1. Use Bayesian Reasoning When Statistical Significance is Lacking.

Let’s say you are trying to optimise a campaign for demographic information/bid adjustments. The campaign is based geographically in New Jersey and is advertising soccer boots.

You’re campaign has only been running for 3 months, so you only have a few conversions in regards to each age group…

Gather All The Trends at All Levels of the Account

To gain further insights – Get the overall age and cost/conv for the entire account.

If possible get the age and cost/conv data for any geographically similar campaigns. E.g. any campaigns in New Jersey

Gain the age and cost/conv data for all soccer boots campaigns, and any similar product campaigns.

Where The Trends Match – Make an Adjustment

Now, if every campaign plus the account shows that the age group 65+ is the most expensive, and so does the New Jersey Soccer Boots campaign, it’s a safe bet that you can reduce the bids for this age group for the New Jersey Soccer Boots campaign, even if your data for this specific campaign is lacking and only includes a couple of conversions.

So if cost/conv is too expensive for those aged 65+ at:

Overall Account Level

Campaign Level - Overall for all New Jersey campaigns

Campaign Level - overall for all Soccer Boots campaigns

Campaign Level - in the campaign we're looking to optimise

If all this data suggests that 65+ age group is too expensive,
 then reduce bids for this age group.

Use a bit of guess-work and common sense if there is a mismatch between the age group and trend for cost/conv between the overall account and other campaign data.

Most of the time, if there’s no pattern between all the levels of data, then don’t make any adjustments until the current campaign you’re looking to optimise has run for longer and gathered more data itself.

Do the same with the locations & ad schedule

 

2. Set KW Bids below First Page, but Increase Bids on Specific Demographics & Devices

Good technique if the campaign is generally running too expensive.

First – Make sure it’s not just 1 or 2 specific KWs or Ads that are causing the campaign to run too expensive.

Set your KW bids, so that they are just below the first page bid recommendation.

Then increase bids on specific demographics and devices – the ones which provide the best cost/conv.

You can then, to a certain extent, dictate which specific users (in terms of age, gender, income, device etc) see your ads.

 

3. Resurrect Old, Expensive Cost/Conv Campaigns with Targeted Audiences

I have a few of these at the moment.

Instead of pausing the campaigns, I have added specific in-market and remarketing audiences and set audiences to targeting.

This means that nobody outside of these specific audiences will be shown my adverts.

Will should reduce the number of irrelevant clicks quite a bit

 

4. Block Competitors’ IP for Competitor Brand Campaigns

You can usually get this from their email header

Sign up to their newsletter or download a pdf and they’ll normally send an email from their office IP.

You can double check the IP is correct by looking up the IPs location.

You can also reduce bids specifically for the competitor’s location – assuming your cost/conv isn’t good in that area for their brand KWs.

View Email Headers: Guide for Email Clients