Personalization means many things to many people, but ultimately, it's about providing a unique experience to every individual based on their own preferences and data. I have a dog and shop for her regularly on Amazon, but for some reason, I keep getting “You might like” recommendations for diapers. It’s been many years since my kids have needed diapers, and yes, my dog is potty trained!
You see, personalization has a unique meaning to each and every consumer. Personalization can be everything from “Dear name” to “insert product” to “implicit/explicit insights” like “has children, loves animals” to fully automating a sequence of offers, content, and journeys leveraging AI and machine learning.
Marketers struggle with this complexity. In fact, new research from Gartner indicates that 63% of digital marketers still struggle with personalization, yet only 17% use AI and ML across the function.
Marketers can’t drive meaningful results and ROI from personalization. The root cause is data. Interestingly, 27% of marketers believe data is the key obstacle to personalization — revealing their weaknesses in data collection, integration, and protection. This is a challenge that Cheetah is uniquely positioned to solve. It’s about leveraging data for good and providing a value exchange with consumers.
They say content is king, but context is queen. If you’ve watched Queen’s Gambit on Netflix, you will know what I mean. The Queen (Context) has all the power. It is applying intelligence and decisioning to determine who gets what when, where, and how, and is the way marketers will thrive. The stakes are high, and if done right marketers can drive 20%+ more efficient marketing, 30% uplift in revenue, and 20%+ incremental boost in conversion rates when coordinating orchestrated and personalized journeys.
5 key questions for your martech vendor about personalization
In order to get the most value out of your personalization strategy, ensure you ask your martech vendor these five key questions:
- Does your platform capture real-time streaming data in digital channels and leverage it for retargeting? This is about listening for signals that indicate interest from consumers and waiting for the right moments to respond. You need to be able to capture the right data, whether it’s batch or streaming, anonymous or known, clicks, opens, browses on web and mobile devices, and leverage the insight to enhance the customer profile and trigger contextual experiences.
- Does your solution personalize content for individuals in email communications? Personalization is a spectrum, and can include “multi-step and multi-stage customer journeys.”The email channel is just one vehicle to get you to an ongoing dialog with customers, but perhaps one of the most fundamental and highest ROI channels you can leverage for success. Applying offers recommendations and intelligence into the email channel really helps to supercharge results.
- Can you deliver personalized content on websites and mobile for individuals? Being able to deliver tailored and contextual offers or content on digital channels like web and mobile is key for personalization in this day and age. Offers don’t have to be coupons or financial discounts, offers can be “thanks for being a great customer,” or “welcome to our program,” or “here is a great piece of content you might want to read,” or images, reminders, and helpful tips. Mobile wallet is an innovative trend we have seen recently where brands can leverage iOS and Android phones’ native wallet apps, enabling their customers to store membership cards, coupons, event tickets, and gift cards in one convenient place.
- Can your platform create multi-step, multi-stage customer journeys? “Customer journeys” is a term that is used often, but journeys in their truest sense are ripe for reinvention. Journeys can go well beyond a multi-stage email campaign, to an always-on hub and spoke system that can connect to multiple touchpoints and deliver the most relevant moments for consumers. Journeys should not be batch oriented or linear in design, they need to be listening and waiting for the optimal path. Applying advanced analytics like predictions and propensities can help further intelligize and optimize customer journeys.
- Can you apply machine learning to recommend products and offers? Machine learning is much more accessible now than ever before. Gartner refers to the concept of models for mortals as Citizen Data Scientist. Adding “intelligence” to offers and content really takes your programs to the next level, where the power of business rules and machine learning can help you scale and automate the offer selection and targeting process. Some of the most popular models we see today are propensities, clusters, recommendations, and send-time optimization.
The value in adopting an effective personalization strategy could mean seeing a 17% revenue increase, a 10x lift from traditional batch-and-blast outbound campaigns, as 88% of US marketers have seen measurable improvements from personalization.
To learn more about our take on Next-Generation Personalization, view this episode of PULSE, featuring our Chief Product Officer, Bill Ingram.
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.