Digital transformation driving the personalized retail customer experience
Photo by iStock.com
By Anton Xavier, co-founder, Label Insight
E-commerce business models are undergoing a dramatic shift. Initially businesses relied on consumers to do the 'heavy lifting' to discover the product and to make the purchase decision. The vendor's role was to ensure that the product was discoverable and — most importantly — available at the geographic location where the transaction potentially would take place.
But the new e-commerce business model is optimized by driving the consumer to subscribe to 'an experience.' Think of Spotify or Apple Music, for example. The customer purchases access to a seemingly endless supply of music and tools that ensure their experience is maximized. The focus of the experience moves from a 'warehouse experience' to more of a concierge, personalized and curated experience. The consumer has already purchased, and so the emphasis is placed on ensuring that they stay engaged and active. Most importantly, the service makes recommendations and learns what the consumer likes, making the discovery of music a delight. In this model the better the tools engage the customers the better the company will prosper.
This new model is being enabled by two key forces — zero marginal cost and AI. The first is related to the zero-marginal cost of distributing a digital product at scale. That is to say, once a digital product has been created — whether that be music, video, or written content — the cost to reproduce it and to distribute infinitum is practically zero. A musical album, once recorded and digitized, can be copied a million times and distributed across the world almost instantly and at little to no cost. This has led to the ability to move toward new business models such as subscription models and to remain profitable. This force explains why digital disruption has focused early in industries where the opportunities for zero marginal costs are inherent — where the products being solved can be digital.
The second force powering this fundamental disruption is the impact of data science and AI systems. New platforms are designed from the bottom up to leverage behavior data and AI learning systems to fundamentally evolve the user experience. The personalized curation that is core to all these new experiences is being powered by the data underlying the consumers interaction with the experience.
Changing consumer experience in Consumer Packaged Goods
And of course, consumer behavior is changing. As the Nielsen Digital Shopping Fundamentals 2017 shows, 90 percent of Fast Moving Consumer Goods (FMCG) growth between 2016 and 2017 were driven by online channels. The impact of AI combined with zero marginal costs will relate not to the physical products but to scaling of personalized experiences. Whereas in media industries the products themselves could be replicated and distributed at zero marginal cost, in the CPG industry it will be the personalized experiences which will be replicated and distributed at zero marginal cost. Artificial intelligence and data science will enable these new experiences, which will provide consumers with curated personalized experiences at scale.
What does this all mean for the future of consumer engagement in Consumer Packaged Goods (CPG)?Artificial intelligence and the impact of zero marginal costs will combine to digitally disrupt the CPG consumer experience. This will lead to fundamental change in how consumers make decisions about what they buy in some of the following ways:
• Endless inventory: Ensuring that the right products are in the right place is a fundamental challenge of the CPG industry. In particular the e-commerce experience promises an endless availability of products to choose from, an expectation set in place by Amazon. The challenge right now, however, is that this is far from the case and that in fact most e-commerce experiences in the CPG industry are limited inventory experiences. However future experiences powered by deep product data will enable more effective search browse and filter experience giving the impression of a much larger inventory.
• Curated personal store: Much of Whole Foods' success can be attributed to the fact that the company creates a curated experience. The company has created the perception that all the products have been deliberately chosen for the cleanliness of their labels. This is a curated experience, which removes much of the challenge of searching and filtering that may be required in a general grocery store. With full product data attributes and the application of artificial intelligence the online experience of the future will provide personalized curated stores for everyone. In fact, each individual's “personal store of the future” will only contain products that suit his or her specific health and ethical requirements.
• Revolution in advertising and loyalty: Traditional advertising and loyalty programs will transition from being push-driven to being pull driven,meaning that the consumers will pull in the advertising and loyalty programs of their choosing rather than having them pushed onto the experience. This will fundamentally evolve advertising and loyalty towards a more consultative experience where consumers will find advert and recommendations a useful contribution to the purchasing process.
As advertising becomes more personalized, retailers will leverage artificial intelligence and data science capabilities to personalize discounting. Discounting will take on a more dynamic, market-driven approach where demand signals what influenced the amount of discount. Data science will help to identify why someone wants to buy a product and whether or not that reason is of high or low demand and will adjust a discount accordingly. This will lead to discounts following an elasticity of demand — and, more importantly — changing the consumer experience to provide more discounts to items consumers are interested in and offer less discounts for items that are either not needed or wanted.
Ultimately, engaging consumers is going to be about deploying data in smart ways. In almost all use cases deep granular product data will be required to create the engagement desired. To empower the consumer experience with personalization and curation, full spectrum product data will be required across all products. Smart retailers will leverage data science and AI technology to provide a better, more curated experience to their customers.