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Navigating the Tumultuous Waters of AI, Ethics, and Accessibility

Hot take: I’m not ready to hop on the AI hype train just yet.

Don’t get me wrong, I understand how the possibilities of AI are there, even if much of it hasn’t been quite realized yet. AI has the potential to make our lives easier. AI will definitely increase productivity. Even if the mention of ChatGPT makes you want to roll your eyes so hard they fall out of your head and you won’t have to be subjected to another useless AI-generated “news article” littering Google’s page one search results, the technology is accelerating at an exponential rate and there’s no turning back now.

It’s just that for me, the very real harms—such as exacerbating racial discrimination in policing and surveillance and scraping struggling artists’ works without consent, to name only a few — still far outweigh AI’s currently novel but ultimately still tepid applications.

Reflecting on Three Sessions from Three 2023 Salesforce Dreamin’ Conferences

A rising tide will carry all boats, but what if you don’t have a boat to begin with? What if you are already struggling to keep your head above water, and the deluge comes?

And yet, after recently wrapping up a hat trick of conferences (Midwest Dreamin’, WITness Success, and Mile High Dreamin’) where the topic of  this year’s sessions and keynotes were inevitably dominated by some permutation of AI (an in particular, GenAI), three sessions that I attended have managed to, if not entirely change, then at least somewhat soften my bearish stance on the whole thing.

At the very least, they’ve given me a lot of food for thought around AI and accessibility: who gets to have it, who doesn’t, and what that ultimately means.

“Generative AI and Ethics: Safeguarding Privacy and Nurturing Trust in the Salesforce Ecosystem”

Robert Wieland, Mile High Dreamin’ 2023

At this year’s Mile High Dreamin’, Robert Wieland, an AI Ethicist and Senior Salesforce Engineer at Verisk Analytics, led his audience through a brief but fascinating history of AI development,  which actually started as early as 1966 with the creation of ELIZA, the world’s earliest AI chatbot. His tour through AI history’s highlights and lowlights centered less on the latest groundbreaking developments and more so on the philosophies, ethical concerns, and questions that have arisen as a result, which made for a refreshing change from the usual shock and awe sales pitches I usually hear when it comes to the wonders of AI.

AI’s ethics framework can trace its roots to the 1979 Belmont Report, which laid the ethical foundation for human subjects research in medicine and the social sciences:

  • Human Autonomy, or the respect for people’s decisions and not injecting bias or manipulation into the decision-making process
  • Beneficence, or how to minimize harm while maximizing human well-being and benefits
  • Justice, or how to ensure equitable access and the equal and greatest distribution of benefits

 “In the realm of AI, ethics involves the thoughtful consideration of the potential impacts of AI technologies on individuals, society, and the environment,” Wieland said. “It prompts us to assess how these technologies align with our shared values and to ensure their responsible development and deployment.”

When it comes to predictive AI and language models, the ethical and social risks are not insubstantial, Wieland went on to explain, something we’ve unfortunately already begun to see play out in an alarming number of ways: from producing discrimination, exclusion, and toxicity to being used for misinformation by malicious actors to the incidental environmental harm as a byproduct of the sheer amount of processing power needed to run these increasingly complex processes to the unintentional harm caused by humans overly trusting a language model or treating it as human-like.

While he’s not looking at the AI world through rose-colored glasses, ultimately Wieland ended his presentation on a more optimistic note. There are, after all, a number of very smart people trying to steer this ship for whom these ethical considerations are always top of mind, including Paula Goldman, Salesforce’s Chief Ethical and Human Use Officer, and Kathy Baxter, Principal Architect of Ethical AI Practice. Together, they put out five guidelines for responsible generative AI development to act as Salesforce’s North Star.

While it’s reassuring to know that Salesforce wants to responsibly balance innovation with ethics, I’m more skeptical than Wieland on this front: I can only place so much trust in a corporate or governmental entity’s ability to be self-accountable to their self-proclaimed principles, something for which even Salesforce is not without controversy. Wieland himself noted,  “Even if you’re following the law, you can do things where people get queasy,” in reference to the 2012 controversy where Target used customer data to predict when someone was pregnant based on their shopping behavior and market to them accordingly. As we’ve seen many U.S. states begin to roll back LGBTQ+ protections and legal access to abortion, just because something is law does not necessarily mean it is ethical or just. How will the power of AI be wielded in those instances?

