“Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Chris O’Hara, co-founder and chief revenue officer of Bionic Advertising Systems.
Standardizing operations on a media management system and putting together a media plan are huge undertakings, with a ton of manual work.
Tracking down all order management, billing and vendor information, for example, is time-consuming. Not to mention all the little things, such as creating the actual plan in Excel, trading emails with vendors in the RFP process, trafficking ad tags and collecting screenshots.
What if computers could streamline much of that work and connect buyers and sellers together more seamlessly?
That would transform the business of a chief digital officer to whom I recently spoke. He’s in the middle of executing these projects for his large agency, which does a lot of digital media buying. He’s largely accepted much of that manual work as part of the cost of doing business.
The keys to truly revolutionizing his business, he said, come down to answering four questions. If programmatic-direct technologies simply nailed down these four issues, the payoff would be enormous.
1. How much should I buy?
This executive basically knows that he will have AOL, Yahoo, Facebook and GDN on almost every plan. For his more vertical clients – in auto, for example – he also knows 95% of the sites and networks he will be on. Sure, he uses research tools to validate those recommendations to his clients, but media discovery is not a huge pain point.
Where they struggle is answering the question of media investment allocation. Should he spend 30% of his budget with Facebook? Forty percent? He really doesn’t know, and often don’t have the right mix until the campaign is nearly over. It would be great to have some business intelligence built into a system that recommended his guaranteed media mix programmatically.
2. What should I pay?
He also has a pretty good idea about what things cost, thanks to the RFP process. When you send RFPs to 40 publishers in a vertical, you find out pretty quickly what your best pricing for guaranteed media is, and you can leverage that information to insure you are giving your clients competitive rates.
Unfortunately, it feels like he goes through this exercise every time, on every RFP. He has the historical pricing data, but it’s all over the place in spreadsheets — and often in the planner’s heads. It would be great if this information was in the same place, and if a system could make pricing recommendations upfront in the process, which would also shorten the negotiation process with publishers.
3. Why am I recommending this?
The biggest thing his agency struggles with is justifying its media choices to its clients. When they present a recommendation, often they are asking clients to invest hundreds of thousands, or even millions, of dollars in an individual vendor. His deck has to have more in it than basic audience information. He must talk about the media’s ability to perform and hit certain KPIs for the price.
It would be really useful to have recommendations come with some metrics on how such placements performed historically, or even some data on how other, similar investments moved the needle in the past. Right now, getting to that data is nearly impossible, and usual resides with the senior planner on the account.
The other obvious problem with that is employee turnover. His best planners, along with everything they’ve learned over two or three years, walk out the door along with his data and relationships. The right system should store all of that institutional knowledge.
4. You need that when?
The other thing a system can help with is speed to market. Publishers hate it when he asks them for huge, innovative proposals — in 24 hours. The reason they do that is because their clients ask them for amazing and innovative media recommendations — in 48 hours. The pressure to deliver plans is huge, and you can easily lose large chunks of business by reacting to such requests too slowly. What programmatic-direct technology may be able to help with is giving planners access to tools that compress the pre-planning process down, and enable agencies to deliver thoughtful, data-backed recommendations fast — and at scale.
Especially for larger agencies, programmatic-direct technology has to be more than just workflow efficiency tools and automating the insertion order, although that must come first. The next generation of programmatic efficiency or guaranteed media must include serious business intelligence tools that can solve the “how,” while simultaneously answering “why.”