Proposed Augmented Reality (Instagram Filter Try-On) as Promotion Strategy to Increase Brand Awareness for Start-Up Business (Case Study on Small and Medium Enterprise Fashion Brand Boboya Wear)

Boboya Wear is a local fashion brand that specializes in women’s fashion that offers daily wear that has unique embroidery accents on each product and has a variety of colors. The main issue of Boboya Wear is bad product sales and tend to be unstable, so that it becomes an issue for Boboya Wear. The purpose of this research is to find out solutions to solve company problems.

One of the problems faced by Boboya Wear is that the product is not relevant to what consumers want or the trend regarding the product has out of trend. Resulting in fluctuating sales and a small variety of products so that consumer choices are low and this caused by bad production timeline and inconsistent promotion strategies. To analyze more deeply the researchers used primary data by distributing questionnaires to analyze consumers and used secondary data from Boboya Wear Instagram and Shopee Insight. Researchers used Ishikawa fishbone diagrams to find out more about the problems faced by Boboya Wear.

After analyzing the internal and external situation of Boboya Wear using 4Ps marketing mix, SWOT, STP, five forces porter, competitor analysis, and customer analysis. The solution is to implement AR Instagram filter try-on as promotion strategy and develop new products and packaging, collaborate with influencers using AR try-on, create bundling promo, and educate the audience about AR try-on technology. The AR try-on technology used is Instagram filter because the installation cost is cheaper and easier.

The results of the questionnaire from total 100 respondents agreed that the implementation of AR Try-on could help them in choosing the product they wanted and create shopping experience more pleasant and fun. The business implementation plan that will be carried out is by optimizing the implementation of AR try-on, making new products and packaging and implementing AR try-on.