According to The Sprout Social Index™, consumers across age groups agree the most memorable thing a brand can do on social media is respond to customers. And not just respond. Consumers want to feel like your brand is speaking directly to them, addressing their unique preferences and needs.

Evolving your social strategy to meet consumer demands requires you to listen better, scale your customer care efforts and integrate your social and customer data. Your audience expects more from their favorite brands than canned responses. They want to feel like your first priority.

To create an exceptional customer experience, invest in your team’s social media personalization strategy. Learn about your audience on a deeper level. Get your business intelligence house in order. Make room for experimentation. These are critical steps toward nurturing and guarding your brand’s competitive edge and creating a cohesive journey for your audience.

What is social media personalization and why are marketers prioritizing it?

Social media personalization is when brands analyze customer behavior across multiple touchpoints, and deliver highly tailored social content or messages that are appropriate for a specific stage in each buyer’s journey. Personalization makes audiences feel cared for and connected to your brand, which inspires loyalty and conversions.

According to Salesforce’s State of the Connected Consumer report, 73% of consumers expect companies to understand their unique needs and expectations. Another 56% expect all offers to be personalized. To reach (and exceed) these high standards and make social media personalization a reality, you need a way to integrate customer data—including social data—in one place. A CRM or other customer data collection software is non-negotiable.

When you take a more tailored approach, social media personalization is a way to drive customer trust, brand affinity and revenue.

What you need to build and execute a social media personalization strategy

To personalize customer experiences on social, you need deep customer insights, comprehensive data and assistance from automated workflows. Carve out time for audience research and build the resources and the right infrastructure into your budget.

Audience research

Every audience is different. Research how your customers want to engage with you, and what kind of personalization efforts would resonate most. Consult data reports from trusted publications, survey your customers, collect competitor intel and sift through past social data.

Seek to answer questions like:

• Where do our customers currently encounter friction?
• What are our customer satisfaction scores? How do customers rate our service?
• What are our competitors and other brands doing well that we could learn from?
• What tactics perform best when retargeting existing customers?
• What content wows our audience? Which posts drive the most engagement?
• How comfortable is our target audience with personalization? What tactics would veer into creepy territory?

Once you have a clear understanding of your audience, take stock of business goals that align with social personalization efforts. Let your customer dictate the purpose and direction of your personalization strategy. Then figure out where your customer and business needs intersect.

For example, if your customers want more robust care on social, then your KPI might be increased customer satisfaction and loyalty. If your customers want targeted promotions, then your KPI might be increased revenue from ads and email campaigns.

The right infrastructure

Personalized marketing is only as successful as the processes and tech that support it. Many teams are already experimenting with customer data platforms that maximize the use of first-party data to prepare for Google finally phasing out third-party cookies. These platforms are key to preparing your business for delivering personalized experiences on social.

But customer data platforms are only effective if your team has the training to use them, and if they “talk” to the other tools in your tech stack. The tools also need a layer of usability so that everyone (not just data analysts and IT team members) can get the information they need. Beyond simply collecting and mining customer data, you need to build on it with AI and automation, analytics and segmentation.

As one member of Sprout’s community, The Arboretum, put it, “With increasing amounts of data available, social marketers will focus on delivering highly personalized content to users. Advanced algorithms and machine learning techniques should be [used] to analyze user preferences and behaviors, enabling tailored advertisements and messages.”

A social CRM platform like Sprout’s empowers your team to streamline data collection and distribution, reply to customers and manage your brand’s presence in one place.

With our Salesforce Marketing Cloud integration, customer data is enriched with social data so you can deliver a world class, omnichannel customer experience. This integration helps teams personalize marketing journeys based on social interactions and inform business strategy with social insights.

Strategic support from AI

Routing hundreds (or thousands) of incoming messages and sifting through millions of customer data points are common barriers to social media personalization. It’s inefficient for marketing teams to be bogged down with these manual, repetitive tasks. Instead they should prioritize meaningful work that requires human intervention. AI solutions help take on the heavy lift of data analysis and deliver insights faster, so that teams can personalize content at scale.

With Sprout’s AI and automation tools, your team can synthesize and manage massive amounts of data so that it’s easier to see what parts of your content you should be personalizing and how. For example, Sprout’s sentiment analysis features analyze incoming messages and classify customer sentiment toward your brand keywords as positive, negative or neutral. This data can reveal areas where customers need more customized support, or when they feel inundated with the wrong messaging.

3 brands experimenting with social media personalization

Some forward-thinking brands have already introduced social media personalization to their strategies. Here’s a roundup of three brands who excel at data-driven targeting, elevated customer care and turning customer insights into content.

The Sill grows their loyal fanbase

The plant delivery service, The Sill, became a personal favorite of mine a few years ago. I regularly peruse their website and social media pages looking for plants that would make the perfect gifts to celebrate the birthdays, engagements and anniversaries of my friends and family. I can assume the company is aware of my activity, as their sponsored posts regularly show up in my Instagram feed.

When I recently resubscribed to their email list while shopping on their site, a sponsored post mentioning the plant in my cart popped up in my Instagram feed within minutes. The Sill’s targeted ad strategy provides a seamless cross-channel customer experience that enriches my shopping and keeps the brand top of mind.

Considerations: As the pressure builds for your team to rely on first-party data, are you prepared to meet your customer across their purchasing journey? Like The Sill, can you provide sponsored recommendations and reminders to a targeted audience? Are there new opportunities to engage and re-engage your most loyal customers to drive revenue?

Chewy immortalizes pet parents’ love of their fur babies

Chewy, the pet retailer, is renowned for their above and beyond customer care efforts—on social and beyond. They are famous for a campaign where they send their customers hand-painted portraits of their pets to celebrate their birthdays and other milestones.

The tactic is one of many initiatives that have come to define the caring nature of the brand. They also introduced a “connect with a vet” chat feature that allows customers in emergency situations to get expert guidance on pet care best practices.

On social, they’re quick to respond to all incoming messages—especially customer issues—with customer information on-hand, ready to dive in where the customer left off.

