Beauty Consumers Desire Assistance from Virtual Beauty Advisors


Automat, a company specializing in AI-driven conversational marketing, has released a market research report titled "Virtual Beauty Advisors Reach Tipping Point: Decoding consumer needs and opportunities for beauty brands." 

Automat commissioned the study— with consumer research company Wakefield Research—in order to "illuminate consumer shopping experiences and attitudes regarding beauty purchases, explore the extent to which technology influences those purchases and identify areas of unmet needs that messaging experiences can help address."

The study was conducted between May 11–23, 2018, and surveyed 1,500 U.S. female beauty consumers between the ages of 18–65 with a household income over $40,000. Additionally, the survey respondents were mobile phone users who have Facebook messenger installed on their smartphones and who have made a beauty purchase within the last three months. 

Findings from the study include: 

  • 70% of beauty consumers are overwhelmed by too many beauty product choices and 63% of consumers are confused by beauty product claims;
  • As a result, over two-thirds of beauty consumers perform extensive online research before making purchases. The most common purchase behavior is researching online and purchasing in a store;
  • Approximately two-thirds of consumers prefer to be left alone while shopping.  Surprisingly, 71% of consumers use their mobile phones to do additional online research while standing at the shelf.  As such, online and offline purchase behavior becomes deeply intertwined;
  • Nearly half (49%) of all respondents said that they would definitely use or likely use a virtual beauty advisor when shopping for beauty products whether online or offline; and
  • Virtual beauty advisors especially appeal to the young, digitally-engaged, frequent beauty purchasers that beauty brands want to reach the most as part of their digital strategies.

Global Cosmetic Industry caught up with Andy Mauro, CEO and co-founder of Automat, to learn how brands can make the purchase process easier, how consumers' emotions are playing into the mix and what challenges arise when dealing with tech-savvy Millennial and Gen Z consumers. 

Global Cosmetic Industry (GCI): As the study shows, brands are working hard to reach digital consumers via mobile, social media, augmented reality (AR) and virtual beauty advisors. What could be a potential next approach to help make the purchase process easier?

Andy Mauro (AM): At Automat, we see a few trends on the horizon. The first one is that marketers will shift toward a more transparent and efficient approach to personalization. Conversational AI is becoming a core part of every marketers' skillset and technology stack because it allows brands to directly ask what they need to know from consumers, instead of monitoring their online behavior. But this is not enough. Beauty brands are waking up to the fact that conversations with customers must be standardized on a single technology platform. This will allow consumers to start a conversation via voice in their home, and to continue it via chat on their mobile devices while in store. Omnichannel extended to conversational AI if you will. It’s also important to make sure that all valuable first-party conversational data is stored in one place so it can be used across all your marketing efforts. 

Secondly, we see a trend towards synthetic influencers (SI’s). Obviously the most famous of these right now is Lil’ Miquela, but we see SI’s as filling a void in the current digital marketing space. It’s hard for consumers to engage with a disembodied brand. It makes a lot more sense to follow, talk or chat with a persona that lives on the platforms where we spend time, like Instagram, Snapchat and others. 

We expect brands to develop SIs for their social feeds, and then to make them interactive on voice and messaging channels using conversational AI. This will make purchasing easier for consumers because they’ll have a relationship with an SI who remembers past conversations, knows their skin type and makeup preferences, and can make smart recommendations that will feel like they’re coming from your friend who knows everything about beauty instead of from a big corporation. This is the culmination of many years of both technical progress but also a real change in terms of how people interact with brands digitally. Getting beauty advice from an AI influencer who’s your friend on Instagram just feels like the natural culmination of so many other trends.

GCI: Some brands are starting to focus on consumers’ emotions when utilizing AI research for retail and product design. Could this emphasis on emotional factors help with the purchase process? Could it help with a brand’s overall digital strategy?

AM: I think it’s important to realize that emotion isn’t a binary thing—if you’re reading this, what emotion are you feeling right now? It’s not obvious even to the person feeling the emotion most of the time. AI requires data to be correctly labelled in order to teach the machine how to recognize patterns, and emotion detection has always felt like a bit of a red herring in that if humans aren’t good at identifying emotions from relatively inert facial expressions or language then it becomes hard to teach a machine how to do it as well. I think a much more fruitful avenue is to ask consumers their preference and to present what they’ve told you they want when they want it. If you walk into a store today and talk to a beauty advisor, they aren’t going to try to infer your mood and emotions as much as they’re going to talk to you to figure out how they can help you best. In a digital domain, if a virtual beauty advisor can learn whether I’m the kind of person who cares a lot about ingredients, or who will read through dozens of reviews and can deliver what I want without my asking is a much more pragmatic way to help smooth the purchase process, rather than trying to infer what a 5.8 out of 10 on a ‘delighted’ scale means. 

GCI: What specific challenges arise when dealing with millennial and Gen Z consumers, who are more tech-savvy than any other generation? 

AM: I think one thing we need to remember is that younger more tech-savvy consumers don’t just gravitate to new technology because it’s new. They gravitate to what is best. Being savvy mainly means that they’re more discerning. I often hear technology-minded folks talk about how millennials are going to be a voice first generation which is just silly. We have eyes, and hands and noses not just ears and mouths. We’re going to continue to use our full range of senses when interacting with technology in the same way we use all our senses when interacting with other people. My advice is that if you find a digital experience lacking yourself, don’t assume that a younger person will find it appealing. Most of the time if you think something stinks a more discerning user will find it even worse. 

In terms of challenges, I think the hardest thing is to know when to invest in experiences that will improve over time. For example, even though I don’t believe in voice-first, I obviously do believe that conversational AI and building brand personas that can talk and chat with consumers is critically important, despite many experiences being relatively simplistic today. The reason for this is that I’ve seen more advancements in the last two years in the field of conversational AI than I have in the last decade which tells me that unless you’re investing now and building up a set of conversational data that it will be difficult to complete as things accelerate into the future. 

GCI: Expand a little on the idea of simplistic guided selling tools, what are they and how can they improve? 

AM: Guided selling is a term that’s often used to describe any tool on a website that helps a consumer narrow down choices. If you’ve ever browsed for a new car online and picked from a menu to build a specific color, stereo and other options you’ve used a guided selling tool. 

In beauty the most often used example would be a simplistic web diagnostic for skincare. These tools have been shown to drive engagement and increase conversion, but they feel like work, and they often don’t perform that well on mobile. Their main limitation is that they force consumers to describe their concerns and preferences in a very binary way, which can be extremely confusing. There’s a lot of finicky picking from drop-down menus and clicking option buttons and it’s neither fun nor natural. Until recently this was the best way to let a consumer navigate through a large and/or complicated product range, but it turns out that guiding a consumer via a conversation works even better. You can drive way higher engagement and conversion rates through a personalized chat conversation rather than via a rigid web interface.

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