Author: Christine Liu

Christine Liu is the assistant insights manager for Carat APAC.

Imagining what’s to come for makeup junkies in quest of progressively quickened paths-to-purchase.

5 minute read

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Not long ago, I uncovered a stack of Seventeen magazines from my teenhood: My prized possessions and authoritative beauty bibles from a decade ago! Every issue stood for each excruciating monthly wait for fresh content on the latest and greatest in cosmetics, for which I was willing to fork out from my allowance to receive.

A quick flip through the issues hit me with another realisation of how patient I used to be with getting dibs on makeup: There were dog-eared articles and ads introducing new makeup products, bookmarked until I happened to get into a physical store to test and buy them.

What a stark contrast to the magazine-eschewing, tech-reliant millennial I’ve grown into. It has become second nature to do a zippy self-source on Google for trending lipsticks, click on the image search tab for real-life user-contributed previews of my chosen lipstick, go straight to Sephora.com to verify my choice with others’ reviews, and cart out my selection immediately to receive it within the same day. I can’t help turning testy when it takes longer, or if a cosmetic brand I’m interested in is absent from the WWW, as if they’d much prefer swatting away my outstretched hand of cash.

RAPID ROUGE
It’s not just me: My hastened tendencies are habitual of most Under-30s, especially when it comes to beauty products: Euromonitor reports that digital channels have been essential to strong global growth of the cosmetics category, driven chiefly by the young, digitally-savvy demographics embracing makeup as an online hobby [1]. They are flexing their wallets obligingly for the clever brands who are paying attention to their demand for hyper-accelerated beauty discoveries and purchases in the digital arena.

Adding to that, the makeup industry is characterised by a proliferation of choice for the consumer’s incessant hunt for their ultimate “holy grail” products. The return to consideration after purchase could take mere minutes, enough time to swipe on a new bullet of lipstick and realise it looks different on your skin than it did in other people’s Instagram swatches. (Bummer.) The speed that digital platforms and innovations can offer to such a category is a godsend, and it’s a rare vertical where consumers have adopted and embraced futuristic upheavals so quickly and easily.

Live face filters powered by augmented reality have been a gladly-received response to this demand for swiftness, especially in the trial stage which is typically most time-consuming and what handicaps  the makeup purchase journey. L’Oreal launched a mobile app called Makeup Genius, which scans the consumers’ faces to impose a realistic, live reflection of what a wide range of L’Oreal’s products looks like on their own skin, as if the phone is a mirror. Sampling cosmetics can now be done anytime and anywhere, with the additional aid of product recommendations, and then bought instantly, all in one platform and sitting.

LOOKS by chat app LINE takes this one step further, enabling multi/cross-brand recommendations, trials and purchases, and Shiseido Japan’s Telebeauty face filters can be shown real-time during Skype calls, which presents opportunities for quick feedback from friends.

Of course, being able to test-drive the actual cosmetic before buying it would take the cake. Maybelline Singapore took a cue from that literally, teaming up with Grab to install beauty stations inside GrabShare cars, allowing consumers to order a ride where they can test products while getting to the next destination. Perfect for touch-ups on makeup-melting hot days, and solving the inconvenience of finding time for testing trips to physical stores.

PRIMPING PROSPECTS
It’s hard to see this need for speed slowing down anytime soon. Let’s peer into the marketing crystal ball and have a go at charting where this accelerated purchase journey is headed in 10 years.

Automated advertising that predict our product preferences is currently based on past purchases, but imagine that in 10 years it may be established from our actual usage instead, because the physical product can be tracked. Manufacturers are likely to realise that for cosmetics, the frequency of post-purchase use is a better indicator of re-purchasing than just the order itself.

For example, foundation bottles may be equipped with sensors to monitor usage and formula preferences, but disguised for consumers as a means for analysing their skin type or health, so as not to freak them out (L’Oreal’s Kerastase is already headed in that direction).

Also, with all minds on virtual reality and constant progress in that space, perhaps the technology will advance into a full sensory experience. Brands may just be able to stimulate textures and smell, shortening and improving the trial of cosmetics even further. Visualise being able to feel the effectiveness of a lip balm on demand—And hygienically too.

But hold up: As social parameters rapidly redefine, and technology permeates all forms of communication (think vacating offices and relying on video calls to connect, getting information from chatbots instead of salespeople, the future of social media as interacting with avatars in VR instead of a webpage), will we even need to wear physical makeup in the future, if no one will see our bare faces any longer? Perhaps we will be buying customised face filters and makeup for our VR avatars instead, which fits into the projected trend of accelerated purchasing of makeup—All it takes is a click to apply a full face of makeup to my cartoon self!

