Dable Success Case for Dating/Marriage vertical (6)
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Today, we are going to share the success case of dating/marriage vertical with you. Please refer to the content below and hopefully it helps you create ad capaigns with great results.
Company Info.
Soohyun is an upper-class marriage consulting agency targeting white-collar professionals in Korea with a nearly perfect satisfaction rate.
Challenge: Collect Leads from users interested in Marriage
SOOHYUN is one of the famous marriage consulting agency in Korea. While running banner ads for its advertisement, SOOHYUN felt typical marketing channels were not enough to draw people’s attention, as marriage service business requires high involvement. In seeking new marketing tactics SOOHYUN came across Dable, whom they decided to partner with to obtain DB from potential customers.
SOOHYUN ran article-type ads for PC users. Ads were shown randomly without considering the audience, so SOOHYUN decided that they need more precise targeting. As a result, it made personality test-type ads for specific targets on PC and mobile. Many of the ads were organized into different campaigns considering the day of the week, time of the day and media. All campaigns were exposed to specific targets by using Dable’s personalized recommendation logic.
Soohyun’s campaign showed higher CTR and lower CPC, compared to existing banner ads, and acquired a substantial number of leads.
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SOOHYUN ran article-type ads for PC users. Ads were shown randomly without considering the audience, so SOOHYUN decided that they need more precise targeting. As a result, it made personality test-type ads for specific targets on PC and mobile. Many of the ads were organized into different campaigns considering the day of the week, time of the day and media. All campaigns were exposed to specific targets by using Dable’s personalized recommendation logic.
Thanks for posting about this interesting campaign!
Amy
Thank you for the interst, Amy I can share a little bit more about the campaign.
In Korea, there has been a huge trend that uses personality test to promote and advertise products or services. A lot of marketers create the test to attract audiences' interst as much as possible first. Customers usually do not recognise the test is made for ads, beause it looks very interesting and exciting just like playing games. With the test, people believe they can identify themselve more deeply and share it with other friends via DM or SNS natually (organic traffic and viral arise here and we can see each customer's data like interest, gender etc). Marketers are able to collect more DB here, and Dable's well-developed personalized recommendation logic helps them to expose appropriate ads to each individual.
I hope the explanation above makes sense for you
Originally Posted by dable_richard
I can share a little bit more about the campaign. In Korea, there has been a huge trend that uses personality test to promote and advertise products or services. A lot of marketers create the test to attract audiences' interst as much as possible first. Customers usually do not recognise the test is made for ads, beause it looks very interesting and exciting just like playing games. With the test, people believe they can identify themselve more deeply and share it with other friends via DM or SNS natually (organic traffic and viral arise here and we can see each customer's data like interest, gender etc). Marketers are able to collect more DB here, and Dable's well-developed personalized recommendation logic helps them to expose appropriate ads to each individual.
I hope the explanation above makes sense for you
Quizzes are nothing new. Many marketers use the answers to segregate the audience (by gender/interest/etc. like you mentioned) and then send suitable offers to each audience segment.
So what you're saying is that the answer each user gives, will help Dable's algorithm as well?
I've never run on Dable, but drawing on my knowledge of Facebook, I can imagine how each answer the user chooses, can trigger a pixel that will add them to a custom audience. So in the end you'd have different custom audiences: e.g. People that like long walks on the beach, vs. people that like to go dancing; people that have a college degree, vs. people that have a secondary school diploma; people looking to date the opposite sex, vs. people looking to date the same sex?
And then on FB (I don't know about Dable) you could create LAL audiences based on each of those custom audiences, using ads tailored SPECIFICALLY to each audience...
I'm not sure if we're talking about the same thing or not.
Amy
I think I should have explained you what Dable focuses on: Customer discovery.
Customer Discovery is a method of finding customers where the system identifies and widens reach towards users who are seen as targets, based on user profile set by the advertiser.
So it's more like the other way. Your examples from FB ads is like you run the campaign first and gather DB later. With the data, you can customise audiences and set the targeting like LAL.
But Dable already has its own users' data: interest, age, gender, geo, language etc, so you can use it for target settings at first. As running your campaigns with us, AI performs machine learning like FB ads does. In this process, you can collect more DB and it helps improve accuracy of targeting. Machine learning technology and innovative personalization algorithms help advertisers gain success in their campaigns.
In the case of Soohyun, they didn't run ads without any targetings running native-ads in the past. There might be several reasons why they decided not to use targeting settings. Maybe there were no setting for it or they might think it's not precise (not sure bc its Soohyun's internal reasons). But their campaigns with Dable were different. Dable already had its own data for personalised recommendation to potential customers. Dable's AI technology helps advertisers target more precisely before gathering user's data by running ads. Moreover, as running ads on Dable, AI performs manchine learning and its personalization recommendations become more sophisticated. Soogyun had run several campaigns for optimisation, and they could successfully show their advertisement to the right target. It led to the higher CTR with lower CPC compared to other banner ads.
Originally Posted by dable_richard
Customer Discovery is a method of finding customers where the system identifies and widens reach towards users who are seen as targets, based on user profile set by the advertiser.
So it's more like the other way. Your examples from FB ads is like you run the campaign first and gather DB later. With the data, you can customise audiences and set the targeting like LAL.
But Dable already has its own users' data: interest, age, gender, geo, language etc, so you can use it for target settings at first. As running your campaigns with us, AI performs machine learning like FB ads does. In this process, you can collect more DB and it helps improve accuracy of targeting. Machine learning technology and innovative personalization algorithms help advertisers gain success in their campaigns.
In the case of Soohyun, they didn't run ads without any targetings running native-ads in the past. There might be several reasons why they decided not to use targeting settings. Maybe there were no setting for it or they might think it's not precise (not sure bc its Soohyun's internal reasons). But their campaigns with Dable were different. Dable already had its own data for personalised recommendation to potential customers. Dable's AI technology helps advertisers target more precisely before gathering user's data by running ads. Moreover, as running ads on Dable, AI performs manchine learning and its personalization recommendations become more sophisticated. Soogyun had run several campaigns for optimisation, and they could successfully show their advertisement to the right target. It led to the higher CTR with lower CPC compared to other banner ads.
This begs the question: Where/how does Dable collect this user data?
Amy
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