Isn’t it interesting how marketing trends and best practices are constantly changing, especially as business landscapes and technological advances evolve? Now more than ever, companies and organizations are adapting to online and hybrid business models to meet user expectations. If brands want to grow and thrive in the digital age, they need to focus on capturing and leveraging data. When they collect valuable information about their industry, competitors, and customers, they can build data-focused marketing campaigns that are effective and well-informed. What are the top five data-driven marketing trends for the coming year that marketers should know about?

Today’s customers are looking for consistent brand experiences no matter who they are or where they are on their user journey, whether they’re shopping in stores or online. Businesses should focus on creating omnichannel marketing strategies to ensure seamless transitions between all of their marketing channels and across all devices.

In omnichannel marketing, companies focus on developing their “brand voice” through cohesive content and messaging. They also use a variety of marketing channels that aren’t typically used in multi-channel marketing, such as SMS marketing and push notifications. Shoppers move effortlessly between user touchpoints without experiencing friction or inconsistencies.

Omnichannel marketing relies heavily on first-party data and personalization in order to be successful. Rather than sending the same email campaign to all of their customers, brands leverage user data to send targeted messages to drive open and clickthrough rates. Instead of using the same strategies for all their social channels, brands develop different approaches for engaging with their respective audiences.

Timberland, an American shoe and apparel company, utilizes near-field communication (NFC) technology to give consumers a frictionless omnichannel experience. They equip stores with tablets, which shoppers use to tap NFC-tagged inventory and learn more about the product. They can also use the tablets to add items to their shopping cart and receive personalized recommendations based on their interests. This helps Timberland monitor store traffic, capture consumer data, and send targeted emails to encourage future purchases.

Walgreens’s mobile app is another example of data-driven omnichannel marketing, as customers can check and refill their prescriptions without contacting their doctor or pharmacy. They can also set notifications for renewal and pick-up, making it easier for users to keep track of their prescriptions without the added friction of needing to make a call or wait in line. 

Virtual reality (VR) and augmented reality (AR) help people explore life-like environments and scenarios. While this technology is typically associated with the video game industry, 35% of marketers utilized VR and AR in 2021 to give shoppers immersive brand experiences. In virtual reality, users view three-dimensional images using specialized hardware. In augmented reality, users view the real world with additional visual, haptic (touch), or olfactory (smell) elements. Virtual and augmented reality offer unique and engaging opportunities to capture consumer data.

One example of virtual reality in marketing is TOMS’s Virtual Giving Trip. Toms Shoes is an American shoe company best known for giving one pair of shoes to a child in need for every pair purchased. In the video, TOMS’s founder takes viewers to a Peruvian elementary school to explain the company’s business model and demonstrate the shoe distribution process. This experience both educates people about TOMS’s brand values and gives TOMS valuable data about consumer engagement for developing future VR marketing strategies.

IKEA’s IKEA Place app demonstrates the practical marketing applications of augmented reality. Shoppers use the app to visualize true-to-scale 3D models of IKEA furniture and see how they would fit into their home or work space. In return, IKEA captures data on user preferences, which helps provide shoppers with more personalized recommendations over time.

Brands also use advanced technology like machine learning and artificial intelligence to simplify their processes, anticipate customers’ needs, and drive conversational marketing efforts. Chatbots use artificial intelligence, machine learning, and natural language processing (NLP) to automate tasks, connect with customers, and capture their data to further personalize their brand experience. Currently, almost 70% of online chats are conducted by chatbots from start to finish. For example, restaurant chatbots assist consumers with booking reservations, viewing menus, and ordering food ahead of time. This data helps serve recommendations in the future, such as restaurants that offer similar cuisine or are located in the same area. Machine learning enables brands to learn user preferences through automated conversations with the majority of their customers, rather than conducting surveys or polls for only select groups.

HelloFresh, a meal kit delivery service, uses chatbots to educate customers, answer questions, and provide special discounts. This helps them understand user inquiries and learn how to better address their needs. It also helps them track their bots’ effectiveness and ROI, as their discount codes are bot-specific.

