Optimize campaigns with demographic and geographic variables
Posted: Wed Dec 04, 2024 9:56 am
Structuring campaigns according to a concept per campaign… ready, you chose the ideal keywords for each campaign… ready, you assigned the ideal match type to each keyword to get better results… ready. You already have a well-structured campaign , with head and tail, and enough time has passed (at least 2 weeks) generating results and it is time to optimize, but…how do I do it?
It is true that there are many ways to list of benin consumer email optimize campaigns with data generated by them, if they are well measured. These can be lists of customers who are stuck in their shopping cart or customers from the last six months, even customers who have visited a certain page on your website and clicked on a specific button.
However, that can sometimes be a bit overwhelming for those who are in solo campaign management mode. A simple and efficient way to get started is with demographic and geographic variables .
Let me explain:
Step 1. Define the variable you will use
It is important that we first define what type of variable you will use to optimize your campaigns. When the reality is that there can be several, the ideal is that so that you do not get overwhelmed, if you are just starting, it is only one. And the ideal way to choose is depending on your type of business . If it is a service, you can do it by location and if it is a product it can be by age.
(NOTE: remember that you can use more than one variable to optimize, but this is a simple way to avoid problems in control).
Step 2. Identify the most profitable segment with your variable
Once you have defined your main variable, you have to identify the segment that generates the most results and generate specific campaigns based on that. Let me explain with an example.
The variable we will use is age and as we can see in this graph, the most profitable age ranges are 18-24 and 25-34. However, this does not mean that we should rule out all the other segments , such as 35-44 and 45-54, which, despite their results not being as ideal as the first age ranges, are generating results.
And the same goes for Unknown, even though it doesn't clearly show how old those people are, it's the one that has the best results at the lowest cost.
Step 3. Define actions
Continuing with the example, as we could see, the ranges with the best results are 18-24, 25-34 and Unknown, then those that generate optimal results are 35-44 and 45-54 and finally the ranges 55-64 and 65+ have generated very low results. With this we can perform an optimization in budget and campaign structure .
Regarding the serious structure, copy and create the campaign that has already been created , but now do each one for each specific age range except those of 55-64 and 65+, since those are generating very low results and therefore must be excluded.
The difference here is the distribution of the budget , which you can assign by sending a fixed value to those with the best performance, and 20% less to those with optimal performance.
And this is a way to optimize using demographic variables and with this same technique it can be applied to locations.
In case you are interested in segmenting using specific lists, at Interius, Premier Partners of Google and HubSpot, we have the Inbound department , which can integrate your CRM to HubSpot without any problem, to automate the creation of this type of lists so you can reach your ideal client faster .
I hope you find it very useful and if you have any questions, please write to us.
It is true that there are many ways to list of benin consumer email optimize campaigns with data generated by them, if they are well measured. These can be lists of customers who are stuck in their shopping cart or customers from the last six months, even customers who have visited a certain page on your website and clicked on a specific button.
However, that can sometimes be a bit overwhelming for those who are in solo campaign management mode. A simple and efficient way to get started is with demographic and geographic variables .
Let me explain:
Step 1. Define the variable you will use
It is important that we first define what type of variable you will use to optimize your campaigns. When the reality is that there can be several, the ideal is that so that you do not get overwhelmed, if you are just starting, it is only one. And the ideal way to choose is depending on your type of business . If it is a service, you can do it by location and if it is a product it can be by age.
(NOTE: remember that you can use more than one variable to optimize, but this is a simple way to avoid problems in control).
Step 2. Identify the most profitable segment with your variable
Once you have defined your main variable, you have to identify the segment that generates the most results and generate specific campaigns based on that. Let me explain with an example.
The variable we will use is age and as we can see in this graph, the most profitable age ranges are 18-24 and 25-34. However, this does not mean that we should rule out all the other segments , such as 35-44 and 45-54, which, despite their results not being as ideal as the first age ranges, are generating results.
And the same goes for Unknown, even though it doesn't clearly show how old those people are, it's the one that has the best results at the lowest cost.
Step 3. Define actions
Continuing with the example, as we could see, the ranges with the best results are 18-24, 25-34 and Unknown, then those that generate optimal results are 35-44 and 45-54 and finally the ranges 55-64 and 65+ have generated very low results. With this we can perform an optimization in budget and campaign structure .
Regarding the serious structure, copy and create the campaign that has already been created , but now do each one for each specific age range except those of 55-64 and 65+, since those are generating very low results and therefore must be excluded.
The difference here is the distribution of the budget , which you can assign by sending a fixed value to those with the best performance, and 20% less to those with optimal performance.
And this is a way to optimize using demographic variables and with this same technique it can be applied to locations.
In case you are interested in segmenting using specific lists, at Interius, Premier Partners of Google and HubSpot, we have the Inbound department , which can integrate your CRM to HubSpot without any problem, to automate the creation of this type of lists so you can reach your ideal client faster .
I hope you find it very useful and if you have any questions, please write to us.