Magpie: Developing and Using Buyer Personas
ABSTRACT
In March 2017, during their final semester in an MBA program, Magpie’s co-founders—Damjan Korać, Gerrit Orem, and Andrea Fantacone—sat on a bus from New York to Boston and discussed the next steps for their venture. Magpie delivered a single-click shopping experience to any image, video, or app on the web, letting publishers natively tag products in their content and letting consumers purchase those products without needing to leave the page. In less than a year, the co-founders had bootstrapped their student startup, focusing on product development relevant to all players in their multi-sided platform: retailers, publishers, and consumers. They were developing a consolidated catalog of all products on the internet with up-to-date pricing and inventory information, an API that would allow Magpie to inject orders directly into any retail system, and a consumer interface that removed almost all friction from the online shopping experience. The founders believed publishers were a key driver for initial adoption. By leveraging existing pages and apps where consumers already interacted with content, Magpie could minimize costly consumer marketing expenses. Other companies had tried to tackle this space and had stumbled with publisher acquisition. Magpie had brought in online content creators for product development input from day one. They were ready to focus on publishers as launch partners in June 2017. Magpie’s offering had received enthusiastic responses from those contacted, but the team knew that excitement during an exploratory interview or focus group would not necessarily translate to a signed contract. Based on the interviews, the team had created four publisher personas in their initial launch segment. They hoped to use these personas to determine priorities, the order in which to target different types of publishers, and the messaging and media needed for marketing to each group. The team also wondered if they had generated the optimal breakdown of publishers into distinct personas. Was their analysis missing any key characteristics of publisher’s goals, motivations, and behavior?
Market Opportunity
The global market for retail e-commerce in 2016 was $1.915 trillion, about 8% of total retail sales. Analysts predicted that retail e-commerce sales would be $4 trillion by 2020, with growth driven heavily by the Asia-Pacific region’s growing middle class, heightened competition among e-commerce players, an increasingly robust internet infrastructure, and greater mobile and internet penetration.1 Strong growth was also predicted in North America, the world’s second-largest market for retail e-commerce, where 2016 sales of $385 billion were expected to grow to exceed $600 billion by 2020.2 Although most retailers’ e-commerce sales were growing, they were far outpaced by Amazon, which accounted for 55% of US e-commerce growth in 2016. Many analysts attributed this in part to Amazon’s success in streamlining its checkout process while offering unrivaled product selection. 3 A number of trends had emerged. First, while desktop browser-based shopping had long reigned supreme in e-commerce, mobile shopping was becoming increasingly salient due to growing smartphone penetration across the globe. Many brands and retailers were seeking better ways to engage consumers and increase conversion rates on mobile devices.4 Second, online influencers and social shopping (sales driven by influencer channels) were becoming important. The top 500 retailers generated $3.3 billion from social shopping by 2014, a 26% more than the prior year, 5 and commissions to online influencers were growing. U.S. affiliate marketing spend was expected to grow at a 10% CAGR to $6.8 billion in 2020, 6 a rate higher than that of the e-commerce market. Retailers were interested in how to capture the power of influencers and social shopping. Finally, an estimated $4.6 trillion worth of online shopping carts were abandoned by consumers in 2015 and about 60% was potentially recoverable if retailers improved the e-commerce experience.7 Studies found that, of the $2.8 trillion in potentially recoverable carts, 27% of sales, or $756 billion, were specifically lost due to friction in the purchase process.8 This represented a big opportunity, especially as more shoppers used mobile where the potential for purchase friction increased significantly.