking for something, scrolling through the search results and don’t see exactly what you’re looking for. Try a different search, still don’t see it. Maybe you try to click on something that could be it, but no. Go back search again. Get frustrated and go do something else. But you still don’t have an answer, so you try again later. 

Behavioral data can help you see these frustrating consumer journeys. What specifically they are asking for, what things don’t help them, and ultimately help you to curate new content that will answer their questions and guide them to your brand. 

Discover the consumer journey

Brands are all trying to build connections that will last with their customers – gain loyalty, be well-known, differentiate and excel above their competitors, and remain relevant overtime. Understanding the consumer journey and all the touchpoints along the way, including when they are not happy and consider switching is vital to showing up strong and maintaining and growing a brand. 

There are a million different ways to approach a consumer journey study. But why not start with actual observed behaviors? How consumers are interacting with your category, your brand, your competitors. How does that differ based on if that person is new to the category or has been with your brand for years? Or what else are consumers doing when engaging with your brand – let’s say they are in one of your stores, but they are on their phone. What are they doing? Checking your site online? Or a competitor’s site? Or looking for help on what product(s) to purchase?

Digital behavioral data can answer all these questions and more, connecting the dots on the activities and touchpoints that are occurring with your brand and key competitors. Paired with a survey or qualitative interview, gaps in the journey such as how they are feeling, what they are trying to accomplish and why they are doing the things they are doing can be layered in. 

Brands are always trying to stay on-top of what new trends or fads are happening and incorporate them into their innovation pipelines. But knowing what is going to be the next ‘hot’ trend is hard to uncover. Looking within your own category and keeping a close watch on your competitors is a must. But some also look to other categories for early-adopters and take cues from them. 

Leveraging behavioral data to watch for upticks in keywords can provide an indication of when the market is really starting to adopt or move on something. Whether it’s the next new cool ingredient, or package sustainability, or something else. Monitoring digital behavioral trends can ensure you’re staying in the forefront of foresights.  

Guide Search Term Optimization

How many times do you start with search versus going directly to a site. A search engine is an easy way to navigate to a website without remembering the exact site you’re looking for. But what if you think you know where you want to go but the results show something different… Did you switch your original plan? 

All brands, whether small or large, want to appear in consumers’ search results. Even if a consumer has already made up their mind where they want to go, if they use the search and see a brand or a product, the opportunity is there for the consumer to change their mind and click on anything that appears. Behavioral data can easily uncover traffic-driving keywords for brands and their key competitors. 

How to be successful with behavioral data:

TIP #1: Know not all behavioral data sets are the same… make sure you carefully evaluate and choose the right behavioral data set for your needs. 

Behavioral data sets are going to vary based on the device they are capturing data on, the size of the data, and what types of data they collect. It’s important to understand your objectives and your target audience before choosing a data set. 

In 2021, 85% of Americans owned a Smartphone and 15% of Americans were smartphone only Internet users.2 And globally in 2020, Internet traffic was reported as 51% mobile, 47% desktop, and 3% tablets. So, consumers are online using both desktop and mobile devices. 3 And what they are doing on each device may differ. Behavioral panels may specialize in just one device, or they may have both, and the best ones have a portion of panelists that are sharing their data on both mobile and desktop. 

With traditional market research, whether qualitative or quantitative, one may be ok with a smaller sample size – say 50 to 300. However, with behavioral data, there are so many different paths and touchpoints that we recommend a larger, more robust sample in most cases. If you’re looking for a niche audience and can get 200-400 people who have exhibited a specific behavior, that is enough to understand who those people are and what they are doing. However, if you’re looking for specific paths people take or want to drill down into various regional or other types of data cuts, a behavioral sample in the thousands is going to get you better insights and ensure you are not missing anything. 

You should also ask about panel representativeness. Now, representation can mean a lot of different things, so make sure you define that before you ask. Do you want a representative within a specific market? Do you want census representativeness? Do you care? Make sure you know the answers to these questions. If you do want representativeness, know all panels skew in some ways. Hence, the question is not ‘Is your panel representative,’ but rather, it should be ‘Can I acquire a representative sample that is analyzable from your panel’. 

The last but one of the most important pieces of information you need to understand is what type of data the behavioral data will provide you with. Some panels track only a certain number of websites, which can be useful to compare brands (if they have your desired sites) but lack the full journey of what consumers are doing online. Others track everything someone is doing online but may be limited to just browser-level data and what is captured in the url. Others may collect the background calls on a page to allow you to see things a consumer is interacting with on a page that are not reflected in a changing url – these typically include pop-ups on a page whether that be videos, advertisements, or even check-out carts. 

In addition to browser-level data, some behavioral panels will have additional behavioral data on consumers. These variables could include geo-location data – venue locations where consumers are visiting, app usage data – what apps consumers have and how often they are using them; in-app data – what people are doing in the app, products viewing, products purchasing, videos watched, etc. 

