Before investing in a managed data warehouse, there are several critical questions you need to ask your team to ensure you’re getting the right data strategy solution for your business needs.
Here are seven questions about data architecture every CMO should ask:
1. What are our data sources, and are they reliable?
Your team should be able to identify all the data sources your organization uses, which could include:
- Customer Relationship Management (CRM) Systems
- Social Media
- Web Analytics
- Market Research
- Advertising Channels
Additionally, your team should be able to provide information that gives insight into the reliability of the tools and processes. They should easily be able to share the following:
- Data sources used and who is responsible for collecting and maintaining them.
- Consistency of data with other data sources. There shouldn’t be any outliers.
- The data collection methodology is sound in volume and process.
- The timeliness of data collected.
- Any potential biases that may exist in the data collection process.
2. What data do we need to collect to achieve our marketing objectives?
Effective pathways to achieving marketing objectives include identifying the data points that are critical for making informed marketing decisions, such as customer:
Your team must also know what other data points are key to achieving marketing success. They could include:
- Web Performance
- Advertising Performance
- Product Performance
It’s important to note that you need the right data, not necessarily all data available to you and your team.
3. How do we store and manage our data?
Once you’ve identified the needed data, you must know how your organization stores and manages it. Your team should have a clear understanding of your current data management strategy and be able to compare it to data warehouses, data lakes, or cloud-based solutions.
Additionally, you need to know how your team manages data from multiple sources and the time involved in aggregating. Is your data analyst spending inordinate amounts of time cleaning and transforming data, so it’s accurate, consistent, and usable? If so, a fully managed data warehouse solution may be worth considering.
4. How do we ensure data quality and accuracy?
Data quality and accuracy are critical for making informed marketing decisions. Your team should have a business process for ensuring data quality and accuracy, such as:
- Implementing data validation rules to ensure that data is entered correctly and consistently. This can include checks for data format, range, and type.
- Performing regular data quality checks to ensure data meets defined standards and criteria. This can include both automated and manual reviews.
- Identifying and addressing data discrepancies to remove or correct any errors or inconsistencies. This can include standardizing data formats, correcting misspellings, and eliminating duplicate records.
- Implementing a data governance framework to ensure data is managed consistently across the organization. This can include policies and procedures for data access, data sharing, and data security.
5. How do we analyze our data to gain marketing insights?
Data analysis is essential for uncovering insights into consumer behavior and optimizing your marketing campaigns. Your team should be using the data and analytics tools and techniques that are best suited to your organization’s needs and be able to extract actionable insights from them.
Your team should be:
- Segmenting your data into groups based on key characteristics, such as demographics, behavior, or purchase history.
- Identifying patterns and trends in data and tailoring your organization’s marketing strategies accordingly.
- Using statistical and machine learning techniques to identify factors that are driving marketing performance. This could include identifying marketing channels which drive the most traffic or which products sell the most.
- Using hypothesis testing to determine if hypotheses are statistically significant. This can help identify which factors are driving marketing performance and prioritize your marketing initiatives.
- Using predictive modeling techniques to forecast future outcomes, such as sales or customer retention rates. This can help you make data-driven decisions about where to allocate resources and how to optimize your marketing campaigns.
By analyzing marketing data, you can gain valuable insights that can help you optimize your marketing campaigns, improve customer engagement, and drive business growth.
6. How do we ensure data security and compliance?
Data security and compliance are critical considerations when collecting, storing, and analyzing consumer data. Your team should have a plan for ensuring data security and compliance with industry regulations such as General Data Protection Regulation (GDPR) or California Consumer Privacy Act (CCPA). This includes implementing access controls, encryption, and regular security audits.
Your team should be:
- Identifying potential risks to your data security and compliance by conducting routine risk assessments. This will help you identify any vulnerabilities in your systems and processes and take steps to mitigate them.
- Fully aware of your data security and compliance policy, including guidelines on handling data, access controls, encryption, and incident response.
- Using security measures such as firewalls, antivirus software, and data encryption to protect your data from unauthorized access and cyber-attacks.
- Trained in data security and compliance policies and procedures. This includes training on data handling best practices, password management, and incident response.
- Aware of relevant regulations such as the GDPR and CCPA and ensure that your policies and procedures comply.
Ensuring your organization’s data is secure will help you build trust with your customers and protect your organization from potential data breaches and legal penalties.
7. How do we measure the ROI of our data strategy?
Measuring the ROI Of your data strategy can be challenging, but there are some key steps to ensure you’re investing your resources effectively. These include:
- Defining your objectives so you can identify the most important metrics to measure and track.
- Identifying the costs associated with implementing and maintaining your data strategy. This includes expenses related to technology, personnel, and training.
- Determining the benefits of your data strategy, such as improved customer insights, increased efficiency, or higher revenue.
- Using the ROI formula: Gain from Investment – Cost of Investment / Cost of Investment.
Helpful metrics to measure ROI of a data strategy include:
- Customer Lifetime Value
This measures the total value a customer brings to your organization over their lifetime. By improving your understanding of your customers through data analysis, you can increase their CLV and improve your ROI.
- Conversion Rate
This measures the percentage of visitors to your website who take a desired action, such as making a purchase or filling out a form. By analyzing data to identify the factors that drive conversions, you can improve your ROI.
- Cost Per Acquisition (CPA)
This measures the cost of acquiring new customers. By analyzing data to identify the most effective marketing channels and targeting strategies, you can reduce your CPA and improve your ROI.
Explore New Path Digital’s Managed Data Solutions
Our team is experienced in managing and analyzing data to drive meaningful insights and growth. Our managed data warehousing solutions help you gain valuable insights to inform and improve your marketing efforts.
Schedule a free consultation to learn how.