Personalization is all about tailoring information or experiences for your customer segments. In the web world, online personalization tools have been around for a while, however recently, more advanced implementation use-cases are starting to develop. In this post, we will look at some of these advanced personalization options including cognitive personalization, account-based personalization, and personalization for the ‘Internet of Things.’
Cognitive Personalization
One of the personalization options discussed at the most recent Adobe Summit, was the idea of cognitive personalization. Cognitive personalization occurs when the user’s personality traits are used as the basis of of your segmentation and personalization rules. IBM’s Watson has a Personality Insights service which can accept text input from individuals, and provide output by way of a tree of cognitive and social characteristics for each person. The text used for the personality analysis can come from any source; whether it be email, social profiles, or other text-based records.
Here is an example output from Watson’s Personality Insights. I’ve used a collection of emails from one of my coworkers (you’re welcome, Jim!), and pushed that data through Watson’s personality service. The resulting output uses the text input to provide a score of his perceived values, needs and an evaluation across the ‘Big 5 personality traits’ (those being openness, conscientiousness, extraversion, agreeableness, and emotional range):
IBM has conducted validation studies to show how user behavior can actually change based on their Watson understood personality characteristics. For instance, IBM showed that ad click-through-rates increased from 6.8% to 11.3% for a segment of people who show the personality trait of openness, but who also showed less emotional range. These findings cover a range of topics including what types of offers users will respond to, what traffic channels they are more likely to use, or if they may also have specific product preferences based on their values.
Besides helping to understand how to reach and engage your users, this information can also help you fine tune your messaging by allowing you to figure out what will best motivate a response from users. When thinking about conversion rate optimization, it is helpful to think about Jeffrey Eisenberg’s idea of “buying modalities” which puts users into one of four buying categories based on their underlying motivations. For instance: is a user interested in competitive advantages, willing to buy spontaneously, looking to understand how the product works, or are they motivated by ethical or social concerns? All of these suggest different content requirements and can be derived from Watson’s personality outputs.
Enabling cognitive personalization on a website may sound difficult as you are crossing between multiple services and tools. However, enabling this can actually be quite simple. For example, integration with the Adobe stack is possible using the Twitter API as the text data source for a user, Adobe Experience Manager (Adobe’s CMS) to store the context data, and Adobe Target to provide customized messaging to users.
Account-Based Personalization
While cognitive personalization helps you to target individuals, account-based personalization is a B2B approach to personalization. Instead of thinking about targeting individuals, you are thinking about targeting businesses. These tools will look at the IP address of website visitors to infer which company they are accessing your site from. The tools build out a variety of fields that can be used for personalization purposes such as company, company size, industry, revenue range, employee count, and location.
Account-based personalization leads to some obvious personalization opportunities, including:
Besides the personalization applications, account-based services can also help with lead gen information quality and form usability. Knowing the company information for site users can change the types of questions you ask via progressive profiling, and will allow you to focus on a different subset of questions. It can also help shorten forms (as company information does not need to be entered), and can help with form completion and accuracy.
Account-based optimization has some compelling case studies. One example comes from the technology company, Citrix, who used account-based personalization to serve up vertical specific banners on their homepage. The result was a 30% increase in clicks on those banners, a 10% increase in page views, as well as an increase with other supporting site engagement metrics.
Personalization for the Internet of Things
The use of the Internet of Things as part of a digital marketing or analytics point of view is still in its infancy. The Internet of Things runs the gamut of sources from wearables to sensors, appliances to vehicles. The impact of this industry is predicted by McKinsey to be as high as $6.2 trillion by 2025. Using information collected by devices can help to develop substantially richer customer profiles with which to use for personalization, but the Internet of Things also offers completely new platforms on which personalization can be served up.
For example, the mobile apps connected to your Smart Fridge may know you are out of orange juice and push coupons to you to help entice your next purchase. This would be a standard online example of personalized content using information from a connected device. Or, the Internet of Things device – the fridge itself – could be used as the means by which to provide the personalization experience. What changes with the Internet of Things is that it’s not just a matter of having access to more information; it’s also changing where and how personalization experiences can occur.
As new services and technologies develop, the ability to use this richer information and provide new personalization touch points will also change. This provides new opportunities to continue to grow relationships with customers and enhance the user experience.
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