TIP #2: Ensure you have the right skill set, expertise, and tools to analyze the data. 

One of the biggest hurdles to date with embracing behavioral data has been the ability to wrangle, analyze it, and ultimately make sense of it. 

If you’re looking to purchase access to the raw data, you’re going to need to be able to analyze and work with it in raw form. From acquisition to cleaning and structuring to analysis. Excel or even SPSS is not going to cut it. You will need to be able to work with S3 buckets, data lakes or data warehouses, and parquet or JSON files. All these things will require the right tools and employees. 

You can also hire a company that is an expert in behavioral data and can structure and analyze the data for you. Providing a more manageable output to work with. 

Either way, having a strong analytical plan of what you want to do with the data is important. An analytical-minded individual who is familiar with the data dictionary and the results of the data is extremely important. It’s often hard for someone who has worked mainly with just survey data to grasp the possibilities behavioral data can provide and build out an analytical plan. 

Data platforms to analyze data are extremely helpful. But be careful because many of the data visualization platforms out there today are great for making charts and graphs to show insights. Still, they take a lot of wrangling of the data before importing as many of them are not built to efficiently analyze and visualize time-series data. There are, however, some great intelligence platforms that specialize in time-series data that can cut the data engineering and data wrangling time from weeks to hours. 

TIP #3: Don’t expect to analyze behavioral data like survey data – it’s different. 

With survey data, you have a finite list of options you’re asking consumers to choose from, or you may ask in open-end form and code them, but still, it typically is a manageable number of codes. With behavioral data you might have millions of different search terms, websites, apps, venues, etc. Manual coding could take days, maybe even weeks. Often pre-existing coding is scrapped, and AI models are built to assist with the coding, training the models to get better and better over time. With behavioral data, we must be ok with some gaps in the data, whether that be missing some of the websites or apps that are not as prevalent in consumers’ behavior or some false positives or false negatives appearing in the AI models. Over time, those working with behavioral data will train and improve these models, and they will get better. 

Another difference between survey data and behavioral data is the ability to exhaust your analysis. Behavioral data is so vast, and the possibilities are limitless – which makes it fun. But you also must have a plan of what you want to explore so you’re getting insights before the data becomes outdated and irrelevant to the decisions you want to make. My recommendation is to focus and hone in on answering specific business questions but leave some room to explore and expand beyond there when you find something interesting in the data.

TIP #4: Combine rich behavioral data with other consumer insights to have a holistic view of the consumer – but avoid redundancies. 

Behavioral data is great and provides so much rich detail on exactly what consumers are doing. And we believe it should be the first place any brand researcher, brand marketer, or brand strategist begins. But oftentimes, more questions will arise or more data will be necessary. 

First, consider additional behavioral data sources that can be appended to the behavioral data through a PII match. These include in-store receipt data, VIN numbers, magazine subscriptions, or even a third-party data set like Acxiom, Experian, or Merkle to help facilitate the creation of look-a-like models. This additional layer of behavioral data can provide more insight into how these individuals are behaving, where you can reach them, and how to resonate best with them. 

Secondly, consider a traditional survey or qualitative research to talk to these individuals and marry the behavioral data with rich attitudinal or explanatory data to explain the whys behind the data. Or if there are behaviors that might be occurring that are not captured in a behavioral data set, for example, signing up in-person or over the phone, those are behaviors that we should ask people about. But make sure you’re asking high-level questions and not trying to get into details consumers can’t recall. 

What we shouldn’t do is ask about things that we already know through the observed behavioral data. When asking consumers to recall how much they spent, the order they did something, or what keyword they searched for, we already know they are going to have a hard time getting us the truthful details. So rather, leverage behavioral data that already exists, and marry it with additional data to provide you with a holistic view of the consumer. 


We live in a digital world, which presents so many opportunities for researchers and marketing folks. However, it can also be scary to know how to leverage all the rich data that exists. And brands don’t want to waste their precious resources – whether that be time or money experimenting with things that won’t help them. But digital behavioral data is not new anymore; it’s just not being leveraged to its full potential. When it is used, it’s changing the way brands do things. It’s improving their understanding of the consumer, it’s helping to grow brand recognition, brand consideration, and brand loyalty.  



1. The 10 Biggest Market Research Fails of All Time (trendsource.com)

2. Demographics of Mobile Device Ownership and Adoption in the United States | Pew Research Center

3. Desktop and Mobile Internet Usage Statistics – 2022 – High Speed Internet


  • Lisa Speck

    SVP Behavioral Insights & Sales @ Qrious Insight. Lisa has almost two decades of custom marketing research experience on the agency side, holding various roles such as research project manager, account manager, quantitative methodologist, and analytics translator.