Data Activation is changing the way online business owners see digital marketing. It seeks to unlock value in data through the development of actionable insights.
Data-driven marketing has been around for years, but the use of Customer Data Platforms (CDPs) is new to the space. The biggest digital markets in the world are taking advantage of CDPs to drive their marketing efforts, especially during the COVID-19 pandemic. Artificial Intelligence is the most essential piece of Data-Activation, as it gives meaning and finds patterns from the vast amount of data. To craft a winning customer experience at scale you need to not only collect data but also know how to activate it.
Here are the most prominent emerging data activation trends for 2023:
1. Key Segments
With the right data activation tools, digital marketers can convey messages to any audience. But one of the downsides of digital marketing is that it’s harder to assess buyer behavior compared with traditional sales platforms. By taking advantage of customer data platforms, online businesses can build personas of ideal customers so they can segment and understand their audience better. This will help enhance the user experience across all touchpoints.
Mapping the Audience Journey: A data-first approach in digital marketing helps define the stages of a customer’s journey. Businesses can plot the path of a customer from their initial purchase through ongoing purchases to the stage where they advocate your brand to others.
Real-Time Targeting: On-site and in-app messaging are the two major channels through which customers are targeted by online businesses. Location-based data helps identify potential customers within physical stores, and offers are sent directly to their phones to encourage them to make purchases. For high-value customers, businesses can offer discounts or make recommendations directly.
Merging Offline and Online Data: Digital marketing isn’t restricted to digital businesses. Marketers who want to take advantage of data can use both online and first-party offline data to boost campaigns. Customer data can be collected offline through physical stores, and that data can be used to create online engagements.
Customer audience profiles are pillars of modern marketing campaigns. By integrating offline and online data to support the creation of audience profiles, businesses can optimize campaigns for video, social and mobile platforms.
Modern customers expect consistency across all communication channels. Through data integration, marketers can create a truly omnichannel experience for all customers across all segments. A one-size-fits-all approach does not work in 2021, and even traditional media channels are realizing that. Modern customers lean toward customized experiences, and proper data integration can help you offer cohesive but personalized experiences.
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2. Audience Modeling
Customer data platforms (CDPs) are adopting new modeling techniques to better analyze customers. Audience modeling can enhance targeting and increase marketing focus. Online marketing agencies have been making use of audience modeling for years, but they’re now taking a data-oriented approach, where performance and modeling accuracy matters a lot more.
Lookalike Modeling: This takes all your existing customer segments into consideration and expands on them. Through demographic and behavioral data, lookalike modeling can help you find potential new customers who share the same characteristics as your existing customers and reach out to them.
The next best option is to eliminate unqualified prospects. Businesses always have ideal customer characteristics and traits in mind. If an audience member doesn’t fit your target demographic, you can remove them from your marketing campaign. Data can be used to identify disqualifying features and make your marketing campaigns more efficient and effective.
Predictive Modeling: Predictive modeling is usually associated with statistics, but it’s making its way into modern digital marketing. The technique involves finding customers or prospective customers based on their purchase behavior and demographics.
Despite the name, “predictive” modeling does not involve predicting the future. Instead, it takes advantage of data analysis techniques to target customers based on their known behavior and demographic data. From direct mails to social media advertisements, predictive modeling can use various types of data to target customers.
Algorithmic Modeling: Algorithmic modeling helps implement marketing automation for data scientists and digital marketers alike. It collects data from data management platforms, advertising data, and retail data to identify potential customers. Algorithmic modeling is not only algorithms, but it’s a mix of economic theory and machine learning, and it helps create the right marketing strategies. It can not only help with customer identification and marketing but also in developing pricing strategies based on customer data.
3. Media Optimization
One of the most critical techniques online businesses are adopting is media optimization. While social media marketing, mailing lists, and direct messaging are standard practices, oversaturating your audience with promotions can hurt your returns on investment for your marketing teams.
This is where media optimization techniques like audience suppression come in. For example, if you’re selling products or services that see long-term usage, you shouldn’t invest in ad campaigns for your existing customers. Instead, you can focus on value-added services for items they’ve already purchased.
Audience Suppression: Many advanced businesses take advantage of application programming Interfaces (APIs) to conduct real-time audience suppression. Modern tools can monitor data in real-time and notify businesses when they identify audience members who are unlikely to react to your marketing campaigns.
Frequency Capping: Custom data management platforms can help you customize your marketing campaigns. Specific ads will reach your audience only when they meet certain criteria. Instead of taking a one-size-fits-all approach for your audience, businesses are leveraging data to segment their audiences and avoid unnecessary retargeting.
Retargeting: Retargeting campaigns are designed to remind website visitors to check out products and services on a website after they leave pages without making a purchase. Taking advantage of customers’ web browsing data, relevant ads can be displayed to try to turn them into buyers.
4. Ecosystem & Architecture Integrations
Staying ahead of the competition in a developing digital economy isn’t easy. It is necessary to deploy new technology capabilities to give your data-driven digital marketing strategies an edge.
Ecosystem Integration: In addition to providing rich business process functionality, customer data platforms need to integrate applications, data sources, sales channels, and other important systems. Digital business platforms are adopting service-oriented architecture and other integration mechanisms that are designed to easily integrate with other systems.
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Businesses have recognized that there are barriers to communication between the marketing teams, the advertising and media teams, and data analysts and data scientists within the organization. They’re beginning to break down the barriers to communication and adopt a tighter and more coherent ecosystem. Teams are working together and trying to relate to a customer’s journey. Through proper collaborations within an organization, businesses can create fully informed relationships with their customers.
Architecture Integration: By centralizing the architecture of customer data platforms, businesses can integrate analytics, data management, marketing, and sales in one place. All stakeholders and teams are exposed to a centralized system that allows them to collect data and work toward better marketing communications. Centralized architecture also leads to more transparency within the business.
By focusing on data-driven marketing, businesses can connect with their customers better than ever before. The use of customer data platforms in marketing is trending now as well as next year, as more businesses are understanding the importance and have taken the initiative of integrating their marketing, sales, and data operations.
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