Five tips to build a successful analytics dashboard

Keep the bigger picture in mind as you build and use your analytics dashboards.
February 3, 2021

Between devices, websites, applications, online service providers, and platforms of all kinds, modern businesses rarely have a single data source to analyze in our continuously connected world. That’s why how information is presented is almost as important as the quality of the information itself, making the difference between leading with confidence or simply flying blind.

So what are the five main action points to achieving an effective and reliable analytics dashboard? Let’s take a look:

1. Seek out and eliminate build errors, delays and bias

Dashboards are designed to give managers a bird’s eye view of the most important aspects of their jobs, be it key operational processes, key performance indicators (KPIs), or industry-specific metrics. But their main flaw is that they are only as good as people can make them. Many dashboards suffer from data bias, false causality, conflation, errors in attribution, or simple misinterpretations of the facts.

According to Analytics Week, the three main mistakes people make when creating analytics dashboards are 1) static interfaces with no follow-up capabilities, 2) no drill-down functionality, and 3) no context behind the numbers, which is often the reason that intermediaries are asked to moderate and pull reports from analytics systems since they are too complex to be used by decision makers directly.  

Such was the case of ParkBee, an Amsterdam-based tech company specialized in renting out private parking spaces out to the public. Initially they had no way to collect real-time parking space data automatically, so managers thought they had to hire both a Data Engineer and a Business Analyst to comb through snapshots of the company database and generate custom reports by hand as needed. However that changed when the synergetic combination of Fivetran and Looker allowed ParkBee to cut to a core metric: tracking parking spaces in real-time. These plug-and-play data modules allowed for data transparency across the organization via central dashboards that neatly displayed the most relevant data to key decision makers.

2. Separate audience attributes from audience actions

While customer demographic data on your dashboard is good, activity-based CBIs (Customer Behavior Insights) make the gap between average and phenomenal analytics dashboards.  

Relevance and intent are the main drivers behind brand growth and sales, so understanding why customers do what they do is more important than who they are (don’t commit the fundamental attribution error). An August 2020 study conducted by Google and Ipsos discovered that “video advertising based on consumer intent has a greater impact than advertising based on demographics [alone]”. To illustrate, YouTube ads that segmented their audiences in alignment with intent drove more impact than demos or intent-based ads alone, with a 32% higher lift in ad recall and 100% higher lift in purchase intent due to these advanced dashboard-enabled CBIs.

You can combine Fivetran’s automated marketing analytics with a 360-degree customer view to capture customer journeys and optimize offerings and sales based on their behaviors and preferences. Through a single dashboard decision-makers can quickly analyze and act on the latest trends.

3. Conduct periodic quality checks and audits

Your data is only as good as the tools you use to collect it. Manual data entry on spreadsheets across several platforms is fraught with inconsistency, uncertain provenance, and human error. It’s important for an organization to be able to trust their data quality and detect errors in a timely fashion in order to fix them well before they can cause too much damage. For that reason, periodic quality checks are indispensable for analytics dashboard maintenance.

But it’s important to remember that quality audits shouldn’t only be internal. Fivetran regularly conducts comprehensive internal and third-party audits of its own applications, systems, and networks to ensure that quality standards are maintained and data protection requirements are always met as regulations evolve over time.

4. Comply with changing rules and regulations

The fourth characteristic of an effective analytics dashboard is full compliance with local and overseas governments’ rules on data transfers, information privacy, and storage. There are multiple ways in which Fivetran maintains its GDPR, HIPAA, and protected data disclosure compliance, but the main ways in which other companies can is by:

  • Storing client data on their own servers for a limited amount of time (24 hrs)
  • Comprehensive end-to-end data encryption
  • Adding overseas servers (to keep PI within specific geographic limits, such as for GDPR)
  • Keeping dashboards accessible while also blocking or hiding protected data for specific internal stakeholders

Check your local and industry-specific legislation for more ideas on how to make the data feeding your dashboards as safe and legally-compliant as possible.  

5. Share your data and create synergies with different players

Going through a middleman to access critical data is a well-known pain point for many business leaders and analysts alike. According to a recent Dimensional Research survey, 62% of data analysts had to wait for centralized dev teams to provide access to requested data several times a month while 34% “wasted time” attempting to find the data they needed themselves.

The key to resolving these operational bottlenecks is to bypass the traditional information pipeline altogether via technology-enabled data integration. In other words, by centralizing data in a single location (such as a data warehouse), analysts and stakeholders alike can independently access the information they need to work together in a more transparent and effective way. Fivetran has 150+ prebuilt data connectors to combine data from all of a business’s applications, databases, and software. An organization can automatically combine data sources to produce powerful metrics that enable data-driven decisions in real-time. People across the organization can use the information in ways that make the most sense for their own teams, share in common successes, and maintain accountability throughout the organization.

For an in-depth look at these analytics-powered dashboards and environments, visit the Fivetran website or request a demo today.

