Digital Marketing
2
min read

How To Build An Analytics Dashboard

Published:
September 23, 2022
Updated:
August 1, 2023

When it comes to building and maintaining an effective analytics dashboard, businesses have access to every digital marketing metric under the sun. However, this same bounty of data can leave many in the dark when it comes to successfully reporting marketing performance results to stakeholders. How can agencies and brands sort through data and gather information about their campaigns to build an analytics dashboard that relays results and tells a story? 

The Differences Between Analytics Dashboards and Reports

The first step to building a valuable analytics dashboard is understanding the difference between a report and a dashboard.

An analytics dashboard IS NOT a client report, and while both pieces of content may contain similar metrics, the strategic importance, audience, and use-cases of each need to be parsed out before either can be built.

Dashboards are dynamic and typically display real-time metrics. Analytics dashboards offer an exploratory interface for a wide variety of client-facing roles to gain information on a campaign’s performance.

Reports are static and prepared using analytics gathered from a dashboard or other performance data sources. Reports provide an explanatory interface, usually prepared for specific roles within an organization, and are curated to guide strategic initiatives.

For more information on client reports, visit our Marketing Reports Template Gallery to access customizable templates you can use to create impactful presentations for your agency or business. 

Deciding on Data Sources for an Analytics Dashboard

Analytics dashboards furnish agencies and clients with an easy way to visualize and share campaign performance data. But the quality of an analytics dashboard isn’t about the metrics themselves. It’s more a function of which performance data sources are selected to be presented and how that data is organized and displayed.

Given the overwhelming amount of data sets available to marketers, it’s easy to opt for quantity over quality by filling a dashboard with as many analytics as possible. This is why an effective brief can be an agency's best friend. 

A comprehensive marketing brief can be one of the most powerful ways to choose the right data to share in an analytics dashboard. Well before an ad campaign goes live, digital marketing KPIs should be defined and data sources delineated. 

If the ways in which an ad campaign will be measured have been articulated in the brief, agencies won’t be left scrambling and sifting through mountains of data to gauge if their efforts have been successful.

Along with predetermined KPIs, the team charged with building an analytics dashboard should be connected to a reliable data warehouse and empowered to easily sort, organize, and report on performance metrics.

Data warehouses are used to store large amounts of information about your business. They help companies manage all types of data, whether it's customer information, product details, sales figures, or anything else. The data stored in a data warehouse is usually organized so that it can be easily accessed by users.

Deciphering Performance from Your Analytics Dashboard

Whether it’s Return on Ad Spend, Client Lifetime Value, Customer Acquisition Costs, or direct sales, there are many ways to report on performance analytics within a dashboard. The question then becomes, what information needs to be collected and presented to clients?

The differences between attribution models in digital marketing can be vast, and when presenting them to clients, the response can range from enlightening to enraging.

Attribution models are used to determine which marketing channels are responsible for generating revenue. The most common attribution model in digital marketing is known as the last click model. This model assumes that all conversions happen when someone visits a website, views a page, and then converts on that site. In reality, many people visit a website, view a page, and leave without converting. Therefore, the last click model doesn't accurately reflect how visitors interact with websites. And the confusion doesn’t stop there. 

When consumers engage with a digital ad campaign, there can be many ways in which the measurement of that engagement can be frustrated. For instance, one person may use several devices when interfacing with a company’s website or their advertisements, making direct attribution difficult while also stuffing performance metrics full of duplicated engagements.

Another point of contention in digital marketing attribution is that in-platform analytics will claim ROI for sales from campaigns that would’ve happened organically. The most famous explanation for this phenomenon is the parable of the pizzeria, retold here on Twitter by the inimitable Rand Fishkin.

The TL;DR version of the story is that a pizzeria owner decides she wants to increase business and hires three kids to hand out flyers with unique discount codes and colors (red, white, and green) for each of them. At the end of the month, she tabulates all of the flyers and notices that the green flyers delivered customers at many times the amount of the other two. When she asks the kid how it happened, the kid admits to ducking behind the alley of the pizzeria and handing flyers to people that were headed into the pizza shop anyway. 

This happens on Google and Amazon all the time. Prepared and aware marketers can catch this pattern, and design and deploy ad campaigns that convert audiences well outside their shop doors into actual sales. This is as opposed to  trusting in-platform analytics that may be taking credit for sales that would’ve happened anyway.

Certain attribution models can always make it seem like campaigns are doing well. But, without understanding which metrics are best suited to report on results — and how in-platform analytics can take credit for sales that were inevitable or confuse activity with action—the effort to build an impactful analytics dashboard will be stymied. 

Why Analytics Dashboards Can’t Replace Strategic Thinking

One of the associated risks with becoming too reliant on an analytics dashboard is that focusing on improving the metrics alone can quickly become your entire strategy. Marketers are increasingly judged by the surface level analytics they can deliver through a dashboard. This causes them to focus their entire campaign strategies around boosting these metrics, resulting in an endless loop of tactical tweaks rather than longer-term optimizations. 

Evidence-based marketing thought leader, Robert Van Ossenbruggen, recently posted an insightful image depicting this trend of marketing-by-dashboard and how it may short circuit an marketer’s ability to think strategically. 

His thoughts are worth quoting: “As the marketing landscape becomes more fragmented and marketers rely increasingly on data, strategy becomes an undervalued asset. A growing number of companies seem to substitute strategy slowly but surely for more dashboards and tooling. Such companies risk drowning in a sea of indicators in which it is easily forgotten why they were measured in the first place. Before you know it the dashboard for marketing becomes the strategy. And you’ll be mostly measuring activity instead of monitoring whether you stick to your plan.”

One of the easiest ways to prevent this phenomenon is to ensure that diagnosis, execution, and strategy are all linked to objectives and key results (OKRs) that you can measure. This keeps the marketer’s eyes on the dashboard and brain on the strategy. 

Closing The Analytics Dashboard Performance Loop

Closing the loop on reportable metrics should be a top priority for agencies working to generate sales for clients through advertising. However, many agencies are foiled when it comes to closing the performance loop on their ad campaigns simply because they lack visibility to their client’s profit and loss statements.

While it may seem like an overreach, without an understanding of the full financial picture of a client’s business, agencies will be unable to properly report on campaign results. 

Analytics dashboards provide marketers and clients with content that provides unending details about a campaign. But, without contextual analysis, simply plugging data into a dashboard will not turn the metrics into a compelling story.

In order to properly close the loop from a campaign to the bottom line, clients should be using all the tools available to track effectiveness. Likewise,They should be sharing those same data sets with their agencies as frequently as possible. The hard work of tracking results from a campaign shouldn’t solely rest on the shoulders of an agency, and it definitely can’t end at the dashboard.

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