Businesses also use machine learning and artificial intelligence for other marketing efforts, such as content creation, targeted advertising, and predictive analytics. One example of machine learning in action is Netflix’s recommendation algorithm. To start, Netflix creates a variety of content thumbnails, then conducts continuous A/B testing to see which thumbnails perform best and improve their clickthrough rates. Their algorithm also creates customer segments to appeal to their individual interests, such as identifying users who click on thumbnails featuring certain actors or users who prefer thumbnails that depict specific genres.

People use comment sections, discussion forums, and social media platforms to connect with people who share similar interests, including their favorite brands. Companies should take advantage of online brand communities to capture and leverage user data in two different ways: user-generated content and social listening.

User-generated content (UGC) comes from a brand’s followers and customers, rather than from the brand itself. It helps businesses reduce marketing costs, increase brand awareness and engagement, and nurture customer loyalty. Some examples of UGC include comments, reviews, and photos and videos. Brands typically encourage UGC creation through contests, branded hashtags, and loyalty programs. From there, they can collect information about their customers’ interests and preferences in order to nurture them along their path to purchase.

Social listening is the process of monitoring online spaces to capture qualitative and quantitative data about a specific topic or variety of topics. Brands utilize social listening to learn what people are saying about their brand, their competitors, and their industry. They can also use social listening to identify influencers and brand advocates who can help them expand their reach. Lastly, marketers use social listening to provide additional insights into their first-party data and vice versa. For example, they might discover video reviews about their latest product that can explain increases in website traffic and sales.

Brands should use online spaces to encourage user-generated content and practice social listening at the same time. For example, they can run a sweepstakes promotion where users enter by leaving a review on their website or submitting a photo on social media. This helps companies both increase consumer engagement and capture data about their customers’ interests. Brand hashtags are another effective way of nurturing UGC creation and gathering user information. Uber created a #BeyondFiveStars hashtag campaign to encourage Twitter users to share compliments and stories about exceptional Uber drivers. This campaign helped them generate reviews, improve their brand reputation, and learn what consumers look for in their Uber experience.

Businesses use social platforms like Facebook, Twitter, Instagram, and LinkedIn to share both branded content and user-generated content. Currently, about 89% of marketers are expected to spend the same amount of money or more on short-form videos for social media in the coming year. Short-form videos, commonly seen on TikTok, Instagram Reels, and Snapchat, prove to be more effective with consumers than long-form videos, due to their short attention spans. Video content relies heavily on data, as social platforms use machine learning to understand consumers’ interests over time and put the right videos in front of the right audiences.

Companies are also starting to focus more on audio content to initiate deeper dialogue and stronger connections with their customers. Audio content helps them gain qualitative user insights and position themselves as industry experts while appearing more approachable at the same time. For example, service platforms like Slack, Ziprecruiter, and Shopify have their own branded podcasts to interview guests and discuss industry-related topics. Brands also use ad slots to reach new audiences and capture data for nurturing their user journeys; podcast advertising revenue is projected to have surpassed $1 billion this year.

In addition to live video streaming platforms like YouTube and Twitch, live audio chat rooms like Twitter Spaces, Clubhouse, and Discord are also growing popular among marketers. Businesses use audio social platforms to practice social listening, share brand updates, lead discussions about industry topics, and foster online communities. They can use data to refine their audio content strategies by determining which guest speakers or topics generate the most awareness and engagement.

Brands often use marketing psychology to create impactful strategies and fulfill consumers’ needs and expectations. While marketing psychology is more based on qualitative principles than quantitative information, data still plays an important role in its effectiveness and execution.

The reciprocity principle is based on the idea that potential customers should get something first to motivate them to make a purchase in return. Businesses practice reciprocity by creating content that adds value to consumers’ initial brand experience without needing them to buy something. They can use data to identify where people are in their user journey and send them relevant information to nurture them into the next stage. For example, they can offer discount codes to users with items in their basket or invite them to join their loyalty program if they’ve already made multiple purchases.

