Churn Analysis Dashboard Overview

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Churn analysis is the core functionality of the MRR Churn application. We take that analysis to a whole new level, both in term of the depth of granularity and in the enterprise-level scope of analysis across multiple BUs and legal entities. Every possible source of change in recurring revenue is isolated and tracked. Over 30 categories, or buckets, of MRR changes are captured for every month, quarter and year, both in terms of month-over-month changes and year-over year changes.

But why track MRR changes down to such excruciating detail? It is simple, really. If any source of change that you may not care as much about is not correctly isolated, then it will, by mathematical necessity, distort the measurement of one or more other sources of change that you definitely do care about. For example, we capture and analyze all recurring revenue in the originating currency (OC) that is actually billed, and we use our own very accurate FX translation engine to convert OC amounts to both the local currency (“LC”) and reporting currency (“RC”) of each legal entity at monthly average or ending rates, depending on which is applicable. That way, all FX impacts on MRR (and DRR) – even when otherwise buried within the LC numbers of the GL – can be completely isolated from all other MRR (and DRR) fluctuations. So, although you may not care as much about uncontrollable MRR fluctuations caused by FX rate changes – or even by partial months of recognition – you most likely care very much about accurately measuring price increases and decreases, quantity increases and decreases, product mix changes, product-specific lapses and reactivations, etc. Unfortunately, there is no shortcut to accuracy in any change category without a rigorous tracking of all potential sources of MRR (and DRR) changes.

Another major issue is how to accurately measure active customer counts, including what is a “new” or “lost” customer vs. a “saved” or “lapsed” customer. And the same applies to active product counts and “new” vs. “lost” products and “saved” vs. “lapsed” products” for each individual customer. There is also the issue of how to track acquired and divested customers, as well as acquired customers who may have also been lost or lapsed within the same year after acquisition. The latter is important to track for M&A due diligence to make sure that every customer that was paid for in an acquisition is a valid customer and was properly billed, with the correct recognition start date, post-acquisition. It is easy for such costly oversights to occur in an M&A transition process. Fortunately, once all sources of change in MRR are correctly isolated, this analysis is essentially fully automated as part of the larger net churn analysis.

With this extreme depth and breadth of net churn analysis data, from the most granular level to the most aggregate levels across multiple dimensions, a broad set of analytical methods and visualizations can be applied to extract a wealth of information. These include the following in the dashboards below, among many more possibilities:

  • Graphical MRR trending by BU and net churn analysis drill downs
  • Trending analysis by customer and product,
  • Continuity analysis/reconciliations,
  • Individual customer or customer segment churn analysis,
  • Individual product or product segment churn analysis,
  • Exception reporting and top customer monitoring,
  • Top lost and lapsed customers for immediate follow-up,
  • Loyal customer attrition analysis, and
  • One-click drill-through analysis down to every invoice and invoice line item comprising any customer level MRR or billed amount in OC, LC or RC.

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MRR Churn Analysis

Break down and isolate all changes in MRR trending vs. the prior month or prior year to an unprecedented level of detail, starting with summary-level MRR changes and drilling down into detailed-level MRR changes across the dashboard panels. While other churn analysis applications can break down MRR changes into four categories, our MRR Churn application can break down MRR changes into 30+ categories, and not just month-over-month (MoM), but also year-over-year (YoY). And beyond these most detailed change categories, the dashboard breakdowns go still deeper by showing the top customers driving each of those categories the most.

Customer Churn Analysis

Break down and fully reconcile customer count changes, just like MRR changes, both YoY and MoM. Accurate customer count continuity is assured, including for acquired vs. divested customers, new vs. lost customers, lapsed vs. saved/reactivated customers, etc. Easily identify who the most significant customers are that either increased or decreased customer count in any period, for any BU or legal entity.

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MRR by Customer Trending

Analyze the trending of MRR and other measures for each customer of the selected BU and legal entity, by month, quarter or year. For even greater detail, expand the trending for any customer to show the product-level trending analysis as well. Apply numerous churn category filters to display optional subsets of customers, such as those who have not yet received a price increase vs. the prior year greater than a user-defined %. And for still greater analysis detail, display the same 30+ categories of churn analysis for every customer and every product line item billed to fully explain how MRR changed by customer and product line item, both YoY and MoM.

MRR by Product Trending

Drill down from the MRR Customer Trending report to the product level detail in this report. Via trending by month, quarter or year, analyze MRR, DRR, revenue billed, all 30+ churn analysis categories, and numerous other customer and product KPIs for any one (or all) products of an individual customer.

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MRR by Invoice and Line Item

Drill down the MRR recognition and analysis still further to invoice and invoice line item to close the entire loop on the revenue recognition audit trail, regardless of how many times a single product was billed or credited to a customer in any time period. Display MRR and billing data in the originating (billing) currency of the customer, along with both the local currency and reporting currency of the legal entity, to allow easy reconciliation with MRR by Customer Trending, MRR by Product Trending, and the ERP billing system. Also display key invoice and line item billing attributes, such as start and end dates of recognition to allow easy verification and understanding of the revenue recognition calculations.

Top Lost and Lapsed Customers

Highlight the top lost customers in any period to allow for verification and urgent follow-up if a customer has not given formal notice of termination. Also highlight the top lapsed customers in any period to allow for verification and urgent follow-up if a customer has in fact not lapsed, thereby indicating that the customer was not fully billed for all subscription periods.

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Click to Enlarge

Loyal Customer Attrition

Analyze the trending of lost customers to see if more loyal or less loyal customers are being lost vs. the average. Also, highlight the lost customers who have been more loyal than the average customer, in descending order, where loyalty is measured by either lifetime MRR to date or customer lifetime months (vs. the average). Urgent follow-up and remediation is required if the most loyal customers are being lost nearly as frequently – or more so – than newer customers.

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