How do I know if my campaign needs to be optimized?
The easiest way to know if your LinkedIn or email campaigns need optimization is to measure their performance. You should track metrics such as open rate, click-through rate and conversion rate so you can determine if your campaign needs to be optimized. If performance is not in line with your expectations, adjustments should probably be made. Additionally, you need to consider testing different elements of your campaign, such as content, timing and formats, to see if they will help improve performance. Sounds simple right? Just what does it mean in line with expectations?
__________________________________________
Learn more about our lead generation services
__________________________________________
What value of open rates should be alarming to me?
In order not to be disappointed with your expectations, you should not have expectations. It sounds ridiculous, but it’s true. It’s much better to have assumptions and move through campaigns depending on how close to those assumptions you manage to land with results. At AutomateMeUp, the average open rate is 50%+. In the campaigns that convert the best and that we ourselves rate as very good, the number of open messages varies between 68% and even 100% of open messages. An open rate, however, means only that we manage to break through to the recipient with our message, in other words: we know how to perform step No. 1. An open rate below 10% may or may not be a cause for concern, as many factors can affect the open rate, such as the quality of the mailing list, the content of the email or how personalized it is. It is best to evaluate the open rate over time to determine the overall effectiveness of the campaign.
How much conversion from response to leads?
Conversion rate is as related to a long list of variables as open rate. If 1 out of 100 responses is positive and manages to conduct a meeting with a potential customer, this is pure coincidence. If, on the other hand, out of 100 responses 1 leads to a conversation and this happens every time you release a campaign, then we already have a basis for calculation and inference: I will get 300 responses, I will have 3 conversations, I will get 3000 responses – 10 conversations, etc. Personally, today I talk to 3-10 people a day representing AMU. When I was a salesman in software houses, I talked to 1 d 5 people a week, but each of these conversations could result in a contract worth a minimum of €25,000. What do these two levels of results have in common? Each time, I knew how many messages I needed to send to get X responses and Y leads. So from campaign to campaign I was able to determine more and more precisely how increasing the database, changing the texts, changing the target group would affect the result. If you always have 10 leads out of 1,000 responses you get, and it’s like this in every campaign, then you can try on optimization. There is no wrong result, there are at most wrong assumptions in campaign design.
Check out our Campaigns on LinkedIn to learn how to get potential customers for your brand!