Perhaps we will be buying customised face filters and makeup for our VR avatars instead.

Obviously, the aid of technology can be a dream or a disaster. Delving into tech innovations just to be part of the industry trend, without careful consideration of whether it will improve the customer’s experience isn’t just a waste of resources, but can make a brand come off as gimmicky. Being a first mover may be tempting an accolade, but it should be less of a priority than making sure these visionary contraptions meet an apparent consumer want or need.

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References:

[1] Euromonitor Passport Beauty Survey: Evolution of Beauty Routine Becomes a Key Innovation Driver, January 2017

Photos:

Magazine article picture: Harper’s Bazaar 2014. Taken from https://rmsbeautyblog.files.wordpress.com/2014/08/rms-beauty_harpers-bazaar_september-2014.jpg

L’Oreal Makeup Genius picture: Taken from https://hautemakeup.wordpress.com/2014/08/07/loreal-makeup-genius/

Maybelline X Grab photo: Taken from @thesmartlocalsg on Instagram

L’Oreal Smart Brush picture: Taken from http://www.adweek.com/digital/loreal-made-smart-hairbrush-analyzes-beauty-habits-and-suggests-products-175350/

 

Christine Liu is the Assistant Insights Manager for Carat APAC.

Both gender and behavioural targeting can work, but it’s stereotyping that is the root of the problem.

5 minute read

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Behavioural targeting seems to have earned a golden rep of being the cutting-edge solution that runs closest to the human truth because it’s touted to be more inclusive by eliminating pigeonholing and bias, unlike the evil alternative of demographic (usually gender) targeting which is faulted for being backdated, lacking thought, and too rigidly segmented to entirely understand an audience’s motivations.

But…
1. Gender and behavioural targeting aren’t opposites, they don’t necessarily have to run in silos, and choosing the right targeting approach really depends on the nature of your business.

• There can be accuracy in targeting primarily by gender, if you know and can prove that people belonging to a certain gender truly do emanate similar characteristics collectively
• Behavioural targeting involves categorizing people into buckets too, and with categorizing there’s always the danger of over-generalising and failing to see the true picture

2. With either (or any other) targeting solution, blind assumptions and typecasting is the real problem at hand. There is no fixed approach to targeting and no shortcuts in research if you want to really understand how your consumers want to be spoken to.

WHEN CAN TARGETING BY GENDER WORK?  
If you know a product is largely used by a particular gender, and have research that confirms it (e.g. sales figures), it only makes sense to address your audience of that gender primarily, because it is the reality of your business. People belonging to a particular gender can have a propensity to share & champion certain beliefs, and to avoid addressing these gendered perspectives could mean missing out on connecting with your audience on an intimate, emotional level.

The famous Always’ “Like A Girl” campaign exemplifies this. For years, the maker of menstrual pads, avoided any blatant feminine cues for their very female audience, choosing to focus on communicating their brand’s value of ‘confidence’ only in a functional, product-focused manner (“With Always, you can play Twister confidently”). However, over time, their utilitarian approach soon became insufficient to fulfill the emotional engagement that younger females grew to appreciate from brands. Additionally, the functional differentiation between their products and those of competing brands diminished, deeming their product communications ineffective.

After thorough exploration to uncover what confidence personally meant to young girls, which involved social experiments, discussions with their potential audience, and surveys, they established that girls go through a confidence crisis during puberty. Compared to boys, girls’ self-esteem drops twice as much during puberty according to their study, because the expectation to conform to feminine stereotypes, like physical beauty and submissiveness, begins during this phase of their lives. They are taught that leadership, power and strength are not for them, but more suited to their male counterparts. And that boys should be raised not to be a girl, as if being female is less superior.

This led Always to create their  “Like A Girl” campaign that challenged and redefined gender stereotypes, both to the benefit of their business, and to society. Before the campaign, the expression ‘like a girl’ was mostly used in a derogatory way. In a post-campaign study, almost 70% of females, and also 60% of males, claimed that the campaign’s video changed their perception of the phrase ‘like a girl’ positively. There was also a higher-than-average lift in brand preference, and claimed purchase intent increased more than 50% among their target, showing that messages tailored for gender can be effective, provided due diligence has been exercised in thoroughly researching the audience to anticipate how the message will be interpreted.

