Experimentation plus personalisation: the magic equation for transforming business outcomes

Over the past year, there has been a significant, permanent shift in consumer buying behaviour. Strict lockdown measures meant that the world had to quickly adapt to working, socialising and shopping online. Although the easing of restrictions means we can once again socialise in-person and we’ve already returned or are planning for the return to the office, the shift towards online shopping driven by the pandemic is here to stay. In order to keep afloat in a sea of online competition, brands need to focus on delivering a seamless, personalised digital experience.

Although personalising and enhancing the customer experience has long been part of many marketing strategies, with a large number of people spending more time online, building a personal connection has never been more important, and is now a crucial element for success in a post-COVID world.


In fact, according to research from SmarterHQ, 72% of consumers say they now only engage with marketing messages that are personalised and tailored to their interests. However, personalising experiences in an effective way isn’t as simple as it might seem; it requires significant thought, planning and technology to engage customers and achieve better business outcomes.


Overcoming the personalisation challenge


Today, being able to personalise the digital experience requires the ability to closely examine each customer’s journey and to understand how they are engaging with your products, your content and your brand. The first step in this process is to map the customer journey and then determine each of the components or attributes that need to be personalised in order to achieve maximum engagement with individuals.


Being able to understand exactly where a personalised experience can impact a customer’s experience is key to success, but how can this be accomplished?


In order to devise the right approach to any personalisation campaign, applying an experimentation mindset is key, which means experimenting and iterating across the whole digital experience.



Embracing the mindset

Experimentation is not only a process, but a mindset that enables organisations to continuously test and iterate on different hypotheses. The two most common ways are to run A/B tests and to run personalisation campaigns, but it’s important to maintain this experimental mindset regardless of the type of test or hypothesis you are executing.

AeroMexico for example wanted to improve conversions through the checkout process, as they noticed a majority of customers were nearly completing the flight purchasing process only to abandon their carts at the last minute.

The airline believed that if it was more upfront about the total price of each flight package earlier in the customer journey, this would decrease the number of people abandoning their purchases and increase conversions. This would eliminate any element of surprise and make sure people were fully aware of all costs before reaching the checkout stage.

Upon reviewing the results of the A/B testing, the company also decided to personalise the experience by making it easier for customers who had abandoned their carts to return to the precise flights that they had originally searched for to purchase them at a later date.

As a result of effectively streamlining the checkout experience for its customers, AeroMexico saw an increase in revenue and sales conversions.

To be successful with any type of personalisation and experimentation, it’s important to continuously test and learn. That means gathering data about your customer interactions, determining what works and what doesn’t, understanding why this is the case, and then personalising messages in a way that will ensure success. Without constant experimentation, personalisation can result in wasted time and resources, and in some cases can even be detrimental to the business.


The importance of data

Personalisation was once achieved through a significant amount of guesswork. Now, through the use of digital experience platforms that leverage artificial intelligence (AI), organisations can take a data-driven approach to personalisation and significantly increase the efficiency of experimentation strategies.


Data analytics and omni-channel insights give marketers, merchandisers and developers the advanced actionable insights they need to understand what is happening in each experience and how to personalise it in order to drive better results.

Personalisation is often perceived as the process of creating one-to-one experiences and is no doubt an admirable goal. But effective personalisation and experimentation means segmenting and creating actionable insights that can create a positive business impact.

Robust experimentation and personalisation programs quite often result in the ability to address larger audiences where you can learn, through behaviour-based decision making, what works better for different groups of individuals. Personalisation can also be a thorny issue, though, venturing into privacy invasion territory. With this in mind, customers should always have a say in the amount of personalised content they would like to receive, and this is where experimentation can play a helpful role.

Optimisation is the key to effective personalisation — by experimenting with your messaging, content and overall digital experience for each audience, you can access more data-driven insights for better decision making and achieve a better long-term impact.

Increased personalisation maturity

A company’s personalisation and optimisation efforts usually tend to increase with time. Although the first few personalisation campaigns may target only a very small audience group, say 10-15% of the entire target population, the audience reach can be extended over time.


Once you’ve built your organisation’s ‘personalisation muscle’, use cases will be iterated relentlessly across 75-100% of the audience to ensure that you are driving new audience strategies.


Depending on your business, there are a variety of use cases you can explore. One example would be carrying out experiments related to symmetric messaging, which is where you personalise your site and engagement channels to ensure there’s a consistent story across each of them. For example, if someone searches for shoes on Google and is directed to your website, you want to ensure they can easily find shoes. Symmetric messaging can help to increase ROI and reduce cost per lead (CPL) from acquisition campaigns.


Engaging digital experiences


It is, without a doubt, the powerful combination of personalisation and experimentation that allows organisations to create the kind of digital experiences that engage their customers and generate better business outcomes.


Personalisation without experimentation can be risky, but by embracing them both, organisations can transform themselves and unlock digital potential.


Kevin Li is VP, Product Strategy at Optimizely and is responsible for the company's overall product strategy, including new product launches, strategic roadmap, as well as M&A/corporate development.