Struggling to know where to start using AI? Our Head of Customer Success James Ede shows how integrating AI into your marketing strategy can be easy.

 
James has been with RedEye coming up to 16 years and has always been involved in email and marketing automation.
 
He has worked across multiple industries including Travel, Finance, Gaming and Retail helping brands develop their marketing automation programmes and deliver successful results.
 
James is at the forefront, advising clients on how they can use AI to transform their marketing campaigns, helping them set up predictive analytics tools against their databases and see big results.
 
So welcome back to our next instalment of ‘What Stopping You’ where James will answer a handful of common questions he gets regularly from those who are either nervous or struggling to start using AI, and dispelling misconceptions about AI in the future.

First of all, we want to address the biggest misconception we hear from marketers, ‘AI is going to replace my role at work’ What would you say to this?

 
While AI is indeed becoming more powerful and capable, it’s important to remember that it’s not here to replace us entirely.
 
Instead, think of AI as a tool that can complement and enhance our abilities, just like how a calculator doesn’t replace a mathematician but rather helps them perform complex calculations more efficiently.
 
AI is great at handling repetitive tasks, crunching massive amounts of data, and identifying patterns that might take us marketers much longer to uncover.
 
This means it can actually free up your time from mundane tasks, allowing you to focus on the more creative, strategic, and human-centric aspects of our roles as marketers.

To someone who wants to start integrating AI into their email strategy but doesn’t know where to start, what would you suggest?

 
A really easy place to start working with AI is to use it to help with data selections.
 
AI is great at analysing and presenting big data sets and here at RedEye, we have developed a series of models that can be applied to your database to help generate new segments and new opportunities.
 
One example of these models is the first-to-second purchase model which takes all of your existing data and works out who is likely to make a second purchase. You can send these customers targeted emails to help persuade their next purchase and begin to convert them into regular customers.
 
Another example is using AI for things like subject line ideas, something that often becomes mundane through the feeling you need to create a new one for every send.
 
Subject line generators can be a great way to spruce up the run-of-the-mill headlines and increase the open rates of campaigns or automated journeys simply by using one example with your keywords, it can suggest multiple other options for you to consider.
 
With these, I’d recommend testing performance regularly and reviewing what works and doesn’t work but the volume of options it can give you to help with the creative process is excellent!
 
Finally, you can use AI to help with your sending frequency. When and how often to send an email is becoming more and more of a focus, as someone that is open to receiving an email every day may be someone else’s idea of bombardment.
 
Using AI like a predictive frequency model can help with tailoring the frequency which can all help with better open and engagement rates, but also help reduce someone from receiving too many emails from you and hitting the unsubscribe altogether.

To those who struggle to ‘trust the AI’ to send automated emails through predictive models what would you advise them?

 
People can often be hesitant to use any new piece of technology or feature but if you are struggling with initially trusting the capabilities of AI then there are ways you can gradually ease yourself in.
 
You can do things such as volume restrictions, so you use a test subset of data initially before rolling out to wider audiences, so it’s not seen as big of a risk before going live.
 
The other factor is that the data is primarily what you would select in more generic comms anyway but adds an extra layer of potential data selection to the process. But for those who are struggling to initially trust AI, the results speak volumes.
 

Using AI and machine learning to predict customer churn

A great example of some results we have seen is allbeauty who added the Predictive Churn model to identify which customers were likely to lapse based on their individual purchase behaviour.
 
This allowed them to optimise their reactivation campaign to target customers at each of their own identified moment they might lapse.
 
Before they were using this predictive model, they were triggering the re-activation to everyone at the same time, but by that point, they had probably lost customers who might have been saved if they had a more personalised approach to the timing.
 
By implementing the model we helped allbeauty to achieve an impressive 414.6% increase in sales and 518.7% increase in revenue from their lapsing segment, simply by letting their customer data drive the decision.
 

Using AI and machine learning to nuture potential VIPs

Another model that has had a great success rate is nurturing VIPs. Travis Perkins had great results from this. This model analyses all customer behaviour from past transactions to website engagement to understand patterns of behaviour and then benchmark these against current VIPs within their database.
 
Targeting the customers who were showing similar signs of behaviour, Travis Perkins was able to nurture more customers to become VIPs which enabled them to increase their VIP segment by 5.3%.
 
Also, their customers within the VIP segment were shown to have an increased CLTV by up to 34% in a single 12-month period, demonstrating investing in your VIPs really pays off.

The future of AI is going to open a host of opportunities, what would you say to someone that is unsure of where AI in marketing will go?

 
There are lots of possibilities, but all seem to be stemming around making things more efficient and a focus on personalisation to a customer’s experience. As we’ve talked about, there is a lot of the focus is on the data and supporting the selection process as well as the creative elements.
 
Focusing on this, I think that we will see is further developments in the actual curation of a campaign and at some stage we will be more used to typing instructions as opposed to building out a campaign canvas or flow from scratch.
 
There will still need to be human interaction to bring that level of personality to the process of course but again, this is just an area of supporting us marketers in the future.
 

Thanks, James, it really helps by first of all not being afraid of AI and its advancements.

 
It is going to be influencing the world of marketing whether we like it or not and now is the perfect time to get on board with it, test and experiment with it.
 
Then as new tech emerges we are already confident with its capabilities, helping us innovate and generate even more content and campaigns as our careers progress.
 
 

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