If you’re creating your first KPI dashboard and you’re anything like most of the startup founders we’ve worked with, you likely won’t get it right from the first go.

In fact, most teams abandon their dashboards after only a few months of using them.

That’s because it takes quite a bit of upfront sweat to create a startup dashboard your team will keep using and drawing valuable insights from well into the future. 

However, there are quite a few reasons why you need to roll up your sleeves and put in some work. Among other things, an effective KPI dashboard for startups allows you to:

  • Have a real-time snapshot of all your business-critical metrics in a single point of truth
  • Monitor your startup’s performance and quickly detect areas for improvement
  • Fuel smart decisions rooted in hard data
  • Enhance team communication and democratize data across departments
  • Improve investor reporting 

Here, we’ll share six must-adopt practices fueled by real-life case studies for building and optimizing your startup KPI dashboard to squeeze the most juice out of it.

Define the game-changing metrics for your industry and goals

The more you tailor your dashboard to your startup’s unique needs, goals, and industry-specific metrics, the better the insights you’ll draw from it. Don’t start without having those core metrics prepared.

To outline the critical areas of focus, engage all the key stakeholders—founders, investors, team members— in the brainstorming process. 

On top of helping you point out critical metrics of interest, having decision-makers weigh in is necessary to:

  • Create a more rounded and holistic dashboard that covers all necessary aspects of your startup—both strategic and tactical
  • Increase the likelihood of your team adopting and engaging with the dashboard due to a sense of ownership and understanding of the tool
  • Ensures the dashboard will cater to the needs of different departments 
  • Set realistic targets and avoid stretching resources

So, what types of metrics should you consider? Think about the following types of metrics:

  • Industry-specific metrics. For example, for e-commerce, it would be conversion rate, average order value, and customer lifetime value (CLTV); for SaaS, it would be churn rate, lifetime value (LTV), customer acquisition cost (CAC), monthly recurring revenue (MRR) and so on. 
  • Startup-specific metrics. These can include customer insights like the demographic you’re going after and customer behavior.
  • Department-specific metrics. Different departments need to track different sets of metrics, and it’s important to cater to each department. For example, investors and CEOs expect high-level information like MRR/ARR, cash on hand, number of new customers, etc., while sales folks will care about the Magic number, Net sales efficiency, etc.

WAVEUP STORY:

We had a client in SaaS who had reached 1M yearly users. The founders were laser-focused on growth, solely tracking metrics like MOM user growth, MRR, revenue per user, etc.

Later on, however, the problem they had no idea about surfaced: their users were churning almost immediately, within one or two months on average. The retention was painfully low.

We recommended they create a dashboard where they would track user lifetime per each channel through which they acquire users. As they did this, they saw that different acquisition channels have drastically different retention rates.

For example, their social media and partner channels were generating customers with much longer lifetimes, meaning users coming from these channels were a much better fit for the product.

As a result, they doubled down on these channels and tripled their retention rate, which hugely helped them in their following fundraiser. 

Set clear KPIs and realistic targets 

Once you are in the clear about what metrics you need to track, it’s time to set up clear goals you need to hit within those metrics.

These goals will depend on two things:

1. Your startup’s stage

Each stage is characterized by a particular set of milestones signifying success. For example, the focus of early startups that already have a product should be on achieving product-market fit, typically characterized by various lagging and leading indicators like

  • customer retention >90%
  • the number of adopted features
  • the time spent on the app, etc. 

Later on—typically Series A and further— the focus will shift towards revenue growth, capital efficiency, and breaking even/achieving profitability. Depending on your type of business, this often means hitting the following targets:

  • MRR
  • CAC payback
  • LTV
  • Gross margin, etc.

2. Industry benchmarks

Each and every milestone you set must be contextualized by comparing them against benchmarks for your industry and stage. 

Such benchmarks serve as realistic reference points to push off of, showing you what’s possible and expected for companies like yours. 

Here are a few strategies to find comparative benchmarks for your startup:

  • Use industry reports and white papers to gather data on the average benchmarks in your sector
  • Conduct a thorough competitor analysis to understand their performance levels and market standings
  • Engage with industry experts to gather insights 

Once done, look at where you stand according to the gathered benchmark data. Don’t follow them blindly, though; rather, customize the KPIs based on your startup’s unique needs and strengths, blending industry benchmarks with internal data.

