Smart Planning on the MediaMind platform centralizes your historic performance data, publisher proposals, budget parameters and historical costs into one interface and allows you to make smarter media buys at a lower cost; eliminating inefficiencies in the planning and buying process. This entertaining video outlines the pain points facing media planners and demonstrates how Smart Planning simplifies and contributes to the planning process.

Let us know what you think.

Data visualization is one of those tools that today’s marketers need in order to quickly gather insights and make decisions. Data visualization is the last step in the process of transforming bits into knowledge. It is the result of the amazing alchemy process of our digital age.

We rely on reports and data to make decisions for the future and if we fail to represent the data properly we could end up making the wrong decision or missing out on a great opportunity. Also data visualizations can help us understand complex problems in a more familiar, easier way to digest.

These tools are also presenting the data with context that support and complement the actual data points we are visualizing.

Let me illustrate with an example. One of my favorite data visualizations artists (yes it is a bit of an art!) is David McCandless. He and his partner Stefanie Posavec recently won a contest to change the way we look at a blood test results. The contest was organized by Wired magazine.

Here is the original:





Here is their inspired re-design:





The difference is night and day. On the second report it took me all of two seconds to realize that I need to exercise more and go on a diet!


When we look at the advertising industry and the reports we present today, we often do not present the data in an optimal manner.  As in the blood test example, we collect a wealth of data, which if combined together can lead to real learning and media optimization. It is our responsibility (and also my job!) to transform how we present the data to our clients.

Data Visualization is not a “nice to have” or a “cool/wow thing” it is a fundamental tool to understand and digest a wealth of complicated, connected information. It can make all the difference between a strategy’s success and its failure. 



Pablo Cohan | Manager, Product Planning and Data enthusiastic

Seventy-three percent of US companies in 2010 reported that they see social media as a powerful marketing tool for creating a dialogue between them and their customers, according to eMarketer. In 2011, eMarketer predicts that social media will become the third most popular marketing tactic after the company’s website. And yet, only 46% of those 73% see the need for an analytical framework to measure the profitability of their investment in social media, and even a lower percentage reported knowing how to measure it.


Ideally, companies should focus on measuring ROI of Social Media investment. Nevertheless, measuring the benefits of a social media campaign should not be limited to a single campaign. Companies also need to take into consideration the long term business value and effect of social media.


A unique approach for quantifying the financial returns of social media was presented in an empirical review by Syncapse “A Value of a Facebook Fan”. In this research, Syncapse calculated a monetary value of a facebook fan by dividing the incremental effect from becoming a fan to five factors:


1. Product spending
2. Brand loyalty
3. Propensity to recommend
4. Brand affinity
5. Earned media value

The authors of the study found that Loyalty is a good indicator to a marketing and product performance, while Word-of-mouth is considered to be extremely credible as a sales driver. Furthermore, Affinity to a brand can be linked to a long term company’s success and drive repeated purchases. All those found to be significantly higher in a group of facebook fans than in customers who were non-fans.


To construct the valuation, Syncapse combined those 5 variables as part of an equation that calculates a fan’s value, by statistically linking them with business and monetary results. The study found that a facebook fan spends incrementally $71.84 more per year on the brand, as compared to non-fans. However, considering also the long term effects of being a facebook fan of revenue, Syncapse concluded that the overall value is as high as $136.38 for the fans of the 20 brands that participated in the research.


Nevertheless, $136.38 cannot be used for all brands across the board in ROI calculation, since brands differ in factors such as purchase frequency, brand strength, and fans behavioral habits. However, this approach can represent an informed way of calculating the ROI for social media and measuring the positive impact that fans have on business results.




Lena Berenstein, Research Analyst

I have been busy over the last few months meeting with different agencies and their media teams, speaking with them about their planning and buying process and needs. The main problem that I kept hearing about over and over again was the workflow inefficiency and overhead that goes with the planning and buying premium media buys. I was quite surprised by that. Well, to be more precise, I was surprised to hear only about this issue.


When you speak with the typical planner about her work while planning and negotiating her premium media buys, you definitely realize how heavy and inefficient the process is and how it leads to sub-optimal media plans and campaign results. But there’s also another problem, a subtle problem that might have even a larger negative impact on the media plan and campaign results. I am specifically referring to the lack of available data to support the planner’s decision making.

 When you ask the average planner which data she uses for planning media buys and negotiating rates, you realize how little data is available for the planner and how much it’s dependent on intuition. Here’s a classic example. One of the tasks that a media planner needs to complete is developing a consideration set – a list of the best sites and networks to be considered for the campaign. In most cases, this task pretty much ends up in pulling few reports from research tools like ComScore, Nielsen or Quantcast as well as reusing sites from previous campaigns. So, what’s the problem with that? These research tools can definitely tell the planner which sites are most relevant for the campaign’s target audience, but they can’t tell her how these sites are going to perform. Sure, the planner can pull some data from the last campaign – but is this 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.

