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Customer data activation drives personalized experiences and business growth by converting raw data into actionable insights for marketing, sales, and customer success teams.
Activation as the final step of the modern customer data stack, enabling data-driven decisions across various business functions.
Choose a customer data activation platform wisely, considering factors like integration, ease of use, and the ability to create personalized campaigns.
Customer data activation is the process of turning customer data from multiple sources into actionable insights and data that customer-facing teams can use to personalize customer experiences and target campaigns. When teams activate customer data, they’re leveraging customer details stored in a central data source, such as an enterprise data warehouse.
Activating customer data leads to more relevant and customized customer journeys by helping marketing, sales, and customer success (CS) teams:
Personalize campaigns and messaging
Improve customer experiences
Drive positive business outcomes
Convert prospects into customers more quickly and at higher rates
Organizations that employ a customer data activation platform don’t have to wait for data teams to pull customer lists. Instead, teams can use the warehouse data in real-time for personalized campaigns and messaging.
Customer data activation helps businesses make decisions that lead to revenue. That’s because those decisions are supported by accurate and useful customer information, instead of arbitrary opinions and generalizations.
Customer data activation benefits businesses by:
Giving teams insights at a glance so they can quickly make business decisions that align with customer needs.
Improving efficiency by minimizing manual data collection and automating processes, so data and marketing teams can focus on activities that drive value.
Reducing costs, including (but not limited to): customer acquisition costs, marketing operations costs, data duplication costs, and costs of products that are not creating value for customers.
Driving transparency and removing data silos through a unified view of the customer.
Supporting more relevant and personalized experiences across every marketing channel and touchpoint.
For a company to effectively activate data, it needs a strong customer data management strategy. Customer data management allows organizations to create a single source of truth for data and keep that data safe, secure, and accurate. Companies must develop a customer data management strategy before data activation takes place to ensure business insights are correct and can drive positive results.
Every customer-facing function benefits from customer data activation because it allows them to understand who they’re helping. They can answer the right questions, solve relevant problems for their target audience, and provide personalized customer experiences.
When all teams have a single source of truth — rather than relying on fragmented data sources — they can all work to achieve the same goals for their audience. Each team is more effective, and the business grows as a result.
Customer data guides informed marketing decisions through information collected straight from the source — also known as first-party data activation. Marketing activation relies on data like how customers learn about a brand, the content they consume along their journey, and when and how they convert.Â
For instance, customer data like email opens and clickthrough rates, engagement on a Facebook ad, and responses to SMS text marketing all give marketers valuable information about what messaging resonates with their customers and which offers are most appealing. From there, they can A/B test copy and messaging across each of these channels to optimize customer journeys, engagement, and conversions.
Data activation also gives marketers the tools to create more personalized marketing campaigns that resonate with an audience. They can guide audiences into appropriate journeys — resulting in improved conversion rates — and craft more helpful and relevant content, which drives customer loyalty.
Data activation helps busy sales teams use their time efficiently and drive customer acquisition. Rather than sending non-targeted or irrelevant outreaches, sales reps can use data to score leads and determine if and when someone is ready and interested in a conversation. Customer data activation offers real-time insights that help sales teams understand a lead’s needs and send helpful, valuable resources over time to nurture the relationship.
Reverse extract, load, and transform (ETL) tools, which sync customer data from warehouses like Snowflake to essential tools like Salesforce or Hubspot, send customer profiles and audience information straight to the tools that sales teams use daily. These insights guide outreach and prepare reps for discovery calls with highly relevant information that encourages prospects to buy.
Customer success (CS) teams rely on customer data activation to better support customers with questions or problems about the user experience.
CS teams play a critical role in customer retention and churn reduction. When support tickets come in, customer data activation lets CS reps see a customer’s health score or support history at a glance. That data helps CS reps prioritize the tickets of at-risk customers first to limit the fallout of any bugs or issues in the product. The faster they can solve problems (especially without customers having to repeat themselves or explain their use of the product), the more likely customers will continue to use the product.
Even before tickets come in, CS can use customer data activation to understand churn risk signals and create alerts when someone has a problem or has stopped logging into the product. Then, they can reach out personally to answer questions or help them get more value from the product.
The modern customer data stack is the full suite of technology companies use to take raw data from source to insights and action. It includes five key components, with data activation as the fifth and final step:
Data Layer. This is where data is stored and includes the data warehouse or data lake. This layer centralizes the data storage to be queried and turned into insights.
Ingestion Layer. The ingestion layer collects data from multiple sources, transforms it, and brings it into the warehouse.
Customer Data Model. Within the data warehouse, the customer data model organizes customer profiles into a single view that teams can access easily. It recognizes the same customer in different data sources and quickly simplifies customer views to drive value as soon as possible.
Visualization and Intelligence Layer. Once customer data is a centralized platform (the warehouse), data visualization and predictive analytics unlock customer insights. These help marketers understand the effectiveness of their campaigns so they can strengthen future efforts and drive growth.