“Tech for Good: AI’s Role in Uplifting Marginalized and Underserved Communities”

Jaye Cherenfant, WITness Success 2023

Jaye Cherenfant is a Salesforce Administrator, tech enthusiast, and AI strategist who spent over a decade empowering Black students in the U.S. and South Africa before founding her own sustainable gardening business and then later launching Vista Tech Solutions, LLC, a tech consulting company.

As a Black, neurodivergent woman in tech, Cherenfant understands the vital importance of leveraging technology for beneficence, especially when it comes to serving the marginalized and underserved. In her session, she was especially concerned with how AI can inherit societal biases, further discrimination, and lead to data privacy violations that disproportionately impact BIPOC communities.

One of the best ways to begin to address these concerns, Cherenfant argued, is to ensure that tech teams, especially AI teams, diversify: Black people need a seat at the table.

But that’s far easier said than done. As of 2021, Black representation made up less than 10% of the STEM workforce, while Black women only represented 2% of the tech industry. These figures also reflect the STEM pipeline, where Black students make up only 9% of STEM degrees at all levels. According to a report from Jobs for the Future, the primary reasons for STEM underrepresentation are “systemic and structural barriers that Black learners confront from an early age into adulthood.” This includes a lack of access to a quality education and resources, which, in the U.S., are allocated based on wealth.

According to 2023 Pew Research, over half of Black households make less than $50,000 in the U.S, with 30% of Black households making less than $25,000.

One cascading effect of these inequities, Cherenfant pointed out, is a growing Digital Divide between children from low-income households and their more affluent peers, a disparity that worsened during the Covid-19 pandemic. According to the Pew Research Center, almost 60% of lower income families experienced at least one of the following digital access obstacles during the COVID-19 school shutdowns:

  • Having to use a mobile phone to complete schoolwork
  • Needing to use public Wi-Fi to complete schoolwork due to unreliable or no internet connectivity at home
  • Being unable to complete schoolwork due to not owning a computer

As the pace of technological innovation keeps accelerating, those who cannot access the knowledge and tools needed to contribute to these advances in hopes of shaping the discourse, nevermind merely being able to keep up with them, will fall further behind and eventually be shut out of these critical spheres altogether.

So where does that leave us? Where can we even begin to address these challenges? Cherenfant advocates that one’s activism can begin locally, from collaborating with her children on generative AI art projects to volunteering at local groups and community-driven events to introduce the community, and especially the youth, to the world of AI and practical AI applications. Giving underrepresented groups access to, knowledge of, and skills to use AI is the first step to giving them that much-needed seat.

My feelings on this are, as ever, somewhat mixed. On one hand, giving marginalized people equitable access to privileged white spaces to empower themselves and others  is crucially important to AI’s future and mitigating the growing harm that systemic biases like flawed racial profiling software and “predictive policing” algorithms are perpetuating.

On the other hand, as Audre Lorde said, “The master’s tools will never dismantle the master’s house.” Can we ignore how, despite assurances, companies are actively replacing or attempting to replace human creative labor, including already underrepresented Black creative labor, with generative AI to the point where even Hollywood has sat up and taken notice? Or how these technologies still betray their systemic bias even when they are being used by Black creators because of the inherently biased data sets they’re trained on?

I don’t know what the right answers are, or if there even are any to be had right now. If the goal laid out in our AI Ethics framework is to make sure AI is doing the greatest amount of good with the least amount of harm, what is an acceptable level of harm and who gets to decide what that is?

“How to Create Accessible Digital Marketing Assets”

Cara Weese, WITness Success 2023

While Cara Weese, CRM & Marketing Automation Strategist at Sercante (and, in full disclosure, one of my most favorite coworkers ever), did not directly address AI during her presentation, her topic was one that runs in the same circles of AI discussions nevertheless: accessibility, and in this case, specifically for those with disabilities.

Weese set the stage for her presentation by sharing her own powerful story as a person with a disability, which further drove home the point that people with disabilities aren’t an imaginary segment of the population to be treated as an afterthought or, worse still, acceptable collateral damage if the cost proves too high or the effort too bothersome to be ADA-compliant. In fact, according to the World Health Organization, 1.3 billion people, or 16% of the world’s population, have a significant disability. 

