Aim/Purpose: This exploratory study investigates the influential factors of users’ decisions in the dilemma of whether to agree to online personalization or to protect their online privacy. Background: Various factors related to online privacy and anonymity were considered, such as user’s privacy concern on the Web in general and particularly on social networks, user online privacy literacy, and field of study. Methodology: To this end, 155 students from different fields of study in the Israeli academia were administered closed-ended questionnaires. Findings: The multivariate linear regression analysis showed that as the participants’ privacy concern increases, they tend to prefer privacy protection over online personalization. In addition, there were significant differences between men and women, as men tended to favor privacy protection more than women did. Impact on Society: This research has social implications for the academia and general public as they show it is possible to influence the personalization-privacy tradeoff and encourage users to prefer privacy protection by raising their concern for the preservation of their online privacy. Furthermore, the users’ preference to protect their privacy even at the expense of their online malleability may lead to the reduction of online privacy-paradox behavior. Future Research: Since our results were based on students' self-perceptions, which might be biased, future work should apply qualitative analysis to explore additional types and influencing factors of online privacy behavior.

Five hundred members of Flooring America, Flooring Canada and The Floor Trader learn the latest strategies to drive growth and market differentiation for independent flooring retailers.

By Jack Pollard, freelance writer.

Retail is one of the most competitive landscapes out there today. Consumption is at an all-time high, but the cost of living crisis means that brands need to fight harder than ever to convince consumers that their products are what they need.

As CTV is pulling in more advertising dollars and viewers than ever before, it's crucial for advertisers to ensure that they are optimizing their reach with the best-targeted data to represent audiences and outcomes, all while respecting data privacy laws and individual rights. What are the most significant challenges surrounding data identity and the privacy economy in today's CTV advertising ecosystem? How can content owners and platform providers supply advertisers with the user data that will maximize growth without violating personal privacy or privacy laws? And how might the idea of "TV" itself be redefined in an era when multiscreen use beyond the living room is so prevalent?

AI-driven Personalization in Digital Media: Political and Societal Implications Research paper sysadmin 2 December 2019

The fallout from disinformation and online manipulation strategies have alerted Western democracies to the novel, nuanced vulnerabilities of our information society. This paper outlines the implications of the adoption of AI by the the legacy media, as well as by the new media, focusing on personalization.

Summary

• Machine learning (ML)-driven personalization is fast expanding from social media to the wider information space, encompassing legacy media, multinational conglomerates and digital-native publishers: however, this is happening within a regulatory and oversight vacuum that needs to be addressed as a matter of urgency.
• Mass-scale adoption of personalization in communication has serious implications for human rights, societal resilience and political security. Data protection, privacy and wrongful discrimination, as well as freedom of opinion and of expression, are some of the areas impacted by this technological transformation.
• Artificial intelligence (AI) and its ML subset are novel technologies that demand novel ways of approaching oversight, monitoring and analysis. Policymakers, regulators, media professionals and engineers need to be able to conceptualize issues in an interdisciplinary way that is appropriate for sociotechnical systems.
• Funding needs to be allocated to research into human–computer interaction in information environments, data infrastructure, technology market trends, and the broader impact of ML systems within the communication sector.
• Although global, high-level ethical frameworks for AI are welcome, they are no substitute for domain- and context-specific codes of ethics. Legacy media and digital-native publishers need to overhaul their editorial codes to make them fit for purpose in a digital ecosystem transformed by ML. Journalistic principles need to be reformulated and refined in the current informational context in order to efficiently inform the ML models built for personalized communication.
• Codes of ethics will not by themselves be enough, so current regulatory and legislative frameworks as they relate to media need to be reassessed. Media regulators need to develop their in-house capacity for thorough research and monitoring into ML systems, and – when appropriate –proportionate sanctions for actors found to be employing such systems towards malign ends. Collaboration with data protection authorities, competition authorities and national electoral commissions is paramount for preserving the integrity of elections and of a political discourse grounded on democratic principles.
• Upskilling senior managers and editorial teams is fundamental if media professionals are to be able to engage meaningfully and effectively with data scientists and AI engineers.