Businesses can also leverage social proof, which relies on “the persuasive powers of experts, celebrities and user reviews” to solidify consumer trust in a brand and its products and services. Social proof marketing is primarily conducted through influencer marketing, online reviews, and user-generated content. Brands can use data to identify experts, influencers, and types of content that their leads or customers trust, then build their strategies around the results. For example, Apple learned that their users weren’t satisfied with the iPhone camera’s capabilities through data. To win back their trust, they launched their #ShotoniPhone hashtag campaign, where people shared their best iPhone photos that were later used in Apple’s advertising as proof of their camera quality.

Scarcity theory revolves around the idea that people place higher value on things that are harder to obtain. Consumers often want a specific product or service simply because it’s exclusive or not readily available. Businesses incorporate scarcity theory into their strategies through gamification, where they motivate users to participate in a promotion to achieve a goal or win a reward. Gamification is typically used in sweepstakes, contests, and loyalty programs to foster awareness and engagement. For example, in Universal’s All-Access Rewards program, users earn points via movie purchasing and other activities to win physical and digital prizes. When they make a certain number of purchases, they move up to a higher program tier, giving them access to more exclusive rewards. 

Loss aversion is similar to scarcity theory, as it’s based on the belief that people care more about avoiding a loss than acquiring a gain, also known as the fear of missing out. In marketing, this includes limited-time offers and exclusive products, where consumers are told it’s their last chance to buy or that there are only a few products left in stock. Marketers mainly execute loss aversion strategies through free trials and gift with purchase programs to encourage brand engagement and product purchasing. For example, Hershey Canada’s Cinema Snack Night gift with purchase program asked consumers to buy three participating Hershey products to earn a $5 Cineplex digital gift card. In both scarcity theory and loss aversion, brands can use data to determine which incentives drive the most engagement and conversions.

Personalization drives customer retention, brand loyalty, and customer lifetime value. Segmented marketing efforts also increase revenue and conversion rates, as customers respond positively to being seen and understood as individuals with their own preferences and behaviors. In order to incorporate personalization into their marketing campaigns, brands need to capture users’ zero-party and first-party data.

Companies collect zero-party data through surveys, quizzes, polls, reviews, and online interactions. Customers proactively and intentionally provide their information so that brands can better understand their needs. Since customers give zero-party data on a voluntary basis, marketers should include incentives to encourage users to share their data, such as discounts or free products. Zero-party data can help brands create customer profiles, drive personalization efforts, and nurture brand loyalty.

User feedback forms and crowdsourcing are effective ways of encouraging brand engagement and fostering customer retention. For example, Lay’s ran a Do Us A Flavor contest in which participants submitted and voted on potato chip flavor ideas via Facebook; the participant who submitted the winning flavor won a million dollars. This not only helped Lay’s create a new flavor, but also led to increased sales, website traffic, and over 1.2 million flavor submissions for future product development directly based on what their customers asked for.

Brands capture first-party data through account registrations, website and app activity, and shopping behavior. Customers knowingly provide their information because it’s necessary for engaging with brands and their products. This includes their contact details, purchase history, and user preferences. Like zero-party data, first-party data can help companies segment customers, build buyer personas, and send targeted messaging based on what they’re looking for. For example, Sephora starts by collecting information about which products their customers are viewing and buying. Then, they send personalized beauty and skincare recommendations to encourage future purchases.

Capture zero-party and first-party data to drive your marketing strategies

The key to effective marketing strategies is zero-party and first-party data. Both types of data help brands create omnichannel strategies, build connections and brand communities, take advantage of developing technologies, and personalize their marketing efforts. Without data, companies would be unable to understand consumer behavior and meet user expectations.

3 tier logic’s PLATFORM³ helps brands create marketing campaigns like gift with purchase promotions, sweepstakes, and loyalty programs to capture first-party data and gain valuable insights. The Data Capture & Analytics module gives businesses the information they need to make strategic business decisions and design data-driven marketing campaigns. To learn more, book a demo with our team today.