If us marketers don’t center accessibility-first strategies in our work, Weese said, we not only exclude a not insignificant portion of the population, we also risk a number of repercussions from missing opportunities to expand our customer base, create positive associations with our brand, encourage inclusivity in others, and improve our quality ranking score and SEO. 

And if that wasn’t convincing enough, businesses who fail to comply with ADA regulations are liable for some hefty penalties should their non-compliant practices be reported.

As Donald A. Norman, author of the influential book Design of Everyday Things, points out, “Designing for people with disabilities almost always leads to products that work better for everyone.” Using large, legible fonts and high contrast in our emails not only helps those with visual disabilities, but consider how much the elderly with failing eyesight would also appreciate these design choices. Or how about the fact that we’re all having to turn on the subtitles to watch TV shows and films these days.

Even in this, class is inextricably entwined with accessibility, furthering the Digital Divide. Assistive technologies such as screen readers are a helpful device for the visually impaired to navigate the digital world, but their high price point can pose a significant barrier for lower income households. And even if one were able to secure a lower cost device, as Weese explained, newer, more expensive screen readers are often more capable of parsing web pages and emails than cheaper ones, even when the content doesn’t entirely meet web accessibility requirements.


I’m not anti-AI.

I’m already eager to see how AI will get better at making inaccessible digital content accessible. I’ve already played around with gen AI for coding and generating seed data for Salesforce imports. I’m looking forward to trying out Jaye Cherenfant’s method of using gen AI to study for her Salesforce exam.

But what is more important to me than what I want AI to do is how I want it to be used — and how I don’t want it to be used. I’d love to see the rich experience of the marginalized to be welcomed and included in AI’s development to not only empower those communities but to improve the accuracy and power of AI itself. I want to see AI close the gap between the privileged and the underserved.

I don’t want to see the worst consequences of AI fall upon the most vulnerable among us: those with lower incomes, those who have been excluded from consideration, those who will suffer the most from climate change, and those who are primed to be heavily exploited by richer, and vastly more powerful entities.

The tide is rising, and the sea is rough. If we can’t stem or even slow it down, then at the very least, I hope we have the courage and strength to pull others out of the water and into the boat with us on our way up.

Original article: Navigating the Tumultuous Waters of AI, Ethics, and Accessibility

©2023 The Spot. All Rights Reserved.

The post Navigating the Tumultuous Waters of AI, Ethics, and Accessibility appeared first on The Spot.

By |2023-09-13T17:31:02+00:00September 13th, 2023|Categories: Community, Events, Real Talk|

Why You Should Delete Marketing Contacts Regularly

Like the title says — if you’re a Salesforce user, then you should be deleting your marketing contacts on a regular basis.

Okay, hear me out.

Of course I don’t mean all your contacts. And I don’t even necessarily mean delete delete (in some cases). Let me explain.

As marketers, we hoard and protect our contacts like dragons guarding our treasure. Our instinct is to grow — and keep — our contacts database as large as possible. After all, more contacts mean more people for the ever-demanding funnel.

But I’m here to tell you: stop it.

Why? Because as with many things in life, quality over quantity is what should matter here, even within the gaping maw that is the top of the funnel. 

And for more reasons than you think. Here are the three main ones.

Reason #1: Salesforce Puts a Cap on Contacts

Let’s start with the purely technical and perhaps thoroughly obvious: Salesforce gives you a finite number of contacts to keep. The number you can have varies depending on the plan you’re on and the optional number contact block add-ons you purchase.

No matter how adequate that number may seem at the time, it will start being not enough very shortly if you don’t have any safeguards in place.

Furthermore, the criteria for what counts towards this limit differs between Marketing Cloud Engagement (or MCE, formerly Marketing Cloud) and Marketing Cloud Account Engagement (MCAE, formerly Pardot… I know one day we’ll get used to the rebrand).

In Marketing Cloud Engagement:

MCE Edition Pro Corporate Enterprise
Base Contact Count 15k 45k 500k

Any Contact record (aka, any record on a sendable data extension with a unique ContactKey) on the All Contacts list counts towards MCE’s Contact Count limit. This includes:

  • Mobile contacts
  • Email subscribers
  • Any contacts from synchronized data sources (e.g., Salesforce objects). 

This is also why it is best practice to use a single ContactKey across Mobile, Email, and Synced Data Sources to prevent duplicates from unnecessarily eating up your Contact Count. 

You can monitor your Contact Count using the All Contacts list in Contact Builder.