With all that spam clogging your inbox, a more personalized experience with the brands you interact with would be a refreshing change of pace. Sharing insights from his research into what brands can do to improve the experience of the people they want to reach, personalization pioneer Mark Abraham highlights a key mindset that can help companies boost their growth (and delight their customers) in the era of AI.

As a UX professional in today’s data-driven landscape, it’s increasingly likely that you’ve been asked to design a personalized digital experience, whether it’s a public website, user portal, or native application. Yet while there continues to be no shortage of marketing hype around personalization platforms, we still have very few standardized approaches for implementing personalized UX.

That’s where we come in. After completing dozens of personalization projects over the past few years, we gave ourselves a goal: could you create a holistic personalization framework specifically for UX practitioners? The Personalization Pyramid is a designer-centric model for standing up human-centered personalization programs, spanning data, segmentation, content delivery, and overall goals. By using this approach, you will be able to understand the core components of a contemporary, UX-driven personalization program (or at the very least know enough to get started). 

Getting Started

For the sake of this article, we’ll assume you’re already familiar with the basics of digital personalization. A good overview can be found here: Website Personalization Planning. While UX projects in this area can take on many different forms, they often stem from similar starting points.      

Common scenarios for starting a personalization project:

• Your organization or client purchased a content management system (CMS) or marketing automation platform (MAP) or related technology that supports personalization
• The CMO, CDO, or CIO has identified personalization as a goal
• Customer data is disjointed or ambiguous
• You are running some isolated targeting campaigns or A/B testing
• Stakeholders disagree on personalization approach
• Mandate of customer privacy rules (e.g. GDPR) requires revisiting existing user targeting practices

Regardless of where you begin, a successful personalization program will require the same core building blocks. We’ve captured these as the “levels” on the pyramid. Whether you are a UX designer, researcher, or strategist, understanding the core components can help make your contribution successful.  

From top to bottom, the levels include:

1. North Star: What larger strategic objective is driving the personalization program? 
2. Goals: What are the specific, measurable outcomes of the program? 
3. Touchpoints: Where will the personalized experience be served?
4. Contexts and Campaigns: What personalization content will the user see?
5. User Segments: What constitutes a unique, usable audience? 
6. Actionable Data: What reliable and authoritative data is captured by our technical platform to drive personalization?  
7. Raw Data: What wider set of data is conceivably available (already in our setting) allowing you to personalize?

We’ll go through each of these levels in turn. To help make this actionable, we created an accompanying deck of cards to illustrate specific examples from each level. We’ve found them helpful in personalization brainstorming sessions, and will include examples for you here.

Starting at the Top

The components of the pyramid are as follows:

North Star

A north star is what you are aiming for overall with your personalization program (big or small). The North Star defines the (one) overall mission of the personalization program. What do you wish to accomplish? North Stars cast a shadow. The bigger the star, the bigger the shadow. Example of North Starts might include: 

1. Function: Personalize based on basic user inputs. Examples: “Raw” notifications, basic search results, system user settings and configuration options, general customization, basic optimizations
2. Feature: Self-contained personalization componentry. Examples: “Cooked” notifications, advanced optimizations (geolocation), basic dynamic messaging, customized modules, automations, recommenders
3. Experience: Personalized user experiences across multiple interactions and user flows. Examples: Email campaigns, landing pages, advanced messaging (i.e. C2C chat) or conversational interfaces, larger user flows and content-intensive optimizations (localization).
4. Product: Highly differentiating personalized product experiences. Examples: Standalone, branded experiences with personalization at their core, like the “algotorial” playlists by Spotify such as Discover Weekly.

Goals

As in any good UX design, personalization can help accelerate designing with customer intentions. Goals are the tactical and measurable metrics that will prove the overall program is successful. A good place to start is with your current analytics and measurement program and metrics you can benchmark against. In some cases, new goals may be appropriate. The key thing to remember is that personalization itself is not a goal, rather it is a means to an end. Common goals include:

• Conversion
• Time on task
• Net promoter score (NPS)
• Customer satisfaction 

Touchpoints

Touchpoints are where the personalization happens. As a UX designer, this will be one of your largest areas of responsibility. The touchpoints available to you will depend on how your personalization and associated technology capabilities are instrumented, and should be rooted in improving a user’s experience at a particular point in the journey. Touchpoints can be multi-device (mobile, in-store, website) but also more granular (web banner, web pop-up etc.). Here are some examples:

Channel-level Touchpoints

• Email: Role
• Email: Time of open
• In-store display (JSON endpoint)
• Native app
• Search

Wireframe-level Touchpoints

• Web overlay
• Web alert bar
• Web banner
• Web content block
• Web menu

If you’re designing for web interfaces, for example, you will likely need to include personalized “zones” in your wireframes. The content for these can be presented programmatically in touchpoints based on our next step, contexts and campaigns.

