I recently posted about inventory strategies and specifically about "leftover" or unsold inventory and suggested 3 reasons why there are leftovers. The first reason is the Self-Fulfilling Prophecy or SFP.
What is the SFP?
SFP refers to the fact that it is "easier" to sell things that you have sold before than it is to locate and suggest new alternatives. Thus, what you have sold before is replicated for the next campaign. All you need to do is change the flight dates and resend the IO. No fuss, no muss.
What's wrong with this, you ask? Nothing. Unless you are selling inventory:
· That is sold out.
· Without adjusting pricing to reflect your current inventory sell-through-rates (why keep a low price if you are almost out of stock?).
· At the expense of recommending other inventory that might be more available and a better fit for your advertiser.
There are many reasons for the SFP including:
· There are too many choices to make. Digital publishers normally have a large and growing number of sellable ad units. For example, a publisher with 4 sites, each with 8 sections, and 4 ad units will have a total of 128 possible ad units to sell, not including run of network/site/section and targeting packages that overlap the entire inventory, which can increase this number by orders of magnitude. For a reference point, an average publisher client of ours has between 1000-5000 different products to sell excluding targeting and other overlaps. Who has the time to hunt and peck through these choices to create the "optimal" proposal?
· Given the above situation, there is very little visibility into alternative choices based on current availability forecasts. Static, manually maintained spreadsheets are unwieldy and out-of-date. They provide little insight into alternative inventory choices. And ad servers generally do not provide this information in a format that is useful to the sales team (tabular, sortable, dynamic, with pricing, real-time availability, etc). Again, who has the time to hunt and peck?
· Little visibility into alternative choices based on expected results. This concept is relatively new to the industry but it is worth discussing. Publishers have a wealth of historical data on client orders and ad performance. Yet, they lack the tools to mine this data for insights into which inventory choices might work best for a specific advertiser. This analysis can be done using a client's history and by creating proprietary predictive models to ascertain these answers based on data the publisher has. Currently for most publishers, it is easier to skip this step and sell the same inventory over and over again.
Why solve this?
There is tremendous potential to increase yield by instituting systems to minimize the SFP and ensure that all inventory is exposed, when appropriate, to advertisers. Most importantly, a publisher can raise their RPMs by selling more of their unsold inventory directly and therefore offering less to the networks and their low and declining CPMs.
Essentially, the publisher can create a middle tier of inventory-inventory that is not quite premium and not quite leftover. The direct benefits include:
· Tiered CPMs. Direct sales will yield higher CPMs than networks. Total yield increases.
· Brand preservation. Direct sales and improved pricing controls ensure that the publisher's inventory is not commoditized as in the case with network remnants.
· Fewer double bookings. Repeatedly selling the same inventory often leads to overbooking, which results in under delivered campaigns and unhappy advertisers (and unhappy sales reps who may have already 'spent' the commissions on these unfulfilled sales).
· Advertisers benefit from having guaranteed, well performing impressions and transparency into the media that they have purchased.
In a future post, I will lay out the economics of better yield management with some examples. The numbers are compelling.