Best practices for integrating CDP into your marketing stack

Customer data is information. How you use that information, or whether you use it at all, can be a serious game changer for your business.

Research has shown that customer data platform (CDP) adoption can increase customer engagement by an average of 20%. This is why CDP integrations with your marketing stack are becoming ever more crucial for businesses across all industries. Here are some best practices for a smooth merger.

Key considerations for CDP integration

Before integrating your CDP with existing marketing tools, there are key elements to take into account during the data integration pre-planning phase.

Assessing your marketing stack

Is your marketing stack designed to handle data from varied sources? How efficient is it to plug social media, email, and Google Ads data into the marketing tools? Ideally, there should be an automated process.

Identifying data sources and collection methods

Determine where you’ll need to collect data. Some common sources include:

• Social media
• Email lists
• Customer profiles from your website
• Surveys and questionnaires

Next, determine how you’ll collect the data. This may include gathering data using an Excel sheet and then integrating the data sets into a master database system. More efficient methods, though, include using cloud data warehouses, available in most modern CDPs.

Defining your CDP integration goals

What do you hope to achieve with the integration initiatives? Increasing revenue, customer, engagement, and lifetime value are common goals. However, goals should go beyond profit-driven benchmarks. Other initiatives include:

• Improving customer data privacy
• Enforcing compliance measures
• Eliminating data silos
• Improving data accuracy by eliminating poor data quality, duplicates, etc
• Improving digital information organization with data archiving procedures

Evaluating CDP solutions

Analyze the current CDPs on the market. If you already have a system in place, assess whether it’s adequate for your established integration goals. Cross-reference your goal checklist with the CDP’s features to determine whether a particular platform is a good fit.

Best practices for CDP integration

Companies across industries implement these methods for their CDP integration rollout.

1. Creating a comprehensive data strategy

You need a detailed data strategy broken into incremental and actionable steps. There should be a separate strategy for each component, such as data security, data retention, data accuracy, etc. 

2. Defining data governance and data quality standards

Your internal data governance plan should heavily model existing industry data compliance standards at the national and global levels. If you’re in the medical sector, for example, then HIPAA should be the main blueprint.

3. Mapping data flows and identifying data gaps

Most CDPs have a built-in process for mapping and cross-referencing data from disparate sources. Use your data platform’s data mapping features and capabilities to identify shortfalls in your data. This may be data that are inaccurate, of low quality, or irreverent to the campaign.

4. Establishing data mapping and transformation rules

Create step-by-step protocols when converting data from one format to another, or when switching metrics or analytic formats. Data transformation rules may differ between campaigns. 

5. Ensuring data security and encryption

When you move and integrate data, the information may be vulnerable if your marketing stack contains exposed attack vectors. Collaborate with your internal or third-party cybersecurity team to determine encryption best practices. 

6. Building a unified customer profile

Customer profiles are a rich source of behavioral and demographic information. When integrating data, it may be worth reevaluating customer profile formats. For example, you may add additional fields, such as income range, gender, and education, while omitting fields deemed less relevant to upcoming campaigns.

Challenges and solutions for CDP integration

Due to the complex nature of CDP integration, it’s not unusual to come across challenges. Here are common hurdles and workaround solutions.

1. Overcoming data silos and fragmented systems

Fragmented data is problematic because it leads to reliability concerns, especially if team A is analyzing one data set and data B examines a separate set. It’s imperative that the CDP has an integration function for merging disparate data sources.

2. Managing complex data mappings and transformations

Does your CDP have a built-in function in place for managing sophisticated data and mappings and transformations? This is especially vital if your data undergoes frequent data transformations for analytic purposes across different campaigns.

3. Addressing data privacy and compliance concerns

No matter how well you follow compliance protocols, privacy concerns may arise. Preliminary data audits may also reveal gaps or misalignments between internal and national/federal-level standards. Develop a comprehensive plan in the event of privacy concerns brought forward by clients, shareholders, or regulating bodies.

4. Dealing with data volume and velocity

Data warehouses have a finite space. Too much data also increases the risk of inaccuracies and outliers. Determine the precise data you need. Have a disposal plan in place for less pertinent and third-party data. Perhaps they can be stored in temporary or “spam” repositories.

5. Aligning CDP integration with business goals

Define short-term and long-term company goals. What’s the timeframe for achieving these benchmarks and how does CDP integration assist in their attainment? Have a written plan mapped out with assessments of the how, what, where, when, and why of data use in relation to your goals.

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Most high-end marketing stacks are still reliant on the accuracy of the data inputted into the system. With Lytics’ CDP, sync your data and acquire new informative insights by unifying cross-channel campaign orchestration, dynamic segmentation, and real-time personalization into a singular point of operation.