Predictions Series 2022: Interview with Assaf Egozi, CEO and Founder at Noogata

Hi, please tell us about your journey into the technology space and how you started at Noogata.

I started at university studying computer science and economics because I wanted to become an engineer. But I quickly realized that I was less interested in building the technology than working with people to understand how the technology can be applied to solve business problems. So I joined McKinsey, where I spent ten years working with enterprises and learning about their processes and challenges. I also completed an MBA along the way. In 2014 I left McKinsey to explore the opportunities for Big Data to make a real difference to enterprises and business decision making. I spent five years working with start-ups and VCs in this space before founding Noogata in 2019. Ultimately, I wanted to make data and advanced analytics more accessible and usable and drive real-world business processes.

What is Noogata and what solutions do you currently offer to enterprise customers?

Noogata delivers a no-code artificial intelligence (AI) platform for citizen data analysts – business users across all enterprise functions, who need to quickly and easily turn their data into actionable insights that drive business decision-making to enable them to compete more effectively, fuel growth, or optimize cost. Noogata’s platform enables these analysts to easily connect their data to our AI blocks, which integrate advanced AI capabilities applied to solve core questions and use cases. We have well-established blocks for e-commerce and have just launched our location analytics library, which is a series of blocks specifically geared for field sales and marketing teams looking for insight and analysis around physical locations. We are continuously adding more libraries and blocks to our platform, covering a growing set of enterprise business functions and use cases.

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What does your Ideal Customer Profile look like? Which industries and titles are you currently focusing on?

We’re currently focusing on the CPG and retail industries and are targeting the e-commerce, field sales, marketing, and product teams within these companies.

These organizations are becoming more focused on leveraging data to drive business decisions, with substantial pressure to implement smarter and more flexible capabilities to compete against the new, digital-native brands.

What future do you see for No-code AI frameworks? Which businesses would benefit the most from the adoption of No-code computing platforms?

No-code AI frameworks are absolutely critical to the widespread use of Big Data within enterprises. Today, almost all business professionals are citizen data analysts, and enterprises must find a way to give their data citizens better tools to process, analyze and use data across every aspect of business decision-making, from sales to operations to HR to finance. No-code AI lies at the heart of this immense digital transformation.

We know that AI use cases can be focused on driving increased sales or profit, but equally, they can be about improving productivity, reducing costs, or enhancing supply chain efficiencies.

Please tell us about the biggest challenges and opportunities you met in 2021?

2021 has been crazy. As the world started opening up a bit, there was the opportunity to do some more travelling and meet teams and investors face to face. At the same time, we were focused on our key customer relationships and starting to onboard new customers while also working on expanding our libraries and building new blocks, including the location analytics library which  we launched in November.

It certainly feels like many of the opportunities are also challenges! But with the support of a great team including our new Chief Revenue Officer, Fleur Sohtz, we’ve been able to continue to work with customers, build new blocks and engage with current and future partners.

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You recently announced Location AI Analytics. Could you further elaborate on the technology and how it makes a Sales team or a CMO’s job easy?

Location analytics allows enterprises with a brick & mortar presence  to leverage huge amounts of data to optimize their real-world footprint, and it works for current locations as well as when identifying potential new locations.

For CMOs and sales teams, the location analytics blocks mean they can get real insight into what’s happening in their current stores. They can combine their own data with external data sources, which helps them to understand which locations are being under- or over-resourced, where there are untapped growth opportunities, and analyze product assortments to optimize field sales.

We saw how the CPG and e-commerce industry became one of the biggest AI ML adoption centers in the COVID era. Could you tell us about the future of AI practices for the CPG industry? How is it different to serve this market compared to other B2C/ B2B/P2B markets?

E-commerce growth was accelerated massively by COVID. McKinsey reported that U.S. e-commerce penetration doubled in the first quarter of 2020 alone. For the large CPG brands this presented both a real threat as well as growth opportunities. E-commerce platforms, unencumbered by shelf space constraints, allow for a much longer tail of competitors, and search-based purchasing process means consumers can find niche brands more easily, making it challenging for the larger brands to maintain the same market share they are used to in the bricks & mortar channels. On the flip side, these platforms also provide a much richer set of data for CPG players, allowing them to get closer to their customers, and identify trends and unmet needs in ways they could not systematically do before. To make sense of all this newly available data, effective use of AI is critical, and we’ve certainly seen many brands embrace this opportunity. For example, we’ve seen our customers leveraging our platform to continuously improve their products’ positioning – price, description and use of promotions – to capitalise on trends and grow market share. The value that analyst teams can derive from AI in this context cannot be overstated. .

Your predictions for the year 2022- what does your product development roadmap look like for the coming year?

We have an exciting product roadmap for 2022!

On the platform side, we will be releasing a self-serve capability in Q1, allowing business users to use a core selection of our blocks on Noogata.com for the first time, without the need for an enterprise deployment. In addition, we will be enhancing our integration with leading cloud providers and BI tools.

On the libraries side, we are continuing to expand our e-commerce and location analytics libraries, and we will release our next two libraries in Q1 and Q2 of 2020 – Brand marketing, which targets the CMO function as well as media agencies, and catalog analytics, which is geared towards the operations and catalog teams at retailers.

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Your thoughts on leveraging AI, Blockchain, analytics and automation for Marketing and Sales functions:

Marketing and sales functions have huge opportunities to benefit from AI and ML. Increasingly,  today’s enterprises have astonishing volumes of data on their products, their business and their customers and can also access similar data for competitors or the market as a whole. By applying these tools to decision making, teams can make better decisions about advertising, pricing, distribution and more. Sales teams can focus their efforts where they’re most likely to see the benefit and increased sales.

It also allows a much higher level of monitoring and reporting. A campaign or product change can be tracked in real time and the results analyzed.

Thank you, Assaf! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]