The Data-Driven Agency

Today’s digital media agency has access to enormous amounts of data, but using it effectively is what is going to make the difference between the shops of the future and the also-rans. Delivering data-driven insights is the key to being a 21st century agency. Here are three ways you should be working with data to secure your future:

Visualize It

How much time are you and your colleagues spending collating data, building reports and formatting spreadsheets and PowerPoint decks for your clients? Most of the agencies I have worked with over the years admit to dedicating an embarrassingly large amount of (highly expensive) time towards these menial tasks. While getting the data to your clients is very important, there are now automated ways to deliver it without burning valuable funds or time.

To paraphrase former agency head and Akamai leader David Kenny, if you are doing things with people that you can be doing with computers, you have already lost. Why spend time formatting Excel spreadsheets and populating PowerPoint report templates with data, when you can be spending salaried employee time selling more services, optimizing campaigns and delivering great strategy and creative content? Today’s automated ad management solutions and digital monitoring products (DMPs) offer powerful ways to synthesize both audience- and ad-serving reporting data into a single interface to get instant access to key metrics, such as frequency to conversion, churn rate and channel attribution.

Ask yourself if the cost of such a system is more than the cost of the time you or your employees have been spending building reports — and, ultimately, more than the cost of your eventual demise, should you ignore changes afoot in your business.

Aggregate and Activate It

Think of all the data you have access to from a digital media standpoint. If you are helping clients execute a digital media campaign, you have traditional serving data from your demand side server, such as DoubleClick for Advertisers (DFA). You probably also have engagement data from your rich media ad server. If you have access to your clients’ website pages (or at least tags there), you have site-side data, including conversion event data. If you are using an audience measurement tool, or are doing audience-specific buying through a demand side platform, you also have audience measurement data. Great. What are you doing with all of it? Moreover, what kind of data does your client have that you can help them add to activate the common advertising data types described?

Let’s take the example of an agency using an audience measurement reporting tool, alongside an ad server report. In this case, it is possible that the analyst knows that the highest frequency converters for his travel campaign belong to a popular Potential Rating Index for Zip Markets (PRIZM) segment, and he may also know that visitors to a popular travel site are three times as likely to engage with his rich media ad creative. Now what? Obviously, the right move is to buy more of the audience segment and double up with guaranteed advertising on the travel site. But what about audience overlap?

How can the advertiser reduce ad waste by ensuring that members of his audience segment, that he is securing for as little as $2.00 cost per impression (CPM) on exchanges, are not overrepresented on the premium site for which he is paying $18.00 CPM? Plus, how many members of that audience are also already registered as customers? If you are not deploying a DMP to aggregate your clients’ CRM (first-party) data alongside the site-side and ad serving (second-party) data and the purchased (third-party) data segments, then there is going to be lots of duplicated uniques in your audience. Smart data aggregation creates ad activation through waste reduction, lifting conversion rates, while lowering cost per conversion. Getting an effective universal frequency cap across digital channels is very difficult, but every dollar not wasted on duplicate impressions is another dollar that may be spent finding a new audience member. Reducing waste adds reach — and performance, which every client likes.

Compare It

As a digital media agency, you’ve run hundreds, perhaps even thousands of campaigns, producing thousands of data-rich reports for your clients. How much of that knowledge are you leveraging? Although you might know the top travel sites and audience segments to reach “moms of school-age children in-market for a beach vacation,” how readily available is that knowledge? Is it sitting inside your media director’s head or is it hidden in various documents that don’t talk to one another? How about access to normative campaign data? How quickly can you find out how certain sites performed against similar key performance indicators (KPIs) without doing hours of research?

Like it or not, advertisers want to know how their campaigns are performing against known standards, and lately, it’s gotten a lot more complicated than beating a 0.1% click-through rate. From knowing how your last 10 travel campaigns performed, to which guaranteed site buys succeeded, to which audience segments performed, to which creatives elicited the highest CTR...this is just step one. Having that data available for quick reference means that every new campaign can start from an advanced performance level, and your media people don’t have to recreate the wheel every time you receive an RFP.

Today’s smart DMPs also feature the ability to leverage your data to an even greater extent, especially for audience buying. Why limit yourself to pre-packaged audience segments that do not include your client’s first-party data? Today’s more advanced DMPs give marketers the ability to create audience segments on the fly, building discrete segments from data that includes available third-party data — but also first-party data, such as registration details, transactional records and signals from hosted social media listening solutions. It’s the difference between buying from an ad network and creating your own.

Summary

Buying into portals’ site sections was the first phase in the effort to bring contextual and audience relevance to ad buying. Networks followed, offering packaged audiences at scale. Then bidded exchange buying came, offering pre-packaged audience segments at the individual cookie level. Today’s best practices include marrying all available data types to give marketers the ability to create their own targeted buys, and modern data management platforms are helping the largest advertisers automate what they have been doing since the first direct mail piece went out: finding targeted audiences. Leveraging today’s DMP technology can not only help you find those audiences more easily, but help you understand who they are, why they respond and help you find them again.