Through their personalized approach to customer engagement, the company is building strong customer relationships and going viral along the way. The brand’s activations require collecting data at every point in the customer journey to deliver best-in-class care.

Considerations: How does your team engage your loyal customers proactively? Are you using data to surprise and delight? Can you tie your personalization efforts to retention, upselling or customer lifetime value?

Lox Club caters to audiences of one for content inspiration        

The social team behind dating app Lox Club curates a social presence that is more akin to a TV show. In fact, some of the company’s followers use the brand’s TikTok account to share their own comedic ideas, as if it were a virtual improv show. Like this follower who suggested the brand act out a raunchy take on KPIs in their social video.

By accepting feedback from their followers and turning it into content, Lox Club taps into the most crucial social media personalization truth: Your audience will tell you how they want to interact with you. They will tell you what tone you should strike, how to position your products and when your content is on the right track.

Considerations: What is your audience saying about your brand right now? Can you turn their feedback into tailored content? Have you considered using this personalization tactic to grow awareness in a targeted way?

Pave the way for social media personalization

In 2024, it won’t be enough for your brand to respond to customers. They want to feel like your first priority. To make that a reality, you need to truly understand your audience, and examine how you can evolve your tech stack to meet rising expectations. As you build your strategy, make room for experimentation and use audience intel to shape everything from social customer care to platform-specific content.

For more insights you can use to guide your team into the future, check out the latest edition of The Sprout Social Index™ and learn how shifting customer expectations will usher in a new era of marketing.

The post Social media personalization: The opportunity and risks to consider appeared first on Sprout Social.

Patagonia has proven social media isn’t just about likes and shares—it can be a driving force for meaningful change, building community, and responsible consumption. When running campaigns on some of the top social media platforms challenged its ethics, their team hit pause. This is a brand that is both data informed and value led – which has proved to be both a smart and successful strategy.

In today’s world, with fleeting trends and too many brands to keep track of, it will be those who build a strong, real connection with their community and stay true to their mission that withstand the test of time. As Patagonia founder Yvon Chouinard says, “A company doesn’t last 100 years by chasing endless growth. [Patagonia’s] success is based on quality in whatever we do, and we’re taking that into the future.”

Tune in on-demand to explore how Patagonia operates “business unusual”, leverages social data, and leans into authenticity and intention to drive their business strategy and growth. In this webinar, you’ll learn how to:

• Lean into authenticity and intention to drive your business strategy and growth
• Use your brand’s social channels to build a strong sense of community and connectedness online and offline
• Make social data work smarter, not harder, to drive business impact specific to your goals
• Get brand advocates, build strong community ties and drive engagement by putting people above products

Your Speakers:

The post How Patagonia Leads from a Foundation of Authenticity and Community appeared first on Sprout Social.

Social was built originally for consumers, not businesses or teams, and we set out to build the software for any organization to be successful. Our early product helped social teams build content calendars, find and respond to relevant comments, publish posts across multiple channels with ease, and track proxy metrics of success (remember Klout scores?).

Over time, social activity ballooned, matured and fractured as new networks, content formats and communities emerged. Consumer usage became mainstream and multi-generational. Brands’ investment in social began to reflect this wider and more committed adoption. Today, more than 4.9 billion people worldwide use social media, and 53% of consumers have increased their social media usage over the past two years. Social ad spending in the US alone is expected to surpass $80 billion by 2025. None of these patterns show signs of reversing course.

Consumers now see social as a connection to the companies and causes they care about—a faster, richer experience than support@ email addresses and 1-800 numbers. No longer just a frontier marketing or niche conversational channel, social is fast becoming the nexus of customer relationships and the primary digital face of brands.

What does that mean for the next generation of social media management solutions? 
Brands will need more than just the next iteration of tools. Simply responding to more customers, publishing on more networks and sharing raw data across teams, will only go so far.

As consumers increasingly make social the digital hubs of their lives, brands have the chance to understand their audiences and markets deeply, and to spread that knowledge throughout their organization. Social media management solutions will evolve into the thread that connects and strengthens the bonds between brands and consumers—woven throughout every team, strategy and customer experience.

The next generation of business on social is not particularly about “social” at all. It’s about real digital customer relationships.

Customer intelligence is converging on social

We’ve seen how social customer care has changed the way marketing and customer support teams operate. Years ago they may not have had a reason to interact or share information regularly, but social media has made them close collaborators out of necessity. As social becomes the primary hub for high-resolution consumer insights, imagine how other departments could transform their work.

Consider the speed and richness of customer information you can glean from social compared to channels like email or phone. Social content is immediate, continuous and more fully represents the person. Email, phone and other channels are far more asynchronous—frustratingly for days with email—and are episodic, giving a limited view of the customer. An Instagram Story reply happens in real time whereas an email might go unread for days, or weeks. Who a customer follows on X (formerly Twitter) and interacts with says a lot more about who they are as a person compared to one service representative’s short conversation on a support call.

With people putting more and more of their lives online—including their lives as customers—social data is becoming the core representation of the customer. This impacts and benefits every team, even when they’re not on the front lines of social. We’re seeing departments like recruiting, legal and product asking to get involved in social, a reality I never anticipated seeing when we started Sprout over a decade ago.

At the same time, social is becoming more complex. Brands need to factor in how quickly social is fragmenting and morphing across emerging platforms and evolving consumer preferences. More social networks to choose from means consumers are exposed to a wider set of perspectives (be them other users, influencers or businesses), making it crucial for brands to demonstrate they understand what their audience wants in each space.

This growing bounty of intelligence means social media will continue to supplant traditional market and customer research, as well as legacy customer records. But businesses need tools that can aggregate, disseminate and analyze social data at scale and across the organization, before it decays—whether that’s because the opportunity passed, preferences already shifted or a competitor acted first.

This will take advanced, yet elegant, technology. Simply increasing budgets and manpower won’t help brands capitalize on the opportunities social media brings to the table. For brands to consistently deliver the exceptional experiences consumers expect, and to fully realize the emerging opportunity to know the customer, social media management solutions will need to become more accessible, intuitive and purpose-built for every team.

