No need to fear – AI-driven personalisation, when done right, delivers results

Personalising your site increases sales value, improves conversion rates and leads to more satisfied customers. Yet, some marketers fear that too much personalisation might scare customers away. But there is no need for concern - the data confirms the opposite.

Tailored messaging, hyper-personalised recommendations and seamless shopping experiences. Today's AI-driven personalisation is all about understanding the needs of the customer and presenting them with relevant content and recommendations that fit those needs. The tools we have allow a dramatic change from the old way of providing a one-size-fits all journey experience.

"75% of consumers wish they could identify options that met their needs more quickly and easily."

Customers are not only getting used to it - they are starting to demand it. According to a recent report by Accenture, 75% of consumers wish they could identify options that met their needs more quickly and easily. But for many marketers one question remains: can personalisation be taken too far?

AI can play a pivotal role in driving conversion rate optimisation (CRO) with different contributions at each stage of
online marketing efforts.

The role of AI in personalisation and CRO

Before AI came into the picture, personalisation was more about segmentation - marketers understanding their customers at a group level and providing solutions based on their analysis.

AI and machine learning are taking us much closer to a truly personal experience than would have ever been possible by human intervention alone, and at a much larger scale. Additionally, AI can be used to tailor strategies to match the patterns and trends revealed by its analysis.

AI can play a key role in driving conversion rate optimisation (CRO) with different contributions at each stage of marketing:

• Analysing qualitative data from reviews and questionnaires.
• Accelerating coding to improve the development process.
• Personalising the user experience by understanding historical purchase data.

We are now seeing our clients achieve very positive results with AI-powered personalisation. One example is using AI to optimise CTAs. Previously, we were limited by the ideas and wording our team could generate. Now, AI can continuously test new versions of CTAs, running through different text options until it finds the phrase that delivers the best results.

Product recommendations are another area where AI excels at identifying suitable complementary products. When done manually, we rely on our product knowledge to match products - for example, a customer buying golf clubs also might need balls, bags or covers. AI, however, takes this a step further by tailoring the customer experience based on past behaviour. It might analyse the brand of golf clubs, their price range, and determine that the customer is a regular golfer who already has gloves and bags.

Instead, the AI would recommend new releases from the brand the customer has shown interest in. This way, AI provides more effective methods to encourage customers to add additional items to their basket, driving an increased average order value (AOV).

Product recommendations is an area where AI excels at identifying suitable complementary products, making the level of personalisation more customised and tailored to specific demands.

Over-personalisation - a real risk?

Despite its clear advantages, marketers often worry about over-personalising, fearing that customers might feel their privacy is being violated. Many of us can relate to the feeling that "Facebook is listening" when personalisation is so accurate that a website seems to know us better than we know ourselves.

"That said, there are risks associated with over-personalisation. One concern is personalising to the point where customers are unable to discover products on their own."

The reality, however, is that in all the user testing we conduct, we have never had anyone report personalisation as "creepy". In fact, the data shows the opposite: AI-driven personalisation helps customers find products quicker, buy more and spend more time on a website. Customers expect a personalised experience and the improvement it brings.

That said, there are risks associated with over-personalisation. One concern is personalising to the point where customers are unable to discover products on their own. If you push visitors too strongly towards a particular brand or style, they may miss out on discovering new options. In essence, you may become so effective at predicting their preferences that they overlook other products.

Another potential issue arises when AI becomes too advanced and starts recommending a broader range of products than expected. For instance, one of our clients sells both clothing and home appliances, and when the AI analyses past purchase data, it might recommend a vacuum cleaner to a customer buying socks. Some retailers may feel uneasy with this and prefer to use a more restrictive algorithm. However, data shows that AI consistently outperforms humans. Marketers who are willing to overcome their fears and allow the AI more freedom will ultimately see better results.

Getting customers to share data

A key requirement for personalisation is customer data, and with GDPR regulations in place, this requires explicit consent. When the consent request is well-designed, around 80 per cent of users agree to share their data. However, if poorly executed, this figure drops below 50 per cent. Given the importance of data, a well-crafted consent module is essential. So, the question is - how do we achieve that?

A well-designed consent module should:

• Present clear, easy to read information.
• Make it simple to opt in and out.
• Explain the benefits of opting in.

To make customers comfortable with sharing their data, we need to clearly explain the benefits they will receive. While sharing data might seem like a one-way exchange, that's far from the whole truth. A relevant and satisfying customer experience saves time and makes decision-making easier. Businesses must be clear about the advantages customers gain from sharing their data.

Rather than asking if we can track their computer, we should ask if we can track their product use on our site to create a better experience for them in the future.

To make customers feel comfortable with sharing their data, we need to clearly explain the benefits they will receive.

Best practices for succeeding with AI-driven personalisation

As you explore how AI-powered personalisation can improve your business, here are a few guidelines that might be useful along the way.

1. Prioritise customer data protection and transparency
   Always make sure customers know how their data is being used and give them the choice to opt in or out of personalisation efforts. Clearly explain the benefits of personalisation - what does it mean for them as customers? Avoid internal jargon and use straightforward language that helps customers easily understand the value they'll receive. When customers see the value, they are more likely to share their information.
2. Use A/B testing to ensure you're enhancing the customer experience
   If you're uncertain about whether you're over-personalising or overwhelming customers with too much tailored content, run A/B tests. This allows you to measure how personalisation impacts key metrics, such as sales or revenue. While customers may claim they dislike certain features, such as social proof (showing that others are viewing the same product), testing often reveals that these features can significantly boost sales. AI-driven personalisation might seem intrusive at first, but it's important to test whether it actually helps customers make quicker decisions and enhances their overall experience before dismissing it.
3. Let AI enhance more than just personalisation
   AI can go beyond personalisation to help increase your conversion rates and improve the overall website experience. One of the biggest challenges that marketing teams face is gathering and analysing customer feedback to gain actionable insights. While many collect data, few have the time to thoroughly review and act on it. AI can step in to identify problems and propose solutions, saving your team time and resources in the ongoing effort to enhance the customer journey.

AI-driven personalisation could become the most hard-working member of your team - are you ready to embrace it?

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