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Personalization at Scale: Delivering Tailored Experiences

In today's digital age, customers expect personalized experiences from brands. Personalization at scale enhances customer engagement, satisfaction, and loyalty through relevant, tailored interactions, leading to stronger relationships, higher conversion rates, and business growth. Achieving this requires the use of data, technology, and automated orchestration for cost-effective, efficient, and rapid delivery, along with real-time optimizations for maximum ROI.

 

Five key pillars to achieve personalization at scale

Graphic image of circles representing the 5 pillars to achieve personalization at scale
  1. Precision Targeting of Audiences: Based on 360-degree customer data from first, second and third-party sources, including data on their interactions across touchpoints, purchase history and customer preferences, among other attributes, to develop deep customer intelligence and insights around their preferences, behaviors, and needs.

  2. Compelling Personalized Content at Scale: Based on deep customer insights, it is important to identify the right experience and design compelling content in order to drive the required customer action. This requires a company to reimagine their entire content supply chain, including ideation, generation, review, approval and activation of content and experiences.

  3. Intelligent Contextual Experience Orchestration: Once companies have compelling personalized content, it is critical to deliver this seamlessly across multiple channels, tailored to a customers’ journey and actions, in real-time. This helps deliver consistent, contextual and personalized experiences across multiple channels, such as websites, mobile apps, social media, and email. This requires automated processes and capabilities such as Decision Engines, CDPs and dynamic website content.

  4. Continuous Measurement and Optimization: As companies start to deliver more personalized experiences, it is critical to strengthen and scale their measurement and optimization capabilities to maximize ROI. This requires continuous testing, experimentation, and rapid optimization along multiple dimensions, including content, channel mix, and more – none of which are possible without greater automation and intelligence.

  5. Agile Operating Model: Achieving all the above requires strategic alignment, orchestration, and cross-functional execution across several teams in an organization, including Brand, Analytics, IT, Legal/Regulatory, etc., supported by a seamless and user-friendly marketing workbench.

Several challenges across the above five pillars make it difficult to achieve personalization at scale

Trust and Compliance challenges with Data: A major obstacle to scaling personalization is the management of data and ensuring timely access to actionable insights at individual level or microsegment level or campaign-level. To personalize effectively, it's essential to have access to precise and complete customer data. Yet, numerous businesses face difficulties with isolated data, disjointed systems. Merging and generating insights from different sources is a complex and lengthy process, which complicates the ability to personalize on a large scale. Additionally, issues of privacy and security are significant concerns. Finding equilibrium between personalization and safeguarding data privacy presents challenges, potentially restricting personalization initiatives.

Efficiently delivering high demand for Content volume and variations: Another significant hurdle in advancing personalization lies in attaining the necessary volume, variety, and pace at which personalized content can be evaluated, approved, and prepared for the market. Personalization demands a substantial transformation in not only producing and storing content on a large scale but also in streamlining the review and approval process for the extensive quantity of modular, bite-sized content, ensuring each piece adheres to precisely tailored personalization rules.

Orchestration challenges across diverse channel centric automation tools: Ensuring the automated orchestration systems are dependable is crucial for displaying the correct content to the intended target at the appropriate moment, in alignment with established personalization rules. Businesses encounter difficulties in achieving cohesive orchestration across various channel-focused automation solutions. The operational costs can skyrocket unless there is foundational investment considered in integrated orchestration solutions.

Lack of an agile operating model: Personalization at scale also requires a clear strategy, alignment and seamless execution across different teams and departments within an organization, across Business and IT. This is an area most large organizations struggle with, as traditional organizational structures create siloes with disconnected goals and competing priorities. Breaking through this paradigm requires companies to transform their operating model to be agile, synergistic cross-functional with shared values and vision for personalization.

The Promise of Gen AI for Personalization at Scale

The advent of Gen AI is unleashing several superpowers that will disrupt and transform the capabilities required to enable personalization at scale.

Based on Publicis Sapient experience, we’ve identified several high value Gen AI use cases across the five key pillars of Personalization. These Gen AI use cases, when complemented by appropriate initiatives focused on MarTech, Data Platform and Operating model modernization,can help clients realize the promise of personalization at scale. 

 

Graphic image of circles representing the 5 pillars to achieve personalization with additional details of each pillar

How Bodhi connected with Adobe can enable personalized content at scale

Publicis Sapient’s AskBodhi is our groundbreaking proprietary solution to power Generative AI use cases by providing a consistent way to connect and manage LLM interactions and enables customers to deploy use cases for efficient content production in a matter of weeks.

Bodhi helps clients supercharge their investments in Adobe tools by using AI/ML across the content supply chain and increase your content production velocity. Context and performance data of generated content and campaigns from Adobe can be fed back to Bodhi to fine tune generated content progressively across its lifecycle as depicted in the following diagram for a sample campaign.

Diagram of sample campaign illustrating the feedback loop between Adobe and Bodhi for fine-tuning generated content based on context and performance data.

The Business Impact

Typical benefits we see from deploying Bodhi to accelerate content generation to support personalization at scale include: 

1.5%
Increase in AOV
30%
Revenue Increase
40%
Improvement in conversion rate

How Publicis Sapient is helping clients on Personalization using Gen AI

We have high commitment to innovate and accelerate leveraging Gen AI to not only drive transformation for our customers but also to enable internal operating optimization to be competitive, cost-effective and fuel our creative dominance.

  • We are investing EUR 300M to build Core AI – a platform to transform Publicis and enable Personalization at scale for clients, bringing the power of Generative AI to all our clients' marketing intelligence. Here’s a summary of Core AI features:
    • Ionsights.IS - Unlocking understanding of consumers and markets to deliver smarter strategies faster.Creative.IS - Driving creative excellence, enabling diversity of ideas and personalized execution.
    • Media.IS - Powering the most effective media through feedback loops, faster evolution of assets and placement, and automated QA.
    • Software.IS - Bringing the best software and digitally enabled products to market 
      at scale faster than anyone.
    • Operations.IS - Supercharging our operations and our people in managing client, team, and individual growth.
       
  • Core AI is powered by our Bodhi platform which creates the infrastructure to build and integrate Gen AI products faster than anyone else.
    • Bodhi is a cloud-agnostic enterprise-ready AI-ML platform that covers the E2E workflow & enables security, scalability, and automation.
    • It has built in capabilities for Insights & Reporting, Experimentation, Model Training, Model Serving and Monitoring and Workflow Management
       
  • Bodhi has out-of-the-box capabilities to accelerate core Gen AI use cases for personalization with:
    • Advance Data Pipeline Integration
    • Advanced LLM Selector for easy, secure integrations with leading LLMs and an ability to keep client data secure
    • Visual Asset Analyzer to achieve media optimization and production-at-scale

Core AI is our vision of a super charged AI/ML driven system using state of the art computer algorithms to accelerate use-cases such as visual inspection, asset digitization, digital on-boarding, object detection, segmentation, image classification/extraction and workflow automations to achieve personalization at scale.

Anshul Acharya
Anshul Acharya
Managing Director
Dana Decker
Dana Decker
Director, Business Development, Adobe Practice