The future of social media management is…

With each emerging generation and as new platforms come online, social will only become further ingrained into both society and, in the business world, every workflow and team. Whether that’s directly interacting with a customer or applying audience insights to the business, social media is the front-line for customer relationships and market intelligence. It’s where your brand, reputation and opportunity exists.

For organizations to be truly customer-centric, the future of social media management solutions must be built with these four pillars in mind:

1. Ubiquitous. With social becoming the kernel of the customer record, social media management solutions will need to become accessible and consumable by every team. That doesn’t mean your sales team is suddenly going to be posting Reels. Rather, democratizing access to your social management platform means upleveling data and insights for specific departments, business processes and decision makers.

Today, only the most forward-thinking companies share social media insights pervasively within their organizations. Tomorrow, this will be table stakes. We’ll know we’ve entered the next era when all teams see social data as critical to competitively addressing customer, product and business opportunities.

2. Personalized. While brands aren’t rushing to remove traditional channels like phone and email from their communication strategies, social is raising the bar for how and when they engage with their audience. Consumers don’t just want brands to respond to them on social; 70% of them expect companies to solve their problem in a personalized manner. But “personalization” has to mean more than populating dynamic fields with standard name or location inputs.

Younger generations, in particular, bring any and all issues to brands on social, assuming they’ll be met with swift and authentic interactions. They expect the people behind the brand account to treat them the way they’d be treated walking into a local, independently owned shop: with empathy and acknowledgement of their individual preferences. With powerful social media management tools that intuitively surface the context they brands need to truly know each customer on this level, they can engage accordingly.

3. Intelligent. Expecting teams to manually collate massive amounts of social listening data and transform it into actionable recommendations takes time away from their core work. Departments need answers, not more chores. With AI innovation, expect to see social media management solutions to automate and elevate how social data is used across teams. AI automation can, for example, present recommendations that empower brands to create highly personalized experiences in no time at all. Beyond saving time and resources, AI advancements in social media management solutions will enable teams to build relationships that influence revenue and loyalty at scale.

4. Interoperable. Customer relationships start, grow and expand on social. So it’s unsurprising that 96% of business leaders expect social data to be integrated into their organization’s CRM capabilities over the next three years. But integration is just the beginning.

It’s not enough to simply grant every department access to social data. Social media management solutions should process, package and seamlessly integrate data with the entirety of your organization’s tech stack. Social media management tools will become the go-to source that every team uses for immediate, in-depth market insights and customer intelligence.

The social media management solutions of tomorrow will be designed with every team in mind

Thirteen years ago at Sprout, we started by helping social teams simplify the tactical functions bogging down their workdays. We strove to empower social marketers, often working in teams of one, giving them the tools needed to keep up with the publishing and engagement responsibilities of their job.

But consumers expect more from brands now as social increasingly becomes the digital hub of their lives. The future of customer experience and understanding starts and ends with social. And social media management solutions must evolve to be more than an island, but a primary source purpose-built for every team to harness consumer insights and build deeper relationships.

For more perspective into how consumers’ social media behaviors and expectations are evolving, download The Sprout Social Index™ today.

The post What to expect from social media management in 2028 appeared first on Sprout Social.

But what was once a clear-cut process has become a complex collage of touchpoints thanks to the rise of digital marketing and social media. As Scott Feldman, Customer Intelligence Practice Lead for Canada at SAS describes, “Buying is not linear, and successful brands know it. Skilled marketers understand that digital and non-digital touchpoints all work together to drive conversions…You must add unique value across channels.”

Ultimately, he explains, it’s about showing up on the channels your customers use, and giving them the experience they’re looking for. To do that, it’s essential to tap into marketing business intelligence. In this article, I’m sharing more from my interview with Feldman where he explains what marketing business intelligence is, and how the insights you gain from it lead to more effective strategies for reaching your customers.

What is marketing business intelligence?

Feldman describes marketing business intelligence (BI) as: “The accumulation of data from all of your external channels.” For example, marketing BI originates from a variety of places including social business intelligence, social listening insights, website analytics, email marketing metrics and more. The data can be applied to functions within and outside of marketing, including customer care, product development and corporate strategy.

He goes on to add, “Marketing BI needs to reside in one place to effectively model and market. It enables a single view of your target audience and customers, and empowers you to track the channels your customers are using. Working off of that model allows us to be better connected marketers.”

How can marketing business intelligence benefit an organization?

Marketing BI is essential to empathizing with consumers at every stage of the customer life cycle. With those insights, you can grease the wheels of your marketing strategy, enabling stronger targeting, increased ROI and an improved customer experience (CX).

Define your ideal customer profile

Knowing who you should be marketing and selling to is key to growing your business. Yet, narrowing down an ideal customer profile is a challenge for many companies.

As Feldman explains, “When I work with brands that aren’t [tapping into BI data], I ask: ‘Do you know who your customer is? Do you know who you’re selling to?’ They often answer: ‘We’re everything to everyone.’ No brand should be a catch-all. Even phone companies don’t sell to everyone. Be true to yourself and your business by knowing who your customer is.”

With accurate marketing BI data, you can segment your audience into different buyer personas. The right BI tools enable you to create data visualizations and reports that demonstrate the defining characteristics of these personas—including their needs, pain points, demographics and even personality traits. The marketing BI insights should also illustrate the arc of a persona’s relationship with your brand—from first encounter to final sale.

For example, with social media intelligence insights, you can surface critical voice of the customer (VoC) data from various sources such as social listening, reviews, surveys and contact center interactions to track brand health, improve products and enhance customer engagement and retention.

Sprout Social’s social listening solution uses AI technology to calculate the overall sentiment of your brand, product or CX, and reveal audience insights from social conversations. This intel might reveal that a segment of your customers is using your product in a way that you didn’t realize, helping you better position your product going forward.

Refine marketing attribution

When it comes to asking for resources, marketing BI can help demonstrate the value of marketing initiatives to your CFO.

“The CFO doesn’t give an infinite budget. Your marketing campaign needs to be important to the business. Prove how your campaign leveled-up to revenue with data,” Feldman advises.

