Marketing analytics, if used correctly, are a tremendous decision-making tool. They can help marketing executives increase their understanding of critical business functions like customer interactions and market campaign performance. Develop a repeatable marketing analytics function to improve decision-making and project selection. Use Demand Metric's downloadable Market Research Report to organize your next Analytics project.

What are Marketing Analytics Programs?

Marketing analytics programs are comprised of processes, tools, and techniques for analyzing & converting business data into usable, decision-making information.
See this map on the different types of business analytics.

• Predictive Modeling - deploying statistical modeling techniques to predict customer behavior, supporting business decision-making & forecasting.
• Customer Segmentation - classification or other techniques to categorize customers into groups, enabling campaign customization.
• Strategic Data Analysis - analysis of key data trends to conclusions with significant business meaning and strategic impact.

Action Plan:

1. Understand What Information is Required - determine which decisions you need to support, and identify which metrics can provide insight. Use our Market Research Report template to document your research problem. Next, ascertain if the information you require is accessible. Data often resides in disparate silos of an organization so check with Sales & Customer Service to determine if you can take existing data and convert it to insightful information. Discern which format the raw data will arrive in, and discover if you will require tools to slice and dice it. Will the data be static or dynamic?
2. Determine Frequency of Reporting - as there are hard costs associated with marketing analytics, select an optimal frequency for delivering decision-making information. Steering committees provide a great forum for reporting; consider delivering analytical insights at these regularly scheduled meetings.
3. Standardize Analytics Methodology & Process - document a consistent process for using analytics so business partners understand their role. Consider industry-standard data-mining application methods such as CRISP, but start with the business problems to maximize value for your efforts.
4. Ensure Clean & Accurate Data - data quality and selection is more critical than the analytical technique for establishing superior results. Audit the data your technical resources are using, to ensure your results are not skewed.
5. Apply Techniques & Evaluate Results - rather than evaluating everything, select a few key areas to apply an analytical approach such as the tried and true logistic regression predictive modeling technique. Produce reliable results before expanding scope.
6. Deployment of Analytics Program - establish a communications plan and integrate your analytical techniques into your business processes. Don't discuss how the analytic technique itself works; instead, quantify the financial/customer impact of changes made based on decisions supported by analytics to grab stakeholder attention.
7. Stay Proactive - the best companies continuously reshape the processes for requesting analytical support and optimizing how this work can help their business. Remind key stakeholders of your capabilities and keep abreast of their unique challenges.

Bottom Line:

Many analytics project fail because their focus is not on the results they are supposed to deliver. Develop a standardized marketing analytics process to increase visibility and support business decision-making.