With global beauty and personal care revenue expected to reach nearly $736 billion by 2028, omnichannel strategies are now critical for brands seeking to capture market share. Recent studies show that 73% of consumers use multiple channels in their shopping journey, and 85% of customers expect consistent interactions with businesses across channels. Additionally, personalization has become a key factor, with 80% of customers more likely to make a purchase when brands offer tailored experiences. However, brands are up against a big challenge—finding the balance between offering personalized, consistent customer experiences and managing their data responsibly.
With 80% of customers feeling their experiences should be better, considering all the data companies collect, and 79% being now more protective of their personal data, the pressure is on. To succeed, beauty brands must develop a data strategy that not only addresses customer expectations but also ensures compliance with privacy regulations.
In this article, we’ll address three core questions that every beauty brand must consider to unlock the full potential of omnichannel: What data is needed, what capabilities are essential, and what organizational shifts are required? Answering these questions can help brands create personalized, data-driven experiences that keep customers coming back and build true loyalty.
What Data is Needed to Deliver an Omnichannel Experience?
To create a unified experience, beauty retailers must consider a variety of data types that help capture the full picture of customer journeys and preferences, including customer data, transaction data, behavioral data, product data, supply chain data, marketing data, customer support data, device and location data, channel preference data, and privacy/consent data. But while collecting all this data is necessary, it’s just as important to be transparent. For example, 44% of consumers are okay with brands collecting first-party data, but only 30% are comfortable with brands gathering third-party data. Additionally 71% of consumers say they would trust a company more if the use of their data was clearly explained.
Each of these data types plays an important role in personalizing the customer experience. For example, a skincare brand can use purchase and browsing data to recommend products suited to a customer’s needs. However, with 51% of customers feeling that their data is not used in ways that benefit them, brands must make sure that the data is not only collected but also used in a way that clearly adds value.
How Can Brands Access Data They Don’t Own?
In addition to first-party data, brands often need to access data they don’t own to enhance their omnichannel strategies. Here are some strategies to acquire such data:
- Partnerships and Collaborations: Form strategic partnerships with other businesses to share data. For example, a beauty retailer may collaborate with a social media platform to gain insights into customer preferences and behaviors.
- Data Exchange Platforms and Aggregators: Use data exchange platforms and work with data aggregators to buy, sell, or trade data. These platforms compile data from a variety of sources, such as demographics, behaviors, and transactions, providing valuable insights for refining omnichannel strategies.
- APIs and Integrations: Integrate with third-party services through APIs to access external data sources. For example, a retailer may connect with a logistics provider's API to gain real-time data on supply chains, which helps improve inventory management and delivery processes.
- Customer Incentives: Encourage customers to voluntarily share their data. Offering incentives like discounts, loyalty points, or exclusive offers in exchange for data not only boosts engagement but also helps brands collect valuable insights.
- Collaborative Data Sharing Initiatives: In some industries, companies collaborate to share specific types of data for mutual benefit. This is particularly useful for understanding industry trends and benchmarking performance.
While these strategies help brands access critical data for their omnichannel initiatives, it’s crucial to ensure that data expansion and integration are managed effectively to maintain data quality and support long-term growth. Learn more about mastering data governance and expansion here.
Take a look at how different organizations have successfully structured their data to drive growth, innovation and competitiveness in their respective sectors.
What Data Capabilities Are Required for Omnichannel Success?
To deliver a seamless omnichannel experience, brands need specific data capabilities that provide real-time insights, offer personalization, and still respect consumer privacy.
Unified Customer Data and Real-Time Synchronization: To maintain a seamless view of customers, brands need systems that integrate data from multiple channels into a single, unified profile. This real-time capability ensures that a customer’s preferences or purchase history are up to date no matter where they engage with the brand. By centralizing data, brands can make sure each interaction feels relevant and personalized. This is important because 80% of customers feel that their experience should be better, considering all the data brands collect.
Cross-Channel Tracking and Centralized Analytics: Effective omnichannel strategies rely on tracking customer journeys across channels to optimize engagement. Centralized analytics let brands monitor key metrics like engagement, conversion rates, and overall satisfaction. This not only helps improve customer experiences across all channels but also provides a complete view of customer behavior, empowering brands to make informed decisions. Whether it's refining social media campaigns or enhancing the in-store experience, centralized analytics ensure brands stay aligned with customer expectations and preferences.
Customer Segmentation & Targeting: Advanced data capabilities enable businesses to segment their customer base effectively and target specific groups with tailored messaging. This targeted approach enhances marketing effectiveness and drives better results.
AI & Automation: Artificial intelligence and automation play a significant role in enhancing omnichannel capabilities. AI-driven insights empower brands to boost personalization, while automated workflow improves operational efficiency.
Personalization at Scale: Leveraging AI and advanced analytics, beauty brands can deliver relevant content, product recommendations, and tailored services. For example, a skincare brand could use personalization to recommend products based on a customer’s purchase history and online behavior.
Privacy and Security Compliance: As customers become more protective of their data, it’s important to stay compliant with privacy regulations. Brands that are transparent about how they handle data will be more likely to gain customer trust.
What Organizational Requirements Enable an Effective Omnichannel Data Strategy?
For beauty brands, building a successful omnichannel strategy goes beyond just gathering data – it requires getting the entire organization on board and supporting a data-driven approach.
Building a Data-Driven Culture: Fostering a culture that understands the importance of data is key to omnichannel success. By educating teams about how data insights can drive better decision-making, leaders can shift the focus from intuition to analytics. This mindset should be integrated at all levels – from marketing to customer service, ensuring everyone is aligned in using data to enhance the customer experience.
Investing in Data Integration and Advanced Analytics Tools: Advanced analytics platforms and integration technologies are essential for managing data. For example, Data Cloud allows for centralized data management, making it easier to integrate, analyze, and get insights from various data sources.
Cross-Functional Teams and Ongoing Training: Collaboration across departments is crucial for a unified omnichannel strategy. By bringing together marketing, IT, and data analytics teams, brands can streamline their efforts, from campaign development to customer support. Continuous training helps the team stay up to date with new technologies, data strategies, and evolving customer expectations, ensuring they can quickly adapt to changing trends.
Focus on Long-Term Data Investments: To stay competitive, beauty brands must view data-related investments as long-term commitments. This involves budgeting for scalable infrastructure, advanced analytics, and AI-driven solutions that grow with the brand. Investments in innovation, like AI-driven product recommendations or AR virtual try-ons, are becoming the standard for delivering personalized experiences.
By understanding the types of data needed, developing key data capabilities, and aligning organizational resources, beauty brands can unlock new levels of personalization and customer satisfaction. A strong data strategy not only optimizes omnichannel performance but also elevates the customer experience – turning every touchpoint into an opportunity for deeper engagement.
Start building your data-driven omnichannel strategy by investing in the right tools, partnerships, and organizational alignment. Reach out to OSF Digital for expert guidance on omnichannel, data, and AI solutions that drive growth, boost customer loyalty, and ensure your brand stays ahead in the competitive beauty retail landscape.
