Amazon is estimated to have pulled in $6-7 billion this year from its 5th annual “Prime Day”, but the e-commerce giant wasn’t the only brand to score big from one of the biggest spending occasions of the year.
In an effort to “hack” Prime Day, Cheerios offered a free family-size box of Honey Nut Cheerios to any Amazon shopper who spent more than $40 on Amazon Pantry. In addition to the box of cereal, customers received $10 off their order. The offer automatically created a Cheerios shopping history for millions of Amazon Prime shoppers, infiltrating Amazon’s recommendation algorithm and moving Cheerios to number one in the cereal category.
The Results? Cheerios became the #1 grocery item on Prime Day and Y-O-Y sales of Honey Nut Cheerios increased by 64%compared with the week before the activation. The campaign also claims that 80% of those who bought Cheerios in July were new to the brand.
Why it’s hot? More households are adopting voice assistants like Alexa and Google and with that, voice-assisted shopping is on the rise. Although voice-assisted shopping is still far from replacing online shopping, brands need to get creative and test the limits of these platforms in order to capitalize on the voice-assisted retail boom.
The traditional hiring process for companies, especially large organizations, can be exhaustive and often ineffective, with 83% of candidates rating their experience as “poor” and 30-50% of candidates chosen by the company end up failing.
Unilever recruits more than 30,000 people a year and processes around 1.8 million job applications. As you can imagine, this takes a tremendous amount of time and resources and too often talented candidates are overlooked just because they’re buried at the bottom of a pile of CVs. To tackle this problem, Unilever partnered with Pymetrics, an online platform on a mission to make the recruiting process more predictive and less biased than traditional methods.
The second stage of the process involves submitting a video interview that is reviewed not by a human, but a machine learning algorithm. The algorithm examines the videos of candidates who answer various questions, and through a mixture of natural language processing and body language analysis, determines who is likely to be a good fit.
One of the most nerve-wracking aspects of the job interview process can be anticipation of the feedback loop, or lack thereof – around 45% of job candidates claim they never hear back from a prospective employer. But with the AI-powered platform, all applicants get a couple of pages of feedback, including how they did in the game, how they did in the video interviews, what characteristics they have that fit, and if they don’t fit, the reason why they didn’t, and what they believe they should do to be successful in a future application.
Why it’s hot: Making experiences, even hiring experiences, feel more human with AI – The existing hiring process can leave candidates feeling confused, abandoned, and disadvantaged. Using AI and deep analysis helps hiring managers see candidates for who they are, outside of their age, gender, race, education, and socioeconomic status. Companies like Unilever aren’t just reducing their recruiting costs and time to hire- they’re setting an industry precedent that a candidate’s potential to succeed in the future doesn’t lie in who they know, where they came from or how they appear on paper.[Source: Pymetrics]
Why it’s hot: As our daily lives become increasingly more busy, and with more platforms than ever competing for our attention, Quibi is taking a huge gamble on the future of TV and the future of wholly-owned short-form video content. With our limited attention spans and on-the-go lifestyles, there’s a growing need for platforms to adapt and change to how we digest content throughout the day.