Customer information is gold dust for marketers. The more marketers know about their customers, the easier it is for them to understand what drives and motivates them. Using this knowledge, marketers can attract new customers with similar tastes and also keep existing customers engaged. In previous years however, customer information was hard to come by and marketers had to scramble up and down the country conducting market surveys. In contrast, marketers today are inundated with so much information about their customers – thanks to the internet – that the challenge now is to aggregate and use all that information in a way that benefits the brand.
Behavioral targeting is the answer to this challenge. Simply put, behavioral targeting is segmentation of the customer base based not only on their demographics (age, sex, location) but also on their online behavior and habits. Using all the information that is collected, marketers can draw a pretty accurate picture of what a person’s browsing habits are, how much time they spend on a website, what kind of products they are likely to buy and so on.
Considering how all this information can be used to the brand’s benefit and also that most of this information is pretty easy to collect, you would expect that a lot of brands are practicing behavioral targeting. Unfortunately, that doesn’t seem to be the case. A report published by digital marketing firm Razorfish shows that 76% of businesses don’t use behavioral targeting to amplify their marketing efforts. This exhibits a great gap in the potential of behavioral marketing and its actual implementation.
So how should a business go about putting behavioral marketing into practice? Well, the first step is to not only collect adequate user data, but also utilize the customer information that you may already have from simple web analytics.
Mining customer information
As described by the illustration above, the three major streams of user data come from –
- Active User Data – This is the information that the customer gives willingly to the website when he/she logs in. This could be a part of a compulsory sign-up or registration process. Depending on what each individual is comfortable with sharing, it is possible for marketers to get the person’s name, their email, their country/city of residence and in some cases even their phone number, all of which is extremely valuable data.
- Passive User Data – This kind of data is accumulated without the user’s active participation, based on the customer’s interaction with the website/app. One of the most popular means of passive data collection is cookie profiling in which the website’s server can associate the user’s computer/mobile with a specific profile and store information about browsing habits, Google searches, history, time spent on the website and purchases made.
- Mobile User Data – With the massive proliferation of mobile devices, there is an entirely new dimension of customer information that can be accessed. The most important data that can be gleaned from mobile users is geo-location which can be used to filter location-specific content to the user. Also, app analytics will provide you with even more information about the tastes, likes and dislikes of the user.
Most businesses would already be in possession of some of this data, putting mobile analytics and cookie profiling in place can get you everything else you require to give behavioral targeting a go.
How can brands put all this data to use?
So now that you’re sitting on a mountain of user data, you’re in a position to implement behavioral targeting. The most important components of behavioral targeting are –
- Creating customer profiles based on online behavior
- Defining the actions associated with each of these profiles
To understand how this works, let us consider an example. John Doe is a 25-year old male living in Mumbai who works as a copywriter in an advertising agency. Although he isn’t earning as much as he’d want, his income is sufficient for him to live a comfortable lifestyle. He likes reading, music and sometimes likes to cook. He has recently bought an Android phone and has installed a number of e-commerce apps, and is new to the experience of online/app shopping. He is also a pragmatist, doesn’t approve of lavish spending and likes to save money.
Based on these particulars and his online behavior, certain actions can be linked to his profile (and of others that resemble John’s parameters).
All the information about John is easily available if you have the appropriate means – his location (using geo-location), his pragmatism (based on his tendency to go for special discounted deals), his conservative spending habits (based on browsing history and items he peruses) and his recent start in online shopping (cookie profiling).
There are many, many more ways in which behavioral targeting can be used by marketers to provide an authentic and personalized experience to the customer. We’re only scratching the surface to shed light on the limitless potential of behavioral marketing that marketers and brands are yet to exploit.
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