Microsoft advertising targeting is usually treated as an afterthought, because most accounts arrive there by import. Someone copies a Google Ads account across, keeps every setting, and then concludes after a month that the channel does not work. What actually happened is that a campaign built for one auction and one audience was dropped into a different one without adjustment. The inventory, the device mix and the context in which people are searching are not the same, and the settings should not be either.
Treated on its own terms, the channel has a specific advantage worth building for. A meaningful share of its search volume happens on work machines, inside browsers and operating systems configured by an employer, often during the working day. For businesses selling to other businesses, or selling considered products to people with money to spend, that context is a real asset. The job is to build targeting that takes advantage of it instead of ignoring it.
Start from the import, then rebuild deliberately
Importing is a sensible way to get live quickly. It is a bad way to stay. After the first few weeks of data, we go through every campaign and reset the decisions that were inherited rather than chosen: location settings, device modifiers, ad schedule, network options and audience exclusions. Each of these should be justified by what this account has done here, not by what a different platform decided months ago.
The most common inherited mistake is leaving search partner inventory on with no separate monitoring. Partner traffic can perform acceptably, but it behaves differently from core search results, and if you never look at it separately you cannot tell whether it is subsidising or sabotaging your averages. Split the reporting, judge it on its own conversion rate, and keep it only if it earns its place.
Audience layers that change microsoft advertising targeting results
Keywords tell you what someone wants right now. Audience signals tell you who they are, and the combination is where microsoft advertising targeting gets interesting. The practical method is to layer audiences in observation mode first, gather enough data to see how each one converts, and only then move the clear winners to a restricted targeting setting or apply meaningful bid adjustments.
- Remarketing lists split by depth of visit, so someone who reached a pricing page is bid on differently from someone who read one blog post.
- Customer match lists for existing buyers, used both to exclude wasted spend and to target expansion offers.
- In-market and similar audiences layered in observation mode until you have enough conversions to judge them fairly.
- Company and industry signals where they are available, which is where the professional context of the network pays off for B2B accounts.
- Location targeting narrowed to where you can actually serve, with the presence setting checked rather than assumed.
That last item catches more wasted budget than anything else on the list. Default location settings often include people merely showing interest in a region rather than being in it, which is right for a travel brand and wrong for a local service business. Check it in every campaign, because an import can carry the wrong choice across without comment.
Device and schedule decisions deserve their own look
The device mix here tends to skew more toward desktop than teams expect, and desktop behaviour differs: longer sessions, more comparison, more form completions and more research done before contact. If your landing pages were optimised primarily for mobile traffic from another channel, they may be underperforming for this audience without anyone noticing. We usually find at least one page where the desktop layout buries the call to action below a hero image that was designed for a phone.
Scheduling follows the same logic. If a large share of your conversions come from people searching at work, the value of an impression at nine on a Tuesday morning is not the value of one at eleven on a Sunday night. Look at conversion rate by hour and day before setting modifiers, and re-check quarterly rather than setting it once and forgetting.
Judging the channel honestly
Volume here will be lower than on the larger search network, and that is not a verdict. The question is whether the traffic converts at a cost that works, and in a fair number of the accounts we run, cost per acquisition is competitive precisely because fewer advertisers are paying attention. Where it does not work, microsoft advertising targeting usually fails for a diagnosable reason: mismatched location settings, unmonitored partner traffic, or audience layers copied across without ever being tested in their new context.
Give the account a proper build, a realistic measurement window and a separate report rather than a line in the Google summary. Then decide. A channel evaluated on inherited settings has never actually been evaluated, and that is the situation most businesses are in when they tell us the platform did not deliver.
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