Personalization at Scale Depends on a Single Source of Customer Truth
According to the Association of National Advertisers, 83 percent of all organizations believe delivering relevant and personal experiences will differentiate their organizations.
What are the other 17 percent thinking?
The idea is simple: Offer consumers what they need, at the time they need it, and deliver it via the channel of their choice.
Unfortunately, this is easier said than done.
From Mass Marketing to Mass Personalization
The age of the consumer, personalization at scale and the segment-of-one all refer to the same idea. How do we change mass marketing (a.k.a. spamming in some cases) to more relevant messaging to individual consumers, while providing everyone the concierge service once only available to select high-value customers?
Organizations know one-size-fits-all messaging, information and offers are not as effective as they were a couple of decades back.
Across industries, digital transformations initiatives are germinating from the mandate of delivering better customer experience driven by mass-personalization. We can observe this trend in life sciences, healthcare, hospitality, media, education as well as local and federal government.
Such personalization depends on a very deep understanding of the customer: their needs, preferences, behavior, choices, demographics, socio-economic information. Disconnected channels, systems, applications must come together to create a single source of truth of reliable customer data to deliver relevancy and personalization.
This requires collecting and understanding all available customer data from internal, external and third-party sources. Data that includes past transactions, omnichannel interactions, social sentiments and co-relate it to store, product and household relationship information.
A Single Source of Customer Truth
Organizations have deployed various systems including data warehouses, business intelligence tools, customer hubs and lately, data lakes to solve this challenge. The outcome of these initiatives has left much to be desired. There has been no significant demonstrable ROI. The data sources and formats have grown at a much faster rate than these solutions can adapt.
As IT struggles to tame this beast, business’ needs change, new applications are onboarded, and data becomes fragmented and murkier.
Success with digital transformation initiatives depends on reliable data driving the processes and consumer engagement. And reliability requires connecting, matching and merging all the necessary data sources in all the different formats into a clean, reliable customer data foundation.
Connecting and combining the data in all systems and channels helps create a progressively richer profile of the consumer. When you add new systems to your infrastructure or purchase a new data source, connect them to the existing data hub so they can add to and access the consumer information from the same single source of truth.
As you deploy new channels, they contribute to a richer view into the customer journey along a single timeline. Such agility and flexibility are essential for today’s dynamic business environment.
Organizations must think of seamless onboarding of new data sources and reliable matching and merging of data to ensure business continuity.
Another key element of digital transformation is to uncover and understand the relationships between people, products, organizations, and places.
Why the relationships?
You do not want to send a customer an offer for a product that you know is out-of-stock or has an active recall. You do not want to send them to a store that is 60 miles from their current location. Moreover, you do not want to send them a coupon for a product already purchased by their spouse.
Graph technology can help you can find out the stores or web properties the customer frequently visits. You can identify individuals in the same household and bundle them together. You can know what each family member purchased and for example, provide with intelligent recommendations for an upcoming birthday gift.
Modern data management platforms not only help manage the master profiles of customers, products, stores and suppliers but also ingest omnichannel transactions and interactions to create a complete view of the customer. Once you have all the master and transactional data together, you can provision that to analytics systems like Apache Spark to get relevant insights and intelligent recommendations about customer engagement.
You can determine the insights for each client, the next best offer and the channel of engagement. Insights such as customer value, churn propensity, cart abandonment probability, or next probable purchase become part of the customer’s profile so marketing, sales and support can take appropriate and timely actions.
Readying Your Business for the Fast Pace of Change
With a reliable data foundation in place that includes all relationships, you have a single source of information for all channels, operational applications (CRM, ERP, order management, shipping) and analytics. With this information you can build contextual data-driven applications for sales, marketing, call center and field service teams and to all other operational and omnichannel customer engagement systems to provide the personalized interactions and connected experiences you strive for.
Digital transformation initiatives revolve around addressing consumer demands and getting the organizations ready for new business and revenue models.
Companies must adapt quickly. Multi-year technology deployment or upgrade initiatives are no longer an option. Cloud-based solutions can help bring all of your data together quickly, cleanly and efficiently, so you can deliver business applications that start impacting the digital experience immediately.