Paid search is sometimes only thought of in terms of its ability to link users with purchase intent to the brand or product they’re searching for, but there’s also the opportunity to link searchers with useful content depending on the context in which they’re searching.

I was in Westfield Stratford for the first time ever recently and realised how frustrating this kind of situation is when you’re in a rush to find a particular shop amongst the many that they have. I couldn’t even find a map to help me, but I realised that by understanding the context of my location, marketers had the opportunity to use this information to provide some genuine value.

Wouldn’t it be great if by typing the name of the shop I was searching for into Google, rather than being directed to the generic homepage or similar in the search ads, (by understanding I was in close proximity to a store) it instead offered to direct me to its specific location in the mall and highlighted any current special offers available at that particular store? Google is actually currently testing a ‘Store Reminders’ product, which demonstrates that it’s aware that PPC ads often don’t serve these types of local searches quite as well as the more general.

Some advertisers still aren’t using location as a key method of targeting

The reasons will differ from brand to brand. In the case of hyper local, it may well be because of the nature of their offering. Cafes (particularly the big chains) for example are in a position where their customers are more likely to be at least semi-regular visitors and many have already developed app-based solutions that offer a level of local functionality.

The incentive to download an app that can provide proximity / location based notifications, offers and loyalty promotions for example is that much higher for regular customers than occasional or even one off experiences. Having to download an app also seems long-winded and misses the impact and immediacy that paid search could potentially have in this scenario. The development of beacons and similar solutions may eventually help solve this problem, but they’re not perfect either.

Quite broadly in terms of what is commonplace right now, country level and potentially some city level changes (typically bidding) in paid search campaigns are being made based on the competition and strategy for that location. Changing the messaging in ads based on the offerings for specific markets is also now the norm. There may also be some more granular tactics around specific store locations, but this is difficult to detect as a consumer and certainly not widespread.

The ease of factoring in location data varies by campaign

While it’s very easy to get the raw data and analyse it, how easy it is to actually action depends on the client’s setup, and the type of actions that you’re trying to implement. Making PPC bid changes to specific locations is very simple due to Google Location Modifiers, but changes to the ad copy itself currently requires additional setup. I believe that in the future, Google will realise the benefit of this to consumers and make it more seamless for users to dynamically change ads, ad extensions and bids all together based on location, which will benefit data-driven advertisers.

On an international scale, there are plenty of instances when even locations that speak the same language (take the US and UK) will differ in the specific words and messages that are most effective from a performance standpoint. At the more local level, understanding when I’m searching at home, or just comparing prices while looking at a product in store are also incredibly useful as an advertiser.

The potential utility of location data differs between small and large advertisers

Small advertisers probably have a more local approach already because they need to make the most out of their spend and this allows them to do that by controlling it at a more granular level. They are more likely to also serve a narrower geographic area so can more easily make smaller scale decisions.

If a smaller UK business is looking to launch in the US for example, it can be very targeted and only go after certain states or cities immediately to do more controlled tests rather than attacking the whole of the US in one go. This tactic allows you to minimise the risk associated with entering a new market. Google also currently has a product in beta in the US that will help marketers make informed decisions called Shopping Insights. This product displays demand for specific items using heat maps that reflect the use of specific search terms in particular areas. I might be able to identify that demand for my products or very similarly related ones are concentrated in particular areas, which would make these areas potentially more valuable to me.   

Any industry can lend itself to using location data

The insights into user intent available through location targeting could impact every single industry eventually. Being familiar with the differences in performance across regions is important and the data generated from measuring this will lead you to potential actions that can help optimise your marketing activity. Any business with physical locations should always be looking to take advantage of those by looking at how user intent might change depending on where the users are at the time of viewing your ad.

What advertisers should be doing differently

Break down the barriers they may have with regards to different markets. Of course there are barriers that are tough to overcome like fulfilment / shipping, but allowing multiple currencies on your site and having as many shipping options as possible will allow international consumers to transact on your site. Even if you’re not running any marketing activity in their location, they will find and use your site if the functionality and logistical options are there. This sort of data is critical when looking into global expansion, particularly if the brand will not also be launching a regional website immediately. On a more granular level, they should regularly be looking at performance data and finding outliers, be it pockets of efficiency or inefficiency, whether it relates to an offline location or not.

In an ideal world a business would have a distinct strategy for users based on their location and any other relevant data or signals such as time of day, device. This could then lead to a scenario where a user searching for a brand near a location and within opening hours is offered directions, a user outside of office hours on a desktop is pushed towards shipping options for their market, and a user within a store is offered a store map or layout to help them navigate the store.

The objective is always to provide the right message, at the right time, as often as possible and this is dependent on context. While ‘context’ is quite an old school term in marketing, it still applies to the location in which a potential customer sees your message as much as the time, channel or the keywords that may have triggered your ad in the first place.