Marketing BI metrics like conversion rate, cost per conversion, return on ad spend, customer acquisition rate and marketing-sourced revenue demonstrate the throughline from your campaign efforts to your company’s bottom line. Continuously analyze marketing BI data to assess the status of key performance indicators (KPIs), measure the effectiveness of your campaigns and make data-driven improvements.

Not only will this data illustrate ROI, it will also guide your future investments in specific channels, and set you up for stronger marketing campaigns. As Feldman says, “Not every channel provides the same ROI. It’s important to attribute revenue and conversions to a certain source.”

For example, when defining actionable social media ROI for your business, using a tool like Sprout Social aggregates your paid campaign results from across channels. These analytics reports directly tie social activity on each channel to business results in shareable, digestible reports all stakeholders can understand.

Deliver a smoother customer experience

What was abundantly clear in my interview with Feldman was his passion for helping brands deliver a smoother CX. It was the crux of his argument for why BI data matters, and how it can help organizations.

“CX should be easy, memorable and positive. That’s what brands need to deliver. That’s what consumers are looking for. Every point of friction is measured against you. What you must create as a brand is an experience that people want,” Feldman emphasizes.

As a real-world example of what a smooth CX looks like, Feldman cites KFC. “Whether you like their food or not, KFC is one of the best brands on social. They’re smart, funny and witty. What you see on Facebook is not what you see on TikTok. They provide different value on each network.”

He goes on to describe how their customer care is second to none. “They’re responsive. It’s not just about being on these different channels. Their customer interactions are next level.”

Achieve this enviable world-class CX by using Sprout’s Smart Inbox to enable stronger collaboration between your social and customer care teams.

The inbox unifies your social channels into a single stream, and when you reply to a user, you see key BI like conversation history and customer relationship management (CRM) data. With this data, customer care reps can provide higher quality support across channels, and improve satisfaction across the customer journey.

Select the right business intelligence tools for your marketing team

Maximizing your use of marketing BI requires following data management best practices. As Feldman puts it, “If you’re working with stale data, then you’re not actually working off of marketing BI.”

To keep your data up-to-date, you need processes and tools that support seamless data collection and maintenance. Here are a few tips when selecting business intelligence tools for marketing teams.

Have an end goal in mind

According to Feldman, the most important step to take before setting out to update your processes or find a new tool is to think critically about what you want your marketing BI data to achieve. Ask yourself: What do we need to learn about our customer to improve our go-to-market approach? Feldman adds, “It’s not the channel or the tool you use, it’s what you get out of it.”

When you audit your processes and evaluate new tools, keep your brand’s strategy top of mind. Be sure you can access the customer intel that’s most important to your brand and industry. A good rule of thumb is to remember that your tools should meet your needs, you shouldn’t retrofit your strategy to fit a tool.

Choose user-friendly tools

In the same vein as serving your company’s unique strategy, your marketing BI tools should be accessible. They shouldn’t be so complex that only a data analyst can use them. The democratization of marketing BI data is what amplifies its impact beyond the marketing department, and makes a material difference in your CX. Usability is also critical for keeping data accurate and up-to-date.

Look for tools that are intuitive to use and make it easy for your team to make decisions that improve business strategy.

Integrate BI tools with your existing tech stack

When marketing BI tools integrate with the rest of your tech stack, the result is deeper customer satisfaction and internal synergy. Yet, many companies don’t have tools that work together. According to a Q3 Sprout pulse survey, only 37% of enterprise companies use integrated technology to address customer care needs, and 42% of all organizations cite gaps in available customer information as a barrier to providing customer support and a better CX.

On top of limited data, many organizations don’t know where their data is coming from, according to Feldman. By introducing complementary tools into your tech stack, you can improve your marketing BI reporting capabilities and improve your approach to customer care.

For example, with Sprout’s Salesforce integration, social data enriches your CRM data to provide a comprehensive view of your customer. With this integration, agents can engage in real-time with all the context they need. With a more complete picture of your audience, you can track customer journeys and segment audiences based on their social interactions with your brand.

Contextualize BI insights

Even as a social media management company, we acknowledge that social isn’t the only source of marketing BI. Feldman agrees. “You can’t attribute marketing BI from social alone.”

Having tools that help you contextualize and streamline all your marketing BI in one place, and illustrate how your different campaigns and channels interact together is essential.

Take Sprout’s Tableau integration. This Tableau BI Connector combines the power of social data with all your key data streams, including display ads, email campaigns, website data and more. You can customize the dashboard with the exact visuals and metric combinations you need, without requiring time-consuming development work.

To aid your search for the best tools for your company, here’s a complete list of marketing BI tools that can level up your business’ decision-making and improve your brand’s CX.

Use marketing business intelligence to better understand your customers

Accurate and up-to-date marketing BI makes it possible to optimize your campaigns, share meaningful data with stakeholders and, most importantly, elevate your CX. With comprehensive BI data at your fingertips, you can decrease customer acquisition and retention costs and prevent churn. As Feldman says, “People buy on emotion. Loyalty comes from having positive interactions with your brand, and forging an emotional tie.”

When used to its full potential, marketing BI is the bridge that connects your brand to your customers. If you want to dive deeper into understanding your customers’ journey, use this CX audit template to ensure your social channels are meeting the needs of your target audience.

The post How marketing business intelligence empowers you to reach your customers appeared first on Sprout Social.

In this session, we will cover:

• How brands can best utilize social media for quick, impactful, omni-present care 
• How to create competitive care strategies using AI to scale efficiency and data analysis 
• How personalization is fueling the future of exceptional care experiences

This session will be led by Sprout Social’s President, Ryan Barretto, and Vice President, Solutions Engineering, Colleen Geiselhart. They will also discuss how Sprout Social’s global partnership and integrations with Salesforce provide a unique perspective on how the world’s leading brands are harnessing the power of social data and insights to build successful Customer 360 strategies.

The post Social Media, AI, and the Future of Omni-Channel Care appeared first on Sprout Social.