 An even more problematic example is the way negotiations are conducted. Ask the typical media planner what was the average price she paid for a certain site, section or a placement over the past few campaigns or year and you’ll get a puzzled look. Don’t even bother asking her if she knows how much her colleagues have paid for the same media buy in the past – there’s no chance you’ll get an answer. So does the planner have any chance to effectively negotiate anything without historical data or any sort of baseline? Not really. The planner ends up negotiating blindly. Very bad.

Can you see how absurd it is? Here’s a highly innovative and data driven space that offers advanced algorithms to manage real time bidding (buying) and laser-like targeting that matches the right message to the right person, but at its core decisions are still made based on… gut feeling, intuition and who knows what else…


All of this is not really the planners’ fault. Planners need access to the relevant historical data and the appropriate tools to properly plan media buys – sites’ historical performance and engagement data to forecast site’s performance and pricing data to effectively negotiate rates.


So, what I’m  really trying to say is that it’s time we start answering the data needs for planning and negotiating premium media buys in addition to improving their workflow. Data is not only important for audience network buys or exchange buys. It is highly important for premium campaigns as well. 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.




Ronnie Lavi | Senior Manager, Product Planning

Search is a mature (if not stagnant) market where a handful of foolhardy entrepreneurs exist in the shadow of entrenched mega-corporations, surviving on meager leftovers like remora on a shark. Right?

Most people would bristle at the thought. But wait — name five search engines. Except Yahoo doesn’t count – that’s really Bing, except in Japan, where it will be Google. Similarly Ask.com is out. So is AOL. Let’s also (unfairly?) rule out Baidu and Yandex, since few people use them for English-language searches.

Did you get five? I couldn’t.

Cuil burned through $33 million (and a lot of talent) in two years before shutting down. Wikia Search couldn’t crowdsource the strength to survive. (You listening, Blekko?) I’ll credit Wolfram Alpha for some nerdy appeal, but it’s about as mainstream as Mathematica.

What happens now?

One thing I’m certain of is that search has a future – the status quo can’t last much longer. If you know the name Schumpeter, you can guess why: discontinuous innovation. (Fine, he called it “creative destruction”.) Technology strengthens and solidifies to a point – and then something entirely new comes along and levels the playing field once again. Search is up there with the San Andreas fault in being overdue for radical change.
I’m excited because we’ve caught a glimpse of what’s ahead — for traditional, non-social, knowledge-based search — from a startup called Qwiki.

Qwiki is in “alpha” right now (in other words, it’s very clunky) and previews have all the appeal of Microsoft Sam reading you a Wikipedia page. I’m not sure Qwiki will be able to pull it together, but let me explain this vision before you take a look yourself.


Every web search begins with a question. When did Samoa join the UN? How tall is Natalie Portman? And so on. In turn, (almost) every web search is not really answered but directed, as if to say “maybe this can help!”. Even sites like Ask will point you to existing answers.

That’s great when you’re in a virtual hunter-gatherer mode, but what if you just want a straightforward answer? Say a search engine managed to collect data across the web and integrate into a coherent and addressable whole, like an encyclopedia as big as the Library of Congress. Now it can answer your question itself.

But will it? Wolfram is amazing when it comes to answering questions about the natural sciences. (How many protons in a water molecule? Ten.) Qwiki promises the same for more important topics, like Natalie Portman. But even if Qwiki has the knowledge, it doesn’t yet have the smarts. I can’t ask how much Natalie weighs, much less how many protons she has. (A rough calculation assuming she was made entirely of water: 1.73 x 1028.) As it stands, Qwiki is like Admiral Ackbar from Return of the Jedi, only offering a visually-aided overview on the basics of topic. (“You can see here the Death Star orbiting the forest Moon of Endor…”) Still, I’m sure we’ll get there eventually.

Back to reality. What does it mean for advertising when Qwiki (or its progenies) is smart enough to understand my lunatic questions?

As you can imagine, one big change begets another. When search transitions from “what about this?” to “here you go!” so does that precious moment of vulnerability, where consumers are more suggestible than ever. Instead of sponsored options, we might see sponsored answers. Assuming consumers demand a basic level of objectivity, this suggests we’ll return to the vintage days of product placement. In other words, brand advertising! Pepsi Max will just happen to be the diet cola Natalie is drinking to maintain that marvelously low proton count.

So as search moves from suggestions to answers, it becomes less of a transaction and more of an experience, and in turn supports brand advertising instead of direct response. Do you see it happening? Feel free to let me know in the comments.



Bryan Melmed | Product Planning Manager