So we’ve established the importance of search queries as a foundation of a solid PPC (Best Practice) strategy. Next up: location bidding, which again seems simple if ‘my customers are in the UK, then I target the UK’. Right? Wrong.

Why is location bidding important?

It’s easy to assume that a consumer’s physical location doesn’t have that much impact on their demand for a particular good or service, which to a certain extent is true, but what is different is their propensity to buy that good online or redeem that service. For example, someone living more rurally may not have as many options in terms of bricks and mortar retailers so will have stronger online purchase behaviour compared to someone who lives just down the road from the high street shops. If you’re within the lead gen industry; then physical location is more important as there will be a distance where people aren’t willing to travel to redeem that service. You may also see differences in locational performance if what you sell is deemed a want or a need, more specifically if it is a want with a high price point then you’re likely to see greater success in more affluent towns/cities/postcodes.

How does location bidding improve performance?

To simplify into a visual view, let’s say the green dots below are our desirable clicks with the highest return, whilst our reds we could give or take as they’re not that valuable in terms of profit, and our grey circles are our bids.

If our end bid in any auction is determined by our keyword/product bid and our location bid (in reality there’s also device, audience, demographic etc. but let’s keep it simple for the purposes of discussion), then if we’re not sophisticated in bidding at location level and leave success entirely up to one keyword/product bid; then the chances of our circles colliding and maximising the volume of green dots is low:

If we tighten up our location bidding, then we end up with something more like this where we’ve increased the probability that our circles collide in such a way that we’re maximising profitable clicks:

How do the circles above translate in practice?

In order the have the greatest success in location bidding, the question you really need to know the answer to is ‘what is the lowest level at which I have significant data that illustrates differences in performance?’, where ‘level’ follows the granularity at which your PPC platform allows you to bid. For example, in Google Ads, the hierarchy of location levels at which you can set different bids looks something like:

If your CRM, Google Analytics or Google Ads accounts don’t have significant performance differences at post code level, then bidding down to this level overcomplicates things. However, if you have a local or lead gen business then postcode is likely appropriate. Once you know what level you want to break things down to, take performance differences as indicated by your data and apply +/- bid adjustments for each location based on its performance. If you’re an ecommerce business that can deliver to all of the UK then you’ll set you’re highest location level as such, but with a lower bid, so that it acts as a catch all and picks up any stray clicks. If you’re a lead gen business, then your top level might be a radius or city, but again, with a lower bid as the intention of being a catch all.

There are a few other things to look out for in setting up location targeting in order to be the most efficient, including how the platform defines each country. For example, something that will happen is that Northern Ireland will always be included when you select a country target of The United Kingdom which makes absolute sense; though people living in Northern Ireland may prefer not to ship across sea as it’s quicker for them to buy from Ireland/Northern Ireland so you might have a longer shipping time frame, hence lower conversion rates. We’d almost always advocate to not chose the default location setting and ensure you change to ‘people in your target location’ as opposed to ‘people in, or interested in, your target location’ as the latter will see you waste budget in locations you don’t want ads shown in.

Conclusion

So now we’ve done the hard work in setting up our location strategy to maximise profitable volume, but that’s not to say it won’t need to be updated on an ongoing basis because things will change. In probably the most extreme of examples; when something like COVID-19 hits and drives a significant increase in online purchasing, then perhaps previously low performing locations thrive as shopping is almost entirely driven online whilst lockdowns are in place locally or nationwide, and so we reverse some of our previous assumptions on where our strongest performance comes from. Food for thought!