ITechnology Interview with Rémi Lemonnier, Co-Founder & President at Scibids

“Cloud marketing leaders like IBM, Oracle, and Adobe are already shifting their focus to complete automation especially as adtech and martech continue to converge.“

Tell us the most cutting-edge AI trends you think would transform Marketing and Sales organizations.

We have seen firsthand how AI is transforming the performance of digital marketing. With the privacy-first era upon us, it’s essential that digital marketing leaders future-proof their media strategies and related advertising technology stacks. This is especially true for advertisers who focus on paid media and the surrounding ecosystem. To assist this group, Scibids AI deploys powerful ad decisioning with up to 70% performance improvement across all addressable media without using cookies, cross-site tracking, or PII to target users.

The marketing world didn’t need to read Google’s early 2021 announcement about removing support for third-party cookies to be reminded that it has a big problem with privacy in general and cross-site tracking in particular. Moreover, the end of cookies will dramatically impact advertisers’ ROI if they continue to rely on behavioral targeting techniques in the years to come. Fortunately, the knowledge exists to create privacy-preserving technologies that rise above the confusing and contorted, cookie-filled digital ecosystem that’s generated such animosity among consumers, web content, and the brands who pay for it all.

AI is raising expectations in marketing, and expectations should be high. Few industries present such an ideal environment for the deployment of machine learning — the scale is global and growing, the operational challenges are mighty, and data availability is near real time. And few industries are as important — digital marketing enables our global marketplace of ideas to thrive, which is why we think privacy-friendly AI will transform marketing overall.

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Please explain how KPIs have evolved for Marketing teams in the last 12 months amid the pandemic.

The pandemic created a rapid and dramatic change in consumer behavior, leaving marketers to rely on accountable and addressable marketing channels. Despite the overall slowdown in economic activity, we saw continued growth at Scibids —  meaning the channels we’re focused on are measurable, the impact is understandable, and spend is accountable. Advertisers are done optimizing towards clicks or visits. We have seen a shift to optimize towards deduplicated conversions that are measurable in external ad servers or maximize return on ad spend (ROAS) taking into account the amount of the purchase. Fortunately, Scibids AI is able to ingest these external data sources and optimize towards these true KPIs. In that context, Scibids saw more pressure on digital marketing to be a significant engine of advertiser sales growth. We have also noticed that advertisers investing in paid display, video, and mobile media buying prioritize finding and fixing campaigns that underspend and underperform, and Scibids AI helps them do that.

In light of the powerful automation that Scibids AI delivers for its clients, campaign managers, media buyers, and planners can turn their attention to growing their client’s efficient media investment opportunities yet further. The opportunity for marketers and their supply chains is to feed AI more relevant proprietary data to create and scale performance across more of the web. Sophisticated trading AI like Scibids can expand the utility and value of almost any proprietary data set by incorporating it throughout bid strategies rather than siloing it through dedicated, manual, and subjective tactics.

Which companies do you keenly follow within the marketing ecosystem as far as developing AI capabilities are concerned?

We’re very proud of the developments in AI coming out of France and these companies in particular have made an impact on the global marketing ecosystem. On the digital marketing side, Contentsquare uses AI-powered analytics and insights to drive revenue and ensure their customers never miss an anomaly, issue, or opportunity. We’re also big fans of Voodoo and how their engineering teams have leveraged machine learning to create innovative gaming and app solutions that drive growth and entertainment.

More globally we draw our inspiration from AI-driven companies like Deepmind, OpenAI or the best quantitative hedge funds in financial markets. They remind us that working hard to create deeply differentiating scientific assets can make companies massively successful.

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How does working in the cloud ecosystem influence the adoption of AI tools and products?

