In a release this week, Turn publicly highlighted its relationship with ad holding company IPG’s buying platform, Cadreon, as well as new media planning tools integrated into the Turn platform for bid forecasting and audience extension. Read more.
Bill Demas, CEO of Turn, discussed updates to the Turn buying platform.
For Turn’s platform, why are media planning tools becoming a requirement in addition to media buying tools?
Media planning has always been critical. However, as publishers employ auction marketplaces for display advertising inventory, traditional planning strategies and tools – based on the concept of guaranteed, up-front buys – used by agencies and marketers were no longer effective. Traditional planning tools can’t forecast availability for custom audience segments, cannot recommend what new targeting strategies should be employed, nor provide pricing estimates to win bids for impression in real time in a word where there are no guarantees of delivery. To be successful in this new world of display, media pros need real-time insights to be fully informed.
Turn’s new bid-forecasting and audience extender tools empower agencies and marketers to test various buying scenarios against targeted audiences in an effort to reduce media waste. From the Turn platform, planners clearly see how their targeting and bid price choices affect audience reach, optimum frequency, and bid estimates on inventory across every real-time ad exchange. These new tools give them the power to play “what if” as they find the optimum bid and targeting strategy.
Can Turn platform clients bring their own data and then use Turn to create look-alikes in the planning process? If so can you share a use case of how this might work?
One example of using look-alike modeling is identifying consumers who have successfully converted for the advertiser over the past 90 days, and using the ‘audience extension’ tools, create look-alike audience segments that find more consumers who look and behave like the advertiser’s existing audience. Thus, media planners can use these new insights to pick and choose which look-alike segments they want to use, and leverage the bid forecasting tools to find their preferred balance between increased audience reach and predicted performance. With just a few more clicks, the planner can launch a campaign targeting the new audience, while excluding any consumers who have previously converted for the advertiser.
A more sophisticated example would work in a similar way, but start with consumers who have not only converted for the advertiser over the past 90 days, but who are also known to have been in the advertiser’s top loyalty program tier at anytime in the past three years. This would dramatically refine the audience that the look-alike modeling will be conducted against, leading to a smaller, but potentially much higher value set of consumers to target.
Let’s also note that agencies or marketers with high volume data can derive further benefits by using their own data to help power the look-alike modeling itself. For example, if an agency has identified through its own clickstream data collection and modeling a range of demographic and behavioral data points on consumers, that proprietary data can be utilized like any other 3rd party data source to build new look-alike audience segments.
How do you merge planning with “real-time”? Is it possible to plan for a real-time marketplace?
Auction marketplaces are very powerful because they allow agencies and marketers to bid a different price for every individual ad impressions in real time. Yet, this requires tools that provide real-time insights for fully-informed decisions — before the first impression is ever purchased. Another challenge for agencies or brands is the fact that there is no ‘guarantee’ of delivery. Other buyers are also bidding for the same impressions, so the pricing and availability for any one impression can change in real-time.
Turn’s planning tools utilize deep data mining to look at the history of which consumers and impressions have been purchased on the exchanges in the past. Using advanced data mining and statistical analysis techniques, the platform is able to provide the customer – whether media planner, executive, or someone else with a forecast of audience reach, impression volume and consumer frequency at different bid price points. Planners can then leverage this data in real time to evaluate whether different targeting strategies under consideration will have a sufficient audience, and whether a given budget goal can be achieved. If the audience or impression volume is NOT sufficient, the media planner is able to use the audience extension tools to adjust their strategies accordingly and again, design successful campaigns BEFORE the first impression is served.
By John Ebbert
