Founder: Vehbi Deger Turan Founding Date: 2018 HQ: San Francisco Website: www.cerebra.ai |
Vehbi Deger Turan is the founder and CEO of Cerebra Technologies
“We tell you what will sell, why, and how to prepare for it.”
What does your company do?
Cerebra is the No-Code Decision Intelligence solution that analyses all available external signals (reviews, trends, seasonality, geographical anomalies, images, unstructured text) and applies this to the company’s internal data, generating ready-made insights for non-technical teams to inform better decision making. Every insight has a call to action and a financial effect aligned with it, allowing businesses to prioritise decisions for the most impact. In doing so, we give retailers the power to understand their existing disparate data, tap into unstructured external signals and produce actionable insights at scale, without the need for specialised data science teams. As a result, clients can expect increased efficiency, higher profits and sustainable business growth.
Which retailer need do you fulfil?
In the retail sector, there is often a fatigue that comes with decision making. The industry is inundated with signals from all directions and there is a resentful acceptance that you’re not going to do a perfect job. For instance, a retailer carrying 300 SKUs might have a good sense of the first 30 or 40 and the rest are long tail odds. There’s always going to be more data signals than is possible for a single human to keep up with – especially in the retail sector.
Our goal is to remove the heavy lifting and for customers to come away from Cerebra with a clear course of action. We provide an actionable overview of the main SKUs to pay attention to and the key trends in the industry where we believe there’s a substantial lift. From there on, the retailer will already know what to do.
How do you deliver on this USP?
Cerebra makes decision intelligence accessible to everyone: we eliminate the need for hundreds of extra clicks and a team of data scientists working around the clock. No extensive data infrastructure, analysts, business intelligence tools, or special training is required. Instead, everybody in the organisation looks at the same numbers in the right way and can act upon them with speed. Our software continually learns and improves with each action, reducing inventory waste, strengthening customer loyalty, and maximising profits.
What do these insights look like?
The platform is broken down into product insights, category insights and customer insights. Retailers will find a list of immediate actions that will have a direct impact, as well as a list of strategic actions which will have a long term effect. For example, Cerebra might flag up an item that is going out of season and advise the user to sell the remaining stock faster in order to avoid excess inventory or reduced margins. We tell you where to promote the item and how to sell the product.
Our technology called Voice of the Customer (VoX) enables sellers to explore where reviews are being placed, and what words and sentences are being used to describe specific products.
This goes beyond reviews on the retailer’s website. We can pull unstructured data from Instagram, TikTok and reviews from external parties to provide a window into the real consumer experience.
What makes you stand out from competitors?
Leveraging external signals is a critical part of the equation we’re trying to solve. There are many data vendors out there who will give you strong market signals but they don’t necessarily connect with your own sales stack. Let alone where your customers are at or what your inventory levels are. On the other side, there are vendors who offer a lot of ERP solutions that are really good at being able to manage your inventory but they will not be able to figure out what else has taken place in the market. We bring these two ends of the story together in a way that actually makes a difference for the end experience of a retailer to be able to make decisions. A lot of solutions out there only lean on internal or external data. We marry these two together.
We also pride ourselves on speed and agility – both very important in the retail sector which has a very short attention span. The data underpins every decision and therefore gives merchants the confidence to move at the pace needed to keep up with the expectations of tomorrow’s retail landscape.
Who are your customers?
We cater for omnichannel and ecommerce retailers that have upwards of 200 SKUs. Even if you have data scientists or employ them, we give them back the time to work on more valuable tasks.
How are you prepared to help retailers tackle sustainability?
There are two ways we’re approaching sustainability. One side is very common in the industry, for example, using sustainable fabrics and having a healthy supply chain.
Equipped with our data insights, retailers can reduce returns rates because they will know exactly what the customer wants. In turn, we will see fewer unwanted clothes piling up in landfills – as well as reduced carbon emissions that would have otherwise been released during the return journey.
The other angle of sustainability is reducing waste in terms of human bandwidth. Waste reduction doesn’t only refer to capital use or resources, it also refers to time being spent right. The most effective way to reduce waste is to put minimal effort into things that don’t yield much value and maximise the sides of the business that are actually interesting. Cerebra helps enhance inventory management, leading to less waste because merchandisers know how to buy and marketers know how to sell more efficiently. This means producing the right amount of SKUs so that heavy discounting can be avoided, while human power and resources can be saved.
How does your solution help build customer loyalty?
It’s about reverting it from making decisions that are based on the SKUs to making decisions based on the customer’s interest. Any loyalty grouping that we provide to our retailers is completely dynamically generated. None of these have any hard and fast rules because the truth is each person is idiosyncratic in their shopping habits. You need to be able to catch them at their own cadence and pair this with external signals.
Loyalty cycles on your own products will always shift dramatically and being able to catch these in a dynamic modeling is difficult. And either a retailer will have a ten-person data science team, a budget and two years to model this out or they work with us and get this seamlessly and rapidly.
How would you describe your vision?
To autonomously power the operations of the world’s fastest growing businesses for a future with less waste, more profits, and higher customer loyalty.