Renovai Are Boosting Design and Shopping Experiences & Results Using AI

Market Analysis

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renovai

AI has been consistently providing an uplift to traditional industries. We see that in real estate, transportation, healthcare, and others. This is a strong indication that the implementation and integration of AI software are being adapted effectively. This can include easier onboarding processes, faster time-to-market integrations, and an understanding from traditional industries that an in-house CTO, with our without a tech team, is essential for the innovation and customer satisfaction of the clients and partners. Not to mention the productivity and competitive aspects.

While searching for a startup that can tell us more about how AI integrates into traditional industries, we have encountered renovai, a visual AI shopping assistant for lifestyle brands. We have talked to their Co-Founder & CEO Alon Gilady.

Hi Alon, it is not a secret that many AI-led startups have been trying to innovate traditionally industries like Real Estate and Healthcare. It seems as you are approaching commerce and retail in the same way. How effective is your technology compared to other solutions developed in-house by large retail enterprises?

Our solutions don't operate as a recommendation engine. They are design knowledge-based and not statistical-driven. We don't segment; we study each shopper's preferences and needs and match them with the right products. We provide the retailers with the ability to offer interior design services for their end-users, saving them a lot of money and all the hassle. No in-house solution can be as elaborated and accurate since our algorithm operates on multiple data sources from all over the world.

It's partially a give-and-take model that fuels our data and ensures that besides the vast knowledge of design rules and best practices, we are always on trend and are able to display items in the proper context.

Visiting renovai's website, we have been kindly advised to check out your ROI Calculator feature. Can you please elaborate on some of the metrics and practical data behind it?

We extract the performance data from the global retailers already leveraging renovai's solutions in the furniture and home décor verticals as the basic layer and enrich the metrics with the provided information - average order value, number of SKU's and the number of monthly visitors.

We know that our solutions approximately increase AOV by 12%, CVR by 16%, and a total 30% revenue increase, so that's the baseline of the calculations.

The output is personalized estimated AOV, CVR, average revenue per user increase, and the total monthly uplift potential for retailers that will implement renovai's visual commerce solutions in various touchpoints across their website.

The retail customer journey is constantly evolving, and more touchpoints are needed. It seems as renovai has that in mind when you provide your clients and partners with multiple solutions, taking into account the end consumers' angle. In essence, this places you as a B2B2C AI startup, which is not like most AI solutions that have decided to focus on one individual target segment. How has that been integrated into your business model?

The B2B2C model is more relevant than ever before. The exponential growth of digitization and e-commerce has blurred the boundaries between B2B and B2C business models into a converged B2B2C model.

With every solution and product we develop, we always think about two tracks - the first is obviously the retailers and eCommerce brands we partner with, and the second is the end consumers.

It is not just about the UX/UI of each product but truly addresses specific pain points. We improve all key metrics for our partners and also reduce the return rate. Shoppers are able to view all items from all angles, placed in hyper-personalized settings; they know what they will be getting and enjoy the shopping experience.

With our B2B2C model, we have access to a lot of user data, and we spend a lot of time researching and understanding the buying journey. The customer experience is critical to the success of our B2B2C model. After all, if our partners deliver a bad experience to their consumers, we will also suffer. The reverse is also true.

Our strategy and business model evolve alongside our Business customer's needs and strategies. We have our core abilities, and each new solution is a natural evolution answering to a specific need. For example, after understanding the significant impact we have on up-sell and cross-sell strategies, we developed a checkout feature that is designed to have the same impact we are witnessing on category and product pages on the checkout stage.

Can you please elaborate on your current product roadmap? What are the next milestones for renovai?

First of all, we are constantly optimizing our current solutions, focusing on our deep tech to make all personal design recommendations as accurate as possible.

We are expanding our abilities to fashion and apparel, translating design knowledge to styling abilities, both for visual search and recommendations but in a gamified way. I will be able to share more about it once we finalize the POCs with our design partners.

Second, we started working on solutions that incorporate the new age of visual search in a way. Currently, our recommendations are based on website interactions, but we are deepening the analysis and our acquaintance with the shoppers, literally getting to know them by the current design of their homes. We will tap into an additional layer of customer data.

It's still a beta version, but eventually, shoppers will be able to take a picture of their space, and we will analyze all items in their room, perform our correlated deep tagging abilities and then offer personalized recommendations in real-time, also incorporating AR.

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