Contexts and Campaigns

Once you’ve outlined some touchpoints, you can consider the actual personalized content a user will receive. Many personalization tools will refer to these as “campaigns” (so, for example, a campaign on a web banner for new visitors to the website). These will programmatically be shown at certain touchpoints to certain user segments, as defined by user data. At this stage, we find it helpful to consider two separate models: a context model and a content model. The context helps you consider the level of engagement of the user at the personalization moment, for example a user casually browsing information vs. doing a deep-dive. Think of it in terms of information retrieval behaviors. The content model can then help you determine what type of personalization to serve based on the context (for example, an “Enrich” campaign that shows related articles may be a suitable supplement to extant content).

Personalization Context Model:

1. Browse
2. Skim
3. Nudge
4. Feast

Personalization Content Model:

1. Alert
2. Make Easier
3. Cross-Sell
4. Enrich

We’ve written extensively about each of these models elsewhere, so if you’d like to read more you can check out Colin’s Personalization Content Model and Jeff’s Personalization Context Model. 

User Segments

User segments can be created prescriptively or adaptively, based on user research (e.g. via rules and logic tied to set user behaviors or via A/B testing). At a minimum you will likely need to consider how to treat the unknown or first-time visitor, the guest or returning visitor for whom you may have a stateful cookie (or equivalent post-cookie identifier), or the authenticated visitor who is logged in. Here are some examples from the personalization pyramid:

• Unknown
• Guest
• Authenticated
• Default
• Referred
• Role
• Cohort
• Unique ID

Actionable Data

Every organization with any digital presence has data. It’s a matter of asking what data you can ethically collect on users, its inherent reliability and value, as to how can you use it (sometimes known as “data activation.”) Fortunately, the tide is turning to first-party data: a recent study by Twilio estimates some 80% of businesses are using at least some type of first-party data to personalize the customer experience. 

First-party data represents multiple advantages on the UX front, including being relatively simple to collect, more likely to be accurate, and less susceptible to the “creep factor” of third-party data. So a key part of your UX strategy should be to determine what the best form of data collection is on your audiences. Here are some examples:

There is a progression of profiling when it comes to recognizing and making decisioning about different audiences and their signals. It tends to move towards more granular constructs about smaller and smaller cohorts of users as time and confidence and data volume grow.

While some combination of implicit / explicit data is generally a prerequisite for any implementation (more commonly referred to as first party and third-party data) ML efforts are typically not cost-effective directly out of the box. This is because a strong data backbone and content repository is a prerequisite for optimization. But these approaches should be considered as part of the larger roadmap and may indeed help accelerate the organization’s overall progress. Typically at this point you will partner with key stakeholders and product owners to design a profiling model. The profiling model includes defining approach to configuring profiles, profile keys, profile cards and pattern cards. A multi-faceted approach to profiling which makes it scalable.

Pulling it Together

While the cards comprise the starting point to an inventory of sorts (we provide blanks for you to tailor your own), a set of potential levers and motivations for the style of personalization activities you aspire to deliver, they are more valuable when thought of in a grouping. 

In assembling a card “hand”, one can begin to trace the entire trajectory from leadership focus down through a strategic and tactical execution. It is also at the heart of the way both co-authors have conducted workshops in assembling a program backlog—which is a fine subject for another article.

In the meantime, what is important to note is that each colored class of card is helpful to survey in understanding the range of choices potentially at your disposal, it is threading through and making concrete decisions about for whom this decisioning will be made: where, when, and how.