Fun gotcha moment: If you’re syncing Salesforce Leads and Contacts and a Lead converts into a Contact, MCE will still count that synced Lead record and the new synced Contact record as two Contacts because they will still have two separate ContactKeys.
Fun gotcha moment #2: Even if you reduce the number of records on your synced sendable data extension, your All Contacts list count may not change. 

You will need to do some additional manual work here to enable contacts deletion from MCE if you haven’t done so already. Go to Contact Builder > Contacts Configuration and then choose the contacts you want to delete. 

If you want to mass delete a large number of contacts, you will either need to:
a) import a list of contacts back into MCE (counter-intuitive, I know) and then configure MCE to delete your contacts based off of that list 
– or –
b) create a REST API call to mass delete your contacts.

In Marketing Cloud Account Engagement (Pardot):

MCAE Edition Growth Plus Advanced Premium
Contact Blocks 10k (additional 10k blocks are $100/month 10k (additional 10k blocks are $150/month) 10k (additional 10k blocks are $300/month) 75k (additional 10k blocks are $400/month)

Fortunately, this is more straightforward. Any prospect record with a mailable status counts towards your mailable database limit. 

That’s it. You can keep an eye on your mailable database limit from the Pardot Settings tab.

Reason #2: Privacy Features Aren’t Going Away

In September 2021 as part of the iOS 15 updates, Apple rolled out Mail Privacy functionality that allowed its users to easily create throwaway email addresses for form fills (a common practice that many were already doing, Apple just automated it). 

Eight years prior to that, Google had broken up its Gmail inbox into tabbed categories in a better effort to keep “less important” emails — like marketing emails — from clogging up your immediate inbox. This year, Google will officially sunset its use of third-party cookies for tracking.

Suffice to say: more privacy features are coming into play and more consumers are concerned with how their data is being collected, stored, and used.

This is all great for consumer privacy, but less so for our marketing efforts.

Without intervention, we could face the possibility of having a database where a sizable portion of our contacts are, at best, completely unengaged, or, at worst, aren’t actually legitimate contacts in the first place.

Reason #3: You’re Skewing Your Metrics

Now take the nightmare scenario in Reason #2 and think about what this does to our precious email metrics. If we consistently send to a database of unengaged or non-legitimate contacts, leading to artificially low open rates and potentially high bounce rates, we’re skewing our own engagement rates from the start.

And if we’re relying on our engagement rates to determine campaign KPIs and attribution, we’ll have already introduced flawed data into our analysis.

How to Keep Your Marketing Contact Database as Clean as Possible

Okay, you’ve made some good points, I hopefully assume you’re thinking. So what can I do?

Well I’m glad you asked, because I have some tips for both Marketing Cloud Engagement and Marketing Cloud Account Engagement users.

Implement a Cold Leads Strategy

This is where I’m asking you to look deep inside yourself and fight against the marketer’s urge to hold onto all your contacts (or leads or prospects or whatever terminology you want to use here) for as long as possible under the hope that they’ll re-engage if you happen to send the right message at the right time.

Sure, you can always purchase additional space for more contacts, but why keep throwing more money after bad? Showing a little less mercy now will improve your marketing efforts later. As an additional consideration for MCE users, you also have to contend with a cap on how many communications you can send per subscription term. So why waste them?

Use Automations to Keep Your Database Clean

To start with, you can automate this process through features like: Automation Rules and Engagement Studio Programs (for MCAE) or Automation Studio and Journey Builder journeys (for MCE)

But the rough idea is to do the following:

Step 1: Put a quantifiable limit on how long you’ll consider someone who hasn’t engaged with any of your communications as “active.” This can be an actual time limit or after a certain number of consecutively unopened emails.

Step 2: Move these cold contacts somewhere else. Take them out of your regular communications, whether it’s through tags, a separate list segment, or a separate data extension. It’s time to put these contacts on a separate slower, low-frequency campaign.

Step 3: Send them an email again in a few weeks, maybe even months. Maybe send them another one later if you’re still full of hope. Give them a few more last chances to show engagement. The goal here is to check for a pulse, not necessarily to market anything at this point. This may also be the place where you can A/B test a few subject lines with pretty low stakes.

Step 4: If they re-engage: great! You can return them to the fold (or better still, use this opportunity to find out what their content preferences are by pointing them to an email preference center and letting them self-select their interests). If they don’t engage, get rid of them. 

