Q Thoughts

ownerIQ's staff (aka – "The Q") shares our insights and opinions on how marketers can more effectively impact today's shopper along the digital path to purchase. "The Q and A" provides honest and practical answers to the questions and challenges facing digital advertisers in the areas of second-party data, programmatic buying, shopper marketing, co-operative marketing, attribution, and emerging media.

ownerIQ’s solution for optimization hurdles

 

In today’s digital landscape, marketplace bidding and optimization see challenges in efficiency, data sourcing, and limitations on lookalike modeling. Further, the way algorithms learn and optimize a campaign can be quite opaque, leading to little understanding of how the technology can help a client.

ownerIQ has a different approach. Our partners provide us with 100% audience transparency, allowing you to see into the data and understand exactly who you’re targeting. We’ve found that the best predictor of shopping and purchasing behavior is shopping and purchasing behavior itself, which we house for activation in CoEx, the largest and most transparent Second-Party Data Marketplace in the space today. Our advanced reporting suite shows the efficiency of our algorithms by showing the product and brand affinities of converting users.

ownerIQ’s optimization philosophy revolves around the idea that algorithmic adjustments enhance the ability to evaluate and respond to data points. Our technology can efficiently crunch data and make decisions at a greater scale than any human mind. To help evolve and maximize our technologies’ capability, the Q always layers on human experts who ensure all technology decisions are executed correctly.

Here’s how it works:

1. Pre-Bid – Ranger & EP Scoring

Ranger is ownerIQ’s bidding algorithm, used to prospect new users similar to those who are already converting. Ranger assigns an Expected Performance score, an estimation of how likely any given opportunity is to convert for a specific conversion tag, to each impression opportunity. While the opportunity is the intersection of the user, associated segments, domain, ad format, and exchange, most of what influences our EP score is shopping behavior.  We engage 220 million shoppers, ingest 2.8 billion shopping behaviors and over one billion dollars in e-commerce transactions. High EP scoring opportunities are nearly 400 times more likely to convert than an ad served at random.

2. In-Campaign – Performance Optimizer & Manual Optimizations:

Every morning, the ownerIQ Performance Optimizer (PO) algorithm runs across every campaign, looking to maximize conversion rates, CTR, or Unique Reach while staying within the optimal price and pace range for the specific campaign. This feature keeps your campaign running efficiently and to its full potential. What’s more, PO is set up to automatically shift weight between audience types and adjusts Weighted Average Cost of Media Targets (WACMt) to reach the ideal state based on recent performance.

ownerIQ has an entire Delivery Team who specializes in overseeing our programmatic decision-making technology, and can manually assist in campaigns when necessary.

3. Reporting – Touching Light on Algorithmic Optimization:

ownerIQ’s Bidder Intelligence Report illustrates the effectiveness of our technology. Ranger creates EP Scores and assesses impression opportunities, then seeks impressions that align with those signals. The Bidder Intelligence Report shows how effective ownerIQ’s Ranger algorithm was at predicting converters throughout the campaign.

Additionally, ownerIQ’s Retail Overlap Report illustrates ownerIQ retail partners that are indexing high against an advertiser’s audience. It provides a view of the opportunities that exist within ownerIQ’s platform.

Finally, with ownerIQ’s shopper audience insights, we are able to identify the precise shopping and purchasing behaviors that ownerIQ’s technology is basing its bidding decisions on.

 

For more information about how ownerIQ’s optimization tactics can boost your campaigns, get in touch today.


Categories:Posts from 2017


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