Nearly 4 out of 5 marketers report using AI capabilities. However, AI comes with its own challenges. Learn how APIs can help you optimize user workflow and meet marketers’ needs.
Last month, Disha Harjani (Director of API Partnerships, Shutterstock) co-presented a panel with Laurie Summers (Global Channels Executive, IBM) and Kit Hughes (Founder, Look Listen) on Optimizing Marketing Workflow with AI and Automation at South by Southwest (SXSW).
During the panel, we discussed the importance of personalization and the increasing use of artificial intelligence (AI) to run personalization campaigns. You can listen to the complete recording of the panel on here.
However, while AI is making personalization easier than ever before, it also introduces a new set of workflow challenges for marketers. That’s why we’re venturing beyond the panel to provide actionable advice on using API solutions to complement personalization capabilities on your platform.
Application programming interfaces (APIs) are a communication layer that allows different applications and servers to exchange data and functionalities quickly. For more information on APIs, check out our article on What is an API and Why do Businesses Care.
Here is what we’ll cover in this article. If your platform does not currently offer any AI capabilities, we recommend that you start with this article on how you can stay competitive by using APIs to deliver search and discovery improvements without straining your internal resources.
AI for personalization
Image by Flamingo Images
According to eMarketer, 59% of brand marketers are already using AI capabilities. Among the different AI capabilities, Salesforce reported that 24% of marketers used AI to personalize the customer journey in 2018.
By 2020, 60% of marketers expressed their intent to use AI for personalization across all channels.
This trend reflects the fact that AI is particularly well suited for personalization. After all, personalization requires real-time processing and responding appropriately to large amounts of user data which are tasks that human cognition is not equipped to handle.
Personalization induced content bottleneck
Image by Sebastian Duda
Despite the promises of AI-powered personalization, marketers continue to struggle with delivering the right content to the right visitors at the right time. This is because, while AI addresses the data processing side of dynamic personalization, it simultaneously introduces another set of workflow issues.
Specifically, marketers are finding it difficult to keep up with the content velocity needed to sustain personalized customer journeys. Content encompasses images, illustrations, video clips, music tracks, copy, and other design choices. In fact, within AI-powered applications, 51% of marketers report struggling with the content creation process.
As Prajwal Barthur (Director of Products, InMobi) explains, “[T]here may be eight variants of a creative with a bunch of targeting capabilities that can give you up to 200 creatives that a user can see.”
Let’s take a simple example to illustrate the personalization induced content problem.
A marketing manager wants to run a personalized ad campaign that targets three different personas across 10 markets around the globe. Each ad needs translated copy that makes sense within the cultural context where it’ll be displayed. Additionally, the copy needs to be supported by localized creative assets such as images, illustrations, video clips, and/or music tracks. Moreover, if she wants to A/B test localized ad variations, the number of creative assets needed could grow beyond the initial set of 30 (personas x markets).
To create at least 30 assets in-house is a big ask for most organizations and may delay the launch of the ad campaign. Thus, the marketing manager has the AI tools to deliver the right ad to the right persona in the right location but she is faced with a resource-intensive task of populating those ads with the right content.
Personalization at scale with APIs
Image by YIUCHEUNG
In the martech space today, many platforms have turned to creative APIs, such as the Shutterstock API, to complement AI-powered personalization. This is because creative APIs resolve the challenges of generating large quantities of personalized creative assets by delivering high-quality images, video clips, and music tracks that can be licensed immediately for commercial use.
Due to this explosive rise in the need for creative assets, many martech platforms such as Google, Facebook, and IBM have turned to the Shutterstock API. With the Shutterstock API, platforms can serve up to 260 million images, video clips, and music tracks directly in the user workflow.
Instead of creating imagery, video clips, or audio tracks in-house, marketers can do a search for localized creative assets directly in her workflow. Shutterstock licensing is simple, instantaneous, and protects the users from potential copyright infringements.
Moreover, Shutterstock API partners can also use our AI image recognition technology to deliver Reverse Image Search, Similar Video Search, and Similar Image Search to further accelerate asset discovery.
Shutterstock’s AI-powered visual search combined with an extensive asset library helps partners resolve a workflow hurdle that prevents many marketers from successfully scaling personalization efforts.
AI has had a transformative effect on many industries including the marketing industry. However, while it makes new opportunities such as personalization possible, it also amplifies the age-old challenge of keeping up with the pace of content creation.
Here we discussed a specific use case of how creative APIs can optimize the end user’s workflow and help them maximize ROI from personalization. For platforms that do not currently offer any AI capabilities, APIs can also help.
Learn more about how APIs can help platforms deploy AI-powered reverse image search quickly.
Cover image by NicoElNino
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