Today, brands that use advertising to drive people to physical locations are demanding deeper insight into how effective their campaign strategy is. However, there are several confusions that hold brands back from the benefits of an offline attribute which is the ability to measure behaviour in the physical world. Below are some of the myths in Location Data:
- Inability to distinguish consumers that visited a store and those that passed nearby
- A small sample of a dataset will not be able to represent your target audience
- Media Exposure must be tied to specific devices to enable omnichannel measurement
- Sales data gives better insights than location data
- Location data equals to retargeting
60% of location data collected from mobile devices are too broad or inaccurate for store-level precision.
Truth: There are two modes in which location data is collected:
- Dense - When a user gives permission for data to be collected continuously, store visits will still be recorded even though the app is not opened.
- Sparse - Store visits will be recorded only when the app is opened as the user only allows data to be collected when the app is in use.
Marketers can still differentiate between someone inside a store, on the sidewalk or inside the store next door because we can weed out erroneous data with the right filters while maintaining the scale needed for the audience measurement. These filters enable marketers to get accurate actionable insights.
For meaningful insights of the target audiences, marketers need to make sure the measured audience is representative enough and large. A small panel of users will likely bring a bigger margin of error. Selection bias is also one of the concerns in which marketers believe that if the demographics of the target audience do not match the provided offline response data, they will get inaccurate metrics.
Truth: Marketers can still look for location data providers that have enough scale to gather behavioural data from all the consumers that served their ads. This sample population is large enough for statistical significance and diverse enough to create precisely matched control groups.
Comparison across publishers is hard, as most solutions handle offline response tracking differently for each channel of mobile, desktop, and TV. The problem of tracking users across different channels has created limits on understanding how each media channel is performing.
Truth: Weighing the effectiveness of mobile, desktop, and TV campaigns against each other is a major priority for marketers. To enable omnichannel measurement, tying up media exposure to a specific device is not necessary as marketers can still match device IDs to individuals and households. Establishing this connection allows the comparison of how different the media combinations influenced consumer behaviour to take place.
There is still a lot of marketers who believe that sales data is the sole indicator of campaign effectiveness.
Truth: Location data can reveal insights that are not visible with sales data alone, such as consumer behaviour and movement pattern. The data volume of location data is massive and substantially larger than any other sample data set.
Having the capabilities to retargeting devices that have been into specific venues definitely help increase the return on investment of a campaign significantly. This is true but many have been misinformed about this is the only way they can benefit from location data.
Truth: Location data can also be leveraged in several other ways, other than retargeting, such as:i. Attribution
ii. Audience modelling/Segmentation
iv. Foot traffic analysis
With the advancement of new technologies, confusion and misinformation among marketers are bound to happen. These confusions are legitimate reasons why some marketers have been sceptical about adopting location-based measurement. But, once we can sort out fact from myth, location data undeniably opens up the door to powerful new campaign insights. Thus, we have to make full use out of location data.