The What, Why, and How of Behavioral Marketing [+ Examples]
Marketing, in essence, is about delivering solutions to those who might benefit from them.
Historically, marketers have had a difficult time using data to correctly identify and target their audiences. With minimal data to work with, organizations practices some less than ideal marketing practices: consumers are bombarded with unrelated ads, emails, phone calls, and other outreach that they inevitably ignore.
Behavioral marketing, however, is a robust method of gathering data on consumer behavior in order to segment and target audiences in a laser-like fashion. This type of marketing is focused on individual patterns of engagement and behavior in order to match specific intents, interests, and needs of the ideal market.
According to McKinsey, organizations that leverage consumer data outperform their competitors by 85% in sales growth and more than 25% in gross margins. However, the practice of behavioral marketing sometimes has drawbacks, particularly for the user — for instance, Orbitz used behavioral marketing to display more expensive hotels to Mac users over PC.
Here, we’re going to explore what behavioral marketing is and why it could make a huge difference for your business. We’ll also include examples of behavioral marketing segmentation and its performance statistics to help inform your decision on whether or not this method is right for you and your marketing goals.
What is behavioral marketing?
Behavioral marketing is the method by which companies target audiences based on their behavior, interests, intentions, geolocation, and other metrics using web analytics, cookies, search history, and other insights. By finely segmenting audiences based on specific behaviors or definitive user profiles, organizations can provide truly relevant content and offers rather than sending a general message to all audiences.
Data is incredibly valuable to marketers, and as companies continue building out massive information caches, they can get better at generating and serving up relevant content to consumers.
As marketing automation and machine learning technologies continue to improve, businesses can leverage their incredible databases to forecast consumer behavior even months in advance. However, data collection is a complicated and nuanced issue, and online privacy is becoming increasingly important as audience listening tools become more advanced.
Consumer data can be used strategically to pinpoint audience preferences and deliver relevant outreach. Businesses can collect consumer data to truly create a more enjoyable experience for their prospects and leads, rather than a more obtrusive one. Banner blindness — the consumer tendency to ignore any advertising they see as too aggressive — is mitigated by behavioral marketing because consumers will only engage with content they’re interested in, which is determined by their previous search patterns.
Keeping messaging and content individual-centric rather than channel- or product-centric is the most effective marketing automation strategy in combating banner blindness. Data, if gathered appropriately and used responsibly, can solve for needs on an individual basis.
Behavioral Marketing Segmentation
An important facet of the behavioral marketing method is thinly segmenting audiences. Consumer segments might be determined differently depending on your organization’s marketing goals and ideal market. However, there are a few common ways that companies split up markets:
This measure is often very accurate due to the sensitivity of tracking. Organizations can tell which continent, country, region, and sometimes even which building a user is located. This can help with local targeting — like selling the right type of clothing for the regional climate. Furthermore, you can also access device data to better understand how audiences are finding and engaging with you.
2. Visit data
This type of information tells an analyst whether a user is new or has visited you before. By segmenting visitors by number of visits, companies can offer higher-value options to repeat visitors, like better benefits or discounts that might push them closer to a purchase.
3. Benefits sought
Data on motivations and intent is gathered when consumers research products or services. Two unique users might appear to fall in the same segment in terms of their demographic or location, but differ greatly in how much they value various aspects of an offering.
4. Transactional data
This segment is particularly valuable — customers who have made a purchase are not only aware of your brand, but they are likely interested in paying for your another one of products, particularly if they were pleased by their initial purchase. You can collect data on the number of purchases, average order value, product category, and time of purchase to better understand your brand’s customer lifecycle.
5. Engagement level
Engagement is defined differently for different organizations, however, it is almost always positive when consumers are interacting with your brand. Data on consumer engagement implies that consumer trust, perception, and intent to purchase are increasing.
Behavioral marketing will often consider the occasion or timing of a purchase of engagement. For instance, there are universal occasions like holidays that may apply to the majority of customers, or rare occasions that are more irregular and specific, like a wedding. Beyond this, marketers can target segments based on certain times during the day they are likely to buy.
Behavioral Marketing Examples
The New York Times wrote a piece on Target’s intensive data collection practices in order to gather detailed profiles on their customers. Target analysts were able to determine their customers’ ethnicities, job history, whether they’d declared bankruptcy, whether they were pregnant, their political leanings, and a whole host of other “predictive analytics”.
The retailer wanted such intimate insights to better sell to their customers — which is convenient for the company, but also controversial in nature due to a lack of concern over their consumers’ privacy. Behavioral research like this could lead to products that are better equipped to improve our lives — so long as we’re comfortable with corporations handling all our personal data.
A smaller example of this is Twitter’s interest targeting — paid ads on social channels can be targeted to users based on their interests. Advertisers can choose from 25 interest categories and 350 subtopics provided by Twitter, and then let the social media platform publish your ad so only groups that are interested in that kind of content will see it. This can be even more targeted by selecting a geolocation or type of device.
Orbitz, as part of a controversial experiment, starting selling more expensive hotels to Mac users than PC users, since their research had demonstrated Mac users tend to spend more on travel.
While Orbitz sees nothing wrong with segmenting based on customer spending patterns, it’s certainly a controversial move, and one businesses should be wary of mimicking — especially since public concern is growing around online privacy and corporate data mining. However, Orbitz argued that the company isn’t displaying different prices to their customers — their customers could easily choose to rank results differently by price.
Zuji, an international travel site, creates personalized display ads to visitors based on their past page performance. Zuji uses past searches, user profiles, and number of visits to push personalized offers to increase the likelihood of conversions — they target only the most relevant users with personalized packages. The goal was to market to segments of just one individual based off their past behavior on their site, and by investing in this method, they generated a 100-fold increase in their ROI.
Netflix — the international media streaming and content creation company — has built its success partially on the strength of its business analytics. The software company recommends media through a service called “Cinematch,” which uses customer behavior, buying patterns, and feedback to best link users to clusters of content they might like. Netflix is looking to be a website that “adapts to the individual’s taste,” using their huge database and predictive algorithms to give their customers a delightfully personalized streaming experience.
Behavioral Targeting Stats
Lastly, we’ve compiled a list of behavioral targeting statistics to further demonstrate the growing popularity of behavioral marketing as a practice:
- Open rates increased by 56.68% and CTRs increased by 147% when companies used an interest based nurturing track.
- 72% of US adult internet users were concerned about the extent of information websites were collecting about them unless they were assured that the collected information was anonymous and non-personally identifiable.
- 86% of companies with high ROI reported that personalization made up 21% or more of their marketing budget.
- Businesses with a full or partial personalization strategy experienced revenue growth 78% of the time.
- 93% of businesses with an advanced personalization strategy experienced revenue growth
Ultimately, when done appropriately, behavioral marketing can be an opportunity for your organization to better meet your customers’ needs by using data on your audience’s behavior to inform your business strategy. However, it is critical that you are cautious when implementing behavioral marketing strategies, particularly with the rising concern of privacy for online users.
Originally published Aug 8, 2019 7:00:00 AM, updated August 08 2019