Audiences are no longer just passively consuming branded content, they’re looking for it. 68% of consumers say they follow a brand on social to stay informed about new products or services. And over half of consumers say the most memorable thing a brand can do is respond to customers, underscoring the increased expectation for highly personalized engagements. 

As buyer experiences continue to go digital, consumer attitudes have shifted and social media is now the new mall. There’s an opportunity for your brand to capitalize on this shift, but to do so effectively, you must hone in on how your social team can make the most business impact and ultimately, drive revenue.

Dive into our newly released Index report to guide your brand on how to refine its social media playbook and give you the data to demonstrate social’s org-wide impact.

We’ll discuss:

• Four key investments guiding the socially sophisticated marketer 
• What consumers are looking for from your brand today
• How to effectively communicate social’s impact on revenue to business leaders

Want to get the most out of this event and connect with other like-minded professionals? Join our community, The Arboretum, to keep the conversation going, access additional resources and get exclusive swag.

Your speakers:

The post New Index Data: Refine Your Playbook for Social Sophistication appeared first on Sprout Social.

The innovation is already gaining traction, but decentralized social media could change Web3 as we know it. But first, let’s define the concept of decentralized social media and break down the most popular platforms. And we’ll outline how decentralized social media could impact marketers.

What is decentralized social media?

Decentralized social media platforms are networks that operate on various independent servers and/or a blockchain. Decentralized social media isn’t controlled by a single entity or confined to a centralized server like the legacy networks we use today. If you were to join a decentralized social media platform, you could send messages and engage with users across networks.

The fediverse, a portmanteau of “federation” and “universe,” is made up of decentralized social networks. It’s similar to the metaverse, but here’s the distinction: Instead of interconnected worlds fueled by augmented reality (AR) and virtual reality (VR), the fediverse consists of interoperable social networks. In layman’s terms, the fediverse enables different social networks to communicate with each other because there are multiple servers.

Since there isn’t a centralized server and blockchain technology allows data to be stored anywhere, it fosters stronger user autonomy and community, which has caught the eyes of many users. Many fediverse networks are guided by decentralized autonomous organizations (DAOS), which make decisions on the development of the platform.

Along with user control and community, there are other factors that attract users to flock to decentralized social media in lieu of traditional platforms. These include, but are not limited to:

• Censorship resistance
• Ownership of personal data
• Increased privacy and/or anonymity
• Economic independence and new forms of monetization (e.g Bitcoin, DAOS)
• User content ownership
• User rewards and incentives
• Transparency and auditability

6 decentralized social media platforms to know

Changes across traditional networks over the past few years have catalyzed the interest in decentralized social media platforms. As we emerge along the timeline for Web3, more people are learning about and joining the fediverse. But before marketers join in, you’ll need to understand the current landscape. Below is a quick overview of some of the most popular decentralized social media networks:

Mastodon

Founded in 2016, Mastodon is the largest open-source, microblogging platform in the world with over three million users. Like other social platforms, Mastodon users can share text-based content, GIFs, images and videos. The feed is in chronological order and users have full authority on what appears in their timeline. Users can join servers that are centered on set topics or interests.

Threads

Okay, technically Threads isn’t decentralized, but Meta plans to use ActivityPub, a decentralized protocol (it’s the same protocol Mastodon uses as well).

Threads is currently a text-based app linked to Instagram, but according to Meta’s website, the platform will enable users to communicate with other fediverse platforms. This means Threads users could follow, share content and interact with others on different platforms.

Steemit

Steemit launched in 2014, making it one of the oldest decentralized social media networks. Steemit is a blogging platform that uses its own blockchain and has a reward system using a native token currency, STEEM.

Users can earn STEEM by creating content and completing engagement tasks, such as upvoting posts. The platform also allows users to follow others and create niche communities.

Lens Protocol

Founded in 2022, Lens Protocol is a blockchain-based open source social graph dedicated to empowering content creators and creatives. Users have complete ownership over their profile, content, following and data. Lens Protocol is Ethereum-based.

Lens can be integrated with other Web3 applications and provides new monetization opportunities. For example, Lens handles are minted as NFTs that users can add to their crypto wallet. The platform currently has over 100,000 beta users, but interested Web3 aficionados can sign up for their waitlist.

Hive Social

Founded in 2019, Hive Social is another newer decentralized social media platform quickly gaining steam. In November 2022, the platform hit 1.5 million users. With polls, image posts, text and profile music, some would describe Hive Social as a conglomeration of X (formerly known as Twitter), Instagram, Tumblr and Myspace, but with several twists. The platform offers a chronological feed and customizable profile features including color themes and text edit functionality. Users can also add their pronouns and zodiac signs.

Hive is only available on mobile and there aren’t any ads, but the platform does use a native cryptocurrency to reward users to create and engage with connect, enabling users to monetize their creative contributions while also nurturing community.

Minds

Minds is another open-source network that aims to give users control of their experience on social media. The Ethereum-based platform prioritizes user privacy and data control, allowing participants to craft custom algorithms. To encourage content creation and engagement, Minds rewards users with cryptocurrency.

This list is truly just the tip of the iceberg when it comes to decentralized social media platforms, as Web3 networks are ever growing.

How decentralized social media could impact marketers

As you can see, many decentralized social media platforms are centered around giving user autonomy. This shift away from traditional systems will affect how brands approach marketing and social media as a whole. Let’s explore the potential impacts on marketers.

New forms of monetization will become the norm

More brands will embrace the new avenues for monetization created by decentralized social media. Digital currency will become necessary to ensure business resilience and maintain customer loyalty. Brands may even need to implement new cryptocurrency initiatives to help facilitate engagement.

Emphasis on organic, community-first social strategies

New advertising formats—or a lack of traditional ads entirely—will influence marketers’ approach to paid and organic strategies. Depending on how things play out, marketers could see an explosion of organic reach tactics because they might have a better return on investment than traditional paid ads.

In our LinkedIn poll below, we asked how decentralized social media will impact marketers and social teams the most. The top answer was community-first strategy, which reflects the essence of decentralized social media.

