TechBytes with David A. Yovanno, Chief Executive Officer, Impact
David A. Yovanno
Chief Executive Officer at Impact
When most people think of partner marketing, they think of traditional affiliate marketing, which has been one of the top three paid marketing channels for decades, alongside search and email. We spoke to David A. Yovanno, Chief Executive Officer, Impact, to understand partner recruitment from a current B2C commerce perspective and how technologies such as AI/ML and virtual assistance could disrupt it.
Tell us about your role at Impact and the team/technology you handle.
As the CEO, I am responsible for the development of the company’s short- and long-term strategy, and creating and implementing the company’s vision and mission. Core to our vision is our belief that science and technology have the potential to massively transform business.
Impact’s technology solutions entail a platform strategy that is creating a Partnership Marketing Cloud, which includes a natively integrated big-data back-end for data tracking and ingestion, data normalization, reporting, identification, audience-building, and single sign-on for four main products: Forensiq for fraud protection; Altitude for multi-touch attribution and unified marketing measurement; Radius for creating and optimizing performance partnerships; and most recently, Mediarails, CRM and marketing automation software for discovering, recruiting and engaging new performance partnerships. AI is also woven into our product set for identifying fraud, marketing automation and predictive analytics for example.
How did you prepare the company for the acquisition?
Impact has experienced tremendous growth in the last two years — doubling both revenue and number of employees. Adding Mediarails to the Impact suite was a natural next step in our evolution, born from recognizing a consistent theme with our Radius clients, in particular. Our clients typically migrate their affiliate and partner marketing programs from a legacy network model, which typically intertwines agency-like services with legacy technology, to the modern SaaS model with Radius. In doing so, most clients experience 50+% channel savings due to the advanced capabilities and efficiencies of the Radius platform. Adding Mediarails provides an outlet for those savings to be invested back into the channel through automating the discovery, recruitment and engagement of new partners to drive growth.
Define Partner Recruitment from a current B2C commerce perspective?
When most people think of partner marketing, they think of traditional affiliate marketing, which has been one of the top three paid marketing channels for decades alongside search and email. Traditional affiliate marketing includes primarily cashback, loyalty and coupon sites to drive customer acquisition. However, this performance marketing channel has experienced a sort of renaissance over the last several years, largely driven by the rise of native advertising, influencers, demand from traditional media publishers and B2B performance partnerships®.
From a B2C commerce perspective, think of it in terms of how Uber utilizes performance partnerships® to promote their service. A relevant influencer is engaged to promote rides to their audience on Instagram for example. This is where Mediarails adds value to our offering: automating the discovery of that new marketing partner or influencer, then automating the recruitment and engagement process.
How do you think new technologies such as AI/ML and Virtual Assistance could disrupt Partner Recruitment and Engagement Automation?
That’s exactly what we’re doing with Mediarails. Automation is the key differentiator in this offering. By bringing automation into the partner marketing process, marketers are given the opportunity to step back and assess the program from a holistic and strategic view. The platform enables performance of individual partners to be assessed in real-time, and automatically outreach to that partner for alerts and assess if they need assistance. Without automation, those CRM-management-type tasks would all need to be completed manually, taking valuable time away from our clients’ marketing programs. We also believe that AI can assist with better matchmaking of brand and marketing partners, that is identifying who is ideally suited to work together.
Which group of customers and markets are best suited to benefit the most from your recent acquisition?
It all comes down to why we made the decision to acquire Mediarails in the first place. Those who are best suited to benefit from this move are brands and agencies who see the benefits of the SaaS model in partner marketing, and are demanding efficiencies to scale their partner marketing programs. In order to take advantage full advantage of these efficiencies and properly reinvest them back into the channel, it is imperative that performance marketing teams do real recruiting, and cast a wide net. Using the automation of the Mediarails tool, performance marketers can reinvest original savings into real recruitment, resulting in traction not seen previously. So basically all marketers who place growth in their programs as a top priority.
Could you tell us more about your Performance Partnership® program?
Performance Partnership® is actually the program of an Impact partner, Acceleration Partners.
How do you think organizations are doing with their marketing tech stack and how will that change in the future?
I think all marketers originally set out to build a super-stack of marketing capabilities. Yet instead of a super-stack it seems what many of us have really built is a “Franken-stack” — a stitched-together stack of tools that are supposed to integrate and feed into each other — but in reality end up creating a beast that is built on bad data, error prone and a time-suck to manage. And this Franken-stack seems to be functioning when it provides answers that make sense at face value, but when you start to dig deeper, the answers aren’t sound by any analytical standard.
Marketers need to start working towards their super-stack, which will be able to track and ingest all marketing data (online and offline) at the event level. This will result in a system of record that can deliver true actionable insights that drive real business growth. So I think you’ll start to see more integrated solutions that reduce or eliminate overlap while creating greater efficiency. Armed with this kind of insight and capabilities, marketers will have the tools, knowledge and confidence to form the best marketing partnerships possible to drive growth in their business.
How do you work with AI and Programmatic technologies for analytics?
Both our Forensiq (fraud detection) and Altitude (marketing system of record for unified marketing measurement and attribution) technologies work with machine learning and AI.
For Forensiq, we leverage machine learning to tease out patterns and meaningful insights from big data that then inform our fraud detection algorithms. Some exploitative activity can be discovered through simple processes on various lists and disreputable IP addresses, or by network monitoring to flag new types of anomalous events. But the hard stuff — the fraud patterns created by really experienced bad actors who have learned, through years of informed experiments, how to evade detection — that can only be found through data mining, AI and machine learning. Big data, AI, and machine learning are central to how we locate the most damaging types of fraud. By outpacing emerging fraud techniques, Forensiq facilitates fearless traffic expansion across advertisers’ performance marketing and digital advertising campaigns.
Our Altitude product harnesses machine learning algorithms designed by Impact’s master team of data scientists, to attribute credit across all touchpoints in the consumer’s journey to conversion through a unified approach that leverages both bottoms-up multi-touch attribution and top-down media mix modeling. Machine learning ensures that credit is attributed across media events in the fairest way possible in order to remove human bias, incorporate externalities and measure incremental lift, so that marketers can best determine which of their media investments are working hardest to deliver the greatest impact.
This attribution process is important in understanding which elements of marketing investment are driving incremental business results. AI is then further leveraged for predictive modeling and scenario planning to help our clients determine the optimal places to invest their next marketing dollars.
Thanks for chatting with us, David.
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