Google hosted an event in Vancouver on March 1st, 2018 called “Decoding the New Consumer”, which promised to help attendees unlock the power of data and machine learning to reach new audiences.
This is an exciting topic for anybody working in digital marketing and advertising today, and I wanted to share some key learnings and highlights from the event. Eight of us from 6S Marketing attended, with everyone from senior leadership to project managers and digital marketing strategists.
About the Event
“Finding the right buyer, at the right place, and delivering them a customized message that turns them into a loyal customer, is not a new business goal.
However, innovations in consumer-based data analytics and machine learning now make realizing this goal more achievable than ever.
Decoding the New Consumer is a full-day event that equips attendees with strategies to unlock the power of their data and utilize machine learning to tap into new insights and new opportunities. Insights are then driven to action through campaign building workshops tailored to their business goals.
During this exclusive full-day event, you’ll collaborate with audience and marketing experts to:
- Learn how changes in consumer behavior have created new marketing opportunities
- Understand how data analytics and machine learning can optimize your ability to touch and influence customers along their new path to purchase
- Build a prioritized, action-oriented campaign that aligns with your business goals”
A Brief Summary
The event was MCed by Nate Stone who is the head of Google Agency Partners. Early in his opening talk, I recognized some key messaging that is becoming familiar. Google has been talking about micro-moments for a few years and they are defined as: “micro-moment occurs when people reflexively turn to a device—increasingly a smartphone—to act on a need to learn something, do something, discover something, watch something, or buy something. They are intent-rich moments when decisions are made and preferences shaped.”
Some new messaging that I have heard and has struck a chord with me was a statement about Google’s approach to newer evolving technologies.
“Google was late to mobile, but we are not going to be late to AI and machine learning.”
I have heard this from several Google employees over the last few days. Nate continued, “Machines understand what we say and now we are talking to them like they are our friends. Today’s consumer is curious, demanding, and impatient.”
Today’s Consumer is Curious.
Nate explained that for both big and small decisions, consumers are using search to ask more unique and varied questions than ever. They want to find the “best” and in the past two years, mobile searches for “best” grew by 66%. For example, mobile searches for “best toothbrush” have grown by more than 150% over the past two years. They also want other’s opinions and searches for reviews on mobile have increased by more than 200%. Today’s consumers define what’s high vs. low consideration for themselves. By understanding when and where people are searching, brands can be ready to show up with the right advice whenever people need it.
Today’s Consumer is Demanding.
They expect technology to know what they want and cater to them personally, without even having to ask. Google has seen a rise of context-free searches and in the past two years, mobile searches for ‘where to shop’ and ‘where to buy’ have grown by more than 100%. According to Google, there has been a rise in conversational searches such as ‘What’s the weather today?’ and these are up 89% since July 2015. Inferring and interpreting context will be crucial. Focus on capturing and using as much contextual information as possible to truly understand what consumers are looking for and deliver on their expectations.
Today’s Consumer is Impatient.
Whether they are searching for answers, completing tasks, or making purchases, consumers want to act immediately and get things done instantly. They’re looking for timely information and in the past two years, search for “open now” has more than tripled. 53% of mobile site visits are abandoned if they take more than three seconds to load. They want to buy things at the last minute. In the past two years, mobile searches related to “same day shipping” have grown 160%. Google recommends that brands need to be fast and frictionless and that high-speed online experiences are now table stakes.
Emily Meinke, Agency Lead, kicked off the event with her talk titled “Beyond Demographics.” She referenced a quote from McKinsey that I have likely botched but the key message still shines through:
“This is the dawn of marketing’s golden age, and those that don’t evolve and adapt will be left behind.”
Spotify is a company that Google likes to showcase. Emily presented an example of how machine learning is used by Spotify to understand who you are and what you want to listen to. She showed us the Spotify billboard that said: “Dear person who played ‘Sorry’ 42 times on Valentine’s Day.”
What Spotify is demonstrating is that they understand us, and it’s not based on demographic information but rather the information and communication that we are consuming.
The key message that I took away was that we need to understand the new consumer and their intent, identity, and context. Understanding your audience and delivering content to them at the right time is crucial. Who are they? What are they interested in? How to find more people that behave like them.
Next, we heard from Jason Fahlstrom, Executive Summits Evangelist, ML & Performance at Google. His talk was about “Demystifying machine learning: A marketing view on AI.” He started things off with a bold statement: “Google wants to become an AI first company.”
Jason talked about Waymo and how Google’s self-driving autonomous vehicles work. The following video was released on February 28, 2018, and describes it perfectly.
Next, he chatted about other machine learning examples and practical uses such as Blue River’s Precision Weed Control Machine. This video demonstrates this very cool farming technology.
He also shared a few key definitions.
Machine Learning: “Machine learning is the science of getting computers to act without being explicitly programmed. – They learn from examples.”
Deep Learning: “A technique of machine learning where algorithms arranged in layers that mimic the human brain’s learning patterns (neuro nets).
The last speaker before lunch was Brooke Taylor, Audience Engagement Specialist from Google New York. She talked about Google’s ability to use machine learning and AI to deliver custom ads based on data that it analyzes in a split second.”In the blink of an eye, Google is able to analyze 70 million signals” to deliver relevant ads.