  • Put them in the recycle bin if you’re a Marketing Cloud Account Engagement user (bonus: if you keep these prospects in the recycle bin, MCAE will automatically restore the prospect if they show signs of activity later on). 
  • Or, delete their record and unsync them in Marketing Cloud Engagement (we’ll talk about how to do this in a moment). 
  • You may even want to consider deleting the corresponding Salesforce record, because Salesforce has a data storage limit too.

If the idea of permanent deletion is too daunting, you can always export them to a spreadsheet and archive them elsewhere. You’ll still have the contact information, but it won’t be taking up space within your database.

Clean Out Your Hard Bounces

Make it routine to regularly clean out (or update) your contacts who have a hard bounce status. 

  • In addition to viewing your engagement metrics for each email send, MCAE also offers a helpful overall Email Bounce report on your prospects (you can find this under Pardot Reports > Marketing Assets > Emails > Email Bounces). 
  • With MCE, you can automate a query of the Bounce Data view and Subscriber statuses in Automation Studio.

Yes, both MCE and MCAE will (eventually) stop emailing any address with a hard bounce status. Yes, MCAE will automatically render a prospect with a hard bounce status as unmailable, meaning that the prospect won’t count towards your contact limit.

But in MCE, even if you can’t send emails to a Contact with a Bounced status, the contact will still count towards your Contact Count. And whether you’re using MCE or MCAE, if the contact has a corresponding Salesforce record, that record will also contribute to Salesforce’s overall data storage limit.

Furthermore, discrepancies between your segmentation lists or data extension numbers and what your email deliverability numbers actually are could cause some initial confusion among any users who aren’t aware of the automated mechanisms MCAE and MCE use to keep you from sending to unmailable addresses.

Be Selective about Salesforce Syncing

Being selective about who in your Salesforce database gets synced to MCE or MCAE will not only ensure that you aren’t sending marketing emails to contacts who shouldn’t be getting them (e.g. contacts who have not explicitly opted in, partners, vendors, and other operational contacts), but will also help you manage your contacts cap. 

In both cases, you will need to have automations in place that will determine the criteria for your sync trigger.

Now with MCE, let’s talk about the vexing problem of Leads and Contacts and the potential for duplicates. As mentioned earlier, even if your synced Salesforce Lead converts into a now synced Contact, your now defunct Lead record will still count towards your Contact Count. 

How to manage this? Build criteria into the automation that updates your MCE boolean syncing field to unsync the Lead when it converts. 

The Leads object has a number of different Lead Conversion-related fields you can use for your criteria — I like using the IsConverted boolean field, for example.

Use a Double Opt-in Signup Process

Using a double opt-in signup process for when a new contact is created is good practice to comply with various global data privacy laws and confirm a contact’s genuine interest in receiving your marketing emails. It also has the helpful benefit of verifying whether or not the email address on record is real. 

While this isn’t a 100% foolproof guarantee that a contact still isn’t using a throwaway email address, it will cut down on the number of outright junk emails entering your database.

Pay Attention to Auto-Replies

The deluge of autoresponders and out-of-office replies that result when you send an email to a large list can be a painful constant in a marketer’s life depending on a) whether you’re using MCE or MCAE (MCE has pretty robust Reply Mail Management functionality) and b) what processes you or your organization have set up to manage auto-replies. 

But there’s a silver lining to all this: what is being said in these auto-replies can be telling, especially in cases where the auto-reply lets you know that the contact is no longer going to be using the email address you have on record for them (usually in cases where the contact used an educational or organizational email address).

Creating a filter for key phrases often found in auto-replies where a contact is moving on from their organization (“moving on,” “leaving,” “no longer affiliated,” etc.) can give you a heads-up on removing that contact from your own database instead of waiting for the pending hard bounce when that email account is deactivated (which can range from very soon to months to never, depending on the organization’s offboarding process, or lack thereof). 

Save yourself from another auto-reply in your inbox, the contact taking up space in your database, and sending who-knows-how-many emails to an abandoned address.

Keeping Your Database Clean is an Ongoing Thing

Contact caps in your marketing database can feel like imaginary numbers to contacts-hungry marketers until their Salesforce Account Executive sends that dreaded over-limits notification. While it’s tempting to simply pay more to keep expanding your database cap, the cost does add up and it doesn’t address the root issues that could be impacting your database.

