Marketing organizations have been working for decades on personalization strategies that resonate with consumers and make them feel like valued individuals. For many B2C brands, classic personalization has been applying simple forms of data like email, name, address, or recent purchases into outbound channel communications to ensure that touchpoints are seen as timely, relevant, and contextual.
Personalization marketing tools rushed onto the scene over 15 years ago to help marketers better engage with consumers in digital channels like web, social, and mobile. These personalization tools helped marketers test different colors, icons, images, or even offers on websites to optimize anonymous web visitors’ experiences. Seldomly did the tools have any meaningful historical intelligence about specific visitors, their interests, their hopes, or their needs. The cookie apocalypse and browser-based targeting solutions just contributed to the challenge of getting to know the customer beyond the classic Amazon “You may also like…”
Despite the trials and tribulations of marketing personalization engines and various analyst reports comparing vendors of vastly different capabilities, getting personalization right is still a massive opportunity for brands. In fact, there is a resurgence underway of brands that want to reestablish meaningful connections with consumers and create a value exchange that allows them to generate longer term, customer lifetime value.
Personalization as a strategy
According to the recent McKinsey study, A Technology Blueprint for Personalization at Scale, personalization as a strategy has the potential to create $1.7 trillion to $3 trillion in new value. Being able to tap into this market potential will require a new mindset, and a next-generation set of marketing tools and solutions to succeed.
According to the McKinsey study, the “4Ds” that drive personalization at scale include:
- Data — Create a customer-data platform (CDP) to provide a 360-degree customer view
- Decisioning — Advanced analytics and machine learning to create customer scoring and real-time triggers
- Design — Content factory model, digital asset management, and agile marketing to drive experimentation
- Distribution — Deliver marketing and experiences across channels and feed response data into a CDP
Source: A Technology Blueprint for Personalization at Scale, McKinsey & Company
While I agree with McKinsey’s framework as a fundamental driver for data activation and the underlying technologies that contribute to it (CDPs, ML, Content, and Messaging), what I have seen emerge from customers is a broader class of marketing personalization requirements.
These tools go beyond anonymous, digital testing, targeting, and optimization, and focus on the ongoing value exchange and customer engagement lifecycle that brands can sustain with consumers, leveraging first- and zero-party data. As Forrester’s Rusty Warner notes in the framework “4C3O,” brands need to:
- Recognize — Identify customers at an individual level
- Context — Merge history with real-time insights
- Offer — Leverage analytics to determine action, offer content, or messaging
- Orchestration — Deliver an ongoing dialog at the appropriate touchpoint
- Optimization — Provide insights for ongoing interactions and strategic planning
The game-changing marketing technologies of personalization
In order to deliver on “4C3O,” brands need to invest in three key game-changing marketing technologies, all of which can be blended together for maximum impact:
Real-time personalization. This is about understanding what the consumer intends to do in that “moment” and includes web interactions, but also mobile SMS, mobile web, mobile app, social, point of sale, session details, and ensures real-time data is captured from these touchpoints and brought back to the platform and appended to the consumer’s profile. This allows brands to learn more about consumers and deliver a better experience every time.
Journey orchestration. Brands want to be able to plan, orchestrate, and deliver multi-step journeys across all customer touchpoints and channels. Journeys should be simple in nature such as triggered events, or multi-stage in approach that unfold over time based on consumer behaviors and preferences. Journeys should be easy to manage and plan, and not require the “spaghetti diagrams” or detailed “journey maps” to achieve. Personalized customer journeys lead to growth in interactions, likelihood to purchase and increased conversions.
Intelligent offers. Offer management is not a new term, but it's definitely being redefined in the market by retailers, CPG companies, Financial Services firms and many others. Offers can be much more than a coupon or a discount, they can be messages, “Thanks for being a great customer,” proactive notifications about accounts, invitations to VIP programs or members only, images, banners, operational messages, and many others. The “intelligence” in offers here is key. Leveraging the power of machine learning and analytics to score content, and determine not only the right offer but sequence of offers, time and optimal context and channel, but format of offers is something that can be greatly automated at scale, driving more efficiency and effectiveness.
There is no doubt that personalization strategies for marketers are ripe for reinvention, and leveraging modern technologies, supported by a sound engagement strategy and supported by an engagement data platform are the keys to success. McKinsey would agree, indicating that when fully implemented, personalization can unlock significant near-term value for businesses — such as 10 to 20% more efficient marketing and greater cost savings and 10 to 30% uplift in revenue and retention.
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Patrick is SVP of Product Marketing at Cheetah Digital, focused on the go-to-market strategy and team for the Customer Engagement Suite. A frequent industry event speaker, Patrick has over 20 years of experience in the technology, consulting, and marketing industries. Prior to Cheetah Digital, Patrick was VP of Product Strategy at RedPoint Global, leading the product roadmap and go-to-market for the Customer Engagement Hub. Previously, Patrick was at Adobe through the acquisition of Neolane, focused on email and real-time decisioning. He has also spent time at Pegasystems, leading product marketing for the next-best-action decision engine, and spent many years at Forrester Research in the research and consulting organizations. He is a certified product manager and holds an MBA from Boston University.