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Data insights
Data insights

Five tips to build a successful analytics dashboard

Five tips to build a successful analytics dashboard

February 3, 2021
February 3, 2021
Five tips to build a successful analytics dashboard
Keep the bigger picture in mind as you build and use your analytics dashboards.

Between devices, websites, applications, online service providers, and platforms of all kinds, modern businesses rarely have a single data source to analyze in our continuously connected world. That’s why how information is presented is almost as important as the quality of the information itself, making the difference between leading with confidence or simply flying blind.

So what are the five main action points to achieving an effective and reliable analytics dashboard? Let’s take a look:

1. Seek out and eliminate build errors, delays and bias

Dashboards are designed to give managers a bird’s eye view of the most important aspects of their jobs, be it key operational processes, key performance indicators (KPIs), or industry-specific metrics. But their main flaw is that they are only as good as people can make them. Many dashboards suffer from data bias, false causality, conflation, errors in attribution, or simple misinterpretations of the facts.

According to Analytics Week, the three main mistakes people make when creating analytics dashboards are 1) static interfaces with no follow-up capabilities, 2) no drill-down functionality, and 3) no context behind the numbers, which is often the reason that intermediaries are asked to moderate and pull reports from analytics systems since they are too complex to be used by decision makers directly.  

Such was the case of ParkBee, an Amsterdam-based tech company specialized in renting out private parking spaces out to the public. Initially they had no way to collect real-time parking space data automatically, so managers thought they had to hire both a Data Engineer and a Business Analyst to comb through snapshots of the company database and generate custom reports by hand as needed. However that changed when the synergetic combination of Fivetran and Looker allowed ParkBee to cut to a core metric: tracking parking spaces in real-time. These plug-and-play data modules allowed for data transparency across the organization via central dashboards that neatly displayed the most relevant data to key decision makers.

2. Separate audience attributes from audience actions

While customer demographic data on your dashboard is good, activity-based CBIs (Customer Behavior Insights) make the gap between average and phenomenal analytics dashboards.  

Relevance and intent are the main drivers behind brand growth and sales, so understanding why customers do what they do is more important than who they are (don’t commit the fundamental attribution error). An August 2020 study conducted by Google and Ipsos discovered that “video advertising based on consumer intent has a greater impact than advertising based on demographics [alone]”. To illustrate, YouTube ads that segmented their audiences in alignment with intent drove more impact than demos or intent-based ads alone, with a 32% higher lift in ad recall and 100% higher lift in purchase intent due to these advanced dashboard-enabled CBIs.

You can combine Fivetran’s automated marketing analytics with a 360-degree customer view to capture customer journeys and optimize offerings and sales based on their behaviors and preferences. Through a single dashboard decision-makers can quickly analyze and act on the latest trends.

3. Conduct periodic quality checks and audits

Your data is only as good as the tools you use to collect it. Manual data entry on spreadsheets across several platforms is fraught with inconsistency, uncertain provenance, and human error. It’s important for an organization to be able to trust their data quality and detect errors in a timely fashion in order to fix them well before they can cause too much damage. For that reason, periodic quality checks are indispensable for analytics dashboard maintenance.

But it’s important to remember that quality audits shouldn’t only be internal. Fivetran regularly conducts comprehensive internal and third-party audits of its own applications, systems, and networks to ensure that quality standards are maintained and data protection requirements are always met as regulations evolve over time.

4. Comply with changing rules and regulations

The fourth characteristic of an effective analytics dashboard is full compliance with local and overseas governments’ rules on data transfers, information privacy, and storage. There are multiple ways in which Fivetran maintains its GDPR, HIPAA, and protected data disclosure compliance, but the main ways in which other companies can is by:

  • Storing client data on their own servers for a limited amount of time (24 hrs)
  • Comprehensive end-to-end data encryption
  • Adding overseas servers (to keep PI within specific geographic limits, such as for GDPR)
  • Keeping dashboards accessible while also blocking or hiding protected data for specific internal stakeholders

Check your local and industry-specific legislation for more ideas on how to make the data feeding your dashboards as safe and legally-compliant as possible.  

5. Share your data and create synergies with different players

Going through a middleman to access critical data is a well-known pain point for many business leaders and analysts alike. According to a recent Dimensional Research survey, 62% of data analysts had to wait for centralized dev teams to provide access to requested data several times a month while 34% “wasted time” attempting to find the data they needed themselves.

The key to resolving these operational bottlenecks is to bypass the traditional information pipeline altogether via technology-enabled data integration. In other words, by centralizing data in a single location (such as a data warehouse), analysts and stakeholders alike can independently access the information they need to work together in a more transparent and effective way. Fivetran has 150+ prebuilt data connectors to combine data from all of a business’s applications, databases, and software. An organization can automatically combine data sources to produce powerful metrics that enable data-driven decisions in real-time. People across the organization can use the information in ways that make the most sense for their own teams, share in common successes, and maintain accountability throughout the organization.

For an in-depth look at these analytics-powered dashboards and environments, visit the Fivetran website or request a demo today.

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