How to A/B test with Dux-Soup
A/B testing has long been a powerful marketing strategy to test which campaign variables give you the best results. Whether comparing your messaging, audience, time of communication or conversion action, the winning combination can send results soaring.
As tempting as it might be to ‘follow your instinct’, you’ll have a better outcome if you follow a more rigorous approach. In this blog we take you through how to A/B test your LinkedIn campaigns using Dux-Soup Turbo so you'll be able to increase conversion rates and get more leads into your funnel.
A/B testing was the subject of a recent Dux-Soup webinar. If you’d like to watch it head on over to our YouTube channel - How to A/B test with Dux-Soup, or carry on reading for the highlights:
- How to set up A/B testing for your LinkedIn campaigns
- Measuring results within the Dux-Dash
- Tips and techniques on what to test
What is Dux-Soup?
Dux-Soup is a Chrome Extension (also compatible with some other browsers), which you can use to mimic human behavior on the LinkedIn platform (Free, Sales Nav and Recruiter).
Select the ‘list’ you want Dux-Soup to process, and Dux-Soup runs the chosen activities against that list. What’s more, the tool allows you to automate human behaviour in the browser to keep your LinkedIn account safe.
What is A/B testing?
A/B Testing is an experiment where two or more variants of something are shown to users at random, and statistical analysis is used to determine which variation performs better.
Or more simply; it’s comparing 2 versions of something to see which works best, also known as ‘split testing’.
Why A/B test?
Suppose you have a connection request conversion rate of 10% and you want to improve it. By changing certain variables and working out which changes are the most effective, you increase the chances of achieving a better outcome.
Testing enables you to maximize the effectiveness of your process(es). If you send out 200 messages in a week, you want to do everything you can to get as many responses as possible.
As every industry and geographical region are likely to react slightly differently, testing is a great way to check which approach is the most appropriate for your audience.
Testing also allows you to measure the impact of the changes you make. When you change your messaging, you can look at why you get a different result.
How do you A/B test with Dux-Soup Turbo?
Follow these 4 steps:
- Decide on your target audience and define your list of prospects.The more time you spend upfront defining your list, the better your chance of success. Don’t forget to make use of the Boolean search terms. Our blog LinkedIn and Dux-Soup - Search and Filtering Masterclass can help with that.
- Build campaigns with different messages.
- Enroll a number of prospects into each campaign.
- Monitor and evaluate the results via the Dux-Dash / Funnel Flow and take appropriate action.
A/B/C test with Dux-Soup Turbo - here’s an example
- Aim: To convert 2nd or 3rd degree connections to a 1st degree connection.
- Target audience: Growth Hacker profiles on LinkedIn.
- Campaigns: For this test we built 3 different Drip Campaigns, with 25* people enrolled into each campaign.
*The sample size must be large enough to provide a valid result for the target population. This is an example test, a larger sample (100-200 profiles) would provide a better judgement on the outcome.
Here are our campaigns in the Dux-Dash, under the Drip Campaigns Option.
(Note: Dux-Soup will still send a connection request if there is no text )
To enroll prospects into campaigns go to Dux-Soup Options and click ‘Enroll Profiles’.
Select the campaign and the number of people you want to enroll and press ‘OK’.
The great thing about enrolling prospects via DuxSoup is that you can never enroll people into the same campaign twice, AND if you are running more than 1 campaign at a time, you don’t need to be selective, because you can enroll prospects into multiple, concurrent campaigns.
A/B/C testing results
The results of the campaigns are monitored in the Dux-Dash Funnel Flow option. Using the example above, after just a few days, we could see progress…
A 24% acceptance rate for the detailed campaign message.
A 20% acceptance for the simple connection message.
The campaign with no message had a 6% acceptance rate.
Conclusion: From this small sample we can see the more detailed message in campaign A resulted in the highest rate of acceptances.
Cloning and monitoring campaigns
Building variations into your campaigns is made simple using the clone and edit function in the Drip Campaigns. Create your first campaign, clone it and then edit it to alter the messaging for the next campaign.
In the Funnel Flow you can break down your performance numbers by date to see how your campaign is progressing day by day, or week by week. The data can also be extracted into an excel spreadsheet where you can pull out the information in more detail.
A/B testing and Dux-Soup Pro
In Dux-Soup Pro the Drip Campaign option isn’t available. However, you can still carry out A/B testing by sending different connection messages to different profiles. Use the ‘Tag profiles’ option to differentiate your messages, and then monitor the new connection responses in LinkedIn.
So, to summarize, here’s your 6-step guide to A/B testing success, and to help you get started, here's your FREE 14-day Dux-Soup trial - including ALL the features.
- Determine your desired outcome before you start. Ask yourself, what does success look like? Is it a 25% acceptance rate, or are you striving for a 40% acceptance rate? Consider what you’ve achieved historically and what’s realistic going forward.
- Decide on an appropriate sample size for your target population. Make sure your sample size is large enough to make a valid decision from the results.
- Use Dux-Soup Pro or Dux-Soup Turbo to create and send your messaging. Be consistent in your approach so you can compare like with like. Write realistic messages that you’d be happy to receive if they landed in your inbox.
- Give the process time to run its course. People can accept or respond to invitations over an extended period of time - a month is a good window of time to give people the opportunity to respond.
- Make your decision based upon the data - try not to pre-empt your results!
6. Then be prepared to change your views, evolve your messaging and re-test.