Zooming in On the Personalization Minefield
Think about your own online shopping experiences or the content recommendations on your favorite app—the more tailored it is to your needs, the better your experience is.
A personalized customer experience is becoming a differentiator for all kinds of organizations to achieve higher customer satisfaction, increased engagement, and stronger brand loyalty. With the abundance of choices that consumers face for every little decision, brands that can help customers easily find what they need or might enjoy will thrive.
According to Forrester Research, in 2016 89 percent of digital businesses reported spending money on personalization, but only 40 percent of consumers think that what they get matches their unique preferences.
Delivering personalized, one-to-one experiences at scale requires oversight of data, technology, and talent. Boards must probe the multiple underlying issues raised by personalization such as avoiding popularity biases, and how data about the evolving intent of customers will be captured and stored. Furthermore, boards should have management explain how they have thought through data privacy: The transparent and responsible use of data is important to building and maintaining trust with customers.
As the strategic imperative of personalized experiences grows, here are key principles that board members should keep in mind in their oversight:
Real-time and one-to-one experiences. With machine learning, customer experiences are moving from being persona- and segment-based (relying on factors such as demographics and general interests) to being truly individual and one-to-one.
As more and more experiences become digital, organizations of all kinds stand to benefit greatly by creating and delivering relevant experiences for their customers—be it in online retail, in-flight entertainment, or personal finance. Being able to combine real-time user activity with what is already known about the customer and products is crucial to delivering relevant experiences. Being able to capture in real time how a specific user is evaluating a product online, such as zooming in to see certain details, may allow the seller to suggest a different product.
These insights can help your organization tailor recommendations to specific customers and suggest similar products, and machine learning can enable you to do this at scale across billions of interactions. As board members, you should ask management for a long-term technology strategy and roadmap that allows the evaluations of customer interactions that stand to benefit from individual personalization. It is also essential to ask management to evaluate how well the company knows its customers today. Boards should question: What are the different data sources that the company has access to, and are there any data gaps that would prevent the company from building a comprehensive understanding of their customers’ preferences? It’s also crucial to evaluate whether or not the organization has the right skills in its workforce for a successful rollout of a personalization strategy.
Personalization across every touchpoint. Brands are increasingly recognizing that personalization throughout the customer journey is intrinsic to building strong loyalty. Delivering relevant marketing and customer care experiences up to the last mile can enable your business to build a flywheel—where every stage of the personalized customer journey feeds the other. For example, understanding what products or offerings are driving engagement in a promotional email can subsequently help serve a more personalized online retail experience.
Just addressing customers by their first names in promotional emails or sending marketing communications based on broad personas is hardly going to cut it. Every such engagement is an opportunity for the brand to deliver meaningful, customized experiences. As board members, ensure that management—especially those in marketing and customer care—is appropriately skilled to build an individual personalization strategy for communication across all points of interaction, be it in-app messages and notifications, interacting with a chat-bot, or a promotional email. Personalized communication means delivering tailored messages, product recommendations, offers, and discounts. Doing this at scale requires a long-term data and machine learning strategy. Directors should ask management to explain what disciplines are included in the personalization project, possibly setting up a cross-functional team that spans product development, marketing, and customer care along with data science and machine learning experts.
Omni-channel interactions and strategy. Most customers interact with businesses across multiple channels: mobile, web, and with various technological devices. Consumers expect a consistent experience every time they engage with your brand.
When building a machine learning-driven personalization strategy, ensure that management is taking a holistic look to bring together these various pieces of data in one place. This is true not only for data from past activity but also for real-time interactions: If a user is searching for a product on a website and then continues on to a mobile app, it is important to factor in the recent web activity to decide what the experience on the mobile app should be. Building a true omni-channel personalization experience requires a strategic focus. When overseeing management, prompt them to consider a personalization strategy that can be applied equally across every channel that interacts with customers.
Praveen Maloo is the senior product marketing manager for Amazon Web Services AI and Machine Learning.
Praveen Maloo is the senior product marketing manager at Amazon Web Services in the AI and machine learning division.