If this is your first personalization experiment, remember, don’t let perfect be the enemy of the good! While you may not have the ideal segment or hypothesis defined, or your reporting completely squared away, that’s ok!
After all, this is an experiment. You can progressively work to improve future personalization programs with useful data from your initial tests.
Prepping Your Content
Content creation is often overlooked and under-resourced when planning for a campaign, but content is a large part of what you are personalizing.
If you are experimenting with unique messaging for specific segments, you will need to make sure that your content:
1. Aligns with your brand voice
2. Is consistent with the language used for your website channel
3. Is specific to the needs of the segment(s) you are targeting
Even if you are focusing your experiment on messaging placement or design rather than unique offers or language, you will most likely need content development, review, and/or approval from your content team, so remember to plan for that time.
Once you have tested, iterated, and successfully optimized your message to a specific segment, designate a team member responsible for making sure the message continues to be relevant and doesn't get outdated or stale.
You can find more detail on preparing content for personalization in our upcoming blog post.
☑ Time and resources for content development
☑ Inputting content into your personalization engine
☑ Any new content you have produced to be approved by stakeholders
☑ Ongoing messaging maintenance
QA Before Launch:
Most personalization tools provide a way to create a test campaign or preview your campaign before it goes live.
You will not only want to ensure that your personalization test appears as it should to the target segment, but you'll also want to get familiar with how the data is reported in your personalization engine. The aim here is to ensure you’re ready to clearly report on the metrics you identified in your hypothesis.
Review the following components of your campaign:
☑ All conversion actions and how they are triggered
☑ Functionality performs as expected
☑ The target segments are served the right personalization
☑ Test URLs and cookie script
Communicate and Document
Socializing your personalization strategy is important to grow support and stakeholder buy-in. Remember to communicate why you are conducting the experiment and what benefit you hope to achieve from it. Doing a little internal promotion for your strategy can go a long way in managing expectations and providing context.
Documenting your process is also a best practice so your team can reference past experiments and hypotheses.
☑ Put together a communication plan
☑ Document process and roles
☑ Create a place for other stakeholders to submit ideas to test
Launch and Measure
With content in place, and everything QA’d, you’re ready to launch, measure, and iterate.
Remember every campaign will provide you with valuable information about your audience even if the outcome of the campaign surprises you. Any results - predicted or unexpected - will inform your next test and hypothesis.
If the campaign successfully boosted your conversion metric, you may choose to run it for longer. If this is the case, remember to continue to check in on the efficacy of the personalization experiment as you get more data and incorporate factors like seasonality and other variances in user behavior into your thinking.
Over time you can start to use your findings in aggregate to get more specific with your target segmentation and get closer to 1:1 personalization.
☑ Add your personalization metric to your reporting dashboard
☑ Share the results widely so everyone can learn from them
☑ Start planning your next experiment based on your results
☑ Plan for ongoing analytics review for any extended personalization strategies
☑ Look for ways to get more specific with your segments
Off To The Races
Congratulations! You’ve pulled off your personalization strategy, and you are already optimizing your conversions and learning more about your customer!
You can now further mature your program. Consider integrating more data inputs together so you are able to start orchestrating personalized experiences across channels. Create more transparency around the way you are prioritizing tests and invite more of your organization to contribute ideas. Oh the possibilities!