With over 1.8 billion photos uploaded to social media platforms every day, it is no surprise that new technologies are constantly being developed to support an ever-growing visual world. In fact, people process images 60,000x faster than text alone. That said, social media platforms have begun amplifying their efforts to not only help consumers engage with visual search, but also aid marketers in leveraging this convergence of visual and data technology. So how are social platforms incorporating visual search elements? Read on.
Platforms Getting Involved WITH VISUAL SEARCH
Twitter + VISUAL SEARCH
Emoji Targeting: In June 2016, Twitter announced an expansion of their targeting capabilities with Emoji Targeting. According to the platform, over 110 billion emojis have been tweeted since 2014, which means a big opportunity for marketers. Emojis reveal sentiments of Twitter users which will allow marketers to target based on their feelings, passions, preferences, reactions, or wants. For example, if a user tweets a pizza emoji, brands such as Pizza Hut and Domino’s can target those users.
What Marketers Need to Know: Emoji targeting is an intriguing glimpse into the future, in some instances, however it could prove challenging for marketers. Many tweets boast superfluous uses of emojis that do not reveal information about the user, or worse, incorrect information about the user. It is difficult to understand the intent of the emoji; whether they use it as a joke, ironically, or actually mean it. Marketers should be mindful about audiences before jumping too quickly into emoji targeting – if ads are served to the wrong audiences through emoji targeting, it could effect a brand’s reputation.
Pinterest + VISUAL SEARCH
Automatic Object Detection & Visual Search: In June 2016, Pinterest announced two new features that will help users connect with products they love. First, automatic object detection will allow users to search for selected items in a pinned photo. For example, if a user finds a photo of a bedroom, the visual search icon will highlight all the searchable objects – things like the bed, night stand, lamp, and rug. Automatic object detection went live on the platform in July of 2016.
The second new feature Pinterest is bringing to the platform is visual search. Visual search will allow users to take a real-world photo of an object on Pinterest and the app will pull up shopping results for items that look similar. This could be used to identify anything from furniture to clothing items. Visual search will go live in late 2016.
What Marketers Need to Know: Pinterest has become a leader in ecommerce. Initially facilitating the information search phase of the consumer journey, these new features will help close the transactional loop. It is important to note the sponsorship opportunities in the future as well. Marketers may be able to sponsor lookalike items when Pinterest users engage with either of these new visual search features. However, the feature could also siphon audiences to other brands. Consumers may use Pinterest lookalike search features to find competitive pricing on certain products featured in pins, which could affect organic traffic and sales.
Image Recognition Agencies
Image Recognition Analysis
New firms and services are emerging that are pioneering visual search marketing and analytics. These services will search through photos on social channels and find commonalities with objects, logos, and some other attributes. Currently the biggest challenge with visual search marketing is understanding context without call-out text. For example, a hula-hoop is a popular children’s toy, but unbeknownst to many brands, the hula-hoop was immensely popular during music festivals such as Coachella. By using visual search on platforms like Instagram brands realized they had missed an important consumer segment and will take those learnings to hyper-localize for future paid campaigns.
What Marketers Need to Know: In understanding context, marketers will be able to execute paid micro-segmentation strategies and more robust content marketing. Consumers are unique in that they use products and services in different contexts and visual search will be able to uncover these behaviors and provide valuable insights to marketers. Image recognition will also affect organic social. Although Instagram currently does not use native image recognition, industry experts predict the platform will use image content as a factor of their timeline algorithm in the future.
WHERE THE INDUSTRY IS HEADING
It is not only social media features that help the convergence of visual and data technology, but the platforms we use to access them. Technology juggernaut Apple will be releasing their latest mobile software – iOS10 – in September of 2016. It will boast a new “Tap to replace emoji” feature. The software will sift through text and recommended where a user can replace words with emojis. Evidently, mobile platforms will help aid in our transition to more visually robust communications and therefore, search.
Google Search has continued to evolve its capabilities in recent years. Google reverse image search has become more dynamic since its inception in 2011, now allowing users to use images like memes, screenshots and more to drive search results. Moreover, in May of 2016, Google introduced a new capability to search using emojis, allowing searchers on Google to integrate emojis in their queries to drive search results.
NEXT STEPS FOR MARKETERS AND VISUAL SEARCH
Ultimately, marketers need to know that the language used by searchers has, and will continue to evolve beyond text queries. Targeting via paid and organic campaigns will become wider and more complex as the world of visual search grows at an astounding pace.