Lay Down Your Cards

Any sustainable personalization strategy must consider near, mid and long-term goals. Even with the leading CMS platforms like Sitecore and Adobe or the most exciting composable CMS DXP out there, there is simply no “easy button” wherein a personalization program can be stood up and immediately view meaningful results. That said, there is a common grammar to all personalization activities, just like every sentence has nouns and verbs. These cards attempt to map that territory.

Picture this. You’ve joined a squad at your company that’s designing new product features with an emphasis on automation or AI. Or your company has just implemented a personalization engine. Either way, you’re designing with data. Now what? When it comes to designing for personalization, there are many cautionary tales, no overnight successes, and few guides for the perplexed. 

Between the fantasy of getting it right and the fear of it going wrong—like when we encounter “persofails” in the vein of a company repeatedly imploring everyday consumers to buy additional toilet seats—the personalization gap is real. It’s an especially confounding place to be a digital professional without a map, a compass, or a plan.

For those of you venturing into personalization, there’s no Lonely Planet and few tour guides because effective personalization is so specific to each organization’s talent, technology, and market position. 

But you can ensure that your team has packed its bags sensibly.

There’s a DIY formula to increase your chances for success. At minimum, you’ll defuse your boss’s irrational exuberance. Before the party you’ll need to effectively prepare.

We call it prepersonalization.

Behind the music

Consider Spotify’s DJ feature, which debuted this past year.

https://www.youtube.com/watch?v=ok-aNnc0Dko

We’re used to seeing the polished final result of a personalization feature. Before the year-end award, the making-of backstory, or the behind-the-scenes victory lap, a personalized feature had to be conceived, budgeted, and prioritized. Before any personalization feature goes live in your product or service, it lives amid a backlog of worthy ideas for expressing customer experiences more dynamically.

So how do you know where to place your personalization bets? How do you design consistent interactions that won’t trip up users or—worse—breed mistrust? We’ve found that for many budgeted programs to justify their ongoing investments, they first needed one or more workshops to convene key stakeholders and internal customers of the technology. Make yours count.

​From Big Tech to fledgling startups, we’ve seen the same evolution up close with our clients. In our experiences with working on small and large personalization efforts, a program’s ultimate track record—and its ability to weather tough questions, work steadily toward shared answers, and organize its design and technology efforts—turns on how effectively these prepersonalization activities play out.

Time and again, we’ve seen effective workshops separate future success stories from unsuccessful efforts, saving countless time, resources, and collective well-being in the process.

A personalization practice involves a multiyear effort of testing and feature development. It’s not a switch-flip moment in your tech stack. It’s best managed as a backlog that often evolves through three steps: 

1. customer experience optimization (CXO, also known as A/B testing or experimentation)
2. always-on automations (whether rules-based or machine-generated)
3. mature features or standalone product development (such as Spotify’s DJ experience)

This is why we created our progressive personalization framework and why we’re field-testing an accompanying deck of cards: we believe that there’s a base grammar, a set of “nouns and verbs” that your organization can use to design experiences that are customized, personalized, or automated. You won’t need these cards. But we strongly recommend that you create something similar, whether that might be digital or physical.

Set your kitchen timer

How long does it take to cook up a prepersonalization workshop? The surrounding assessment activities that we recommend including can (and often do) span weeks. For the core workshop, we recommend aiming for two to three days. Here’s a summary of our broader approach along with details on the essential first-day activities.

The full arc of the wider workshop is threefold:

1. Kickstart: This sets the terms of engagement as you focus on the opportunity as well as the readiness and drive of your team and your leadership. .
2. Plan your work: This is the heart of the card-based workshop activities where you specify a plan of attack and the scope of work.
3. Work your plan: This phase is all about creating a competitive environment for team participants to individually pitch their own pilots that each contain a proof-of-concept project, its business case, and its operating model.

Give yourself at least a day, split into two large time blocks, to power through a concentrated version of those first two phases.

Kickstart: Whet your appetite

We call the first lesson the “landscape of connected experience.” It explores the personalization possibilities in your organization. A connected experience, in our parlance, is any UX requiring the orchestration of multiple systems of record on the backend. This could be a content-management system combined with a marketing-automation platform. It could be a digital-asset manager combined with a customer-data platform.

