New: Improve Your Accuracy With Manual Data Editing. We would love to live in a world where subscription data is always perfectly clean, and where subscriptions can be seamlessly moved between billing methods. Sadly, we don’t. Over the years we’ve noticed a few common problems that have made it difficult to provide all of our customers a way to arrive at a full and accurate picture of their subscription metrics. Today we’re solving for that with the launch of manual data editing. While this may not sound like the biggest, sexiest update, it’s actually our most requested feature, and something that only ChartMogul can do. Let’s take a look at some of the problems manual data editing solves. Problem #1: Moving subscriptions between billing systems A frequent occurrence we see, especially among B2B businesses, is that a customer will request to stop paying by credit card and instead pay by wire transfer. The business might cancel the subscription in their billing system (for instance, Braintree) and send the customer an invoice requesting payment by bank transfer. In this scenario it would look like the Braintree customer has been cancelled in ChartMogul. You could then create another subscription manually and merge the Braintree record and manual invoiced customer record into a unified customer record. But while the customers are merged, the subscription objects are still separate, even though conceptually the only thing that has changed is the payment method. In ChartMogul, this will look like a churn event, followed by a reactivation.  A less common — but far more painful — occurrence is the total migration of all subscriptions from one billing system to another. This could be a migration from a homegrown billing solution to a SaaS solution like Recurly or Chargebee, or from something like Stripe to a more enterprise billing solution like Zuora. In the event of a company-wide migration to a new billing system, you can add the new data source to your ChartMogul account; however, you’ll still see 100% of your customers churn (in the old data source) and then 100% of them reactivate (in the new data source). This creates the same issue from the first scenario, but on a much larger scale. The solution: Connect your subscriptions to eliminate the false churn We’re fixing the issue of moving subscriptions between payment methods and systems with a feature called Connect Subscriptions. With this feature, you can easily combine multiple subscription objects that originate from different billing systems into a single conceptual subscription object. Navigate to an individual customer profile to view and edit subscription history. Problem #2: Messy billing data (AKA the “garbage in, garbage out” problem) No matter what billing system is being used, something will occasionally go wrong with a customer’s billing and the business will end up doing some sort of manual fix to resolve the issue. This generally results in messy data in your billing system. The adage “garbage in, garbage out” then holds true in these situations and, based on the data alone, it can be impossible to interpret what the MRR should be for a customer at every point in time. The solution: Manually edit MRR to clean up your data Now you can clean up incorrect MRR history caused by these billing issues with manual data editing. Navigate to an individual customer profile in ChartMogul and select Edit MRR to manually define the MRR history for any given customer. It should be a really nice user experience — you can either manually enter the correct MRR or use your mouse and a slider to set the right MRR. Navigate to an individual customer profile to view and edit subscription history. We hope you find these two new features useful! They represent a big leap forward for ChartMogul, and put us closer to our ultimate goal of serving as the single source of truth for all revenue metrics. And this is just the start. In the future we’d like to be able to auto-detect the most common issues and apply these data edits on your behalf. For now, I’ll leave you with this image. With ChartMogul, “garbage in” no longer has to mean “garbage out”.
[INST] New: Improve Your Accuracy With Manual Data Editing [/INST]
 We would love to live in a world where subscription data is always perfectly clean, and where subscriptions can be seamlessly moved between billing methods. Sadly, we don’t. Over the years we’ve noticed a few common problems that have made it difficult to provide all of our customers a way to arrive at a full and accurate picture of their subscription metrics. Today we’re solving for that with the launch of manual data editing. While this may not sound like the biggest, sexiest update, it’s actually our most requested feature, and something that only ChartMogul can do. Let’s take a look at some of the problems manual data editing solves. Problem #1: Moving subscriptions between billing systems A frequent occurrence we see, especially among B2B businesses, is that a customer will request to stop paying by credit card and instead pay by wire transfer. The business might cancel the subscription in their billing system (for instance, Braintree) and send the customer an invoice requesting payment by bank transfer. In this scenario it would look like the Braintree customer has been cancelled in ChartMogul. You could then create another subscription manually and merge the Braintree record and manual invoiced customer record into a unified customer record. But while the customers are merged, the subscription objects are still separate, even though conceptually the only thing that has changed is the payment method. In ChartMogul, this will look like a churn event, followed by a reactivation.  