Without a little routine maintenance and ruthlessness to weed out your unengaged contacts and outright bad email addresses, your database can very easily become a hot mess, and any cleanup efforts thereafter will only become more challenging the longer it is allowed to go on. 

But a smart strategy (with help from a little automation) to filter and clean up your marketing database will not only be more cost-effective, but will maintain the integrity of your data.

Have any hot tips to share for keeping your contact list clean? Tell us in the comments.

Original article: Why You Should Delete Marketing Contacts Regularly

©2023 The Spot. All Rights Reserved.

The post Why You Should Delete Marketing Contacts Regularly appeared first on The Spot.

By |2023-02-08T15:54:25+00:00February 8th, 2023|Categories: Getting Started, Real Talk, revive, Setup & Admin, Strategy|

Marketing Cloud Personalization: 3 Use Cases and Implementation Tips

Salesforce Marketing Cloud Engagement has so many complex ways to create personalized experiences for the audiences the platform touches.

And if you haven’t gathered from the title, Salesforce Marketing Cloud Personalization (formerly Interaction Studio… RIP Interaction Studio) is a great way to level up your personalization game. This is for the pros who have long since mastered things like personalization strings, dynamic content, and even AMPscript in the platform.

However, as with many Marketing Cloud features, Marketing Cloud Personalization offers so much flexibility and configurability that it can be challenging to know just where and how to begin.  

Three Marketing Cloud Personalization Use Case Examples

Perhaps the best way to get started is to understand some industry-specific use cases for when Marketing Cloud Personalization web and mobile personalized campaigns can be strategically leveraged to create a customized, unified, and value-driven experience for your customers at every stage of the life cycle. 

Use Case #1: Serve targeted educational content for prospective customers in the finance industry

A financial advisory company knows that potential new customers frequently conduct more research in the earliest stages of the buying lifecycle. Fortunately, the company maintains a finance blog on their site that features thought leadership from their advisors for just this very purpose.

When a new customer first comes to the company’s site, they may see an assortment of featured blog posts on the home page. Some posts on mutual fund investments capture their interest, so they click into them. They may then use the navigation menu or site search to investigate further.

Tracking content engagement

Meanwhile, Marketing Cloud Personalization tracks their site activity, such as which blog posts and product pages they spend more time on. They use this information to build a  profile of customer preferences and affinities. Then, surface content in which the customer has indicated an interest using this customer profile information.

Showing profile-specific content

The next time the customer navigates to the home page or the blog landing page, they see featured posts on best tips to diversify their funds and an explainer of what investment objectives, risks, charges, and expenses they should be aware of when selecting a mutual fund. The customer clicks into the posts and successfully becomes further engaged with the company’s website.

Use Case #2: Enrich a student’s higher education on-campus experience.

With tuition more expensive than ever and the pool of college students ever shrinking, a regional college knows that one of the strongest differentiators they can offer their students is a rewarding college experience that isn’t just confined to the classroom.

Showing targeted reminders in the college online portal

When a student subscribes to a college campus group’s mailing list, Marketing Cloud Personalization tracks that activity. The tool displays reminders of upcoming meetings hosted by that group on the home page of the student’s online portal account. 

And, Marketing Cloud Personalization highlights a promotion for an upcoming lecture hosted by a notable product designer when the student browses the college’s events calendar. That’s because the system knows the student once took an elective on product design.

After class, the student stops by a local art gallery that features art from fellow college students. Marketing Cloud Personalization notes the geolocation and time spent within the store. It uses that information to display a 15% discount code for the gallery in an infobar banner ad within the college’s mobile app. The student also sees an ad for the store when they get the monthly campus newsletter they subscribed to.

Enhancing the overall student experience

By being served content that is tailored to the student’s own personal and educational interests, the student is more connected with their campus and, as a result, their satisfaction with their college experience increases.

Use Case #3: Onboard new app users with well-timed contextual tips and cross-sell to existing customers in the same place, at the same time.

New users logging into a company’s app for the first time may need initial guidance on how to use the app to encourage adoption. But there also needs to be a balance between providing timely instruction and not being obstructive. 

Marketing Cloud Personalization first designates which users are logging into their accounts for the first time and those who have already been using the app extensively into two audiences.