Spark conversation by naming consumer examples and business-to-business examples of connected experience interactions that you admire, find familiar, or even dislike. This should cover a representative range of personalization patterns, including automated app-based interactions (such as onboarding sequences or wizards), notifications, and recommenders. We have a catalog of these in the cards. Here’s a list of 142 different interactions to jog your thinking.

This is all about setting the table. What are the possible paths for the practice in your organization? If you want a broader view, here’s a long-form primer and a strategic framework.

Assess each example that you discuss for its complexity and the level of effort that you estimate that it would take for your team to deliver that feature (or something similar). In our cards, we divide connected experiences into five levels: functions, features, experiences, complete products, and portfolios. Size your own build here. This will help to focus the conversation on the merits of ongoing investment as well as the gap between what you deliver today and what you want to deliver in the future.

Next, have your team plot each idea on the following 2×2 grid, which lays out the four enduring arguments for a personalized experience. This is critical because it emphasizes how personalization can not only help your external customers but also affect your own ways of working. It’s also a reminder (which is why we used the word argument earlier) of the broader effort beyond these tactical interventions.

Each team member should vote on where they see your product or service putting its emphasis. Naturally, you can’t prioritize all of them. The intention here is to flesh out how different departments may view their own upsides to the effort, which can vary from one to the next. Documenting your desired outcomes lets you know how the team internally aligns across representatives from different departments or functional areas.

The third and final kickstart activity is about naming your personalization gap. Is your customer journey well documented? Will data and privacy compliance be too big of a challenge? Do you have content metadata needs that you have to address? (We’re pretty sure that you do: it’s just a matter of recognizing the relative size of that need and its remedy.) In our cards, we’ve noted a number of program risks, including common team dispositions. Our Detractor card, for example, lists six stakeholder behaviors that hinder progress.

Effectively collaborating and managing expectations is critical to your success. Consider the potential barriers to your future progress. Press the participants to name specific steps to overcome or mitigate those barriers in your organization. As studies have shown, personalization efforts face many common barriers.

At this point, you’ve hopefully discussed sample interactions, emphasized a key area of benefit, and flagged key gaps? Good—you’re ready to continue.

Hit that test kitchen

Next, let’s look at what you’ll need to bring your personalization recipes to life. Personalization engines, which are robust software suites for automating and expressing dynamic content, can intimidate new customers. Their capabilities are sweeping and powerful, and they present broad options for how your organization can conduct its activities. This presents the question: Where do you begin when you’re configuring a connected experience?

What’s important here is to avoid treating the installed software like it were a dream kitchen from some fantasy remodeling project (as one of our client executives memorably put it). These software engines are more like test kitchens where your team can begin devising, tasting, and refining the snacks and meals that will become a part of your personalization program’s regularly evolving menu.

The ultimate menu of the prioritized backlog will come together over the course of the workshop. And creating “dishes” is the way that you’ll have individual team stakeholders construct personalized interactions that serve their needs or the needs of others.

The dishes will come from recipes, and those recipes have set ingredients.

Verify your ingredients

Like a good product manager, you’ll make sure—andyou’ll validate with the right stakeholders present—that you have all the ingredients on hand to cook up your desired interaction (or that you can work out what needs to be added to your pantry). These ingredients include the audience that you’re targeting, content and design elements, the context for the interaction, and your measure for how it’ll come together. 

This isn’t just about discovering requirements. Documenting your personalizations as a series of if-then statements lets the team: 

1. compare findings toward a unified approach for developing features, not unlike when artists paint with the same palette; 
2. specify a consistent set of interactions that users find uniform or familiar; 
3. and develop parity across performance measurements and key performance indicators too. 

This helps you streamline your designs and your technical efforts while you deliver a shared palette of core motifs of your personalized or automated experience.

Compose your recipe

What ingredients are important to you? Think of a who-what-when-why construct: 

• Who are your key audience segments or groups?
• What kind of content will you give them, in what design elements, and under what circumstances?
• And for which business and user benefits?

We first developed these cards and card categories five years ago. We regularly play-test their fit with conference audiences and clients. And we still encounter new possibilities. But they all follow an underlying who-what-when-why logic.

