The 5 pillars of personalization at scale
Personalization helps build brand loyalty by creating customer experiences (CX) your customers actually want to experience, over and over again. The potential value of personalization is well-established, but to engage today’s demanding customers in an environment of increased data privacy and decreased trust, it’s essential to take the next step — personalization at scale. Personalization at scale means coordinating all aspects of your operations — from inventory and supply chain to sales and service — to make each customer interaction curated and valuable.
There are five organizational requirements, or pillars, to support personalization at scale. They’re a starting point that sets the solid foundation you need as you design and build your strategy and operations. They encompass not only technology but also core aspects of how your business operates. Let’s consider them in detail.
1. Establish responsibility for the customer experience
Consider a simple retail personalization use case — designing a virtual mannequin that lets customers create an avatar and dress it in clothing options that are recommended for that customer. Who’s responsible for defining the key features and attributes of this project? And who’s responsible for fitting it into a larger personalization strategy? The CMO? The merchants? The CTO? The head of ecommerce? If it’s not clear who’s ultimately responsible for creating seamless experiences that foster customer loyalty, the project is much less likely to succeed.
This dedicated role — the CCXO — is important because it both signals an emphasis on CX and puts in place the reporting structure and resources necessary to make it possible. The CCXO must bring together multiple areas of expertise, including integrating vision and budget, as well as collaboration across IT, data, customer service, supply chain, marketing, communication, and manufacturing. The CCXO also determines KPIs and measurable ROI and NPS improvements and does everything with a clear vision that guides actions.
Whatever the specific title and whatever the previous remit, clear, executive-level responsibility and support is essential to ensure different areas of the company can all work together to develop, deploy, assess, and refine meaningful personalization efforts at scale.
2. Embed customer-centric thinking into new skills and ways of working
The CCXO personifies and drives an organization-wide focus on CX, but that focus is transmitted to the entire organization when you embrace new skills and ways of working. These should prioritize agile, cross-functional teams that work iteratively and support a culture to enact projects quickly, assess feedback, and learn from experience.
To collaborate on projects effectively and build process consistency across teams, it can be helpful to employ a workflow management tool such as Adobe Workfront. But achieving new ways of working happens through new processes and mindsets, not just new tools. Cross-disciplinary teams and flexible work styles can bring together expertise from different parts of the business, using connected data platforms and governance tools to make personalized experiences both insightful and timely.
3. Unify customer data to create individual customer profiles
Personalization demands a unified data foundation that can connect data from multiple customer touchpoints. However, individual channels — such as online, in-store, customer service and supply chain — often use standalone platforms that are not fully, or even partially, integrated. As a result, customer data is trapped in multiple systems without being tied to a single, consistent customer ID. To be successful, you must make use of multiple data types, including:
- Data captured through company platforms such as click-throughs and heatmaps
- CRM and first-person data that customers provide to the company specifically to improve experiences
- Third-party data collected from sources without a direct relationship to the customer
- Master and transactional data available in ecommerce systems and ERPs
- Insights and business intelligence data available in data lakes
Connected and curated data supports a 360-degree view of each customer, which you can either use individually or aggregate to create audiences or dynamic profiles. Profiles can be dynamic in that they evolve over time as customers change how they engage with your brand and new avenues of engagement behavior become known.
4. Maximize the value of advanced analytics
Once your data is collected and connected, you have the foundation for advanced analytics. The specific applications of analytics will vary depending on your company’s capabilities and goals, but they can include:
- AI at scale
Use behavior predictions and look-alike models to figure out the best experience for each customer in real time. In contrast to earlier versions of predictive analytics, you can do more than just identify the best customers to be shown a given campaign or product. By combining knowledge of the customer’s profile with observation of their behavior, you can determine the best offer to make or approach to take.
- Real-time segmentation
Quickly select the right audience and segment for activation efforts. By applying rule sets and intelligent tools, you can create and update segments in real time, as well as manage segment overlap and contact frequency. Unlike AI at scale, you’re not predicting behavioral outcomes with segmentation — rather, you’re assigning customers to salient groups for personalized advertising and marketing program activation.
- Real-time customer journey analytics
This kind of omnichannel reporting can standardize terms that are used in different ways by different segments of your business — for example, different departments might measure “engagement” differently. An analytics-driven customer journey report can facilitate company-wide understanding of the value of personalization and help you look at things from a customer’s perspective instead of a channel perspective.
5. Create a fully integrated and synchronized tech ecosystem
Connected data can still be complex and disparate. Coordinating the right data with the right users is the final — and often overlooked — pillar that supports personalization at scale. The orchestration layer, which coordinates integration across marketing, sales, manufacturing, finance and supply chain can be the answer to the biggest challenges.
This layer can take the form of APIs, gateways, integration services, microservices or something else. The important point is that it sits between the data store and the systems being accessed, which are otherwise known as systems of engagement. It exposes context-sensitive personalized data to the apps that consume it and drives personalized experiences for the end user.
The orchestration layer makes it possible to drive results across widely separated layers of the tech stack. For example, you can use data stored in an ERP system and ingested into a data lake to personalize the experience in a user’s mobile app, all in real time. In addition to supporting current personalization efforts, an orchestration layer makes it far easier to adapt and support future use cases that are either not practical right now, or entirely unknown.
Put these pillars to the test
Implementing personalization at scale isn’t easy. It takes enterprise-wide alignment, a clear vision, and requires leaders who put customer experience above all else. But if you use these five pillars as your blueprint, you can build the solid foundation you need to design the right strategy for your business — one that empowers you to deliver personalized experiences across every digital touchpoint.
Interested in a real-life example? Register for our session featuring Albertsons at Adobe Summit, where the grocer shares its personalization journey with IBM over the last six years.
And if you’re ready to learn more, download the full paper, The 5 Pillars of Personalization at Scale.
Pierre Charchaflian is a senior partner in IBM’s Adobe practice and the leader of North America’s marketing transformation offering. Pierre has spent over 25 years at the intersection of customer strategy, data, analytics, and technology — helping companies transform their customer-facing capabilities to capitalize on their growth opportunities.