A recent survey of more than 300 marketers by Resulticks found that almost half thought artificial intelligence was an overhyped industry buzzword and 40% felt skeptical when they saw or heard the term. The survey also found that 47% of marketers believed AI was more fantasy than reality.
Artificial intelligence has certainly become the buzzword of 2018 as brands and retailers increasingly explore how it will impact their business this year and beyond. Speaking at an event recently hosted by StoryStream on the hype behind AI in marketing, it became apparent that whilst AI is in its infancy today, many brands and retailers are already actively using AI for the likes of content creation, content management, customer insights, personalization and customer acquisition.
Brands including Aston Martin, Shiseido and Mars are already actively embracing AI experimentation in marketing and some have been at it for some time. Food producer Stonewall Kitchen re-platformed it’s entire ecommerce site with Salesforce Commerce Cloud in 2016, creating an entirely AI-driven on-site experience for their shoppers and have already been reaping the results in areas like cart abandonment and average order values. Stonewall’s Director of Marketing and Direct-to-Consumer Sales, Janine Somers estimates that AI technology has been responsible for about 10% of their year-to-date product revenue.
Berlin-based footwear retailer Shoepassion has seen results from utilizing the personalization technology stack Dynamic Yield in the areas of customer segmentation, optimization, messaging, recommendations and connecting the online and offline data to provide a seamless, personalized and connected customer experience at scale. Whilst beauty Start-up Wunder2 has also been experimenting at speed and recently became the first major cosmetics brand to launch an Amazon Alexa Skill. “As a business, we are fascinated with the rapid integration of AI into peoples’ lives. We think the level of adoption will exceed many peoples’ expectation, and create fluid recommendation experiences using AI technology found in Google Home, Alexa, and the recently launched Apple HomePod – it is something we are absolutely developing already,” says Co-Founder and CEO Michael Malinksy.
The expectation and demands of today’s customer are increasing exponentially, whilst the overflow of content and the rising number of content sources makes it more challenging for marketers to manage their content and publish relevant content across multiple channels. CEO and Co-founder of StoryStream Alex Vaidya says, “today’s customers are ultra-connected, looking for instant gratification and searching for high-quality personalized purchasing experiences from brands.” The UK’s fifth largest retailer Co-op recently used StoryStream’s new AI platform Aura for their #nowcookit campaign across content analytics, digital asset management and multichannel publishing which saw dwell times on their website increase by up to 5x, an 11% conversion rate and an 8x improvement in content curation time for the retailer’s marketing team.
Cosmetics company Shiseido use Salesforce’s Marketing Cloud and Equals 3’s cognitive companion Lucy. Their Chief Digital Officer Alessio Rossi says, “with these platforms, we are building a more complete view of who our customers are by aggregating and analyzing all the data fragments to build customer profiles that are more meaningful and actionable for us.” Whilst the digitally native cosmetics brand Wunder2, famous for having produced the Internet’s most viral brow product, has been utilizing technology from IBM Watson to do analysis on 500,000 Customer FB posts and comments to identify sentiment, allowing them to categorize posts and comments. This has given them large scale data to help understand typical concerns, questions, sources and instances of negativity and build strategies to address and pre-empt them where possible.
With so many choices out there, choosing the best AI platforms for obtaining customer insights and delivering personalization at true scale is key for retailers. As Anoop Vasisht, GM Europe at AI technology platform Dynamic Yield points out, “building online experiences had traditionally been accomplished through a disjointed series of solutions. Retailers would turn to one vendor to serve pop-up messages, another for email personalization and another to provide product recommendations. This not only resulted in data silos but became increasingly difficult to manage so many technologies in the marketing stack and ultimately customer experience took a hit.”
Working with retailers including Sephora Digital SEA, Ocado and Shoepassion, the Dynamic Yield AI technology stack permits marketers to consistently scale personalization across multiple channels within a single solution. Berlin-based retailer Shoepassion is now able to identify the context of their consumers at scale online via an automated segmentation platform. “If you know that a customer likes to buy a certain type of leather shoe every Winter, you want to be in a position to deliver that content to that customer in their shoe size every time they interact with your brand, across all channels,” says Vasisht. Personalized messaging and product recommendations across web and email are other areas where Shoepassionhas used the Dynamic Yield stack. “If for example it’s a repeat buyer, you may want to show similar products to previous purchases whilst for others, you may want to show the most popular products. Dynamic Yield allows you to personalize for different audiences and optimize the different strategies at scale.”
Stonewall Kitchen has also found success in personalizing their customer relationships through the areas of customer segmentation, email personalization, predictive recommendations and optimizing cart abandonment. Emails shared with their customers and prospects who hadn’t opened one in more than six months had a 9.7% click rate and a 4% conversion rate. Additionally, predictive recommendations resulted in $182,000 in attributable revenue. Somers says, “Salesforce’s AI capabilities have helped solve for many challenges including ’empty cart syndrome,’ providing our shoppers with personalized product recommendations if their cart remains empty for a certain amount of time. Overall, we’ve seen 83% of these suggested products added to a shopper’s cart.”
For many, an AI approach to customer segmentation has also increased the number of segments that they look at. For example, AI has helped Magic Day’s owner Maksym Podsolonko connect the dots between requests, their proposals and customer feedback. It has also led to increasing the customer segments from 7 to 61, whilst only focusing on targeting 4 of them. This level of segmentation and precise targeting has helped them increase revenue with minimal resources making his business ultimately more efficient.
In addition to segmenting existing customers, AI technology is also being used to identify new potential customers in new markets by both Aston Martin and Mars. Aston Martin recently used AI technology KanKan to identify potential customers in China. They wanted to understand the difference between a Tesla buyer and other luxury car brands and were able to do this by aggregating data from both social and retail behavior.
Mars Wrigley Confectionary has been using a reply-based social advertising tool on Twitter called Respondology for their goodnessKNOWS brand to offer product incentives to new audiences outside their existing fan base. Through the platform, they’ve been able to find and vet target-right consumers and offer them a discount off their online purchases. Whilst they are still in the infancy of leveraging the platform to its fullest capability, they have already seen an increase in online ecommerce sales and consumer engagement from it. “One of the biggest benefits so far for goodnessKNOWS has been that we can accelerate a process that we’ve typically done manually, to ultimately reach more brand-right consumers who are looking for a product like ours. Our Respondology campaign has enabled us to reach target-right consumers with relevant product messaging based on conversations they are already having online. We’ve seen a more engaged social community and a ripple effect of consumers sharing their love for our brand and product,” says Eric Epstein, Marketing Director of Snacks for Mars Wrigley Confectionary.
The potential for turning endless amounts of consumer data into actionable marketing campaigns, provide personalization at scale across multiple channels and drive increasing efficiency within marketing teams are key for brands and retailers competing in today’s hyper-commoditized landscape. As AI experimentation continues in these areas, it will be important for brands and retailers to select the right technology partners, be willing to try out new strategies and ultimately, figure out what does and does not have an impact on their bottom-line, at speed.