Every day, billions of people turn to Google to search for answers to questions big and small. Of all the searches we see, it's the complex tasks — like planning a family vacation or fixing a broken appliance — that are the most challenging to solve.
Unlike a simple task where you know exactly what you want — like “what’s the weather tomorrow?” — complex tasks require a broadening and narrowing of searches to explore a topic or find an answer. In fact, it takes people eight searches on average to complete complex tasks.1
At Google’s recent Search On event, we shared how innovations in AI are helping make the world’s information more helpful, while empowering people to tackle complex tasks faster and easier than ever before. And that has implications for consumers as well as the marketers trying to reach them.
Complex tasks take an average of eight searches to complete.
New milestones for understanding information
Since the announcement of the Multitask Unified Model (MUM, for short) earlier this year, our consumer teams have been experimenting with its capabilities to help solve complex tasks. We saw a preview of what’s possible at Search On.
MUM represents a significant leap forward in Google’s ability to understand information and deliver better Search results. It’s one of our first multimodal AI models, meaning it can understand information across a wide range of formats simultaneously — like text, image, and video. In addition, it can unlock information in new ways by inferring connections between concepts, topics, and ideas.
Taken together, these latest advances will enable entirely new ways to search by helping Google understand complex tasks and questions in ways never before possible.
Better answers for complex tasks
Imagine you’re enjoying a Sunday afternoon bike ride when you notice that your gears stop shifting. You can see the problem with your bike, but you don’t have the words to describe the issue. If a bike mechanic was nearby, you might point at the issue and ask for their advice.
Soon you’ll be able to use Google Lens to do just that. By pointing your camera and asking, “how do I fix this?”, Google will be able to identify the problem — in this case with the rear derailleur — and connect you to helpful information across the web to fix it, like a YouTube video.
In fact, we recently added the ability to pinpoint key moments in videos — directly from search results — so that you can jump to the content that’s relevant to you. The bike manufacturer might have a step-by-step troubleshooting video, or a content creator who’s passionate about cycling might have a how-to for a broken derailleur. Either way, you’re on the right path to fixing your bike.
Using MUM, Google could then surface “related topics” referenced in those videos and help you better understand the task in front of you. You might discover that the chain on your bike is worn out and needs to be replaced to prevent future derailleur issues.
These are just a few examples of what will be possible. As Google Search continuously improves, people will be able to tackle complex tasks faster and with better results, so they can get back to what they love, like enjoying a bike ride.
The need for automation is growing
With these updated search capabilities, it’s not hard to imagine all the new ways people will find answers to challenging questions and advance their discovery and exploration of topics that are important to them.
Some forward-looking advertisers are adopting automation across every aspect of their Search advertising campaigns.
To be successful in this new world, businesses will need to be ready for constant change by adopting an agile approach to make sure they show up across search in all the moments that matter. While search marketers have traditionally invested in manual processes and intuition to find their customers, build creative, and optimize for performance, this approach simply won't keep pace for most advertisers given the new ways people are searching.
Some forward-looking advertisers have already realized this and are adopting automation across every aspect of their search advertising campaigns.
Zalora, a leading online fashion platform in Southeast Asia, saw its campaign performance limited by traditional manual ad structures. With COVID-19 causing additional challenges, Zalora decided to rethink its Search strategy. The brand chose to adopt full automation across its campaign setup by expanding keyword coverage, using smart bidding to efficiently allocate budgets, and switching entirely from a last-click conversion model to data-driven attribution. With this automated approach, Zalora increased conversions by 137% while reducing its cost-to-income ratio by 9%.
As we look to the future, updates and innovations in Google Search will continue to create new ways for people to access information and connect with the businesses around them. Now is the time for marketers to get ready for what’s next and explore how adopting automation can help build long-term resilience and growth for the future.