Here are three examples for a subscription-based reading app, which you can generally follow along with right to left in the cards in the accompanying photo below. 

1. Nurture personalization: When a guest or an unknown visitor interacts with  a product title, a banner or alert bar appears that makes it easier for them to encounter a related title they may want to read, saving them time.
2. Welcome automation: When there’s a newly registered user, an email is generated to call out the breadth of the content catalog and to make them a happier subscriber.
3. Winback automation: Before their subscription lapses or after a recent failed renewal, a user is sent an email that gives them a promotional offer to suggest that they reconsider renewing or to remind them to renew.

A useful preworkshop activity may be to think through a first draft of what these cards might be for your organization, although we’ve also found that this process sometimes flows best through cocreating the recipes themselves. Start with a set of blank cards, and begin labeling and grouping them through the design process, eventually distilling them to a refined subset of highly useful candidate cards.

You can think of the later stages of the workshop as moving from recipes toward a cookbook in focus—like a more nuanced customer-journey mapping. Individual “cooks” will pitch their recipes to the team, using a common jobs-to-be-done format so that measurability and results are baked in, and from there, the resulting collection will be prioritized for finished design and delivery to production.

Better kitchens require better architecture

Simplifying a customer experience is a complicated effort for those who are inside delivering it. Beware anyone who says otherwise. With that being said,  “Complicated problems can be hard to solve, but they are addressable with rules and recipes.”

When personalization becomes a laugh line, it’s because a team is overfitting: they aren’t designing with their best data. Like a sparse pantry, every organization has metadata debt to go along with its technical debt, and this creates a drag on personalization effectiveness. Your AI’s output quality, for example, is indeed limited by your IA. Spotify’s poster-child prowess today was unfathomable before they acquired a seemingly modest metadata startup that now powers its underlying information architecture.

You can definitely stand the heat…

Personalization technology opens a doorway into a confounding ocean of possible designs. Only a disciplined and highly collaborative approach will bring about the necessary focus and intention to succeed. So banish the dream kitchen. Instead, hit the test kitchen to save time, preserve job satisfaction and security, and safely dispense with the fanciful ideas that originate upstairs of the doers in your organization. There are meals to serve and mouths to feed.

This workshop framework gives you a fighting shot at lasting success as well as sound beginnings. Wiring up your information layer isn’t an overnight affair. But if you use the same cookbook and shared recipes, you’ll have solid footing for success. We designed these activities to make your organization’s needs concrete and clear, long before the hazards pile up.

While there are associated costs toward investing in this kind of technology and product design, your ability to size up and confront your unique situation and your digital capabilities is time well spent. Don’t squander it. The proof, as they say, is in the pudding.

As more businesses yield the benefits of NLP-powered analytics and conversational interfaces, demand for single-vendor solutions will increase.

This free Trip Planner is a perfect tool for travelers to discover new places, create a personalized itinerary, and have an organized vacation.

StoneShot's Financial Marketer Mindset study reveals biggest challenges facing financial marketers today and the impact of technology on marketing strategy

Aprimo CMO says marketers are currently struggling with what he calls “digital sameness” — where everyone is doing the same thing online.

Please visit Marketing Land for the full article.

2 December 2019

The fallout from disinformation and online manipulation strategies have alerted Western democracies to the novel, nuanced vulnerabilities of our information society. This paper outlines the implications of the adoption of AI by the the legacy media, as well as by the new media, focusing on personalization.

How the global hotel chain's loyalty program offers the data it needs to create tailored experiences for its guests.

How the retail pharmacy chain uses customer data to make its marketing messages relevant

It's time to move beyond mere product recommendations.

AI plays a huge role in how Spotify delivers personalized playlists to users, so it's somewhat fitting that the companys new partnership with Microsoft is focused on messages about how AI can impact all aspects of life -- including education, healthcare and philanthropy. Those messages are going to be showing up in the Discover Weekly playlist for free users, the first time that Spotify has lets brands have full customization and control over advertising in that feed.

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One of the struggles that marketers face is how to send the right message at exactly the right time to target people in a way that will appeal to them. To solve the problem, businesses need to get themselves acquainted with new technologies and the power of personalization. In the past few years, digital marketing […]

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