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3 Data Visualizations to Get Started in Periscope Data

When a company first starts using a platform like Periscope Data, it can be difficult to determine where to start building, so we’ve put together a few options we’ve seen customers use to be successful quickly.

Once data is plugged in, beware the temptation to start building a bunch of one-off charts to experiment with how the tool works. Doing too much ad-hoc analysis without tying it back to the business objective is not a very good way to establish a single source of truth and get your entire team used to the tool.

The absolute first step to getting value out of Periscope Data is to decide on a baseline set of metric(s) to track. For some companies, this is simple — revenue. For others at different stages of growth, they may value active users, customer retention, time in product, lead conversion, etc. Most of the time, these are metrics that a company already has top-of-mind. On top of that, there’s usually a monthly, quarterly or annual goal to hit as well.

Once a company or department has decided on that mission-critical metric, there are a foundational visualizations that can communicate the current state, historical performance and places for optimization. Here are the first charts to create to start uncovering that story:

1. Gauge chart

Once a company has decided on one key metric to drive toward, there’s a natural first question to ask: “How close are we to hitting our goal?” These charts can take a lot of different forms but they all track the progress of a current metric against a goal. It only takes those two numbers to create a gauge chart, but it’s an easy way for an entire company to establish and maintain visibility on the most vital data.

For example, consider a young company that makes a commitment to gain 100 new customers by the end of the year. They could create a radial progress chart with a needle that moves 1% toward the goal with every new customer. Everyone in the company can have access to this chart and can monitor the company’s progress as often as they’d like.

2. Historical performance line chart

After addressing the initial question of current progress toward the goal metric, other questions will naturally come up. For example, it’s logical to look back and track historical performance in regards to that specific goal. Is the company trending up or down? What did the same metric look like at the same time last month or last year? If there is a clear time period that we want to compare against the previous, a good way to track this data is a simple KPI chart.

If there is a need for seeing the continuous change over time, a line or bar chart may be a better option. For example, the same company from above that is driving toward 100 new customers could build a line chart that tracks how many customers they’ve added each month for the past year. They could track their total number of customers every month to see whether their growth is increasing or decreasing. That data might help them anticipate which months might be ripe for growth. Their team could apply filters to see if certain types of customers are growing faster than others and change their strategy to focus on that type of new business.

3. Conversion Funnel

After answering basic questions about the past and present performance of the most crucial KPI, most companies begin to get curious about steps they can take to improve that metric in the future.

An easy way to dig into those questions is to build a funnel chart that shows every step in a company’s intended journey (in this case, from lead creation to a closed deal). A simple way to organize this funnel can be a series of bar charts that illustrates conversion and dropoff at each stage. Data for this funnel will be more complicated to gather than for the previous charts, but its construction will eventually deliver more value than simpler reporting visualizations.

To go back to our example company, they might build a funnel chart to track the sales process. From here, they can filter by lead source and change their strategy to maximize the highest performing channels. They might also notice that a huge percentage of leads who take a certain marketing action are likely to convert to paying customers. In that case, they’d try to push other leads to take the same action.

This series of visualizations is a great way to dip your toes into Periscope Data and start seeing immediate value. If you’re interested in learning more about creating captivating charts, check out our How to Chart Your Data Discoveries blog post or join the discussion on the Periscope Data Community.


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Christine Quan
Christine spends a lot of time thinking about data visualization theory and building tools to empower data teams. When she is not constructing SQL queries or building visualizations in R, Python, or Javascript, she can be found dissecting Taylor Swift lyrics through text analysis or analyzing emoji use in surveys.