Automate first-time user adoption

When a first-time user logs onto the app, they receive a pop-up window offering them a brief tutorial on how to use the app, with the option to entirely skip or end the tutorial at any time. The tutorial displays step-by-step contextual pop-ups at different places on the screen to demonstrate the app’s functionality and features. The tutorial finishes by pointing out to the user where they can access the support center for future assistance. If the user skipped the tutorial or exited out of it early, Marketing Cloud Personalization can note this.

Ensure continued use over time

Marketing Cloud Personalization can then monitor these new users for a defined period of time to evaluate whether they are using the app, and place them on a journey within Journey Builder to issue reminders and feature highlights. Once a user becomes comfortable in using the app, they can be moved from the first-time user audience and into other segments for further targeted marketing.

Create deeper connections over time

For the audience of existing users, Marketing Cloud Personalization can display inline banner promotions for other products they may be interested in or useful tips on how to use the product that they bought based on their actions, how long they’ve been a customer, and their personal attributes, all within the app, on the company website, and in marketing emails and text messages.

While targeting two different audience segments, Marketing Cloud Personalization can display content not only based on customer activity, but also at strategic moments and through different statuses, such as whether they’re a first-time user or not. Customers, in turn, not only receive personalized content, but content that is served to them at the time they would benefit from it the most.

Three Things to Prepare Before SFMC Personalization Implementation

The above examples are hardly an exhaustive list of all the ways in which companies can engage potential, new, and existing customers with Marketing Cloud Personalization. But no matter the industry or use case, there are also three things you should do to set your company up for success long before you implement.

Step 1. Align Internal Teams

You need to align your internal teams. The lift for setting up Marketing Cloud Personalization is quite a bit heavier than many of Marketing Cloud’s other tools. Depending on your business needs, the tool will require more resources of varying specializations. 

  • You’ll need web development resources for deploying the necessary code to your website and apps (and the more frequently your site changes, the greater the demand on your web development team). 
  • Your marketing and graphic design teams will need to create all the variations of content and assets that could be displayed to your audiences. 
  • It is also highly recommended that you invest in UX Design resources as well, because…

Step 2. Know Your Audience

You need to know your customers. Not only should you identify all potential customer personas, but you should also map the journeys each persona could have across your website or app, whether it’s a first-time visitor browsing your site or a long-standing customer who wants to change the billing information associated with their account. 

Identify customer interaction points

This process involves identifying every point of customer interaction, including areas where your customer is likely to experience frustration and reward (there’s a reason, after all, that Marketing Cloud Personalization is called a Real-Time Interaction Management platform). 

A good UX designer will conduct research and testing to accurately paint a full picture of how customers use your website or app. From there, you will be able to create a strategy for how Marketing Cloud Personalization will display the right messages in the right ways at the right time to deliver the highest value for your customers.

Step 3. Create Content Beforehand

You must frontload your content. Of course, with all that pre-planning and journey mapping means you’ll actually have to create the content you’ll be using for every personalized path your strategy involves. 

Determine content categories and tags

You will also need to make sure your content is properly categorized and tagged for the audiences and customer interaction points with which they’ll be associated, and this is even more crucial. 

For example, you want to feature other recommended products (let’s say, a moisture-resistant jacket, water bottle, and thermal socks) that are related to the product that a customer is viewing on your website (hiking boots). 

You’ll need to decide on the content tags that determine what other related products to display (hiking, moisture resistance, outdoors) and for what type of audience segment attributes (new and returning customers, hikers, outdoor enthusiasts, beginner to intermediate experience, ages 20-45).

Completing Marketing Cloud Personalization implementation pre-work is totally worth it

While the amount of pre-work required to leverage Marketing Cloud Personalization can seem daunting all on its own, it’s important to remember that a hyper-personalization system requires a hyper-detailed amount of content to feed into it. 

And all that work is likely to pay significant dividends in the end. According to a McKinsey & Company report, over three-quarters of consumers report that personalized communications are a key factor in brand considerations and increase the likelihood of repurchase. 

When implemented (and maintained) correctly with the right personalization strategy in place, Marketing Cloud Personalization can give your company a powerful tool to sharpen your communications and truly engage with the full breadth and depth of your customers.

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Original article: Marketing Cloud Personalization: 3 Use Cases and Implementation Tips

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By |2022-11-23T19:27:00+00:00November 23rd, 2022|Categories: Getting Started, revive, Setup & Admin|