Defining the right strategies for personalization and weaving them into business as usual is a key challenge for brands. On the one hand, the business case is clear. Consumers are demanding more relevant content experiences from brands, and increasingly penalise those that still take a one-size-fits-all approach, either by ignoring them, or turning to their competitors. Personalization done well can deliver better engagement, five to eight times the ROI on marketing spend and an incremental increase in sales performance.
However, there are also tricky issues to navigate in order to achieve success with personalization. Data privacy, the right level of personalization (eg. one-to-one) and striking an effective balance between adding value for consumers versus being intrusive and annoying.
In the context of this blog, personalization at scale is the ability to deliver highly relevant content, in different formats, to thousands or millions of customers and prospects, across channels and touchpoint. Here we looks at some of the key building blocks that have to be in place for success.
STRATEGIES FOR PERSONALIZATION
When a company first talks to us about having a ‘personalization strategy’, it’s a ‘hold your breath’ moment. Is the expectation that we’ll answer all the questions required to deliver success in an extensive planning process before execution. Or is the brand looking to create a clear plan of action focused on one or a few use cases, with the intention of testing ideas with real customers, tracking results to generate meaningful insights and then rapidly iterating to build momentum and growth.
Knexus is a big advocate of a ‘test, learn and grow’ approach to personalization, so we sit much more comfortably with the second option. And certainly digital marketers should be very familiar with operating in this way. But given personalization may bring together cross-functional teams responsible for content, data, brand and customer experiences, creating a robust and systematic approach with the right tools and capabilities is key.
A study of marketers in the US undertaken in Feb 2016 found 59% said they do not personalize content because they don’t have the technology. This is changing fast as increasingly sophisticated marketing technology becomes available in the market. With the ability to integrate disparate systems through APIs, the potential exists to tie together content, data and distribution systems to deliver personalization capabilities.
More often than not, companies have disparate sources of both content and data. Finding technology that can bring these capabilities together and scale without creating over-sized business disruption or excessive upfront costs can be key.
Customer data is the oxygen of personalization, and today comes from a range of sources including profile, preferences and transaction history, user behaviour based on marketing activities and third-party data.
Brands are tackling a myriad of data-related challenges. Too much data, not enough data, data in the wrong places, data in the wrong formats, integrating the right sources of data, having the right systems to manage data.
Putting in place capabilities that bring data together from disparate sources, interrogate it effectively and extracting data parameters that match individual customer needs or target segments, is critical to a scalable approach to personalization.
For personalisation to succeed at scale, brands need lots of good content and also the ability to harness that content effectively. The tide of content creation is rising fast as content marketing continues to grow as a priority.
But the state of content maturity in many brands remains quite low. Brands have a fragmented rather than unified view on the performance of content, which undermines the ability to determine with certainty what content performs best. Without robust measurement, content investment is sub-optimal.
Similarly, content is often siloed across a range of different channels, systems and teams. This undermines the brand’s ability to most effectively match customer needs with the best content experience.
Advanced analytics sit at the centre of any personalization operation, determining which content experience to automatically deliver for a prospect or customer. How that decision making takes place and what data is used, can vary widely. For example, are decisions based on rules or predictive analysis. And is the predictive analysis looking at data from a single channel or multiple sources of data, for example both first party and third party data or customer behaviour based on content served.
Brands need to consider the balance between acquiring sophisticated decision making capabilities early, and thereby building in the ability to scale, versus unlocking business value from personalization using simpler solutions before increasing ambition.
It’s also important to think about the users ie. marketers. Sophisticated decision making capabilities can also be complex, requiring expert data analyst skills. Brands need to be careful not to constrained their ability to operate with agility, or alienate their marketers, when choosing to put these capabilities in place.
At present, the majority of personalization is narrowly focused by channel, whether that’s email, a brand’s websites, social media or paid advertising. But today’s digital consumer is channel agnostic, and not only expects relevant experiences from brands but also seamless, consistent experiences. So content distribution capabilities, whether through microsites, landing pages, ads, blogs or other content, increasingly need to be deliverable on an omnichannel basis, or at least have the potential to extend out across channels.
Our Knexus platform provides fully personalized experiences delivered into chosen digital touch points, ensuring high relevance, timely content that matches customer needs and exceeds expectations, resulting in maximized engagement ROI.