Bhuvi Gupta: How Marketers can both make money and save money via behavioural targeting

13 Jul,2021

Bhuvi GuptaBy Bhuvi Gupta

 

It’s often said half of the monies spent on advertising are wasted, you just don’t know which half. Before the advent of digital advertising this was true. I ‘d say that the vast majority of advertising was a waste and only a fraction reached the right audience, because marketers relied on high-budget, high frequency ATL campaigns to get mass visibility. This was because while behavioural targeting made sense in principle, it was near impossible to execute and marketers had no choice other than relying on demographics to reach potential customers. Hence, attributing marketing spends to customer acquisition always ended up being vague and immeasurable.

 

While demographics like age, gender, financial status are a precursor to behaviour, they are not a determining factor. Statements like ‘she doesn’t act her age’, ‘spendthrifts’, being mannish, ‘spinsterhood’ et al while used derogatorily have always been common and defined a larger part of the population than we‘d like to believe. Therefore, depending solely on demographics means losing customers, which may not even feature in the target audience. With gender fluidity, freedom and credit cards gaining acceptance, demographics have lost relevance even more as people can afford to now fit into which ever buckets they like.

 

With digital advertising demographic targeting should hence be used only as a filter. There is a wealth of information that digital advertising platforms like Facebook (via Custom and LookAlike Audiences) and Google (via Tag Manager) allow you to access that can help marketers to target consumers in more nuanced ways through their behaviour, personal interests and hobbies and life stage.

 

In 2019, P&G changed its targeting strategy from demographic based to a psychographic based. They called it ‘smart audiences’ and described it as “reinventing brand building from wasteful mass marketing to mass one-to-one brand building fuelled by data and technology. Based on a 1 billion strong customer database they defined up to 350 + new narrowly targeted audiences focused on the intersections of behaviours, mindsets and P&G products minus typical demographic information. Examples of these newly targeted audiences included ‘first-time moms’, ‘first-time washing machine owners’ etc. The move helped them cut $350 million from their advertising budget while increasing sales.

 

The caveat here is that a company the size of P&G has a wealth of first-party data that it can leverage to great effect. However, for smaller companies, this is just not possible. A similar way to reach audiences is to leverage third party cookies or lookalike” or “actalike” audiences offered by large advertising platforms (like Google, Facebook, Snapchat, and Pinterest).

 

Cookies to avoid the cookie-cutter approach

Bad puns aside, Cookies are trackers that are placed on a user’s computer by a website or application. These trackers collect data that is used to provide the user with a more relevant web-surfing experience. Cookies also store user settings, login information, and other useful information. There are two main types of Internet cookies: first-party cookies (like used by P&G) and third-party cookies.

 

First-party cookies are stored by the website and third-party cookies are created by domains other than the one currently being viewed. First-party cookies make a user’s experience on the website more streamlined, while third-party cookies streamline user experience across the Internet by serving relevant ads on other websites.

 

Third-party cookies can be used to personalize user experience across the Internet. For smaller companies that do not have access to first-party data, they must be used for retargeting and advertising.

 

Hence, focusing on behaviour and life-stage that are now disassociated from demographics like gender, income, location, age is key to measuring the Return on Investment for marketing. As technology evolves using tools like Artificial Intelligence and automation, personalisation to improve customer experience will become crucial. Behavioural targeting will be key to unlock the future. The sooner marketers jump on the bandwagon, the better it is for them and the customer.

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