Article Type: Personalization Strategy Guide
Published: October 7, 2024
Reading Time: 7 minutes
Author: Aaron Li
Personalization at scale has been a hot topic over the past few years, accelerated by digitally-rewired customer expectations post-pandemic. With an increasingly omnichannel approach to purchasing, customers are interacting with brands across more channels meaning more interactions and more touchpoints. They are always comparing their experience with your brand versus the last best experience they had. To keep up with evolving customer expectations, personalization at scale is critical to continue delivering relevant value to your customers no matter where they are in their buying journey.
Definition: Personalization at Scale refers to the practice of delivering highly relevant experiences to large numbers of customers through the use of data, technology, and automated systems. And in doing so, brands can consistently meet customers where they are in their buying journey in real time with messaging and offers tailored to specific needs, behaviors, and preferences.
It's no secret that customers have emphatically embraced the idea of having personalized relationships with brands:
Personalized experiences make customers feel valued and understood, fostering stronger connections to the brands that get it right. As customers engage with brands across more channels and create more touchpoints, getting personalization right for just a single customer becomes increasingly challenging.
Personalization at scale is the answer. Brands and marketers should embrace personalization at scale because it significantly improves their ability to deliver an experience that resonates with customers; leading to increased customer satisfaction, more repeat purchases, and improved CLV (customer lifetime value).
Effective personalization can help brands:
When brands succeed at personalization:
Personalization is a win for both customers and brands. The next step is ensuring your business has the resources and strategy to effectively deliver the right messaging, offers, and experiences to all customers.
Consider this analogy: if personalization is akin to a bespoke suit, then personalization at scale is tailoring thousands of suits simultaneously. In designing a suit, tailors must know the exact measurements, fabric and color preferences, and style choices of each and every customer to ensure a successful design. Foundational to the success of such a design is rich customer data, and it is no different when scaling personalization in other scenarios.
Capturing and managing rich customer data, especially zero and first-party data, is critical in achieving 1:1 personalization. Access to these types of data offers deeper insight into individual preferences and improves content relevancy to your customers.
Fortunately, customers understand the value of a personalized experience and have overwhelmingly indicated they are willing to share data with a brand, with the caveat that they expect something in return.
Key Finding from Kognitiv Global Loyalty Insights (2023):
As mentioned, brands' ability to hyper-personalize communications and offerings increases as more data points are gathered. From the research, customers are willing to share valuable zero-party data provided it will lead to an improved shopping experience.
Strategic Takeaway: Investing in strategies to gather, analyze, and unify customer data is the first step in scaling personalization efforts. With the right data strategy, brands can ensure their communications with customers are tailored to individual preferences and behaviors, resulting in more meaningful interactions.
Building on top of a strong data foundation, equally important is having a robust library of content to draw from as personalization efforts scale in size and complexity. Personalization inherently is not a one-size-fits-all approach; different audiences have unique preferences, interests, and behaviors that require unique content.
A content library offers the flexibility to experiment with different content formats, messaging, and delivery channels to understand what resonates best with customers and continually refine based on feedback and performance metrics.
Not only do different customers and segments have unique needs, behaviors, and interests, they are also at different points in their buying journey. It's not only about different content based on what products you sell, customers in different stages of their relationship with your brand need different messaging:
Kognitiv's SmartJourney® methodology is a holistic, customer-centered way to understand how your customers travel through key engagement stages, and how this varies across your customer segments. This allows classification, quantification, and prediction of customer behavior - and in the context of driving personalization at scale, ensures your content library is aligned with your customer lifecycle.
When delivering communications to your customers, reaching them at the right place and the right time is crucial. This challenge is only becoming more consequential:
An omnichannel strategy helps harmonize data and content to ensure that customers not only receive the right content, but also in a channel and cadence of preference. Executing this process efficiently across an entire customer base becomes increasingly complex as the number and types of communications evolve to meet customer expectations.
Fortunately, the emergence of AI can help alleviate these complexities through real-time campaign decisioning and automation that identify the right content, offer, and timing of communication to a customer.
Optimizing personalization at scale relies heavily on the consistency of measurement and attribution. When measurements and attribution are standardized across all channels and touchpoints, it becomes easier to compare and aggregate data, giving a clearer understanding of customer behavior and preferences.
Brands can track subtle shifts in customer behavior over time which can help identify emerging trends and insights that may otherwise go unnoticed in isolated data sets. And in doing so, brands can proactively adjust their personalization strategies accordingly.
Consistency in measurement and attribution allows brands to better assess the ROI of their personalization efforts and leads to further optimization of marketing spend and resource allocation toward the most impactful opportunities.
To enable personalization at scale, you need an optimized martech stack. Here are 5 key components that are instrumental in generating effective personalization at scale:
A CDP acts as a unified source for data management and storage. A CDP can be helpful in mitigating or eliminating data silos, which can hinder efforts to drive personalization at scale such as performance issues, delays, and inaccuracies.
A CRM platform helps track customer behavior and interests, acting as another source for data to fuel personalization.
Customers have spoken and there is clearly a strong appetite for deeply personal experiences & interactions with brands. Trigger-based or segment-based communications only go so far and can risk turning customers off if the message is not delivered properly. Personalization software that supports 1:1 personalization is the answer.
Truly achieving 1:1 personalized communication is no small feat. Automation software helps ensure that these efforts are scalable, ensuring that critical engagement moments are met, and personalized content is delivered to the right audience at the right time.
While testing and experimenting with creative content can help identify what resonates best with customers, equally important is the ability to measure the incrementality of these efforts, so budget and time is invested in what best drives results.
Loyalty programs can be a valuable asset in driving personalization, serving as, among others, a platform to capture detailed customer data, segment customers based on behaviors and preferences, and facilitate omnichannel experiences.
Kognitiv's AI-native outcome-based martech and loyalty platform enables brands to deliver relevant omnichannel experiences to their customers.
What it is: Kognitiv Pulse is an insights and activation tool that helps quickly identify key areas of opportunity and target customers at an individual level.
Key Benefits:
What it is: Kognitiv Inspire is a cloud-native loyalty management platform designed to help create and maintain successful loyalty programs.
Key Benefits:
What it is: Kognitiv Ignite is an AI-native outcome-based personalization software that allows brands to automatically optimize campaigns across email, SMS, and in-app push to reach their pre-defined business objectives.
Key Capabilities:
What it is: Kognitiv Amplify is an AI autopilot for paid media that skyrockets paid media campaigns' conversion rates with AI-powered personalization, cross-channel automation, and real-time optimization.
Key Capabilities:
What it is: Diverse partner benefits that give your customers more choice and experiences they love.
Book a demo with one of Kognitiv's loyalty & personalization experts to learn how you can maximize your marketing performance.
Kognitiv provides AI-native outcome-based martech and loyalty platform solutions that enable brands to deliver relevant omnichannel experiences to their customers. The company offers a comprehensive suite of products including Pulse (insights and activation), Inspire (loyalty management), Ignite (owned channel personalization), Amplify (paid media optimization), and Marketplaces (partner benefits).
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