When time and effort isn’t taken to dig deep into the gender-related perspectives and motivations of your audience, and to ensure that these views are representative, gender targeting tends to go awry. Marketers become inclined to complacently rely on what they think they know: Over-generalised gender clichés, whether it’s assuming the gender of their audience or the gender-related values that their target identifies with. This usually results in a patronising message that’s bound to draw negative flak for their brand… and that’s if luck is on their side.

Vera Bradley thought they couldn’t go wrong by backing their It’s Good To Be A Girl campaign with their own consumer research on women. To find out what females think is “good about being a woman in society today,” the brand interviewed 100 women on the street and turned their answers into the copy for their ads. The outcome was a campaign that highlighted handbags, shopping, and being the more deserving gender, as some of the best things about being female. The reaction was overwhelmingly negative—because Vera Bradley’s marketers were blinded by data and stereotypes, and failed to see that the consumers’ responses are ultimately still individual opinions, and to peg these to the whole audience of the campaign by using “we”, a collective term, makes it seem like all women identify with these views, which are also really quite overworked and stale ones in present day.

WHEN CAN TARGETING BY BEHAVIOUR WORK?  
Behavioural targeting as a primary method might work for products/services that have a psychographic, interest-based appeal. This may be why it works well as Netflix’s main tactic (they do utilise gender & other demographic layers; it’s just low on their hierarchy of data points), as TV content has much more gender-neutral appeal than aftershaves or lipsticks, for example. It’s only natural to de-prioritise gender in this case.

“Real behaviour” is a phrase commonly used to explain the benefits of using interest-based targeting over other strategies, implying that nothing cuts closer to the “human truth”, but let’s not be idealistic about it: At some level, these human behaviours and interests are boxed into categories too. This stage of compartmentalising is essentially the same fork in the road in gender targeting where your strategy could begin to take the wrong turn, because in categorising, there’s always the risk and potential consequences of overlooking the nuances within a sub-group.

In a Guardian journalist’s probe into Spotify’s “taste profiling”, he highlights that gaps exist in the understanding of their audience, even with the years of users’ behavioural data they have. It’s likely due to what their strategists decide on as implications of a certain category (e.g genre, mood, artist):

“Is someone streaming Michael Bublé lots in late December showing a propensity for crooners, or simply exhibiting the Christmas spirit? Is that user heavily playing the Frozen soundtrack a huge Disney fan, or the parent of a huge Disney fan?”

How close can we get to identifying the right context for every consumer each time (or even most times)? One trait could be attributed to a plethora of different reasons and implications when you apply it across a group of individuals, and it’s easy to predict the association incorrectly: just like Spotify serving me localised ads in foreign languages I don’t comprehend when I’m travelling. The reality of the context presents targeting opportunities still, for example to point me to local businesses or activities I would be interested in as a tourist, in a language I understand, and Spotify has overlooked that based on their over-generalised assumptions of my behaviour.  Multiply my experience with that of all the tourists in the world at any given time, and you can imagine the amount of ad wastage an oversight in behavioural targeting can result in.

OVER-GENERALISING IS THE ISSUE AT HAND, NOT THE METHOD OF TARGETING  
The effectiveness of using gender and/or behaviour to target your audience, really depends on the audience themselves. If you have a goal of fitting your ad strategy as close to your consumers’ preferences as possible, and on a personal level, it’s unreasonable and insensible to assume a fixed, formulaic approach to reach out to them.

As marketers trying to understand a massive group of consumers as personally as possible, we face constraints such as insufficient time and availability of information, and coping mechanisms such as categorising, labelling and making assumptions are a necessary evil. Where caution can be exercised is not to make blind stereotypes and broad deductions. But this doesn’t come easy: Great business acumen and intuition is developed through a personal motivation to go all out to understand both similarities and nuances of the individuals within their audience, even if it means questioning supposedly-reliable data and research. Tim Donza, Netflix’s ex-consumer insight director, offers similar guidance:

“What we want to do as marketers is connect with people and build brand love. We want to build those deep emotional connections so that our brands become friends and trusted partners, from now going forward. There are many of us… who are seeking that perfect algorithm or that perfect gut, that data that will really tell us what to do. A good and powerful Oz who can make everything we want for our brands.

But if you pull back the curtain there is really just people hard at work… we as marketers have to be disciplined in and avoid the temptation just to rely on data or just rely on gut.”