Louis Vuitton, The Highest Value Luxury Brand, May Need To Balance Artistic Endeavor and Market Demand

High-value luxury goods such as Louis Vuitton, Fendi, Burberry, Gucci, and Prada have high exchange value. Louis Vuitton (LV) is the highest value luxury brand of 2018, with a brand value of $28.4 billion. Their products are sought after, making security an issue of the utmost priority. If the LV boutique stores were not secure, it would have lost most of its brand value, since the products would circulate the market.

Furthermore, some people walk in to look at LV but do not buy their products, for various reasons. Taking into consideration that LV’s niche is quality, value for money could prevent people from buying LV. Perhaps they feel that the quality of the material has decreased or design is too avant-garde or boring. Maybe, people do not purchase products since LV uses animal skins as products. All in all, it could be a variety of reasons, and all of them could be affecting LV’s target audience of high-income consumers.

With the knowledge about mass consumers’ decision-making processes, LV can ensure that their artistic output complements existing market demand. LV can also ensure that the shopping experience at their boutiques is improved.

Sapiengraph: The CCTV That Will Revolutionize Retail

Sapiengraph is a CCTV that aims to help with both security and analyzing customer trends for your business.

The camera that comes with the software is of the best quality, used by Xiaomi and Wyze (a big CCTV startup). The chipset and camera design are one of the most efficient and effective hardware amongst all CCTVs. LV will get the best quality videos and cameras to identify security threats. This camera is also compatible with the cloud.

The use of the cloud is to ensure the safety of your footage. When there is a physical storage space for security footage, people would be able to steal or damage the hard disk. The use of cloud circumvents this. Furthermore, we do not charge for the cloud, and LV may use as much of it as they want, as long as you continue subscribing to Sapiengraph. LV would be able to store the security footage of all their boutiques on the cloud, which is useful for potential reference.

Here’s the cherry on top: there are retail analytics functions embedded into Sapiengraph CCTV. Sapiengraph identifies every consenting customer of LV and pulls up social media profiles and information about them from the Internet in real-time. Through the dashboard, LV boutique management may see their consumer preferences, and report back to the various departments of Singapore’s LV management. This process enables LV to see what consumers’ profiles are, thereby helping LV to see trends in the people buying and people browsing LV goods. LV can optimize their retail and make more accurate decisions.

The dashboard is user-friendly and similar to that of Google Analytics. LV can integrate Sapiengraph into their retail processes easily. Store managers can visualize the feedback from the customers coming in and out of the store and send feedback of the aggregated analytics back to LV Singapore headquarters.

Are you interested in finding out more? Click here for more in-depth details about Sapiengraph, and click here if you want to read our FAQs.

Indicating Your Interest For Sapiengraph and Our Follow-Up

From our launch post and FAQs, filling up our Google Form is the most direct way.

Sapiengraph CCTV aims to help you as much as possible to grow your retail services with the best quality camera, unlimited cloud storage, and retail analytics functions, all at a low price of only $50.

We are also on hand to help you with the integration of your daily retail procedures into Sapiengraph. We want to ensure that you have a seamless, fuss-free experience throughout your entire subscription with us.

If you have any questions at all about the CCTV, please call 9655 9294 or email [email protected] for more information. You may also indicate your interest by filling up our Google Form!

Nubela is a 5-year-old company founded by NUS Computer Science Alumni