Closing the Loop: Getting the Full Revenue Picture in Salesforce
In Madrona's last post at AdMonsters, we highlighted how you can set up Salesforce to forecast media sales. This article builds on that approach and adds a technique to blend data from the ad server to get a true all-up revenue forecast.
Revenue Forecasting Is More Than Just Tracking Sales
Revenue forecasting for media companies can seem like a black art, but with a little patience and effort it can be understood and effectively rendered in the one tool the sales team all uses. The start of this journey is simply to break down what we mean when we talk about a revenue forecast. There are four primary components for an ad business –
- Pipeline Data – Deals that are not yet sold, but are in Salesforce. These deals have a revenue amount and schedule attached to them.
- Sold Deals – Deals that have been sold, but the campaign has yet to begin. This data is in Salesforce and these deals have a revenue amount and schedule attached to them.
- Active Campaigns – These are deals that have been sold, entered into the ad server, and the campaign is actively running. This data is both in Salesforce and the ad server, but some months are most accurate in Salesforce and some are most accurate in the ad server.
- Completed Campaigns – These are deals where the campaign has run it’s course, and the customer has been invoiced. This data is both in Salesforce and the ad server, but the most accurate data is in the ad server.
Blending Actuals With Opportunities Is the Key
The key to getting the true revenue forecast in Salesforce is to blend the data coming out of the Ad Server with what already exists in Salesforce. You can do this by leaning heavily on out of the box features with just a little bit of custom data integration to close the loop.
Here are the three key steps to make that work:
1. Close a Deal, Create an Order – Today this happens manually, and there are a range of options for how much you should automate this process. That said, the key takeaway is that as long as you have setup your line items as products in Salesforce, you can post the line item ID from the Ad Server into Salesforce and now you have the foundation to blend your data. Here’s how that might look once it’s stored with your products – 
2. Deliver Impressions, Push to Salesforce – This is the single biggest gap in most media companies Salesforce implementations. In order to be truly useful to the sales team, the results of campaigns need to be pushed into Salesforce. This can be done in real time, nightly, or even weekly, but provides ops and sales management with significantly greater visibility into the overall performance of the business. If you follow along with the approach in number 1, you can simply update the Salesforce line item with this data. Here’s how that might look – 
3. Design Reports That Display Sold and Delivered – The last step is to dive into the out of the box report builder and setup reports that will roll up the line items and clearly display where the organization is all up between sold and delivered for any given month. Here’s one way to display that data, but many alternatives exist once you familiarize yourself with Salesforce reporting functions like formula fields and buckets – 
If you’re interested in learning more about the nuts and bolts, feel free to reach out and I can provide some more detailed guidelines on each step.
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Darren Smith is a senior consultant, customer relationship management, at Madrona Solutions Group. He is a skilled consultant and project leader with deep experience working in and with sales operations teams, and with multiple CRM platforms, including Dynamics CRM and Salesforce.com. He brings a business-focused perspective to his technology engagements that results in great alignment between the technology solution and his client's business needs. Darren is a certified salesforce.com administrator. In his spare time, he enjoys cycling and spending time with his family. Email Darren here.







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Comments
Excellent article Darren.
Was pleasantly surprised to find others were using this approach for revenue scheduling. To build on this architecture, we've created a Salesforce managed package that supports multiple ad servers and reconciliation of 3rd party impression tracking with ad server delivery metrics.
The limitation on rollup summary fields and master-detail relationships makes it challenging to build a true all-up summary on many common dimensions in the media revenue recognition model. For this reason, our data warehouse is hosted separately from Salesforce, but viewable through native inline Visualforce in SFDC.
We use role-based hierarchies to manage revenue rollup by Sales Region (Territory management is not needed for media forecasting when using this monthly revenue scheduling approach).
We chose to create custom objects specifically for Orders and LineItems, rather than use out of box Opportunities.
Salesforce ends up effectively becoming a system of record for Sales journal entries when these integrations are enabled. The end-of-month close process can then be done in Salesforce, exporting to any Financial GL in CSV format (or ideally pushed via integration, such as to FinancialForce, keeping the entire E2E process in SFDC).
-Mike Leach
http://www.placements.io
Great post, Darren.
While this could work towards getting a full revenue picture, it's prone to long term scale and accuracy issues. Most publishers these days are using more than one ad server and changing it frequently. This puts a lot of stress on publishers that don't have time to maintain a Salesforce.com integration(s). "A bit of custom data integration" can be a huge project depending on how they used Salesforce and how their ad server or ad servers are set up. Also, remembering to put the ad server ID in every time involves people...we know how that goes.
The long term solution should involve a business management system or some form of ERP system that becomes a source of revenue forecasting to include real bookings, first AND 3rd party data (another issue that comes with the above strategy, i.e. above, you're only forecasting of 1st party data, which can be misleading since you often bill on 3rd party).
I suggest if publishers use this, it's more of a stop gap solution due to the upkeep, accuracy and the fact that first party deliver data is only used for billing less than 30% of the time.
That all said, this is a pretty crafty solution and sounds like it could hold publishers over until they are ready to do something that involves a longer, more scalable solution.
Lorne