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Early in the pandemic, as many enterprises looked to digitally transform their operations, marketing and merchandising departments turned to AI to automate the increasing workloads. According to Salesforce, marketers’ use of AI soared between 2018 and 2020, jumping from 29% in 2018 to 84% in 2020. A separate survey from ManageEngine — the IT division of Zoho — found that analytics for marketing, driven by automation and AI, experienced a 44% adoption surge in over the past two years.
Retail and consumer products executives, responding to a recent IBM survey, said that they believe that intelligent automation capabilities could help increase annual revenue growth by up to 10%. Adopters in marketing cite benefits like accelerating revenue as well as getting actionable insights from marketing data. In fact, that’s the sales pitch of Cerebra, a platform designed to provide “data-driven direction” to marketing teams by analyzing “external signals” and applying this to companies’ internal data.
Cerebra today announced that it raised $15 million in a series A round led by Notion Capital. Deger Turan, cofounder and CEO, says that the financing — which brings Cerebra’s total raised to $16.5 million — will be used to expand Cerebra’s workforce and support R&D efforts.
Turan, a founder at San Francisco, California-based venture fund Atomic, launched Cerebra in 2018 after a brief stint as a software engineer at data analytics company Palantir. He claims that Cerebra’s technology can analyze external and internal data sources, marry them together with algorithms, and provide insights to drive marketing outcomes based on business goals.
“The data sources used by Cerebra are the ones [that] customers deem relevant. Apart from internal data sources like Google Analytics, inventory, returns, transactions, catalog, customer relationship management data, marketing data, product images, and more, we use external data sources to which unstructured data belongs,” Turan told VentureBeat via email. “Unstructured data entails datasets that aren’t stored in a structured database formats — reviews, social media, and more. Cerebra identifies what resonates with your users, and why, and provides action recommendations about how [customers] can build better products and market them more effectively.”
For example, Turan says, Cerebra can predict optimal product stock allocations based on sales forecasts and discover which discounts to offer to which customers for products expected to see a drop in sales. Ostensibly, platform can also identify the best-performing discounts for each campaign and spot abnormal return rates — automatically adjusting “problematic” product descriptions.
“Cerebra’s insights gives additional layers of data and context to the data and technical teams. For organizations that have large data science teams, it gives them more ammunition to work with … For companies without data science teams or with smaller ones who are overwhelmed, it lets the business access the output of a data science team but without needing to hire additionally,” Turan explained. “Either way, the customer is still in control of the data and output, and can consume it in the manner that best suits — whether by Cerebra’s interface or through their own existing.“
From the data it collects, Cerebra attempts to find out which customers are ready to buy and win back customers potentially at risk of churn. The platform can also create product bundles and promote cross-sales — i.e., encouraging customers to purchase products in addition to the original items that they intended to purchase — based on customer behavior, product affinity, and price preferences.
“Every insight has a call to action and a financial effect aligned with it, allowing our clients to prioritize decisions for the highest impact,” Turan said. “Cerebra tells you what you should focus on and why, so you can move forward with the action faster than ever before … It’s this part of Cerebra’s AI technology that makes business teams move faster and more efficiently, saving and making money throughout the entire process.”
Twenty-three-employee Cerebra, which offers plugins for existing ecommerce ecosystems like Shopify, competes with startups like Constructor, Zoovu, and Klevu in the growing marketing and merchandising automation segment. Klevu applies AI to help ecommerce merchants deliver search experiences powered by customers’ behaviors. Similarly, Constructor’s AI-powered software aims to address the challenges with discovery tools including search, autosuggest, browse, recommendations, and collections by aggregating data and learning from shoppers’ search queries.
Gartner predicted that at least 60% of organizations would start using AI for digital commerce by 2020. But not every company is so eager. RMG reports that 12% of senior merchants have “no plans” to adopt AI as of 2021, due to a lack of expertise to manage a pilot, high costs, unorganized data, and a lack of understanding about the benefits of AI.
Turan asserts that Cerebra is well-positioned to overcome the hurdles that it faces. Cerebra currently has 80 users and plans to use the funding to ramp up hiring and R&D, as well as customer acquisition.
“Every company is competing for attention and seeking growth. E-commerce is growing more rapidly than it has ever before. Most companies are really well funded, making the battle for bidding for attention more and more expensive every day. Giants like Amazon, Shein, and others are winning based on managing data, not because their retail products are the best,” Turan continued. “[With Cerebra,] everybody in the organization looks at the same data, in context to their own role, and can act upon it with speed. This means an enhanced customer lifetime value, more ROI from spend (growth of profitability), optimized inventory to reduce waste and minimize loss of revenue, and less waste on activities that don’t add to the bottom line.”