However, the underlying technology needs for accurate location intelligence are exceedingly complex. Like a Russian doll, there are multiple layers beneath the surface -- all working together to collect and interpret massive amounts of data, and determine the best way to deploy intelligence in a dynamic and ever-changing world.
Admittedly, new technologies are inherently complex. Their norms have not been established, and standards compete for consensus. One recent model we've taken note of is Cost Per Visit (CPV). On the surface, it seems like a simple way to use location. But when you peel back the layers, there's a lot that is unclear.
What is CPV?
CPV is a new metric that aims to charge advertisers only for new store visits that are driven by media, and so increase the efficiency of an advertiser's spend. Some companies are testing these waters. Pokemon Go, for example, recently cited CPV as a way to charge advertisers for sponsored locations. While CPV may be applicable for specialized gaming applications, there are many challenges to overcome before it can be reliably used as a transactional metric for standard advertising. For now, if you are evaluating CPV, here are three important things to consider:
1. Panel projections are used to measure visits. You are not paying for visits, you are paying for projected visits.
Current CPV offerings use panel-based projections to validate visitation measurement. While fine for directional insights, small panels aren't ideal when projecting a precise number of visits for locations. This is because panels only measure a very small portion of all visits; the rest of the measured visits -- visits that advertisers must pay for -- are only assumed to have happened.
2. Projections account for a majority of the visits a media company takes credit for, representing between 99.5% and 99.7% of reported visits.
Think about it this way: If 1,000 people view your ad, standard campaign panel match rates (we've seen between 0.3% to 0.5%) means that about 4 panelists (out of the 1,000) will see your ad. If only 1 out of the 4 panelists visit your store, the other 996 ad viewers (nonpanelists) would be assumed to visit at the same rate (25%). This means you would be charged for 250 visitors, even though only 1 was measured as a visitor.
This can be a game changer, especially considering the cost may vary for advertisers, depending on the consumer's purchase potential. For example, a specialty retailer with high-end goods will likely pay more per visit than a fast food chain, with a lower price point. This all boils down to an alarming thought: the current CPV model charges advertisers for assumed visits, and at a rate that is determined by assumed purchases.
3. The control group methodology used to calculate incremental visits is flawed, which means you will pay for visits that would have occurred anyway.
To account for an audience's normal visitation behavior (i.e. loyal customers), it is essential to withhold part of your audience from advertising. This is known as a B control group, and is used as a benchmark to measure expected, predictable behavior. True control groups mirror the group who do receive ads as closely as possible -- typically down to the DMA and demographic level. In addition, a proper B control group will include previous visitation patterns to isolate the incremental visits driven by your campaign. If someone shops at Kroger every week, it would be disingenuous to credit an advertisement with generating their usual weekly grocery run.
Unfortunately, available CPV offerings do not use well-planned B control groups. This means they are reporting inflated visitation metrics, and advertisers are being charged for visits that would have occurred anyway. Without a proper control group in place to account for this, an advertiser will end up paying for normal visits, instead of incremental visits.
To summarize: with a CPV model as it exists today, you are paying for projected visits, based upon a panel that measures only 0.3% to 0.5% of your audience. To complicate things, those visits likely aren't incremental, and we have no way of determining ad-driven visits since a true B control isn't used.
Would you pay Google for 1,000 clicks, after 3 clicks occurred?
Would you declare the winner of a marathon after 138 yards?
While one day a proper and accountable CPV system may exist, the structural realities of available data are the natural gating factor. As such, marketers should consider CPV to still be in its primitive stages, with many challenges to address before it can be a reliable metric to transact against. For those testing the waters, it is important to dig deep with your vendor, ask questions, and understand their underlying approach. This will enable you to make the best decision for your campaign, your budget and your brand.