ad operations

The Four Stages of Managing Digital Ad Inventory

Digital inventory management is usually handled in one of a couple ways at most major companies, depending how granular they sell, and how much traffic they get.  These are the main strategies, listed in order of sophistication as I see it.

1. Complete and utter reliance on the ad server’s availability forecasting tool
2. An excel-based inventory model based on historical ad server reports and pivot tables
3. A technology solution as part of a workflow suite such as Solbright, or Dart Sales Manager, often called DSM in the industry
4. A stand-alone technology solution for inventory management such as Yieldex

There aren’t too many major publishers left wallowing at stage 1, and those that are likely have more inventory and traffic than they can possibly sell.  There is a glut of impressions across the net, but unlimited is a lot, and there aren’t more than a handful of sites that are truly in this situation, except perhaps some of the social media and user-generated content sites like Youtube, MySpace, Facebook, etc.  For full disclosure, I have no idea if these companies are indeed flying by the seat of their pants or have a more sophisticated solution in place to manage their digital ad inventory.  On the other side of the coin, there are certainly a few small publishers out there that need an inventory solution, but either can’t afford the investment in the people or technology to push them forward.  These are the small publishers that hold a moderately valuable audience, or perhaps a big piece of a niche demographic, but drive the agency teams crazy with their constant underdelivery.

Stage 2 is usually a stepping stone to Stage 3 or 4, where a company has recognized it needs someone in an analyst role to help them deliver campaigns and support their sales team to build realistic proposals.  This is the start of a true inventory management branch of an Ad Ops department, and the best people in this role have a consultative approach and help sales find creative solutions to adjust plans before they go out the door, and what can be done to help struggling campaigns.  Unfortunately, as great as ad server reports are, this isn’t a manageable solution for any company with a significant sales team or significant growth.  At a certain point, excel doesn’t have the firepower, and human fingers aren’t fast enough to keep up with the sales machine.  When the department becomes overwhelmed, campaigns start underdelivering again, or a company loses the talent holding things together, they typically look to a technology solution.

At this point, things go one of two ways, and honestly, the decision tends to come down to what kind of billing system the company is already using, and if they are already paying for some kind of sales pipeline / workflow management tool.  The choice is between a stand-alone technology for the Ad Ops department, or a full-fledged, workflow management system that organizes everyone from Sales Management to ad traffickers.  Getting a whole company to buy into a solution and rethink their current system is not an easy undertaking however, especially when the ones clamoring for help are usually the back office folks.  Making the transition and fully integrating something like a Solbright is also daunting, and usually a year-long, full-time project for a handful of people who represent each end-user.  Sales has to be involved, management has to be involved, Ops has to be involved, billing has to be invovled, and usually, IT does, too.  These tools do a laundry list of tasks as well, so it’s no surprise they’re also more expensive.

For companies that are already on something like a Salesforce.com or proprietary / legacy billing system, a stand-alone solution probably makes more sense, and is usually faster to implement, barring a complex custom integration.  My experience with Yieldex has been somewhat limited, but I have had an opportunity to work with the system for a few months at this point, and when it works, it works impressively.  The main challenge I see with Yieldex is from a usability standpoint.  While the system provides an incredible level of data, it’s often very difficult to get to that data quickly, and en masse.  Still, Yieldex is certainly one of the more exciting options to come to market for companies looking to increase accuracy and visibility across a set of complex, overlapping products.