Consumer Behavior Data

What is Behavioral Data?

Consumer behavior data gives insights into how consumers interact with brands and products throughout the consumer decision journey. If demographic data and other kinds of identity data help companies understand who their customers are, then consumer behavior data reveals something equally important — what they do.

With increasingly personalized product offerings and the continued blurring of traditional market segment boundaries, companies need to know more than just who their customers are. Behavioral data gives companies new ways of understanding and segmenting consumer groups, helping companies both target the increasing number of consumers who defy demographics and identify emerging trends before they are reflected in other data.

Consumer behavior data is generated early and often in the purchase process, as consumers leave behind digital traces not only of financial transactions but of the decision making phase that precedes these transactions, as well as the interactions with manufacturers and other consumers that occur after purchase and consumption via online reviews and social media posts. By leveraging the insights contained in this data, companies can better understand consumer preferences and product affinities and better anticipate consumer behavior, helping them make better decisions about how and when to intervene in the increasingly complex consumer decision journey.

Consumer behavior data can be used in combination with demographic and consumer lifestyle data to help you get to know your customers as never before.

Who uses Consumer Behavior Data and for what use cases?

Consumer Behavior Data is used in product development, product management, marketing and post-sales customer service, and is vital for companies that are:

• Expanding geographically, particularly into unfamiliar markets
• Launching new products or services
• Customizing products or services for specific target markets
• Expanding their demographic reach
• Seeking to increase customer retention/loyalty

Understanding and being able to predict customer decision making, purchasing, and loyalty behavior helps companies tailor their product offerings as well as marketing and promotional activities to maximize both sales and retention.

Consumer behavior data is used to generate the recommendations that we are familiar with from online retailers and streaming services, in this case by finding patterns in purchase histories and product affinities. But you don’t have to be an industry giant to leverage the up- sell and cross-sell opportunities that consumer behavior data makes possible.

For example, you might know what your customers want to buy, but when are they most likely to buy? What are the most common triggers? What kind of interactions, via which channels, typically precede a purchase? Data showing how and when customers interact with your brand — via social media, first or third party websites, mobile apps, email marketing etc. — can guide decision making about the timing and personalization of your marketing interventions to maximize sales.

Companies can also use consumer behavior data to develop ways of reducing customer attrition or churn. Clearly, data on the timing and frequency of negative reviews or inbound contact with customer service can help companies predict the likelihood of customer defection and act preemptively. But consumer behavior analytics can also help uncover patterns that predict defection for the vast majority of unhappy customers who never express negative sentiment, thereby improving retention and the revenue it generates.

What are typical Consumer Behavior Data attributes?

Consumer behavior data has expanded beyond its traditional reliance on the RFM model (recency, frequency, monetary spend) to encompass a variety of information collected throughout the customer decision journey. There are many different kinds of consumer behavior data at different levels of granularity. Some of the most common include:

• Clickstream data shows pages visited, time spent, origin, and destination
• Loyalty program data including join date and activity
• Social media usage data
• Keywords scraped from online reviews or social media posts
• Product affinity data showing which products are typically purchased together or in sequence

How is Behavioral Data typically collected?

Consumer Behavior Data is collected from a variety of sources, including websites, help desks, CRM systems, and mobile apps. Some of these sources — purchase information, CRM and help desk data — are internal to the company, while others are external. Traditional market research like surveys and questionnaires also also yield consumer behavior data.

Surveys and questionnaires provide information about brand recognition and affinity during the initial consideration and active evaluation phases. Browser cookie tracking reveals exactly how consumers navigate your website, which features they interact with and which they don’t, and what paths lead to successful sales. While data on how customers arrive at your digital platforms helps evaluate and focus marketing expenditures.

How to assess the quality of Consumer Behavior Data?

Consumer behavior data should be targeted to your needs, up to date, and accurate. In some cases too much data can be as bad as not enough. Determining up front in consultation with a data provider what kind of data will best benefit your company can save costs and frustration in the long run.

Consumers are always consuming and always generating data, so you need to ensure that your data is keeping up. Only data that is updated regularly — or even in real time — will help you stay abreast of your markets. Frequency refers to the regularity with which data is collected, while latency measures the delay between collection and distribution. High- frequency low-latency data will keep you up to date. Data also needs to be accurate and representative in order to be relevant to your customer segments, and data providers must ensure that appropriate sampling techniques are being used to ensure accuracy.

Some things to consider when purchasing data:

• Completeness - are any important attributes missing? Rarity - is this data unique?
• Usability - how easily can the data be turned into insights? Volume - how detailed is the data?
• Latency & frequency - how up to date is the data? Accuracy - how accurate is the data?

How is Behavioral Data typically priced?

Consumer Behavior Data is typically sold either as a monthly subscription, which may or may not include a one-time enrollment fee, or in a single block, as with reference or historical data.

Other pricing formats are often given in CPM (cost per mille, or thousand data records), and can differ based on the geographic region covered in the data. For example, pricing may be different for EMEA (Europe, the Middle East and Africa) vs. ROW (rest of the world).

Many data providers are also willing to give out custom quotes for clients with special needs.

What are the common challenges when buying Behavioral Data?

Given the potentially unlimited scope of consumer behavior — which can include everything people do in their roles as consumers — and the vast quantities of data being generated and captured digitally, it can be difficult to know which kinds of data best suit your needs. Speaking directly to data providers is a good place to start.

Consumer behavior can also be quite volatile at times, and this volatility is reflected in the data. So it is important to make sure you’re getting the right data covering both a representative audience and the right time frame, up to and including the present.

What to ask Behavioral Data providers?

Questions you might want to ask your data provider include:

• What specific kinds of Consumer Behavior Data best suit my needs?
• How and how often is the data collected? How up to date is it?
• What format is the data supplied in, and will it work with my current enterprise software?
• Do you offer sample sets for testing purposes?