One commenter said marketers will need an audience-centric approach, but since this is less scalable, decentralized community management will require more boots on the ground to extend reach and achieve the same results traditional social would:

We may also see an increase in community-first strategies that focus on one platform. Instead of having to create and manage multiple accounts across several networks, decentralized social media opens the door for marketers to center on one platform of their choice. We’ll see a focus on making high-quality content that is malleable and resonates throughout the decentralized social media platforms.

More extensive crisis communication plans

Censorship resistance is one of the major appeals of the fediverse, but it also creates a slippery slope for misinformation and disinformation. Marketers will need to implement proactive frameworks for preventing misinformation/disinformation, along with extensive crisis communication plans to safeguard their brands.

The future of decentralized social media

Although decentralized social media is very different from traditional platforms, one thing remains the same: a desire for connection. Just like the other waves of innovation, marketers will adapt and nurture relationships to amplify their brand. Read more predictions about the future of social media to help inform how you should be shaping your community.

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As social media teams across the world figure out strategies to not only incorporate Threads  but also excel at it, this webinar will examine what we’ve learnt so far and explore thoughts on what we think is in store. 

Hear insights from social media consultant and industry analyst, Matt Navarra, and Senior Social Media Manager from financial favourite and industry disrupter, Monzo.

You will learn:

• The current state of Threads and how early adopter brands leverage its capabilities
• How businesses can use Threads for community building, customer care and more
• Key distinctions and differentiations between Threads strategy vs. other social channels
• Predictions for 2024 and beyond

Your speakers:

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Besides workflow efficiencies, AI tools provide nuanced insights that can transform your customer journeys to become more engaging and supportive. They enable you to develop a compelling customer experience strategy to serve customers better, provide personalized offerings and build meaningful relationships.

In this article, we’ll break down what AI customer experience is all about and the technologies that power it. You’ll also see eight practical applications of AI for creating a memorable, personalized customer experience.

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What is AI-driven customer experience?

AI customer experience is the use of AI technologies like natural language processing (NLP), text analysis and sentiment analysis to delight customers wherever and however they interact with your brand.

AI tools not only help replace cumbersome processes with highly efficient workflows, they seamlessly analyze unstructured data to extract important business intelligence. These valuable insights empower employees to make better decisions that improve the overall customer experience and satisfaction.

In fact, per The 2023 State of Social Media Report, 96% of business leaders believe AI will help companies significantly improve their decision-making processes going forward.

Technologies powering the AI customer experience

There are many AI-based technologies that work in conjunction with each other to elevate the customer experience. These are the most prominent ones.

Natural language processing

NLP helps a computer understand human language through text analysis, complete with colloquialisms, language-based nuances and emojis. To do this, NLP uses two other AI subtasks: natural language understanding (NLU) and natural language generation (NLG). NLU and NLG power smart assistants and AI-driven chatbots so they can be used for round-the-clock, enhanced customer service.

Sentiment analysis

Sentiment analysis detects emotions or sentiments in data, which can be used to gauge how customers perceive your brand or your services. The technology identifies sentiment in feedback from a wide range of sources such as platforms like Trustpilot or Google My Business, social media comments and direct mentions, surveys and news sources.

Predictive analytics

Predictive analytics understands patterns in customer behavior to anticipate future customer needs. It is used to optimize sales, plan logistics and supply chain, or boost brand promotions for maximum impact. For example, by studying customer data, retailers can anticipate ebbs and flows in footfalls based on location, events or seasons and allocate resources accordingly.

Predictive analysis can also be used to stem customer churn by identifying contributing factors based on voice of customer data.

Machine learning

Machine learning (ML) is used to mine insights from huge amounts of data automatically. AI systems use machine learning to automate subtasks such as topic extraction, feature classification and text parsing necessary for text analysis and sentiment analysis.

These models analyze data through artificial neural networks (ANNs) to understand and correlate patterns in data and learn as they go. This means, when they process customer experience data they can dig into audience demographics, interests, trending topics and other factors to provide increasingly accurate insights over time.

An example of this is how Spotify uses machine learning to improve content recommendations. It predicts what consumers may like based on their current listening choices and offers personalized suggestions across musical genres, playlists and podcasts.

Named entity recognition

Named entity recognition (NER) allows a computer to identify important names that occur in data. These named entities could be people, businesses, currencies or locations and are necessary for competitive analysis. An NER model can be trained to recognize millions of data points and apply them to industry-specific contexts.

Computer vision

Computer vision helps in image recognition and optical character recognition (OCR), which helps a system detect patterns in image-based big data. This technology is often used to identify celebrities, brands and products on social media platforms for targeted advertising and competitive analysis, and to diagnose customer issues.

8 ways to apply AI to the customer experience

According to our research, business leaders see vast potential for AI to make their brands more customer-centric. Here are the most useful applications of AI and machine learning that executives feel will build a richer, more effective customer experience.

1. Behavioral segmentation for targeted products and marketing

According to The 2023 State of Social Media report, 49% of business leaders think AI will be critical for behavioral segmentation to identify and target specific customer segments.

AI capabilities scan millions of data points from various sources such as social media and review websites to spot hidden patterns. This is how they provide insights beyond traditional demographic stereotypes (like, all gamers are male), allowing you to narrow down segmentation as much as you want. These insights help you develop more effective targeted marketing campaigns and a higher level of personalization in products and services.

For example, this makeup company has a targeted Facebook marketing campaign for women above 50 for a section of their makeup line, based on audience profiling.

2. Predictive analytics to forecast future customer behavior

Per the same report, 45% of leaders believe using predictive analytics to indicate future customer behavior will be an essential AI application.

Predictive analytics uses machine learning to analyze data, both internal (sales and customer data) and external (current events, competitor data, review and social media comments) for insights. These are critical for anticipating market trends and informing decisions around inventory control, marketing spend and other investments.

For example, alcoholic beverage company Diageo uses AI to get real-time forecasts of customer demand, commodity prices and creditor payments. It also uses AI insights to inform investment decisions based on factors like the timing, length and reach of a marketing campaign.

