Best Data analyst report templates for marketing teams and agencies (2024)

Automate marketing reporting with dozens of 100% customizable, white-label Data analyst report templates. Used and made by +10,000 marketers in over 60 countries.

Brand awareness Report template for Marketing teams and agencies

Awareness report template consolidates key metrics like CTR, CPA, and conversion rate from Social Media, Instagram Insights, and LinkedIn Pages. Analyze demographics, psychographics, and behavior over time. Perfect for marketing teams to track performance and strategy, providing actionable insights into audience engagement and organic search ranking.

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Google Ads PMax Report template for Marketing teams and agencies

Track key metrics with this Google Ads PMax report template. Measure conversion value, CTR, and impressions. Analyze by campaign type, audience segment, and time period. Consolidate data from Google Ads and Paid Media for actionable insights. Ideal for marketing teams focused on optimizing PPC performance and achieving strategic goals.

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PPC Report template for Marketing teams and agencies

Optimize your PPC strategy with this report template. Track metrics like conversion rate, ROAS, and CTR across Facebook Ads, TikTok Ads, and Google Ads. Analyze by audience, channel, and time. Ideal for marketing teams to measure campaign performance and achieve objectives efficiently.

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SEO Report template for Marketing teams and agencies

This SEO report template helps track key metrics like conversion rate, ROI, and CTR. Analyze organic search traffic and keyword rankings. Segment by audience, channel, or time. Integrate data from Google Search Console and content marketing. Ideal for marketing teams to measure performance and achieve specific goals.

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Twitter Ads Report template for Marketing teams and agencies

Analyze key metrics like CTR, conversion rate, and social actions with this Twitter Ads report template. Track performance by campaign objective, ad format, and audience targeting. Segment data by time, location, gender, and age. Perfect for PPC specialists to consolidate Twitter Ads and Paid Media strategies for actionable insights.

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Community manager Report template for Marketing teams and agencies

Community manager Social Media report template tracks key metrics like conversion rate, cost per conversion, and engagement. Analyze dimensions such as campaign duration, budget, and audience demographics. Monitor likes, shares, and comments across Social Media platforms. Ideal for community managers to consolidate data and refine social media strategy.

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Google Analytics 4 Report template for Marketing teams and agencies

Optimize your e-commerce strategy with this Google Analytics 4 report template. Track conversion metrics, session duration, and bounce rate. Analyze impressions, CTR, and average position. Segment by campaign, age, gender, and device. View data by hour, day, or year. Perfect for marketing teams to enhance website performance and achieve objectives.

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Video marketing Report template for Marketing teams and agencies

Optimize your social media and YouTube strategies with this Video marketing report template. Track CTR, conversion rate, ROI, likes, shares, and views. Analyze demographics, psychographics, and geographic data. Gain actionable insights to enhance performance and meet marketing goals. Perfect for marketing teams seeking to unify key metrics and drive success.

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Website Report template for Marketing teams and agencies

Analyze key metrics with this Website report template. Track conversion rates, average order value, and customer lifetime value. Measure audience demographics, interests, and behavior using Google Analytics 4. Segment data by time periods. Perfect for marketing teams to consolidate insights and refine strategies.

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What is a data analyst report?

A data analyst report is a document that consolidates data from multiple sources (e.g., SQL databases, Excel, Google Analytics) to track and display key performance indicators (KPIs) (e.g., data accuracy, processing time, error rates), enabling analysts to monitor data quality and performance and create presentations for stakeholders and executives. 

Data analyst reports are typically created using flexible tools like Google Looker Studio, Power BI, Google Sheets, or platform-specific solutions to enable high customization and integration of multiple data sources.

What to include in a data analyst report?

An actionable data analyst report balances context and specificity based on the audience (executives, managers, and analysts) and their use cases.

Executive data analyst reports

Executive reports for CIOs, CTOs, and stakeholders show data's impact on business decisions. Reviewed weekly, monthly, or quarterly, they include:

  • Data quality analysis: by source, using validation checks and error tracking.
  • Data processing efficiency: processing time, resource utilization, and throughput.
  • Trend analysis: patterns and anomalies in data over time.
  • Add text for additional context to translate metrics for non-technical audiences. Present in slide decks and simplified Looker Studio reports.

