The majority of marketers believe that personalization can improve customer experience (CX) and increase conversions. In fact, 90% of US customers find the idea of personalization appealing according to Statistica, and while most businesses will rank personalization as their number 1 priority, based on customer sentiment, they’re not there yet. More often than not, personalization efforts end in frustration for customers and this is no surprise.
It’s almost humanly impossible to accurately personalize at scale and remain relevant to an individual customer. Is all this talk about making strides towards greater personalization just hot air, or is there really a way to achieve the impossible?
Personalization is still relatively new and there is little specific research to guide strategy, perhaps because very few brands have successfully achieved personalization at scale. Still, indicators are that 80% of customers are more likely to buy from a company that provides a tailored experience. 80% of brands that have implemented some form of personalization strategy have seen measurable results with an average lift of more than 10%.
The challenge is that personalization requires data. Knowing what data is relevant and understanding how much data customers are willing to trade to get better experiences is only the first stumbling block. Finding that sweet spot of getting personalization right requires meeting the expectation that customers have - that brands should understand their individual needs and preferences, adapt the content, and then serve up relevant unique experiences accordingly.
Currently personalization in e-commerce doesn’t extend much beyond product recommendations. While this might initiate return shopping or increase the average order value (AOV) and customer lifetime value (CLV), it doesn’t really have a huge impact on overall CX because it only targets one small part of the customer journey: the checkout.
Some conversion experts argue that checkout is the most important part of the customer journey because it’s where the ultimate conversion happens. While true, if the digital experience fails to engage visitors the minute they land on a website, and it doesn’t lead them further along the customer journey, they’ll never get close to checking out. Personalization that drives positive CX needs to start much earlier in the customer journey through the various touch points or micro conversions that lead to the purchase event.
The statistics tell the story and the tremendous lost opportunity if a brand is not able to execute on an increasingly more personalized CX. 71% of customers are frustrated by impersonal shopping experiences and 63% won’t even buy from brands that have poor personalization. A common misconception is that personalization can be achieved using third-party cookies and the demographics data they contain. Relying on third-party cookies or historical browsing data actually won’t enable the relevant unique experiences customers desire. They lack the real variable that matters: the visitor’s intent.
The right solution is to continuously experiment and deliver more personalized experiences which capture the visitor’s intent. Being able to serve up hundreds of unique ideas in thousands of combinations gets a lot closer, especially when you’re able to track live visitor responses and then tailor the next part of the digital experience to serve up more relevant ideas.
Personalization creates the expectation that each website visitor is served up a unique experience, relevant to their personal interests, needs, and preferences. As an added challenge, these interests are constantly changing, so it’s not enough to optimize the digital experience for today. It requires ongoing learning that can keep pace with new intent.
This is where artificial intelligence (AI) and machine learning (ML) provide the technology that marketers need in order to deliver better experiences to customers. Continual learning through AI-driven optimization enables brands to navigate the infinite complexity of optimizing digital experiences, anticipate the needs of their customers, and delight them with relevant experiences that convert.
By analyzing live visitor behavior, it’s possible to discover touch points in the customer journey that connect and lead them towards conversions. But the key advantage of AI is that it can learn and adapt in real time - always seeking out the best experience to serve up to customers.
The number of variables and complexities involved with personalization of digital experiences goes beyond what can be processed manually with any level of efficiency. By contrast, AI thrives on complexity and is highly efficient in identifying experiences that connect with customers.
Having the ability to serve up thousands of ideas in millions of combinations and learn from live visitors helps brands create better connections with their customers. Through continual learning, brands are able to evolve digital experiences and move closer to a greater degree of personalization with each learning, delighting customers each step of the way.