Marketers understand that consumer data, both their own and that available from third-party vendors, is rich with potential to guide effective online advertising efforts. But the challenge is determining what type of data is right for your campaign or brand and whether it’s really delivering value. The good news is, with advanced capabilities of real-time bidding through a demand side platform, data can be better understood and put to work more effectively for display campaigns. Before getting into “how” to best test and learn about data tactics, let’s first review “what” types of data are available.
While the industry is abuzz about so-called third-party data from specialized brokers, it’s worth emphasizing the primacy of a brand’s own data. Such first-party data is a by-product of online and offline marketing efforts, transactions, and CRM (define) systems. Major sources of this data are ad servers, Web sites, and customer histories from back-end enterprise systems:
- Ad server: Site context, frequency, clicks, and view-throughs for ads served – the kind of data used to report on and optimize a campaign.
- Web site: Page visits, referral URL, offer type (e-mail, print ad, etc.), site engagement and conversions (downloads, purchases, registrations), etc. – the kind of data used for retargeting campaigns.
- Customer: Purchase habits and history, loyalty programs, and response to offers. Direct customer data is often used to define characteristics of desirable consumer segments to target.
The starting point for successfully using data to drive your marketing efforts is collecting, organizing, and analyzing your brand data. But there are well-known challenges to doing this: the data resides in different silos maintained by various vendors and corporate functions. Moreover, while recent enterprise data warehouse initiatives have succeeded in creating better integration and reporting of historical consumer information, they struggle to operate in the real-time context increasingly required for online marketing success. And most marketers lack tools and expertise to use their data to predict and optimize marketing activities. Advanced data analytics vendors, some of which offer integrated real-time bidding systems, are overcoming these challenges, finding innovative ways to put first-party data to use for their clients’ campaigns.
In addition to first-party data, marketers often turn to sources of third-party consumer data to help inform their marketing efforts. Ideally, the two types of data are used together for best results. Third-party data generally falls into two categories: 1) traditional data used for offline direct marketing and segmentation, which is very user-specific, but not readily addressable online, and doesn’t convey current intent, and 2) online data, which is highly intent based, but often lacks granular transaction and economic data. Within these two categories, the primary types of third-party data include:
- Intent data (e.g., BlueKai, eXelate): Based on recent display or search activity, this type of data is very specific, often indicating an imminent consumer purchase or action.
- Unique personal data (e.g., TARGUSinfo, Experian): This data includes specific consumer contact information and other unique personal identifiers.
- Other (e.g., Bizo, Equifax): Both traditional and online data are used to identify consumers by personal interest, profession, credit profile, etc.
Sizing Up Your Data’s Value
With the many types of data available, deciding which ones are best for your campaign isn’t easy. Start by using a tool to help you understand the value of your data, then layer in third-party data to understand the incremental value. The question of value is best answered after the data has been tested, and there are actual campaign results to analyze. Here are some considerations to keep in mind when evaluating your data’s impact:
- Coverage: What is the reach of the data? How many users does it cover for your desired segment, and is it enough to matter for your goals?
- Cost: If you look at your campaign’s ROI (define) based on the all-in cost of media plus data versus media alone, is your ROI still healthy? Ideally, marketers can determine the incremental ROI value of data and any optimization to their eCPM by comparing results to a control campaign CPA (define).
- Quality: Did the data help deliver the desired types of consumers? Direct response marketers can generally determine this based on campaign performance. Brand marketers often rely on post-campaign research to measure the qualitative value of data.
Real-Time Bidding Makes Data More Powerful
Given the many variables in any campaign, the value of data can vary from one campaign to another, but the emergence of real-time bidding through demand-side platforms can offer additional ways for marketers to apply the data. These include cookie segment targeting, use of first-party data to inform bidding, and audience extension that combines both techniques.
Real-time bidding can also significantly enhance the value of your data, in three key ways:
- More opportunities to reach your segment. The larger audience offered through ad exchanges, or better still through demand-side platforms that look across them, means a greater likelihood of reaching desired consumers and messaging frequency.
- Better targeting of segments. The optimization advantages offered by demand-side platforms, in combination with the impression-level pricing of real-time bidding, can make finding and buying your segment more cost-effective.
- Global frequency control. If you are targeting similar segments on several ad networks, chances are, you may waste impressions serving your ad to the same consumer more often than you intended. Demand-side platforms that can provide global frequency capping across impression sources eliminate this issue and allow you to spend your budget more effectively.
Taken together, real-time bidding and advanced demand-side platform optimization capabilities offer exciting possibilities for marketers to unlock the value of any data they possess and target their desired customers with much greater precision.
Advertisers are more concerned than ever about brand safety, and one of the primary ways they're trying to keep their ads from appearing in unfriendly places is through whitelisting. But as more and more brands turn to whitelisting, some are talking about the impact this will have.
We all know that Facebook is a viable source of huge amounts of mobile traffic with relatively cheap CPCs). It’s too good an opportunity to ignore in today’s digital landscape - even if your mobile landing-page experience isn’t up to snuff.
For years, advertisers have tolerated a big elephant in the room: the fact that their digital ads aren't always appearing where they would want them to.
Deep learning tools are the next major area of AI-based research, and it will spark a wave of future innovation in every industry – bringing a new era of marketing which both advertisers and end-users will benefit from.