Behavioral Targeting: Manifestation of Accountability

Behavioral Targeting: Manifestation of Accountability By Heath Podvesker, VP Client Services [x+1] Behavioral targeting, specifically with regards to the audience optimization process, opens a new level of accountability in the marketing space. It makes agencies accountable to their clients and for clients to be accountable to their customers. The audience optimization process adds much needed rigor to the assessment of marketing success, forces transparency in reporting and creates a living view of customer intent and behavior. On-site and on-line media audience optimization uses testing to create a process of measuring marketing success: it's difficult to deny the realities of lift over control. Moreover, optimization uses additional measures that force the assessment of on-line creative elements (call-to-action, offer, value proposition, graphic design and media selection). The testing process also increases the level of transparency in reporting because the collaboration between client and agency should force the review of measurement and reporting practices. In addition to all of these hard measures, an increased understanding of the customer that goes beyond just focus groups and surveys is realized: it show how they react and interact with online communications and web properties - in short, it is the customer affirming what is good and bad and what is relevant to them. Recently, [x+1] had an engagement with a large telecommunications company regarding the optimization of their home page and product section page's creative assets. This resulted in a 38% improvement in orders placed. The optimization was set-up as a test where we ran our optimization (the experiment) versus business as usual (the control). What we learned was that the creative that was previously thought to be effective was not and that the segments that were designed around business rules (and supported by corporate culture) were not reflective of the customer base. The team's work was suddenly accountable to customer actions in real time. The results were that the creative assets evolved from a prominent photo and small text to creative that had a strong value proposition and offer. In addition, segmentation moved from the conventional approach of business rules to a sophisticated model. The model was predictive of actual customer behavior which allowed us to optimize based on conversion results using incremental orders as our measure of success. Each segment had their 'favorites' that were at times shocking to the team. Testing put the control in the hands of the customer and we were accountable to their desires. In addition to testing, optimization increases accountability by leveraging indexes that most marketers are not accustomed to. The conventional approach is to look at CPA, CTR and response rate to judge success. These measures can often be misleading because an ad or piece of on-site content that has a low cost per action may not be delivering strong value. An index that has been successful is VPM or Value per Thousand. Value per thousand is an index that measures the monetary value of an ad in relation to other ads it is running against. For example, the below chart, the offer (#4) that delivered the highest click through rate (CTR) delivered little value while the ad (13) that had a less then stellar CTR demonstrated the strongest value: New Registrant Existing RegistrantOffer ID CTR Offer ID PC SR Offer ID PI SR Offer ID PC SR Offer ID PI SR Offer ID VPM4 99% 12 0.0004% 10 0.0030% 14 0.0002% 17 0.0040% 17 $ 1.777 82% 14 0.0003% 17 0.0029% 11 0.0001% 18 0.0035% 18 $ 1.489 82% 13 0.0002% 6 0.0029% 10 0.0000% 16 0.0034% 16 $ 1.451 78% 11 0.0001% 15 0.0029% 2 0.0000% 2 0.0033% 15 $ 1.458 67% 17 0.0001% 3 0.0028% 17 0.0000% 5 0.0033% 13 $ 1.4314 1% 16 0.0001% 21 0.0028% 19 0.0000% 15 0.0033% 10 $ 1.4312 0% 18 0.0001% 18 0.0027% 6 0.0000% 10 0.0033% 3 $ 1.4011 0% 3 0.0001% 11 0.0027% 3 0.0000% 13 0.0033% 6 $ 1.3717 0% 2 0.0000% 13 0.0027% 18 0.0000% 3 0.0030% 11 $ 1.3610 0% 20 0.0000% 14 0.0027% 13 0.0000% 6 0.0030% 2 $ 1.3221 0% 15 0.0000% 16 0.0026% 1 0.0000% 21 0.0030% 21 $ 1.292 0% 10 0.0000% 2 0.0025% 4 0.0000% 11 0.0029% 14 $ 1.1815 0% 6 0.0000% 19 0.0022% 5 0.0000% 20 0.0026% 19 $ 1.0816 0% 21 0.0000% 20 0.0020% 7 0.0000% 14 0.0026% 20 $ 1.036 0% 1 0.0000% 5 0.0019% 8 0.0000% 19 0.0024% 5 $ 0.9618 0% 4 0.0000% 12 0.0012% 9... [download for more]