❗️Important: Keeping all your KPIs up to date and making timely adjustments to make accurate decisions is a must. Old or inaccurate data can lead to wrong conclusions and poor decision-making—and really hurt team performance and morale.

Your targets and KPIs aren’t set in stone and must be regularly reevaluated to reflect your startup’s current strategy.

How do you achieve this? By implementing real-time (or near real-time data) updates. Utilize data integration and automation tools to pull data from various sources and keep it continuously updated. 

This way, you’ll provide stakeholders with the most accurate and up-to-date information.

Make user experience top of your mind

Dismissing visual and usability aspects is a common blunder founders commit when setting up their first KPI dashboards. 

In 99 cases, their teams abandon such dashboards within the first few months. Those who stick around just end up getting the same results as they would by using basic Excel sheets.

Your dashboard can and must do better than this. But to get 100% use out of your dashboard, you need to put effort into making it as visually appealing, interactive, and easy to understand and navigate as possible. 

Here is how to optimize your dashboard for user experience:

  • Employ visual aids like charts and graphs
  • Include interactivity elements like filters and drill-down options
  • Customize your dashboards for different audiences, i.e., view for Ceo/investors, for sales, marketing, operations, etc.
KPI dashboard example
A great KPI dashboard example from Databox illustrates how you can visualize data for better comprehension

These steps will prolong the lifespan of your dashboard, boost team engagement with the tool, and improve your team’s ability to draw valuable insights from it.

Apply the Occam’s razor principle to your dashboard content 

You may have heard of the Occam’s razor principle. If not, the principle is as follows: when faced with a challenge, ‘shave off’ all the unlikely explanations and focus on the simplest one.

This minimalist concept applies to numerous purposes—including what information you should allocate on your KPI dashboard. 

Here is how you can apply this principle to your dashboard:

  • Separate financial metrics—such as revenue and expenses—from operational metrics, like customer satisfaction and product usage
  • Use clear visual elements such as charts, graphs, and icons—they help to effectively convey more data
  • Get rid of any data or visual elements that don’t serve strategic purposes or contribute directly to the understanding of key metrics
  • Use logical groupings, sections, or visual separations to guide users’ attention and help them navigate the dashboard intuitively
  • Allow users to select specific metrics or adjust views according to their preferences or specific needs

The Occam’s razor rule allows your team to get a quick yet comprehensive overview of all essential metrics without getting confused or led astray by irrelevant information.

Keep your information updated, a-l-w-a-y-s 

Your dashboard’s primary goal is to help you make informed decisions quickly. This is impossible without having continuous real-time (or near real-time) data updates.

Not once a fortnight or a week. The information flow must get updated as frequently as possible, ideally—with alerts being set up for the most critical issues. 

Here are a few practices you want to implement:

  • Automate data collection: Integrate various tools and data sources like Google Analytics, Zapier, Hubspot, different APIs, cloud computing, etc., into your dashboard to streamline data collection and provide real-time synchronization
  • Schedule reporting: Set up automated alerts and notifications to receive scheduled updates 
  • Conduct dashboard audits: Periodically review your dashboard to make sure the data you’re receiving is accurate and the features/settings reflect your current needs

Put your data in a context

This might sound counterintuitive, but hard data can be very misleading if put out of context. To get the full picture of where you stand, you must always mix your dashboard data with qualitative insights and contextual information.

WAVEUP STORY:

We were helping a blockchain company whose dashboard showed increased churn. However, a closer look showed that the churn was only happening in the channel that was bringing enterprise prospects.

Putting their data in a context revealed that the company wasn’t ready to move upmarket but was doing great among the mid-market segment. This gave them a choice: to adapt their product to the enterprise clients or to focus on a more scalable product-led business model for a mid-market segment. 

At the time, they chose the latter, which allowed them to grow revenue—even though a cursory look at the data showed that they were losing clients.

In other words, any numbers must be viewed in line with strategy and quantitative insights from customers, management, key stakeholders, and so on.

Want to explore more posts on the topics of startup growth, fundraising, and financial modeling? Check out Waveup’s blog to get lost in some crème de la crème content.

13 posts

Anna

Content Writer

Hi there! I’m Anya, a Content Writer at Waveup. I’ve been working with startups in various industries for over 4 years, soaking up the knowledge and learning from their business strategies. Now, I collaborate with the best minds here at Waveup to pick up their expertise and share it with the readers.