A less common — but far more painful — occurrence is the total migration of all subscriptions from one billing system to another. This could be a migration from a homegrown billing solution to a SaaS solution like Recurly or Chargebee, or from something like Stripe to a more enterprise billing solution like Zuora. In the event of a company-wide migration to a new billing system, you can add the new data source to your ChartMogul account; however, you’ll still see 100% of your customers churn (in the old data source) and then 100% of them reactivate (in the new data source). This creates the same issue from the first scenario, but on a much larger scale. The solution: Connect your subscriptions to eliminate the false churn We’re fixing the issue of moving subscriptions between payment methods and systems with a feature called Connect Subscriptions. With this feature, you can easily combine multiple subscription objects that originate from different billing systems into a single conceptual subscription object. Navigate to an individual customer profile to view and edit subscription history. Problem #2: Messy billing data (AKA the “garbage in, garbage out” problem) No matter what billing system is being used, something will occasionally go wrong with a customer’s billing and the business will end up doing some sort of manual fix to resolve the issue. This generally results in messy data in your billing system. The adage “garbage in, garbage out” then holds true in these situations and, based on the data alone, it can be impossible to interpret what the MRR should be for a customer at every point in time. The solution: Manually edit MRR to clean up your data Now you can clean up incorrect MRR history caused by these billing issues with manual data editing. Navigate to an individual customer profile in ChartMogul and select Edit MRR to manually define the MRR history for any given customer. It should be a really nice user experience — you can either manually enter the correct MRR or use your mouse and a slider to set the right MRR. Navigate to an individual customer profile to view and edit subscription history. We hope you find these two new features useful! They represent a big leap forward for ChartMogul, and put us closer to our ultimate goal of serving as the single source of truth for all revenue metrics. And this is just the start. In the future we’d like to be able to auto-detect the most common issues and apply these data edits on your behalf. For now, I’ll leave you with this image. With ChartMogul, “garbage in” no longer has to mean “garbage out”.
<sys> [INST] New: Improve Your Accuracy With Manual Data Editing [/INST] We would love to live in a world where subscription data is always perfectly clean, and where subscriptions can be seamlessly moved between billing methods. Sadly, we don’t. Over the years we’ve noticed a few common problems that have made it difficult to provide all of our customers a way to arrive at a full and accurate picture of their subscription metrics. Today we’re solving for that with the launch of manual data editing. While this may not sound like the biggest, sexiest update, it’s actually our most requested feature, and something that only ChartMogul can do. Let’s take a look at some of the problems manual data editing solves. Problem #1: Moving subscriptions between billing systems A frequent occurrence we see, especially among B2B businesses, is that a customer will request to stop paying by credit card and instead pay by wire transfer. The business might cancel the subscription in their billing system (for instance, Braintree) and send the customer an invoice requesting payment by bank transfer. In this scenario it would look like the Braintree customer has been cancelled in ChartMogul. You could then create another subscription manually and merge the Braintree record and manual invoiced customer record into a unified customer record. But while the customers are merged, the subscription objects are still separate, even though conceptually the only thing that has changed is the payment method. In ChartMogul, this will look like a churn event, followed by a reactivation.  A less common — but far more painful — occurrence is the total migration of all subscriptions from one billing system to another. This could be a migration from a homegrown billing solution to a SaaS solution like Recurly or Chargebee, or from something like Stripe to a more enterprise billing solution like Zuora. In the event of a company-wide migration to a new billing system, you can add the new data source to your ChartMogul account; however, you’ll still see 100% of your customers churn (in the old data source) and then 100% of them reactivate (in the new data source). This creates the same issue from the first scenario, but on a much larger scale. The solution: Connect your subscriptions to eliminate the false churn We’re fixing the issue of moving subscriptions between payment methods and systems with a feature called Connect Subscriptions. With this feature, you can easily combine multiple subscription objects that originate from different billing systems into a single conceptual subscription object. Navigate to an individual customer profile to view and edit subscription history. Problem #2: Messy billing data (AKA the “garbage in, garbage out” problem) No matter what billing system is being used, something will occasionally go wrong with a customer’s billing and the business will end up doing some sort of manual fix to resolve the issue. This generally results in messy data in your billing system. The adage “garbage in, garbage out” then holds true in these situations and, based on the data alone, it can be impossible to interpret what the MRR should be for a customer at every point in time. The solution: Manually edit MRR to clean up your data Now you can clean up incorrect MRR history caused by these billing issues with manual data editing. Navigate to an individual customer profile in ChartMogul and select Edit MRR to manually define the MRR history for any given customer. It should be a really nice user experience — you can either manually enter the correct MRR or use your mouse and a slider to set the right MRR. Navigate to an individual customer profile to view and edit subscription history. We hope you find these two new features useful! They represent a big leap forward for ChartMogul, and put us closer to our ultimate goal of serving as the single source of truth for all revenue metrics. And this is just the start. In the future we’d like to be able to auto-detect the most common issues and apply these data edits on your behalf. For now, I’ll leave you with this image. With ChartMogul, “garbage in” no longer has to mean “garbage out”. </sys