People are increasingly searching for products on the go, with 50% of people searching for products on their mobile devices. It’s more important than ever for marketers to have an omnichannel people-centric approach to marketing that helps consumers pick up where they may have left off with searches from their mobile to their tablet or computer.
In the first part of this series on the future of search, we shared how advanced voice search is changing the game for marketers. Now, let’s dive into the value and opportunity that advanced visual search holds for marketers seeking to help consumers find products they love.
Visual search algorithms can use an image as a query instead of text, according to Search Engine Watch. When consumers shop online, they rarely start with text. They’re thinking of an item they saw, so they’re using descriptors as keywords, i.e. “red clutch brass buckle.” Social media platforms are catching on to this trend to create new and exciting ways to take consumers down an image-first sales cycle.
Case in point is Pinterest Lens, launched in November 2017. Since then, an average of 600 million visual searches per month have been performed through Pinterest. More recently, Snapchat announced that it’s partnering with Amazon to allow users to scan a physical object or barcode, which brings up a card showing that item and similar ones on Amazon Prime and other websites. These are just two new advertising opportunities brands can consider incorporating into their paid social media strategy.
Let’s take a look at three ways advanced visual search is changing how people search, along with the opportunities available to marketers with these new capabilities:
Reduce the “Discovery Problem” in Retail
The Discovery Problem happens when shoppers have so many options to choose from on a retailer’s website that they stop shopping altogether—the horror! To help shoppers stay the course, marketers are retooling their digital offerings with visual search because content with relevant images earns 94% more viewers than ones without images. When people see something they want and only a few other related options, they’re more likely to go through with a purchase.
Knowing your audience is and always will be of paramount importance. It’s safe to assume that Gen Z or consumers ages 17-21 prefer this way of shopping: 69% of young consumers show an interest in making purchases based on visual-oriented searches alone. The future of visual search will depend on how effectively brands optimize visual search capabilities to meet their target audiences’ searching preferences and needs.
Amplify SEO Insights with More Data
Scientifically, thinking visually first makes sense. A study by MIT found that 90% of information transmitted to the human brain is visual. Creating technology that can understand and process images as quickly as the human mind is a massive undertaking. Recent advancements with machine learning enable images to be processed and uploaded to a search engine which is then able to generate visually similar results. As more images are uploaded, classified, and “learned” by search engines, more search results become available.
What does this mean for marketers? To optimize for visual search, marketers need to ensure that the metadata on their brand’s website images are update. This means their current SEO efforts might not cut it. All titles, alt tests, and descriptions must contain proper keywords so users can easily access them. Secondly, size matters. Marketers should select appropriately sized images to ensure consumers can easily get a solid visual of what they’re searching for but not get frustrated by an unnecessarily large image that takes too long to load.
Leverage User Insights to Uncover New Marketing Opportunities
Marketers can gain insight into their customers’ visual buying preferences by using social listening tools to identify trends. When computer vision is applied to social listening platforms, marketers can gather details about when the products are being used and the sentiments of those who are using them. This can help uncover unique marketing opportunities.
For example, Starbucks searched social feeds for its brand logo and it discovered that a number of images displayed dogs enjoying “puppucinos” (yes, it’s as cute as it sounds). Without this image analysis, Starbucks would have been unaware that dogs and dog owners are a valuable target.
Image analysis and machine vision can help brands stay a step ahead by predicting future trends. This insight allows retailers to spot gaps in product lines and base future designs and updates on it. This can create a more customer-centric strategy that is flexible and responsive to the interests of consumers and brand advocates. For example, Home Depot analyzed what was trending on Pinterest in terms of color palettes and decorating trends and used the insight to create a video for its “Built-in Pin” campaign.
Marketers will need to continue to adapt to changing visual search habits as Pinterest, Instagram, and Snapchat push the envelope in the evolving visual search landscape. Optimizing advanced visual search capabilities will help attract more website traffic, boost search results, and gain a better understanding of target audiences’ buying preferences and patterns.
What to know more about marketing and technology trends? Register now for RampUp 2019 in San Francisco on Feb. 25-26, 2019, to hear from more than 100 thought leaders in the industry.