Lyuba Tuz, Head of Analytics & Data Monetization
Do you ever wonder about the stereotypes of the target audience segment you belong to? Being identified only as a “woman aged 25-45 years old” doesn’t feel right to me. Actually it makes me angry. Am I the only one who feels this way? And it’s not just about gender stereotypes, (though those piss me off too) but it’s about all of the opportunities businesses are missing out on because they don’t understand (or at least try to) their target audiences.
Let’s imagine a case. I (a 25-45 year-old woman, by the way) want to buy a dress for myself. At some point, targeting algorithms identify my intent and start to show me lots of ads. And surprise-surprise: most of the advertising materials are very feminine, playfully offering “to unveil my femininity” and “to attract the eyes of others” and blah-blah.
The day after, I realized that I needed to buy a drill as a gift for my grandfather’s birthday. And after a few simple manipulations in the search my “ad feed” turns into a collection of relevant items from marketplaces. Such “not creative” ads actually helped me to collect a valuable consideration set. I didn’t even need to see any emotional stories about the “happiness derived from owning the best drill”. They. Just. Didn’t. Show me. Them.
So, dear targetologists who are creating ad campaigns, brand-managers approving gendered creative materials and all other participants of this hypocrisy dance, I have a question.
Aren't you still the same shopper whether you're buying something for yourself or for someone else?
“Yep, definitely” – would be your answer.
“In fact, this is true. But it’s not obvious from your purchasing behavior” – I would report back.
Tens of thousands of live product video translations are generated with eyezon monthly. Our content analytics flow is built around collecting all available content (live video records, audio messages, text messages), transcribing audio and video files to text and aggregating all text content into a single dialogue (including shoppers’ and shop assistants’ speech). Text content is analyzed using regularly updated client-customized vocabulary to deliver analytical dashboards. Moreover, we are working on semantics analytics to improve the quality of content analytics. The most common questions which are already included in our analytical vocabularies are:
At what stage of the customer journey is the shopper?
What are their needs and barriers to purchase?
We have daily access to live communication between shoppers and shop assistants in the form of quick analytical snapshots in all of the 15 industries we work with, due to well-adjusted work with data.
The first time we realized there was a conflict in the audience personas (including age, gender, social status and interests) was within the eyezon team while testing speech-to-text scripts.
During a manual analysis of a large sample of dialogues, the following situations were found:
A woman who chose a mattress based on the main criteria “it shouldn’t sag under my heavy husband”.
A man who asked a shop assistant “Is it ok to have a red smartphone for a man?”
A man who was trying to choose a beauty box for his girlfriend.
I have 6 years of experience in a digital agency as a strategist and I have never seen a brief which would consider such simple and common situations. At the same time, 70% of all briefs included personalized scenarios for precision targeting to drive purchase intent in an “efficient way”.
You have to admit, it would be extremely inappropriate to show a woman looking for a mattress with this criteria a display banner with a thin model and a copy about “light sleep”. Showing her a neutral banner about a high-quality and durable orthopedic mattress would be a perfect fit.
An ad with a fancy actress languidly holding a "gorgeous scarlet" smartphone will be a pain in the ass for a man who wants a red smartphone but is shy to buy it. And just showing him a banner with a smartphone, a price offer, and quick delivery options is perfect.
You might argue that such cases are extremely specific and it is impossible to keep in mind all of these possible purchase scenarios. I am not going to argue with you over that. After all, this is one of the pillars of creative and media budgets.
I just want to give you some figures from our analytics, the sample of which can be considered quite representative.
There were more than 400,000 live video product consultations across 17 industries with eyezon in 2021.
About 25,000 dialogues contained mentions of the intended purchase recipient.
40% of live consultations contained mentions of other people as the product end-user.
The biggest share of purchases made “not for myself” were in the electronics & home appliances, fashion, and household & DIY industries.
Electronics & home appliances purchases were considered “not for myself” in 30% of cases.
The most frequent requests in this category are:35% of shoppers were searching for optimal wearable devices, tablets and laptops for their kids.
The most frequent criteria of consideration were parent control functions, entertaining functions and game support.23% of shoppers were searching for gifts for their partners.
You can find smartphones, wearable devices and even large home appliances among gift ideas.
Shoppers very often turned to shop assistants for their personal experience and impressions about the products in order to make purchase decisions quickly and not screw up.20% of shoppers were searching for smartphones, laptops and large home appliances for their parents.
The main requirements of these devices were ease of use, quality and reliability.
Fashion products were considered “not for myself” in 21% of cases.
One out of two live sessions were about searching for products for a partner.
A quarter of all live consultations in fashion were about choosing products for children of any age even if they are already grown.
The focus of the live sessions here were on quality and sizing.
Household & DIY products were considered “not for myself” in 10% of live translations.
Almost half of them were used to make a purchase for kids and 20% were to make purchases for parents and partners.
Here I would like to praise marketplaces because they are aware of the non-linearity of shopper behavior and they try to make their advertisements as neutral as possible.
Such awareness is not a coincidence, they just have enough data. For them, you are not Mary 28 y.o. with kids.
You are Jane Doe, a shopper who has interests in specific product categories.
And they also have predictive modeling which helps to predict your interest in other complementary categories based on their data.
Marketplaces show you ads with specific product offers, which you need now or you may need in the near future, based on their predictive data models.
And this is honest! And it works! And you know it’s true, especially when you are competing for your audience with marketplaces and trying to lead shoppers to your own shopping platform.
It seems that quick delivery, loyalty programs and other services are not the only point here.
It’s about how you invite shoppers to your platform.
Are you toying with the idea of dividing your target audience into separate personas and using “precision creatives” to reach them? Or are you just offering your shoppers something that they really need right now and right here? This is the question.
Now pay attention, this next part is important.
Audience persona is what helps you to make a specific advertising campaign more meaningful, catchy and clear to specific audiences in order to break through the clutter.
Shopper portrait is what determines the behavioral patterns of your audience of specific users.
Such a portrait will help you to understand your shopper’s actual or predictive needs and to offer them exactly what they need.
And in this case, there is no proverbial clutter to break through – when you really need something, all offers that you get in that moment are valuable.
The shopper’s age, gender, social status and religion are totally irrelevant when there is a specific stated need.
One and the same customer can have a lot of shopper portraits depending on whether they shop for themselves or for someone else.
This is not a problem – this is a huge opportunity.
This is the opportunity to collaborate with data vendors, who know the exact purchase behavior of your customers.
This will allow you to make very unexpected discoveries along your customer’s journey and to transform it to make each step better.
This opportunity will help you to think bigger picture, beyond the briefs and approved brand-strategies and to find new sources of business.
And we have no doubt that businesses will adapt with time and incorporate neutral but precise communication within their media plans more and more.