3. Optimize pricing based on demand

Forty-five percent of business leaders say that AI and ML will be critical for building dynamic pricing models in the future.

This is not surprising given that dynamic pricing is common in industries such as hospitality and tourism with fluctuating customer demand (e.g., the popularity of a flight/destination) and seasonality (weekends or weekdays).

AI algorithms analyze both historical and real-time data (e.g., inventory, demographic-based sales, competitor pricing and social media posts) to pull highly relevant, time-sensitive insights. With this information, teams can customize product pricing and messaging proactively so you can increase your competitiveness and meet revenue goals.

4. Sentiment analysis to understand customer feedback

Among the business leaders we surveyed, 44% report AI-driven sentiment analysis will be key to understanding customer feedback and responding to customer issues more efficiently.

A sentiment analysis software can specify what customers like and dislike about your brand by giving you targeted negative and positive metrics on a topic or aspect of your business. For example, a health system can use social media sentiment analysis to identify which aspects of their organization patients are happy with and which need to be improved.

In this manner, sentiment analysis can identify factors affecting your brand image, customer retention rate or brand loyalty.

In Sprout, you can do so from a variety of social listening sources like Twitter and Instagram. You can monitor and organize social mentions in real-time and measure sentiment based on terms and hashtags you want to track, all in one unified platform.

5. Personalize content and improve customer engagement

Forty-four percent of survey respondents feel using content recommendation engines to improve personalization is one of the most promising applications of AI.

AI tools provide customer-specific insights from purchase histories, website behavior (searches, scrolls and clicks) and comments to predict what they may be interested in so you can tailor and optimize your content for maximum impact.

You can also drive customer engagement and improve customer response rates significantly with personalized, pre-approved suggested replies using tools like Sprout, as ice-cream brand Carvel did for an enhanced customer experience.

6. Image recognition to analyze visual content

With visual content dominating everything from social media to web search, 43% of business leaders believe AI will help with image recognition to identify and analyze visual content.

Visual AI algorithms identify patterns in visual content, analyze search histories and provide targeted suggestions for design ideas or variations. Many popular brands such as Canva and social networks like Pinterest have already integrated this AI feature into their platforms for a richer user experience.

Visual AI is equally critical in sentiment mining, competitor analysis and personalized marketing and advertising tactics. For example, while searching for “gray wall bedroom ideas” on Pinterest, I also received targeted ads from home decor brand, Wayfair.

AI for visual content also includes video content analysis.

Videos are just a series of images or frames shown at an accelerated speed. AI algorithms break down these frames and scan for celebrity faces, brands, logos, locations or other elements they’ve been trained to look for.

This ability is a game-changer because it enables you to measure sentiment in videos as easily as in text data. You can measure customer sentiment and conduct competitive analysis on competing brands from videos on platforms like TikTok, Instagram and YouTube.

7. Improve customer service through improved chatbot interactions

Forty-one percent of business leaders think NLP will play a key role in improving customer interactions via virtual assistants and intelligent chatbots.

NLP enables virtual agents and chatbots to understand conversational language and respond to customers by automatically generating responses based on set parameters.

Unlike rules-based chatbots, AI-driven algorithms have the ability to understand semantics and therefore identify customer issues more easily. They can even recommend next steps like directing the customer to a live agent.

Brands like Walmart are already adopting conversational AI capabilities with ChatGPT to enrich their customer experience. Apart from having access to intuitive customer service, customers will also be able to add products to their cart by texting or using voice commands, via the Walmart mobile app.

8. Optimized voice search for better customer experience and SEO ranking

Last but not least, 40% of leaders believe voice search optimization is one of the most important applications of AI going forward.

AI-based voice search optimization improves your website’s content and structure to boost visibility so you fare better in voice search rankings. This is a growing need for brands, given that voice-enabled purchases through smartphones and smart devices in the home are anticipated to grow by 400% within two years (2021 to 2023).

Similarly, AI is helping replace tedious interactive voice recording (IVR) systems with intelligent voice automation to increase customer service efficiency.

Build a more human customer experience with AI

AI tools can fast-track your way to a richer customer experience built on personalized care, quicker support and authentic engagement.

Conducting a customer experience audit is a good place to start so you can identify what’s currently working and what areas need your attention. It will also give you a better idea of what AI capabilities will best serve your business goals.

Take a look at some of the templates we’ve developed to help you audit and optimize your customer experience.

The post The role of AI in creating a more human customer experience appeared first on Sprout Social.

There’s been a lot of discussion around the role of artificial intelligence (AI) in marketing and communications and for good reason: AI has the potential to reshape the corporate communications landscape. Corporate communications teams have become responsible for safeguarding their brand from potential misfires caused by AI technology. However, knowing where to begin in assessing the risks and benefits can be challenging.

Rachelle Bedell, Communications and Engagement Manager for the City of Gilroy, CA, has been experimenting with generative AI as she develops content to build connections between Gilroy’s local government and its 60,000 residents.

We spoke to Bedell about her big takeaways on the benefits and drawbacks of using AI in communications roles. In this guide, we’ll cover her tips, along with more advice on how communications leaders can empower their teams to use this technology with confidence.

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What can communications teams do with AI?

Many people claim that AI can increase your team’s productivity, but is there any evidence to support this? According to Bedell, there is.

“Not only does it make us more efficient, it makes us go further,” says Bedell. “It’s like the invention of the graphing calculator for math. We don’t have to sit around and add numbers with paper and a pencil anymore. Instead, we can take what it provides and do so much more.”

But what does “more” look like exactly? Here are three practical corporate communications applications that can help your team save time.

Streamline content ideation and creation

Coommunications professionals not only have to come up with creative, compelling brand messaging, they also have to tailor that message for specific channels, audiences and events. Meeting the right person with the right message at the right time is only getting harder.

Luckily, AI is here to help.

Generative AI tools like ChatGPT can’t provide you with ready-to-publish content: There’s still a lot of ambiguity around whether AI-generated content is protected under copyright law. To safeguard your business, it’s important to customize the final output with your brand’s distinctive tone. This will ensure a personal touch that maintains your brand’s image.

