Over the past few months, I’ve met with different agencies and their media teams, speaking with them about their planning and buying process and needs.

Guess what their biggest complaint was? Workflow inefficiency. It is well known in our industry that media planners are over-worked and too bothered with overhead and inefficient process that could lead to sub-optimal media plans and campaign results.

But from my perspective, there’s also another problem, a subtle problem that actually might have even a larger negative impact on the media plan and campaign results. I am referring specifically to the lack of available data for media planners to make a sound and well-informed decision during their planning process. It’s no wonder that media planners rely on their own intuition since there’s little data available for the average planner.

Here’s a classic example. A media planner must develop a consideration set – a list of the best sites and networks to be considered for the campaign. In most cases, they turn to research tools like ComScore or Nielsen as well as reuse the same sites from previous campaigns.

So, what’s wrong with that?

Although these research tools can definitely identify which sites are most relevant for the campaign’s target audience, they cannot predict or tell how these sites will actually perform. Sure, the planner can pull some data from the last campaign but it’s not enough to make a calculated decision. So, the planner ends up making an important decision with a huge impact on the bottom line, while seeing only a small portion of the big picture. Not good. 

As if making uninformed decisions while creating the consideration set aren’t bad enough, it gets even worse during the negotiation stage. Ask a media planner how much he/she spent for a certain site, section or placement for a recent campaign or even over the years, and you’ll probably get a puzzled stare back. So can the media planner negotiate anything without historical data or any sort of baseline? Not really. The planner just ends up negotiating blindly.

Can you see how absurd this is? We work within a highly innovative and data driven space that offers advanced algorithms to manage real time bidding (buying) for non-premium buys and laser-like targeting to match the right message to the right person, yet when it comes to premium buys (which still constitute the vast majority of the ad spend and stand at the core of the media agency work,) critical decisions are still made based on gut feeling, intuition and who knows what else.

There is no reason why premium buys cannot be data driven as well. In my opinion, a standard planning procedure should always include few success metrics that will be defined based on historical campaign data (I would recommend using a primary success metric and one or two secondary success metrics). These success metrics should be used as a compass to make any decision during the planning process for an upcoming campaign.

So what goes into these success metrics?

Success metrics can be performance oriented (clicks, conversions, etc.) or engagement oriented (dwell time, interactions, etc.) and they should be based on historical campaign data. When combined with the reach and site centric data from research tools like Nielsen and ComScore, these success metrics can help the planner focus on relevant sites, prioritisation and building optimal site list (a.k.a. consideration set) for the campaign.

For example, when Nielsen spits out a report with 50 relevant sites for the campaign’s target audience or when ComScore includes a list of most visited sites in a certain site category, the planner should use the success metrics to filter and prioritize these lists. Which of these sites will perform well against the success metrics? What is the expected performance compared to the industry benchmark for the vertical and/or region? The planner can combine these puzzle pieces together and finally see the bigger picture.

Sometimes, contextual relevancy and publisher’s brand can play a factor in the media buying decision process, but there should be no site on the media plan that is not going to meet the planner’s success goal. Sometimes, the advertiser will specifically request a certain site because A) the site is a category leader, B) it makes sense, C) the CMO expects it, D) all of the above. In this case, the planner’s job is to use the relevant data to backup the decision not to choose the specific site and convince the advertiser that even though the site might seem relevant for the brand and target audience, it is not going to drive the desired performance and/or ROI. That’s a bulletproof argument that no rational person can dismiss.

The success metrics can also include cost metrics (e.g. CPM, CPC, CPA) which obviously are very important for any campaign planning. What’s less obvious is how to factor in the cost metrics . Too often, pricing is ignored until the negotiations phase or used as the only criteria during the planning stage. Both are bad options.  What the planner should be doing is evaluating sites based on a combination of the site’s relevancy (using audience composition and site centric data such as unique visitors) and the site’s expected performance and expected price (using historical campaign data).

Historical pricing info is specifically important for the planner during the negotiations phase with different publishers. This is a no-brainer but too often it doesn’t happen. The planner needs to evaluate the publisher's suggested price against historical performance or engagement benchmarks and know the average price paid for previous placement and/or package. The media planner should also not be shy to find out the average price that his/her colleagues at the agency paid. Once the planner has this historical data, he/she needs to use it to evaluate the proposal. If the proposal is more expensive than the historical benchmark, the planner has two choices: either go back to the expected performance data (again, focus on your success metrics) and justify the higher price or negotiate the price down. There is no way around it. If the planner doesn’t do this, he/she will just end up negotiating blindly.

To apply all the above into the planning process, media planners need easy access to the historical data and the appropriate tools to effectively use this data. It wasn’t always like this and it doesn’t have to be. We can make the change. And, by we, I mean any company in this space with historical data relevant to the premium buying space – be it performance data, engagement data, brand data or pricing data. Data is not only important for audience network buys or exchange buys. It is highly important for premium buys as well and at the end of the day, most of the online media spend still goes to premium media and will remain so in the near future.