AI is needed to meld brick-and-mortar with e-commerce
Retail trends today show that the line between pure-play e-commerce and brick-and-mortar retail is not as clear as it once was.
Whether it’s the surge in mobile traffic or new revelations around consumers’ omnichannel preferences, the way people browse for goods and services online is changing fast and often. And with AI-driven analytics, retailers in both camps can meet the needs of their customers, whether they are in-store, at home or on the go.
Pure-play brands have an unmatched understanding of their audience because they have developed their entire business strategy around digital consumer behavior. A cosmetics brand like Lime Crime, for example, has expertly shaped its user experience into a language that communicates its uniqueness and offering while taking fans on the seamless digital journeys they have come to expect.
When it comes to building digital experiences, pure-play brands certainly reap the rewards of a digital-first mindset, and enjoy higher conversion rates across all devices. And with the bulk of digital retail traffic now coming from mobile, anything but a mobile-first approach to customer engagement is not going to cut it. Brick-and-mortar brands with digital platforms are lagging behind the pure-players in this area, and the conversion gap between them is telling.
A higher product reach rate, a healthier cart reach rate and better results at checkout — pure play-brands are clearly doing something right. But that doesn’t mean brick-and-mortar retailers don’t have some advantages of their own. They’re providing a critical answer to consumer reliance on physical stores. And data shows they’re also delivering on the digital front, since their visitors bounce less and consume more pages. When it comes to keeping customers engaged, many of the legacy brands and traditional retailers are meeting the challenge with success.
Pure-players have one main KPI — ROI — whereas for traditional retailers, engagement, awareness and education must be taken holistically to evaluate performance. Most people still research products online, whether they complete their purchase digitally or in store. And since most purchases are done in-store, these metrics are key for these brands’ short- and long-term business success.
Purchasing journeys vary greatly from one type of platform to another; what matters is identifying which UX elements are obstacles along the journey, and which elements are driving the most ROI. AI-driven analytics can help both pure-play and brick-and-mortar brands understand the frustrations of their users at an elemental level — which buttons remain unclicked, which form fields make them leave, and which customer paths are dead ends.
And analytics today have also benefited from the lessons of best UX practices — easily accessible, highly visual metrics mean that user behavior data can be leveraged by entire digital teams, not just data experts.