In the world of online retail, it’s Amazon and everyone else.
While many factors allowed Amazon to climb to the top of the online-retail food chain, their ability to provide individual consumers with a personalized, 1:1 shopping experience is perhaps their biggest asset.
The provision of a 1:1 retail experience at depth and scale isn’t easy, but Amazon’s commitment to data collection and real-time data modeling make it possible—and it’s a commitment other retailers would be wise to adopt.
Because data and real-time data modeling allow Amazon to…
- Treat customers like individuals.
- Anticipate acute customer needs.
- Better understand the customer journey.
Treating customers like individuals
The depth and diversity of Amazon’s retail marketplace means their access to point-of-consumption data (e.g. products researched, products purchased, frequency of purchase, time of day purchased, etc.) is unrivaled. By modeling this data in real time, Amazon can provide 1:1 personalization across all the touchpoints that encompass the customer experience. In other words, Amazon can offer true personalization, not just personalization based on lookalike audiences. The result?—a better customer experience that can lead to as much as a 30% uplift in revenue and retention.
(Want to know more about personalization and how it’s shaping consumer decision-making? If the answer is yes, check out this recent whitepaper from Zeta.)
Anticipate acute customer needs
A big part of the Amazon user experience—perhaps the biggest part—revolves around its ability to anticipate the needs of customers with impeccable accuracy. This is made possible, of course, by Amazon’s reliance on large-scale data collection and subsequent real-time data modeling; it’s how they identify and understand the shopping patterns and habits of individual customers. Thanks to those insights, Amazon can make UX-boosting, 1:1 predictions that can be deployed across its platform—from “recommended for you” products to preemptive shipping, increasing sales by as much as 44%.
Better understand the customer journey.
Real-time data modeling allows Amazon to know (with virtual certainty) why consumers take certain actions—knowledge that makes it easier to map individual customer journeys, not just audience-based customer journeys. In understanding the customer journey to such a granular degree, Amazon can have far greater impact and influence with its marketing. They can determine…
- Who they want to target
- What message they want to communicate
- What offer they want to make
- At what time (and through which channel) they want to make an offer.
…and they can do it on a 1:1 basis.
Online retailers can learn from Amazon
Few businesses—retail or otherwise—collect data within their four walls as effectively as Amazon. The company tracks everything from purchases to browsing habits, material preferences to preferred price points for each of it’s approximately 172 million customers.
To replicate Amazon’s success in creating a 1:1 customer experience through the use of data collection and real-time modeling, retailers must either:
- Match Amazon’s investment in terms of money, technology, infrastructure, and manpower to create an industry-leading, in-house solution for mass data collection and real-time modeling.
- Form a strategic partnership with an external organization that has access to both a massive proprietary data set, and AI-powered activation abilities.
Given the capital (both upfront and ongoing) required to replicate Amazon’s capabilities in-house, most retailers striving to bring true, 1:1 personalization to their customer experience will need to pursue option #2.
The good news is, retailers can expect to reap all the same user-experience benefits as Amazon, if the right partner is chosen.
What makes a partner the right one?—Three things:
- A massive data cloud that can augment a retailer’s existing first-party data.
- The ability to source consumer signals, interests, behaviors, etc. from across the open web at scale (i.e. a contextual engine).
- Real-time data modeling capabilities that harness the power of AI, machine learning, and natural language processing to obtain the true interest and intent of consumers on a 1:1 basis.
In other words, data collection and real-time modeling will be the backbone of success in the retail industry from here on out. The ability to aggregate large quantities of data related to customer intent, and process that data using real-time signal intent as well as AI-powered modeling will lead to game-changing customer learnings. Using those disparate learnings, retailers will be more effective in both predictive decision making and the never-ending optimization of a 1:1 customer experience.
To learn even more about the productive mechanisms powering Amazon’s success, and how those mechanisms can be applied in your business, check out Zeta’s webinar on the impact of AI and data-modeling on the retail industry.