It’s another matter entirely when it comes to Out-of-Home (OOH) methods of advertising, like billboards, street furniture, and more. How much of a lift in foot traffic at a given store can be attributed to a particular advertising campaign or a specific ad?
OOH requires a unique method of measuring the impact of physical advertising in public spaces on in-store visitors. Ubimo’s unique methodology accounts for evaluative errors that have made OOH lift measurement challenging and inaccurate until now. For example;
Error #1 – Disproportionately representing “active” devices
Location intelligence platforms tend to be biased toward active users, and ignore passive users, skewing results.
Error #2 – Not accounting for “regulars”
Many people who see a billboard will visit the advertised store because they would have anyway, and not as a result of seeing the ad. Ignoring locals/regulars can inaccurately inflate lift.
Error #3 – Lack of accurate control group timing
In order to truly measure OOH-influenced lift, a control group observed prior to the campaign is necessary to compare with campaign visitation numbers.
These errors and more can render lift data completely inaccurate and useless. Here are just a few examples of Ubimo’s lift measurement vs traditional methods that commit these errors: