Search Marketing Influencer Series – Chris Knoch (Part 1)

Chris Knoch - Search Marketing Influencer Series

Chris Knoch is President of Big Squid Interactive. Chris pulls from a wide array of experience across agencies, digital ad technology, and consulting roles while still acting as a day-to-day marketing practitioner and industry evangelist. Chris and his team at Big Squid develop integrated solutions across SEO, analytics, paid search, affiliate marketing, display, mobile and social marketing.

Now that we’re firmly into 2016, what do you anticipate as the evolution of SEM, particularly as it pertains to local search?

One reason why we have been so successful in SEM up to now, compared to other parts of the digital ecosystem (display, video, etc.), is because we have had a much easier time proving ROI around it, since the majority of our campaigns focused on last click or “direct click to action.” As a result, we typically met or exceeded performance goals and consistently grew search budgets with our customers.

One thing concerning me as we move into 2016 is that many of these same search executives, now in more senior roles, have come up through the ranks viewing digital advertising as marketing by numbers – via spreadsheets and through tools like Google Analytics, Site Catalyst, etc. As a result, there could be an assumption that we do not pay close enough attention to our customers, to the user experience, or to other related brand interactions. It’s something I constantly stress with my team: always keep the customer at the center regardless of the latest tech or targeting innovation.

Good Point. It sounds like you see 2016 as the “year of the customer.”

More specifically, the ​mobile ​customer. Android, iPhones, and smartphones in general have become pervasive. This only happened in the span of 5 years. In 2016 we are creeping ever closer to full marketplace adoption. Now we are seeing the early incarnations of AI and machine learning – via the likes of Siri, Google Now, and Alexa – dynamically offering suggestions based on proactively anticipated needs versus waiting on a consumer’s expression of intent.

When it comes to local search, 9 times out of 10 we are doing it on our phones. The results we receive allow us to immediately connect with businesses directly or find the shortest path for getting there. Not to mention they come chock full of reviews, social mentions, photos, and other pertinent details that help a consumer navigate through their search experience. Add AI or machine learning to the mix and users ultimately becomes less of a decision factor, as technology is essentially doing the “thinking” or “heavy lifting” for them. For example, land in a new city, open Google Now, and watch your smart phone automatically make suggestions on where to go for lunch, where to sightsee, or where to shop.

Are you saying search as we know it is over?

In the last couple of years, we have gone from searching to being told what to do, particularly on Android handsets. Google’s Eric Schmidt said it 2 or 3 years ago, “We want to know what you want to do before you look for it.”

In many ways as an industry we are getting close to such a reality via smartphones and local – AI machines learning what we might be looking for based on location, app usage, reviews, previous searches, purchases, etc. In addition to location, suggestions would factor in weather conditions, a user’s calendar, traffic, and so on. Even more compelling when these results are integrated with local services and review sites from YP, Yelp, 4square, and TripAdvisor (to name a few).

By shifting to more anticipatory platforms in the face of AI’s spontaneously making better, more relevant suggestions, how does this change the search practitioner’s workflow?

The number one result has never been more important. When I ask an AI what to do, it will tell me what to do. It will not offer me “these 10 things” and click the next page for more.

Being in first position is more vital than ever since users will be provided with the perceived best results without ever actively searching for those results. It’s also worthwhile to mention that a portion of this is due to the lack of space on mobile SERPs. There is just not enough space to display a neverending list of results.

To be continued…in Part 2

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