TechBytes with Wayne St. Amand, Chief Marketing Officer, Visual IQ

Visual IQ

Wayne St. Amand
CMO, Visual IQ

Marketing Intelligence is a critical part of any Martech stack today. In this TechByte, Visual IQ’s CMO Wayne St. Amand take us through the nuances of multi-touch attribution, channel optimization and ad fraud and how a marketing intelligence platform benefits marketers.

Tell us about your role at Visual IQ and the team you handle.

As the CMO of Visual IQ, I oversee the global marketing strategy for our Marketing Intelligence Platform and work closely with sales leadership to drive revenue and growth for the organization.

How do CMOs build a flexible tech stack? What technologies would such a stack feature?

CMOs have a plethora of technology at their fingertips to help their teams be more efficient and effective. Modern tech stacks include core platforms, such as CRM and marketing automation systems, as well as additional tools for email marketing, search engine marketing, online and offline advertising and more. But the innovation in marketing tends to happen around the edges of these systems. Building a flexible stack means choosing vendors that allow you to test their software before doing a significant amount of implementation work.

Every marketing team faces challenges that are unique to their organization. There is no such thing as ‘one-size-fits-all’ in martech, and each organization’s stack has to be flexible enough to meet a variety of different needs. The ability to test and prove an application prior to a full implementation enables teams to be more flexible in their approach, and more successful in their efforts overall.

What do you mean by “precision” in reach strategies and attribution? How far are marketers from achieving that precision in their campaigns?

As consumers take a winding path toward the marketers’ desired KPI, each and every interaction offers an opportunity for the marketer to curate the customers’ brand experience. The more precise marketers can get in tracking those touchpoints, the more controlled that curation process can be.

However, if there are blind spots in the consumer journey, marketers lose their ability to reach, influence, and convert customers and prospects at critical points in their journey. Multi-touch attribution can help shine a light on those touchpoints. When done right, attribution enables marketers to track the entire consumer journey across marketing and advertising channels and tactics, and measure the impact of each interaction. They can then use this insight to curate better brand experiences while pushing consumers toward their desired KPIs, whether that’s an online conversion, in-store sale, content download or other desired outcome.

What are the key parameters in arriving at the “forecast of marketing goals”? Would revenue from tech adoption be a part of this forecast?

A successful marketing forecast starts by reviewing the business’ revenue goals and then working backwards to determine what key elements of a marketing plan can aid in hitting those revenue metrics. A marketing plan without a strong understanding of what the business is trying to achieve is not a good plan. Additionally, the entire organization needs to understand and agree on what the marketing department’s contribution is to the business’ end goal.

Another factor that CMOs must consider when forecasting goals and outlining their plan is whether the department has the capacity to achieve their goals. Often CMOs only think about the budget they have to work with, but not the resources required to deliver on those goals. It’s crucial for CMOs to consider whether they have enough people to execute against the budget and plan.

Finally, CMOs need to consider if their martech stack is an accelerator toward the business goals, or if it’s simply getting in the way. Sometimes a marketing department can achieve scale through technology instead of hiring another person, but CMOs need to weigh this carefully as they put their plan together for the year to come.

On what basis can B2B marketers decide their strategy for “daily channel optimization‟? Would this decision be based on the size and marketing goals of the company?

The need for real-time data cuts across companies of all sizes and an ever-growing list of tactics. For marketers that use advanced multi-touch attribution, where data is refreshed on a daily basis, the ability to optimize channels and tactics in near real-time becomes much more feasible. Today, programmatic platforms are the norm, and they require the most accurate and up-to-date metrics to inform buying decisions. If a marketer’s ability to analyze data isn’t moving as fast as their execution platforms, then there’s going to be a problem.

Would 2018 witness tighter controls on ad fraud, transparency, and data privacy?

In 2018, we will see tighter control and less ad fraud simply because visibility into the problem has never been greater. Advertisers are less prone to invest in channels that don’t create ROI for them, and ad fraud is inherently ROI-free. Marketers won’t invest in fraudulent placements that only deliver empty clicks. The technologies that are gaining speed with marketers are those that delivers visibility into meaningful conversions and business impact. With greater visibility into what’s truly working, ad fraud will start to lose its grip.

On the data privacy side, the advent of GDPR has put a lot more regulatory pressure on companies as it related to data protection. In 2018, brands are going to have to figure out how to deliver their best marketing to the right people while still being compliant — though it will likely take several years to create meaningful solutions and approaches that work.

How do you see the martech buying process maturing in the years to come? Would AI be of any help to CMOs in picking the right technologies for their businesses?

The way martech vendors sell their solutions in the year ahead will be less about “selling” and more about helping CMOs determine if the technology is a good fit in the first place. The buying process for CMOs has always been about their ability to test. I expect more and more vendors to offer paid pilot programs that help CMOs determine fit and usefulness prior to a full-scale implementation. These types of programs will help CMOs make better decisions about which tools to add to their martech stack.

Although AI is mostly a marketing buzz word at this stage, any CMO evaluating a martech solution will look for some evidence that the vendor roadmap includes AI or machine learning. Marketing has become a data-intensive practice, and AI and machine learning can help marketers do a better job at sifting through all this data to uncover patterns and trends at scale.

Thanks for chatting with us, Wayne.
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