MarTech Interview with Chris Gladwin, CEO and Co-founder at Ocient

A good data-privacy policy can actually benefit both marketers and end users; Chris Gladwin, CEO and Co-founder at Ocient dives deeper in this Q&A:

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Welcome to this MarTech Series chat Chris! Tell us more about your B2B/Tech journey and also, we’d love to hear about Ocient.

It’s my pleasure to be in touch. My journey throughout B2B tech includes starting and exiting companies that service persistent needs for large addressable markets. Prior to Ocient, this included starting Cleversafe, the leading data provider of the largest data storage systems in the world.

While on that journey, I consistently heard from customers that they needed a way to analyze their massive datasets – datasets that were only continuing to grow at exponential rates. With the introduction of new industry hardware, fast networking and high-core-count processors combined with our background in storing massive datasets, I co-founded Ocient in 2016 to rapidly analyze the world’s largest datasets at speeds and performance levels previously unheard of.

At Ocient, our focus extends beyond data analysis to the transformation and loading of complex data types as fast as possible so customers are always up to the minute, while also enabling them to query, or analyze, more data to generate precise and valuable insights. We also enable customers to plug into powerful visualization tools fairly seamlessly, so they can carry forward their insights into new products, services and revenue streams that empower multiple parts of their organization as well as their customers.

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Take us through the key fundamentals of Ocient’s recent collaboration with MediaMath, and how that will change the game for end users.

MediaMath handles more than six million bid opportunities per second with 10-12 petabytes of new records per day. That’s a ton of data! The solution we built for MediaMath enables their customers to plan their advertising campaigns with higher resolution insights, leading to more accurate predictions across various engagement points – including connected TVs – with less waste and higher ROI. In AdTech, demand- and supply-side platforms may otherwise be looking at smaller samples of their data, or creating “rollups” to approximate results. The volume of data is just too large or cost prohibitive to process high enough volumes with older, legacy technologies, meaning the technology platform is likely to miss needle-in-the-haystack insights that will provide customers with more competitive insights.

One of the challenging parts about working with hyperscale data is the speed and scale required to get data into the right system and format to quickly execute massive analytical queries. At this volume, moving data around, getting it into a system, transformed, indexed and queryable in a fast and efficient manner is a feat in and of itself.

For this reason, Ocient has adopted a solutions-first approach. We don’t just sell a technology product. We partner closely with our customers to build end-to-end solutions that ingest data continuously, making it available for query in seconds. We help index data, we write and test queries, and we ultimately develop a production-ready solution tailored to our customers’ business requirements.

This approach ensures customers like MediaMath have a tailor-made solution without investing the intensive time and resources typically required to customize and optimize a technology like this. Our ability to deliver a complete and fully functional solution enabled MediaMath to save months of custom engineering time and investment which, in turn, means their customers can start utilizing this new, highly requested product faster.

Why should marketers and advertisers today be more strict about their campaign insights and how they procure this information?

The digital media landscape is expanding as consumers adopt new technologies like connected TVs, connected vehicles and other “smart” technologies. All of these create new pathways to reach and engage consumers in more contextual and intelligent ways. There’s no way to do this without analyzing massive complex datasets in near real time. The ability to create more targeted segments, find more impactful moments, and personalize branded messages is facilitated by data analysis of trillions to quadrillions of records happening in seconds.

At the same time, data privacy is of utmost importance and marketers must therefore be diligent to ensure the technologies they use to target, reach, and engage audiences will not only enable them to stay on top of an increasingly fragmented landscape of high- volume data, but to also do so in a privacy-safe way.

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How in your view can marketers and advertisers further optimize their campaign measurement and execution tactics given today’s typical challenges?

As digital ad spend grows, so will ad fatigue across digital platforms. Ensuring you have the highest fidelity insights possible when planning and managing campaigns will be key to future success for marketers leveraging digital media.

What will the future of AdTech shape up to be, given today’s dynamics and innovations?

Given the explosion of data volumes across more objects and platforms, AdTech firms have an opportunity to create deeper data pipelines from emerging avenues leveraging data from sensors, connected vehicles, smart moving objectives, and from Internet of Things (IoT) devices. The ability to go beyond “screens” and digital audio to advertising through connected objects and reaching audiences in motion will be interesting challenges to tackle. AdTech firms may also develop strategic services to enable marketers to tackle complex data pipelines and create more personalized engagements with their audiences.

We’d love to hear a few thoughts on your views on the global MarTech and AdTech industry and what are some of the most innovative solutions and features from around the world that have grasped your attention and why.

The big trend in MarTech and AdTech is that the volume of analyzed data just keeps getting bigger and bigger every year – and there’s no end in sight. This makes the field ripe for innovation and we look forward to being at the forefront of that evolution with leading organizations like MediaMath.

Some last thoughts and takeaways, before we wrap up!

At Ocient we have the opportunity to work with and learn about the largest data analysis systems in the world.  And one of the things we’ve learned is that AdTech has become an industry where the solutions are as large, complex and challenging as those in any other industry.  As a result AdTech is attracting many of the most experienced and most talented technologists and it has been really fun to get to work with many of these people.

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Ocient is the leading hyperscale data solutions company that enables organizations to unlock value by analyzing trillions of data records at performance levels and costs previously unattainable. Leading organizations around the world trust Ocient’s team of industry experts to design and deploy proven complex solutions that enable and fast-track new revenue opportunities, streamline operations, and improve security on 5-10x more data while reducing their storage footprint by roughly 80%. Ocient’s pilot-to-production solutions are rapidly deployed on-prem or in the cloud with little to no resource-intensive integration. Ocient is a carbon-neutral company, headquartered in Chicago, and backed by leading investors including Greycroft, OCA Ventures and In-Q-Tel.

In 2004, Chris founded Cleversafe which became the largest and most strategic object storage vendor in the world (according to IDC). He raised over $100M and led the company to a $1.4B exit in 2015 when IBM acquired them. The technology he started generated over 1,000 patents granted or filed, creating one of the ten most powerful patent portfolios in the world. Prior to Cleversafe, Chris was the Founder and CEO of startups MusicNow and Cruise Technologies, and led product strategy for Zenith Data Systems. He started his career at Martin Marietta, and holds a mechanical engineering degree from MIT.

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