Award-winning Case Study For Blum South East Asia By Adspy - BigSpy

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Facebook is the world’s largest social media platform. 80% of brands choose to advertise on Facebook, which is full of business opportunities. Whether it’s individual users, small and medium enterprises like “Blum South East Asia”, or large enterprises, they have established a Facebook page for advertising and promotion. “Blum South East Asia” chose to advertise on Facebook and achieved success. Now, BigSpy do a case study and research on “Blum South East Asia” through the method of adspy!

Blum South East Asia Facebook ad Introduction by ad spy method

“Blum South East Asia” introduction:Blum - A byword for functional beauty.

“Blum South East Asia” Facebook ads last run:2020-02-17 07:20:35

BigSpy is an adspy tool. BigSpy can capture ads from multiple social media such as Facebook, Instagram, Twitter, etc. It can spy ad information in 40 countries and store 160 million ad data. It is the world’s largest ad database.

BigSpy tracks and analyzes “Blum South East Asia” ads data to help “Blum South East Asia” find the best conversion ad creatives and ad copy. BigSpy makes the advertising world transparent, helps more businesses to increase sales conversions through adspy. 

Now BigSpy generates an ad report for “Blum South East Asia”. In this report, we analyze in detail the best ad cases of “Blum South East Asia”.

Blum South East Asia Top3 Ads Case Study:

 1st2nd3rd
Advertisers Blum South East Asia Blum South East Asia Blum South East Asia
Ad title Featured urbanKITCHEN urbanKITCHEN by blum Durable kitchens tailored to your needs.
Ad text urbanKITCHEN in a landed property by Home Trend Furniture. The contending black and white aligne... Expect nothing less than excellent quality. urbanKITCHEN is a European-style that is exclusively... Affordable European-quality kitchen with original Blum hardware. Smart solutions for your urbanKI...
CTA type LEARN_MORE LEARN_MORE LEARN_MORE
Ad format Carousel Image Carousel
Categories Shopping & Retail Shopping & Retail Shopping & Retail
Duration 1 days 1 days 1 days
Like 0 0 26

Blum South East Asia Facebook ad case study and analytics

1.Ad format case study:

The ad formats used by “Blum South East Asia” top 3 ads are: Carousel,Image, and Carousel.

Ad format analytics and optimization suggestions:

The Facebook algorithm indicates that Facebook will show more video ads to users. So, to get more ad reach, consider video ads.

“Blum South East Asia” likes to use Carousel ads as material. In fact, Facebook’s creatives determine the user’s first sense. “Blum South East Asia” perform A / B testing on different creatives and use different creatives according to different audience types. In addition, you can also use BigSpy to spy the industry’s latest ads and competitors’ ads. BigSpy provides the material download function to help you solve your creative troubles.

2. Ad copy case study:

  1st 2nd 3rd
Ad title Featured urbanKITCHEN urbanKITCHEN by blum Durable kitchens tailored to your needs.
Ad text  urbanKITCHEN in a landed property by Home Trend Furniture. The contending black and white aligne...  Expect nothing less than excellent quality. urbanKITCHEN is a European-style that is exclusively...  Affordable European-quality kitchen with original Blum hardware. Smart solutions for your urbanKI...
Ad type  other  other  other
Ad word count 658  609  137

The text in the ad is an important part of the ad, and it is the key to let the ad users convert into actual customers. Among all the ads of “Blum South East Asia”, the text type used is other to obtain the best ad performance. “Blum South East Asia” can use this copy style more. On the other hand, “Blum South East Asia” mainly conducts A / B testing on the copy, because the different lengths of the copy, the symbols used, and the subject of the copy all directly affect the CTR.

Ad copy analytics and optimization suggestions:

Different copywriting effects are different. The core of designing copywriting is to capture the user’s psychology and the selling point of the product and retain the user with clever language. In addition, BigSpy monitors user responses for different copywriting. Before designing an ad copy, “Blum South East Asia” can learn competitors how to write a good ad copy.

3. Type of CTA case study:

The types of CTA used by “Blum South East Asia” are:LEARN_MORE,LEARN_MORE,LEARN_MORE.

Without the CTA button, the conversion cost per ad will increase by almost 2.5 times. Selecting the CTA button is better than not selecting it.
In the 1st ad, the use of “LEARN_MORE” help “Blum South East Asia” gets a higher conversion.

CTA analytics and optimization recommendations:

Facebook ads must be tested in the final round of CTA when performing A / B testing. This detail may help you save a lot of budgets. In addition, BigSpy can filter competitors’ CTA types of Facebook ads through filtering, which can be used as a reference for the “Blum South East Asia” test.

4. Ad schedule case study:

When doing Facebook ad marketing, “Blum South East Asia” top 3 ads schedules are: 1 days,1 days, and 1 days.

Ad scheduling analytics and optimization suggestions:

Your ads are not valuable 24 hours a day, 7 days a week.

Check your Facebook ad report, you will find that the “Blum South East Asia”‘s top 1 ad duration is 1 days. Every advertisement has a life cycle.
“Blum South East Asia” should put ads in the best time period, so that ads get the most value in a limited time.

Related “Blum South East Asia” ad case study report

If you want to check the best ad case study of other advertisers related to “Blum South East Asia”, you can click the name below to view the related report.

Finally, the above is the ad spy and case study for “Blum South East Asia”. The analytics and optimization of Facebook ads is a long-term accumulation process. In this report, the basic design of ads was learned through BigSpy. In real advertising marketing, marketers also need to have an in-depth analysis of products, grasp the audience’s psychology, learn about marketing, and make precise calculations of data.