Data manager reports

Manager reports have cross-department views with drill-downs to see performance by team, project, data source, and process stage. They help align teams, define strategies, and include:

  • Cross-department reporting: overall data quality and processing efficiency across departments.
  • Goal tracking: compare current performance vs objectives.
  • Audits for prioritization and spotting issues 
  • Data source analysis for integration and optimization.
  • Data cleansing and transformation processes

Operational Data Analyst Reports

Operational reports for analysts and data engineers have granular, customizable KPIs to solve technical issues. Monitored hourly, daily, or weekly, they cover:

  • Data ingestion: data flow, latency, and error rates.
  • Data transformation: processing time, accuracy, and efficiency.
  • Data storage: capacity, usage, and retrieval times.
  • Data visualization: report performance, user engagement, and feedback.

Operational data analyst reports are highly customized, built in flexible tools like Google Sheets or Looker Studio to enable data cleaning, blending, annotations, and integrating multiple sources.



How to build a data analyst report?

To build a data analyst report, connect your data sources, choose a template on Looker Studio or Sheets, build your queries by selecting metrics and dimensions, choose charts to visualize your data, customize the report, design and share via link, PDF or email. 

Here’s the breakdown: 

Connect data sources

Define and connect the data sources to bring to your report. Common sources are SQL databases, Excel files, Google Analytics for web data, CRM systems for customer data, and cloud storage for large datasets.

To connect your data sources, go to portermetrics.com, choose the data sources to bring to your report. 

You can follow these tutorials on connecting your data:

Choose a template

Choose from dozens of data analyst report templates in Google Sheets or Looker Studio, designed for use cases like data quality monitoring, processing efficiency, and trend analysis. 

Learn to copy Looker Studio templates

While templates are the starting point. Make them specific for your business or agency. Map your specific metrics, especially custom data transformations, CRM contact data, and all the fields and metrics that you define as "key indicators" and "performance metrics".

Depending on your reporting tool—Google Sheets or Google Looker Studio, pick any of the dozens of templates created by our team and customers to solve your data analysis use cases, such as data quality monitoring, processing efficiency, and trend analysis. 

Select metrics, dimensions, and charts

Once your report template is downloaded, you may 1)modify it or 2) create a blank page to build it from scratch. Whatever the case, setting up a query always follows these steps: 

  1. Select the data source and the account connected to it
  2. Choose metrics (e.g. Data accuracy, processing time, error rates, etc.). 
  3. Choose breakdowns to segment your data (e.g. by date, data source, process stage, etc.)

You can follow these tutorials on adding data to your reports

Design

To make your data analyst reports truly white-label you can add logos, colors, fonts, and styling to mirror your brand. 

Follow these tutorials to design your data analyst reports:

Share

Share your data analyst reports via links, PDF, schedule emails, and control permissions.

KPIs to include in a data analyst report?

Data analyst reports should include a mix of data quality, processing efficiency, trend analysis, and resource utilization metrics and KPIs to fully understand the performance of data processes towards business goals. They include:

Data quality KPIs measure the accuracy and reliability of data: 

  • Accuracy metrics: error rates, validation checks, data consistency
  • Completeness metrics: missing values, data coverage, data freshness
  • Timeliness metrics: data latency, processing time, update frequency

Efficiency KPIs compare your data processing outputs to the cost, including:

  • Processing time: average processing time per dataset
  • Resource utilization: CPU, memory, and storage usage
  • Cost: operational expenses, resource allocation 

Effectiveness KPIs compare the input with the output from one data stage to another

  • Data transformation: transformation success rate
  • Data integration: integration success rate
  • Data visualization: user engagement, feedback

Resource and cost KPIs show the bottom-line impact of your data processes:

  • Resource usage: server uptime, resource allocation
  • Cost: operational expenses, resource allocation
  • Efficiency: ROI, cost savings
  • Effectiveness: data-driven decision impact

To analyze these data KPIs, segment them by:

  • Data source: internal, external, structured vs unstructured
  • Time: Hourly, daily, weekly, monthly
  • Process stage: ingestion, transformation, storage
  • Business: department, project, region
  • Data type: numeric, categorical, text, image
  • Visualization: charts, graphs, tables