5 Marketing Metrics That Pop as Data Visualizations

By Amy Chisam

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Your business is more complex than just sales, website traffic, conversion rates, and other fundamental marketing metrics. Today’s marketers need more sophisticated ways of measuring their business. The best way to present these analytics snapshots? With data visualizations.

“Dataviz has been an imperative for competitive companies,” says Scott Berinato, author of Good Charts. “Those that don’t have a critical mass of managers capable of thinking visually will lag behind the ones that do.”

Good visualizations should easily explain the information they’re conveying. But more importantly, visualizations should highlight opportunities to grow your business.

1. KPIs by Geography.

Most key performance indicators can be tracked in table format. Qualified leads, customer acquisition costs, sales growth.

“What were sales variance by state last year”

For many of these KPIs, you want to go deeper and get a breakdown by country, state, or region. You can certainly do this in a table. However, a map visualization lets you quickly detect geographical trends. For instance, although the highest states in sales are California and New York, several of the Southeast states are top performers.

Maps with color shading (these are called choropleth maps) put outliers in the spotlight. Why would Iowa be doing so much more poorly than anywhere else? This gives you the jumping off point to ask follow-up questions about Iowa’s performance.

2. Customer Retention

Of course you’re already tracking customer retention. But you may not be getting granular enough to see critical churn breakpoints.

“Show the customer cohort by quarter for the last five years for TVs”

A heat map with cohort analysis elevates your customer or product data by letting you study behavior over time. So for instance, start with all of the customers who purchased TVs on a given date, with rows that segment by basket size. Each subsequent column would show what percentage of that original set spent any amount the following week. By arranging the data in this format, you’ll be able to quickly see your retention patterns.

3. Channel or Category Segmentation

Imagine this dialog with your CMO:

You: “Overall sales last month were down $40.1 million.”
CMO: “OK, thanks for that information.”

No marketing executive would ever stop at a bottom-line metric, especially when it’s bad news. Prepare to get asked why, and this will take you down the path of understanding variances by category.

“What was the target variance by category in December 2016?”

Waterfall charts are great for showing cumulative inputs. In this example, breaking sales down by category lets you quickly see that video games is one of four categories outperforming projections, whereas laptops and computers are most off the mark. A table of numbers could give you this same information – but this visual display more quickly shows the relative sales contribution for each category.

This same type of visualization is handy for showing marketing channel contributions. Say you’re trying to understand how various inbound channels contributed to overall website traffic, month over month. A waterfall would give you that relative breakdown for organic search, direct traffic, social media, and more.

4. Customer Migration Patterns

Understanding customer lifetime value (CLV) is critical. To do this, you first need to think of your customer base in tiers – those with the highest average orders are tier 1, for instance. Next, study their behavior over time. Are these top customers still buying at the same rate? Have they dropped their average spend? Or have they stopped buying altogether from you?

A migration chart is a variation of an alluvial diagram, which shows how values change over time or between your specified parameters. With AnswerRocket, it’s as simple as asking a migration question that includes date ranges and filtering criteria.

Once generated, this chart type can help you identify customers who have churned or are new adopters. The first group identifies save opportunities; the second, which ones to further upsell. For instance, in the chart above, 169 of the original top tier customers did not make a purchase a year later.

What makes this chart even more powerful is the follow-up. Drill in on any segment to automatically generate the list of customers for which you can develop a marketing campaign.

5. Customer Segmentation by Multiple Dimensions

Customer segmentation lets you get very targeted with your analysis. You’re no longer just interested in “empty nesters” – but “empty nesters who purchased TVs, based on the type of store they visited.”

“Segment stores by sales increase of TVs to empty nesters last year”

Scatter plots do a good job of showing correlations and highlighting outliers. The more your data falls into a southwest-northeast diagonal line, the stronger the correlation is between two metrics.

However, scatter plots with segmentation give a more sophisticated view of your data. AnswerRocket’s clustering algorithm dynamically detects relationships between fields. In the above example, every store is represented as a dot. Each color is a region. So in using one visualization, each store’s sales and growth can be compared against all other stores as well as those just in their region.

The possibilities with this chart type are numerous. You could survey your customers about their purchase experience, and then generate charts showing their net promoter score (NPS) against type of purchase and another metric.

Visualizations aren’t just appealing to look at – they’re powerful tools to show what’s really going on in your business. Share these in your next executive presentation or team meeting, and then quickly answer the inevitable follow-up questions with even more visualizations.


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