Activation Layer. At the activation step, companies leverage customer data and insights to define and export the customer segments that marketing, sales, CS, and product teams use for targeting. Then, those teams can create more personalized messaging, define more sophisticated customer journeys, and reach more customers across a wider range of marketing channels.Â
Collaboration is crucial for starting data activation. The implementation process for data activation should include both the teams that will use the data for customer interactions (like marketing and CS) and the teams that will implement the strategy (like IT and data teams). Relevant teams include:
Marketing teams
Sales teams
Customer success
The product team
IT and data teams
Executives and decision-makers who approve major expenses
Customer-facing teams need to collaborate closely with data teams when determining business requirements, selecting platforms, and creating a feedback loop. Collaboration between these teams ensures that the data warehouse and data activation tools meet the organization’s needs for analysis and integration.Â
When these teams work closely early on, they ensure that:
The strategy matches the marketing team’s goals
They build activation tools into the martech stack from the start
They have a shared foundation for any later changes by opening the lines of communication
Customer data activation involves three key steps:
Data collection. This stage brings raw data from various sources into the data warehouse. Sources include customer relationship management (CRM) platforms (such as Salesforce), marketing channels like social media and websites, media impressions, transactional data, SQL databases (such as MySQL), and others. Marketing should be heavily involved in ensuring every source is accounted for so that the data teams can connect each source to the data warehouse.
Data analysis. Once brought into the warehouse, the data is ready for analysis and modeling. This process generates business insights that teams will use to drive decisions. Analysis examples include look-alike modeling, sentiment analysis, and audience profile analysis. Customer-facing teams need to ask data teams for the insights they need so that proper analysis can occur.
Data integration. After the data analysis, the insights are integrated with each team's software tools. This step might reveal the pain points and priorities for a specific audience segment, along with the data needed to target campaigns for those customers. That way, marketing and sales teams can personalize messaging, timing, and calls to action.. This is where the true value of data activation takes place, giving marketing, sales, and CS the tools to make more informed decisions that drive revenue.
Start with an exhaustive list of data sources. In addition to marketing, lean on teams like product and customer success for additional input on data sources, like channels that gather information about customer health.
Customer data activation is a major undertaking, but companies don’t have to start with every use case for data right from the jump. Trying to solve every problem at once will result in spreading resources too thin and ultimately, nothing will get done.
 Instead, start with one use case, like improving lead scoring for marketing and sales teams. Once you’ve used data to strengthen one area and can build processes to take action on that data, you can move on to other use cases.
Identity resolution uses data sets from different sources and reconciles your data to create a single view of individual customers. It is an essential piece of customer data activation because it ensures teams can align their efforts, rather than reduplicating them. You should handle identity resolution in the data warehouse — this is the most efficient way to account for all of your data for each customer.
Segments allow you to note patterns of customer behavior and attitude so you can efficiently market, sell, and serve groups of people who think similarly. Use customer data to create audience segments, including their job title, company type and size, and goals and pain points. Create well-defined groups that tend to move through a customer journey in a particular way so you can send them the right messaging and resources at the right time and convert them more effectively. The better you know a specific audience, the more effective your cross-channel marketing efforts will be.
Use audience segments and individuals’ customer profiles to personalize campaigns across channels like email and advertisements. Individuals’ behavior can signal when they’re ready for certain messaging, so send highly relevant campaigns based on these milestones consistently across every channel.
Collaboration with data teams isn’t one-and-done. Stay in contact with data teams for updates to the data analysis and activation. That relationship will remain important throughout the data activation strategy when you need to add data sources, resolve problems, or activate data in new ways.
The right customer data activation platform offers several benefits:
It makes data accessible to different departments for self-serve access
It creates a single source of truth and eliminates data silos
It enriches data by turning it into actionable insights and enabling marketers to personalize customer journeys for higher and quicker conversion rates
It guides more effective decision-making for better business outcomes
When choosing a customer data activation platform, look for a platform that will integrate with your existing systems, meet your organization’s needs for ease of use and volume of data, and allow you to run A/B tests of marketing campaigns.
Many organizations use a customer data platform (CDPs) for their data activation efforts. A CDP handles each step of customer data activation, ingesting the data, employing identity resolution, and building audiences. There are two key types of CDP: traditional and composable. A traditional CDP stores data outside of your existing infrastructure. A composable CDP is more flexible — it’s an activation layer that allows you to create audience segments, build and optimize customer journeys, and activate data to your marketing tools, all from your data warehouse.
Traditional CDPs require organizations to conform their data to the constraints of another platform. Because they exist separately from the data warehouse, traditional CDPs create another data silo rather than centralizing and creating a single source of truth. Composable CDPs don’t have this challenge — they work with your existing data infrastructure to streamline data integration, analysis, and segmentation for powerful activation, more personalized marketing campaigns, and optimized customer journeys.Â
Here are a few examples of platforms for data activation:
Segment
GrowthLoop
Hightouch Customer Studio
Treasure Data
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