By Kunal Puri, Head of Customer Success, Infosys Equinox
Today’s digital marketers have no lack of data, analytics, attribution models and machine learning tools to optimize digital journeys. And it’s shown that brands and retailers who excel at personalisation drive 5-15% higher revenue and run up to 30% more efficient marketing campaigns.
But the challenge remains — what about offline behavior? What about anonymous visits? What about customers’ social graphs, tastes and preferences? Many brands and retailers still struggle to stitch together siloed first and third-party data to create true 360-degree views of customers. Without unified customer data, it’s impossible to effectively personalise customer journeys across all engagement points.
What do marketers need to reach the hyper personalisation Holy Grail and build 1:1 customer relationship?
Building unified customer profiles with CDPs
Serving a “segment of one” is no longer out of reach for everyday marketers. With a wealth of AI-driven personalisation engines and CDPs (customer data platforms) to choose from, marketers can capture and aggregate data from multiple first and third-party sources across channels, browsers and devices to build a unified customer database that can be exposed to the ecommerce platform, email and SMS marketing, loyalty profiles, mobile apps, CRM, chatbots, call centers, point-of-sale systems, ad networks and more.
What is a customer data platform?
Customer data platforms ingest data, clean it for use and can even match identified and semi-identified visits and records to individual customers (identity resolution). This data can then be translated into rich customer profiles (genomes) based on hundreds of specified attributes. These genomes dynamically update in real time based on online and offline engagement to provide insight into lifetime customer journeys and behavior.
With rules-driven audience segmentation and machine learning, CDPs can apply advanced predictive analytics to target customers down to 1:1 granularity, depending on the business’ objectives and strategies. Serving as an orchestration layer across data sources and the martech stack, the CDP can trigger the right content, offers and merchandising to the right customers based on real-time context.
Benefits of using a CDP
With a CDP, marketers can provide the most relevant experiences to consumers, serving them more of what they want, and less of what they don’t. Customer data platforms are designed to update customer attributes and track changes to these attributes in real-time, drawing from multiple data sources including customer service channels, online communities, the social graph and affiliate channels. Combined with dynamic segmentation, this ensures customers are always segmented and re-segmented to fit your targeting strategies.
For example, a customer may be a “VIP” in one department or brand, but rarely purchase from others. A buyer may shift spending across product categories with changes to their income, marital and family status, geographic location, health or lifestyle. As customers’ attributes morph, a CDP can match shoppers to the behavioral trends of “customers like them” with predictive analytics.
More accurate targeting improves conversion rate, order values, reduces customer churn and improves customer lifetime value (CLV). Stitching online, offline and off-site context helps optimize campaign performance across channels. Knowing your customer also helps you build look-alike audiences to acquire new profitable customers and serve the right messaging to prospects and new visitors.
Connecting customer data to commerce
Having a CDP is only the first step to hyper personalised selling across channels and touchpoints. The CDP needs to integrate with the commerce platform, ideally one that already supports omnichannel selling. Today’s modern headless commerce platforms that leverage microservices are the ideal pairing for CDPs.
Microservices-based headless commerce platforms provide well-defined APIs for every component of the commerce back end and can interface with any front end or channel. For example, in-store POS and online checkout can share the same cart and payment capabilities, and tie into the same loyalty applications and promotions engines. These same services can extend to mobile apps, social platforms, chatbots, in-store kiosks, and unmanned retail (showrooms, pop-up galleries and smart vending machines). They can even connect to Internet of Things devices like smart appliances and TVs, cars, voice assistants and wearable tech.
Paired with the customer data platform, headless commerce can extend personalised site content, product recommendations, pricing, promotions, mobile notifications and more. This merchandising can be extended to in-store signage, mobile apps, email campaigns and the like. Site and store visits and online engagement can be tracked, and customers can be effectively retargeted across channels — even using proximity marketing to target alerts when customers are near physical stores.
“Segment of one” in action
The combination of a CDP and headless commerce enables brands and retailers to leverage richer customer data and connect it to innovative content, customer service, marketing and experience initiatives. The ability to target the most relevant content, the most timely reminder, the most enticing offer or the most helpful advice on a 1:1 basis deepens customer relationships, boosts customer satisfaction and increases conversion and revenue.
How are marketers and digital leaders leveraging hyperpersonalisation?
Leading CPG brand targets taste profiles
One of the top five food and beverage companies in the world collects hundreds of consumer attributes to build “taste profiles” based on the customer genome. It applies this insight to the end-to-end customer journey across social networks like Facebook and over its 250 brand and recipe sites, connecting Taste Profiles to online and offline engagement and purchases (including transactions across its retail channel partners).
Motorcycle parts dealer revs up revenue
One-to-one personalisation is not just for very large enterprises. Mid-market, online pureplays are also in on the action. A dot-com motorcycle and power sports parts dealer leverages rich profiling to anticipate when customers need replacement parts, service appointments or would be most likely to buy new gear. Combining demographic and lifestyle data with vehicle-specific information, service history, online visits and behavior, email response and more gives the merchant the ability to tailor messaging and products to each individual customer at the right time and provide a more “human” digital experience.
Ready to hyper-personalise omnichannel commerce?
Hyperpersonalisation is not reserved for only large brands. Today’s technologies make 1:1 targeting more accessible to businesses large and small. If you’re just starting out or have a smaller budget, focus on known customer pain points rather than greenfield experiments. The goal is to make commerce more human — surveying your in-store sales staff, live help agents and customer service groups can help you identify the low hanging fruit. Look for ways you can match customer data to these pain points, and where you can inject personalisation into customer journeys.
Effectively serving a segment of one requires both a customer data platform and a modern, microservices-based commerce platform that can connect to any customer experience touchpoint. It also requires skilled data analysts and IT talent to craft targeting logic, co-ordinate flows and orchestrate data across systems and experiences.
If you don’t have these capabilities in-house, look for experienced consultancies and systems integrators that understand the technologies and can work with your team to map out targeting strategies, business objectives and technical details. Personalization is not just a one-time project but a program. Choosing the right implementation and strategic partner can help you stand up your solution and continually optimize your personalization efforts over time.