According to the Macroeconomic Impact of Artificial Intelligence report by PwC, AI will be the number one driver of GDP growth by 2030. The cloud ecosystem is helping to power that growth and how businesses and consumers interact with AI every day — in smart home systems like Amazon’s Alexa, in pocket devices like Apple’s iPhone, and in recommendation engines of all kinds. Indeed, AI has become so ubiquitous that if you use a device that doesn’t employ AI, you feel that something is wrong — that the device isn’t working well. Devices missing AI create a noticeably inferior product experience.

Scibids AI is accessed through the user’s demand side platform (DSP) and is easily customized via a simple UI with a light interface for supplemental input. It is engineered to understand unique business and campaign goals — including real-world constraints — to deploy unique bidding algorithms based on specific objectives and requirements. In addition, Scibids AI learns quickly and progressively from abundant, non-personally identifiable metadata from bid requests on websites to create better alignment between brands and consumers. Put simply, Scibids AI is engineered to deliver dramatically better results on paid digital marketing today.

As we should expect, the AI becomes smarter and more valuable to brands and their partners as more privacy-friendly information is made available to it — more media, data, and specificity around the KPIs that advertisers seek to scale. This scaling intelligence enables an ongoing and strong relationship between machine and human. For example, media planning and buying resources can magnify their impact by delivering more performant media the AI can scale.

What is the future of AI in Marketing and Sales? Would we see larger groups of marketing leaders shifting their focus to complete automation for Sales and Marketing trends?

As our lives become more digital, so, too, will marketing. To thrive, the digital marketing industry will need to demonstrate systemic respect for consumer privacy while creating reliable, scalable returns for marketers. Until now, privacy concerns were mainly addressed via regional privacy laws like GDPR or CCPA whose goals are to ensure that browsing data collected through cross-site tracking were not linkable to “personally identifiable information” (PII) such as an email or IP address. However, in 2021 important actors like Google Chrome and Apple have begun defining a new paradigm: they are actively preventing cross-site tracking, which hobbles nearly every current digital marketing use case.

To further complicate matters, several adtech players have been developing their own IDs, sometimes individually and sometimes via a consortium. The goal is to  preserve cross-site tracking as it is today. It is impossible to predict how these disparate efforts will resolve, meaning, unfortunately, that risks will endure for the foreseeable future.

Cloud marketing leaders like IBM, Oracle, and Adobe are already shifting their focus to complete automation especially as adtech and martech continue to converge. Given the scale of their platforms and audiences, investment in AI is essential to provide advertisers with an intelligent and automated ability to comply with privacy-first principles while having access to scalable and customizable technologies.

With powerful AI comes the opportunity not only to scale and optimize campaigns but to also improve the business process that surrounds them. That business process should be designed to give the AI as much latitude (and as few targeting constraints) as possible. This symbiotic relationship enables the best possible performance and scale, minimizing the human effort to manage specific settings and maximizing human effort to create the most scalable data and media environment for a campaign.

The future of digital marketing and the business growth it enables is bright. Privacy respecting AI can seize this opportunity to grow the category and the significance of digital marketing while reducing friction between consumers, brands, and the economic engine of the web.

At Scibids, we hope to enable the industry to move confidently beyond these issues and embrace a future in which the interests of consumers, regulators, brands, and the digital media supply chain are harmonized.

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Expert tip on how to grow an AI-focused Marketing Technology company:

My Scibids co-founder, Julien Hirth, and I are passionate students of math and computer science and have applied this training to our other passion — building AI to raise expectations in digital marketing performance. As a result, our team is constantly growing. We look for bright and brainy individuals who bring the right dose of crazy ideas to create new value for advertisers worldwide without reliance on personal information. 

Maybe most importantly, we try to build an environment where they will absolutely thrive, by promoting excellence, rigor, ownership, and collaboration in every decision we make. A well-known Silicon Valley motto states that the best tech companies hire “10x” engineers who can bring 10 times more value to their company than the average. At Scibids, we have the ambition that every Scibidsian becomes a “10x” AI specialist, building the Scibids team to be a “100x” team!

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