May 20, 2020

Running Your Own Marketing Analytics Workbench

Vikalp Jain
Joseph Bartman

Vikalp Jain and Joseph Bartman

Running Your Own Marketing Analytics Workbench

Marketing analytics is the science of collecting, measuring, and analyzing raw data in order to draw meaningful insights. These insights are critical to organizations because they enable continuous optimizations, resulting in higher productivity and ultimately higher marketing return on investment (MROI). Many organizations leverage outside agencies to run their digital marketing campaigns, and these agencies in turn leverage platforms such as Google, Salesforce, and social media that produce a wealth of customer data as users engage with campaigns. The question then becomes: Who owns this data? Is it your organization, your visitors, or the agencies that run your campaigns?

Through the course of this article, we’ll discuss the primary benefits of owning your own customer data and running your own marketing analytics.

Why Should You Run Your Own Analytics?

Why should your organization run your own marketing analytics? In short, it gives you the freedom to utilize your data to drive business value without the restrictions that come with externally owned data. We’ll walk through the following six capabilities you can unlock by owning your own data and analytics functions:

  1. Flexibility and customization

  2. Actionable insights

  3. Campaign-level analysis

  4. Data-driven forecasting

  5. Precision targeting

  6. Ongoing testing and optimization

1. Flexibility and Customization: Combine Dimensions and Metrics in Valuable Ways

Many providers have limits on the number of dimensions or metrics that are allowed for a given query. For example, Google Analytics API limits you to seven dimensions and 10 metrics in any given query, and the interface itself limits even further to only five dimensions. For example, if you want to analyze how long it takes after the first impression for a user to take a certain high value action or when impressions occur most often (e.g., before or after a click), you will need to perform this analysis yourself.

Alternatively, owning your own data allows you the flexibility to customize analytics to your business objectives and measurement framework. Implementing an analytics workbench enables the collection of data from multiple sources and subsequently allows for meaningful analysis to inform decision-making and optimizations. External vendors may not be tracking the same objectives and measures you find important.

2. Actionable Insights: Better Understand Customer Conversions

For companies with data owned by external providers, it can be difficult to draw customer insights from the data due to the disconnect between the various entities that own the marketing campaigns and the associated data. For instance, one agency might handle your digital media performance, while another might handle the sales funnel.

On the other hand, handling data within your organization provides a greater understanding of the customer path to conversion since all the data is in a unified location. For example, marketers would be able to determine how many people clicked on an email promotion, navigated to the product details page, and completed the purchase. These types of insights allow organizations to more fully understand impactful moments throughout a customer’s journey and drive hyper-personalization that is backed by data.

3. Campaign-Level Analysis: Combine Data With Marketing Campaigns

Data ownership gives companies the ability to tie marketing campaigns to their analytics data in order to understand and analyze outcomes on an individual campaign. Using this capability, companies can drill down to a specific marketing campaign to mine for insights and trends, analyzing various aspects such as geography, device, customer segment, time of day, or other key data dimensions. This level of analysis is crucial to evaluating campaigns against defined objectives and KPIs, as well as informing micro-optimizations and future campaign planning.

4. Data-Driven Forecasting: Create Predictive Models

Owning analytics data allows businesses to begin to utilize more advanced analysis tools such as predictive models. Predictive modeling uses data, algorithms, and machine learning to predict potential outcomes. In marketing, predictive modeling allows marketers to forecast future revenue based on propensity analysis of customer behavior.

These insights can be used to optimize the customer experience to lead users to high value actions that result in higher MROI and drive desired business outcomes. However, predictions and models are only as good as the quality of data informing them. Owning your own data allows you to create a common data model to ensure your data is accurate and clean, resulting in highly effective predictive models.

5. Precision Targeting: Build Your Own Audiences and Augment With CRM Data

A comprehensive view of all data allows businesses to analyze data for common characteristics and behaviors. The outputs of those analyses can then be used to segment users and create audiences. The analytics data and audience segments can be utilized further by combining with CRM data to create ads that are personalized and relevant to the user.

6. Ongoing Optimizations: Enable Multivariate Testing

Using the audience profiles created from the collected user data, businesses can integrate technology that enables multivariate testing for content optimization. Multivariate testing eliminates the need to run several sequential A/B tests, as tests can be run concurrently with a greater number of variations. Multivariate testing allows organizations to measure the interaction between multiple independent elements of a user experience to optimize how assets of a site work together and to continuously optimize content to ensure the right message is delivered to the right person at the right time.

Taking Charge of Your Marketing Analytics

While owning your own analytics provides flexibility, personalization, and advanced capabilities, it also may mean adding additional analytics resources to your internal team, including technical resources, data scientists, business analysts, and subject matter experts that understand the data sources you are trying to analyze.

We understand the world of analytics can be tricky to navigate and setting up an analytics workbench can be a daunting task. Unfortunately, there is no one-size-fits-all approach, and any data solution should be customized to the nuances of your business. At Credera, we take a proven approach to understanding and unlocking organizations’ data to truly work for them and lead to better business outcomes and user experiences. To learn more, reach out to us at

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