“I use it most often for rewrites,” says Bedell. “I’ll ask for ideas on how to rephrase content so it’s more engaging or so that it drives a specific action, then I evaluate its response and refine from there.”

AI-powered tools can give you a new perspective and spark creativity, guiding you in the right direction without having to wait for inspiration to strike. To maximize the efficiency of a tool, we need to master the art of writing an AI prompt or query so that the tool can pick the exact aspects of what needs to be delivered.

“It’s a great starting point for creative ideas,” says Bedell. “For example, I’m working on the city’s annual Pride Month campaign. We’ve done campaigns in the past where we’ve explored the symbolism of the Pride flag, and another where we highlighted important historical figures of the movement, but this year I wanted to do something different. I asked ChatGPT to generate some ideas and dove in from there.”

At Sprout, our communications team employs generative AI to develop creative titles for press releases and media pitches. A simple prompt like “Write 3-4 press release headline variations related to X, Y, and Z” can return valuable starting points for further refinement.

Collect social insights

Audience insights are the foundation of better brand positioning. With AI, communications teams can gain a deeper understanding of the customer’s mind through social media sentiment analysis.

Sentiment analysis tools use machine learning to gather information about consumer attitudes and assess their emotional state. In communications, these insights are commonly used to sharpen media pitches, messaging and executive comms.

For example, the Indiana University marketing and communications team relies on insights from Sprout’s Social Listening tool to stay up-to-date on campus conversations and get ahead of potential crises. These insights allow them to take proactive measures toward managing their reputation online.

At Sprout, we’re committed to building on this technology with a series of new AI features across the platform. We’re combining the power of our proprietary machine learning and automation capabilities with OpenAI’s GPT model. The new features will be available throughout the Sprout platform, starting with additions to listening, publishing, customer care and advocacy.

Gain a global advantage

Multilingual sentiment analysis uses native language machine learning to gather meaningful sentiment data from content across several languages. These tools capture the nuances specific to each language’s unique grammar rules.

These insights strengthen communications efforts geared toward non-English audiences, allowing you to build a brand that serves the diverse needs of your audience. For communications professionals like Bedell, such insights can ensure that all audiences receive messages that are both effective and equitable.

“California just passed a state-wide law allowing sidewalk vendors,” says Bedell. “Now, we’re changing our processes to accommodate state law. That includes creating ways to make the permit accessible to both our English- and Spanish-speaking populations.”

In the future, Bedell could use multilingual sentiment analysis to ground this work in data gathered from Spanish speakers in the region. This would help her create a more personalized message that reflects how residents are discussing the issue.

How communications teams can mitigate risks when working with AI

AI will undoubtedly transform the field of communications, but the professionals behind the screen are irreplaceable.

“The other day I saw a headline that said communications teams will eventually be replaced by AI,” says Bedell. “I knew it had to come from someone who isn’t currently working in communications. There’s too much nuance in the role for it to be fully automated. The tech isn’t there yet.”

On top of that, there’s a foundational communication skill that will always need a human touch: relationship-building.

“I don’t think people realize how much relationship-building goes into communications,” says Bedell. “It’s half the battle. The success of our content is dependent on our relationships with downtown businesses, the public health department—the list goes on.”

Instead of asking whether AI will replace our jobs, we should consider how it will transform them. The collaboration between AI and communication professionals creates a path toward a future where technology enhances human creativity, insight and productivity, redefining what’s possible for individuals at every level.

However, it’s crucial to acknowledge the risks associated with adopting AI. Finding the right balance between AI and human effort is key to achieving the best outcomes. As you embrace AI’s potential in communications, it’s important to understand and address the risks that come with it.

Double-check everything

Professionals who use text-based generative AI solutions should be cautious of potential avenues for misinformation, like “chatbot hallucinations” or faulty claims.

Bedell has experienced these issues firsthand. “I’ve had times where I’ve asked ChatGPT to share its sources and it hasn’t always worked out. Once, when I was looking for a source for an example it included, it told me that it didn’t realize I wanted a real example and had included a hypothetical option instead.”

When using AI-generated content, it’s crucial to ensure its accuracy and originality by reviewing it thoroughly. Always ask for sources from AI-powered assistants, and take the time to verify their validity. These steps are essential for maintaining your brand’s safety and avoiding potential crises.

Prioritize data security

Speaking of crises, any comms pro will tell you that even a mild data security mishap can be an absolute nightmare.

Communication teams aren’t responsible for setting the rules around how and why teams use AI. They will, however, have to deal with any fallout that occurs if an employee shares confidential information with an AI tool, creating an unfortunate privacy issue.

“You have to have conversations with legal and technical teams to understand the pitfalls your organization may face when working with AI,” says Bedell. “It’s important to find safe ways to let your employees leverage this type of tool.”

At Sprout, we’re prioritizing the security of our data and intellectual property by educating our teams on safe usage of generative AI. To ensure responsible use, our legal and IT teams worked together to create a policy outlining approved and prohibited use cases.

The policy is concise and straightforward, even for individuals with limited experience using AI tools. This helps busy teams navigate changes more easily, even with the rapid developments of generative AI.

Embrace experimentation

There are risks that come with using AI. That said, not using AI also presents risks of its own.

Bedell broke it down like this: “On one hand, you have companies that are embracing AI. On the other, there are companies that have chosen to prohibit its use entirely because it’s too new. I understand being concerned about the risk, but I feel like they’re missing a huge opportunity to let their people learn how to truly leverage it.”

Artificial intelligence is here to stay. We’ll continue to find more applications for AI in communications, media and PR. To avoid falling behind, it is essential to encourage your team to experiment frequently with AI technology.

Harnessing the power of AI in communications

Artificial intelligence can be a powerful ally in the ever-evolving world of corporate communication. When we combine AI with human expertise, we open ourselves up to a new era of communication that allows professionals to connect, resonate and drive success at scale.

For more insights on how communications leaders are extracting value from emerging technologies like artificial intelligence, machine learning and more, check out Sprout’s 2023 State of Social Media Report.

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