Keeping up with Consumers’ Buying Behavior and Expectations for an Individualized Customer Journey
If you are a business leader adapting to post-pandemic reality, chances are you are living the fast-forwarding of digital commerce and innovative customer experience solutions. Intelligent Personalization engines, not so long ago an emerging technology, are rapidly becoming imperative for keeping up with the customer’s buying behavior and expectations for an individualized journey.
Fast-forwarding of decision making is called for as well. Gartner article ’Use Personalization to Enrich Customer Experience and Drive Revenue,’ by Analysts Penny Gillespie and Guneet Bharaj, provides foundational information to help situate and strategize personalization in your digital marketing roadmap; assure optimal implementation to enhance your customers’ satisfaction, and ultimately increase revenue.
Consumers have an abundance of options and information readily available to them, across most demographics. They are looking for an exceptional buying journey, an engagement that is intuitively easy, constantly adapting, and attuned to their personal values. Differentiated customer experience is key to keeping ahead in today’s competitive landscape.
What does it take to deliver a winning customer experience?
Well, knowing your customers is a good place to start. Personalization begins with insights based on the customer data that the business collects through various channels. The deeper the customer knowledge the more powerful the personalization capabilities can be, provided the right analytical processing solution is utilized.
Gartner suggests six mainstream approaches to personalization across appropriate channels, which are intertwined and vary in their innovative capabilities.
Digital Commerce Platform buyer preference
This approach is more of user experience customization, where the customer can influence future experience by setting preferences; sharing individualized data with the business to tailor their own experience. For example: saving payment information on the business mobile channel for a quick transaction during visits, or adding shoe size information for better recommendation once logged in.
Channel and communication preferences
The customer/ user can specify their preferred channel of communication and content (when relevant) to create a personalized interaction. An advanced utilization would be inferring the customer preferences based on historical data if no preferences are provided.
Delivering personalized experiences based on the product data, specifically dependencies to preempt a potential problem the customer might run into, and thus enriching their experience. In the simpler form, this might mean alerting the customer about a required dependant product as part of the search, whereas an advanced form would be pushing recommendation for supplementary products based on intent predictions specific to the user.
The user’s location data can be inferred from IP address data, physical addresses stored, and geolocations; including date and time. This is powerful data for real-time personalization and is highly efficient for marketing messages. It is more commonly used in mobile apps as customers sign in and authenticate their information.
Personalization at the content level gives businesses a chance to influence the buying journey at an individual level by assuring the content sent to the customer is aligned with the customer’s needs and sentiment. The influence could be a specific offer or messaging at any point in the customer’s journey to boost retention and loyalty.
The most complex to execute, personalization based on a complete view of the customer is also the most effective. Enhanced data sourcing and analytics enable better customer segmentation and accuracy in customer personas. Tailoring the experience to better align with the customer at the moment of interaction increases satisfaction, loyalty, and ultimately revenue.
These six approaches range from simple to advanced implementation and should be used in combination for maximum strategic advantage. The gears of digital innovation move swiftly and so, the mainstream is now leaning towards the latter three solutions to enable that differentiating individualized personalization, utilizing data and analytics more effectively by means of advanced Machine Learning models and Artificial Intelligence.
Strategic planning of personalization efforts should also account for cross-channel implementation. Modularity is essential to align with customers, especially in the post-pandemic reality, when the ‘normal’ itself keeps shifting. ‘Keeping all your eggs in one basket’ is not recommended as a long term solution. Website implementation is a good starting point, however, as soon as enough customer behavior analysis is done, it is wise to ‘spread’ and strategically implement personalization across other customer engagement channels like mobile, Social, physical stores, support centers, and email. Important to note that advanced personalization engines have channel-agnostic abilities providing the business with an intuitive cross-channel solution.
The right foundation allows for a fast-moving implementation
The goal for customer-centric businesses should be achieving personalization at the business’s foundational level and ‘moving up’ to reach all customer touchpoints at scale and consistently. Understanding these foundational building blocks of personalization is necessary to achieve that and prevent poor execution that will mitigate strategic and revenue lift efforts.
Digital Personalization is Moving forward at the speed of innovation
Gartner recognized that “Digital personalization engines for commerce integrate to one or more digital commerce platforms, or to alternative technologies used for selling (web content management, portals, etc.). These engines have moved beyond basic customer segmentation to continuous real-time session activity based on customer interaction. They make presentation-layer changes for a specific customer with every customer click stroke, based upon their persona or profile.”
Advanced personalization solutions commonly exhibit:
- Intricate individualized data gathering
- Real-time continuous customer profiling
- Enhanced analytics capabilities
- Predictive actionable personalization based on and aligned with the specific customer journey
- Continuous adaptation of content based on customer intent
- Deliver instant business metrics like engagement rate, revenue lift, and conversion rates
Luckily, a complete organizational reengineering isn’t called for anymore. Modern personalization engines, like ZineOne’s Intelligent Personalization Platform, are scalable and easily integrated without the need for data engineering or programming skills. Use of predictive analytics, machine learning, and Artificial intelligence enables businesses to deliver highly contextualized experiences to their customers, predict intent with better accuracy and speed to allow early intervention, and ultimately lift revenue. Wait, there’s more! The channel modularity mentioned above is also attainable with these advanced solutions. The ML models can be customized to fit specific use cases and business goals prioritized by the business, based on closely monitored metrics and benchmarks.
Gartner’s article emphasizes the importance of defining goals and success measurements (like KPIs) so that customer experience leaders can assure the continuous long term success of the personalization strategy for the business. Specifically for AI-driven personalization engines with adaptive learning models; the intelligent layer adapts fast and with great accuracy to deliver a real-time personalized experience that not only resonates with the customer but also with the desired business goals.
Evolution of a use case
Have a use case in mind? Thinking about the six personalization approaches described above really accentuates how advanced personalization technology has become. With the right strategic planning, implementing AI-driven real-time personalization allows CX and Marketing leaders to fully utilize the potential of cutting edge data science with ML models that are customized to specific use cases aligned with your industry, business, and customers’ needs, both in the short and long term.
Be sure to check out this curated resource library to help guide your planning. Last, but not least, if your business is experiencing budget cuts due to COVID-19, ZineOne recently rolled out a budget-conscious product version to help businesses kick-start their personalization efforts.