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Strategic AI Implementation: Crucial for CX Improvement

June 18, 201910min

Artificial Intelligence (AI) plays an important role in Customer Experience, marketing, and personalisation; It has the power to generate predictions about what goods and services customers are likely to want, when the demand will arise or propensity to switch will occur, and which platforms they are most likely to purchase on.

As a result, AI has become critical for brands wanting to improve their capabilities to offer personalised experiences, offers and recommendations. What’s more, marketers should not overlook the importance and the business case for investing in AI technology to deliver high-quality personalisation at scale.

Personalisation is key to customer loyalty, customer experience and increasing sales, with Accenture recently finding that 91 percent of European and American consumers are more likely to shop with brands which provide relevant offers and recommendations. Clearly, enhancing a brands ability to engage with customers on an individual basis is critical for brand success.

However, investment alone is not enough – in order for AI to provide effective personalisation, it must be implemented and used in the right way.

Organisations need to develop more sophisticated AI capabilities which can collect and analyse data in real time to offer tailored services and products. This capability must be advanced enough to work for customers as they move through an omnichannel journey which often spans across websites, apps, email and high-street stores, for example.

Omnichannel journey: Real-time data analysis is key

While it is true that AI has the potential to bring about this ‘new era’ of personalisation, the technology alone cannot guarantee quality personalisation. For that, business leaders must appreciate the value of AI, develop a clear strategy for implementation and ensure that it is monitored and improved by experts who truly understand it. 

Make the business case for investment

One common barrier to the adoption of sophisticated AI and machine learning technology is business leaders being deterred by the cost of the initial adoption process. While it’s true that AI can remove the manual, time consuming, and often overwhelming challenge of managing and understanding vast amounts of data, just like any new technology, the initial set-up process can be expensive and labour intensive.

Also, the skills required to implement this level of technology mean that organisations may face the added time and expense of employing dedicated data scientists, and adjusting towards a culture where marketers and technologists must work closely together  As a result, organisations may feel that there is not a viable business case to invest.

To counter this point of view, take a step back and consider the long-term benefits of the initial investment. If AI is implemented strategically, the future pay-off will be enhanced capabilities for personalisation, improved Customer Experience, and increased sales.

Even as far back as 2014, McKinsey found that maximising customer satisfaction, which today largely comes from offering personalised experiences, would result in a 15 percent increase in a brands revenue. More recently, research from Econsultancy found that 93 percent of companies see an uplift in conversion rates from personalisation. Together with a well implemented AI strategy, brands can personalise even more effectively and potentially see even greater conversion rates.

Develop a clear strategy first

It is important to understand that simply having AI and machine learning capabilities does not guarantee that a brand can offer a higher quality of Customer Experience. In order to see significant improvements, organisations must first decide what CX problem they are aiming to solve, which data sets they need to collect and monitor, and how they are going to use the data to remove the particular pain-points that customers face.

Strategy: Organisations must decide what CX problem they are aiming to solve

Whether a brand wants to convert more website views to purchases, increase the number of customers returning to the site, offer a smoother transition across different touchpoints, or improve online self-service, these priorities must be decided from the outset. Then, the right data can be collected and harnessed to address the issue.

With an overwhelming amount of data being generated and collected by companies today, this is an effective way to streamline efforts and ensure the most important issues are dealt with first.

Shoe retailer Footasylum provides a great example of the benefits of strategic AI implementation. It focused first on the specific pain-point of friction in the customer journey between stores and the web by using AI to link in-store purchases with online systems such as loyalty schemes, to create a single customer view. The brand can now predict which customers are most likely to purchase particular products and when. As a result, it has seen an 8,400 percent return on ad spend. Footasylum’s next mission is to breathe life back into the high-street by using AI to enable the web to automatically share valuable customer information with brick and mortar stores.

Lay the foundations for advanced AI

In order to get a good understanding of which CX problems to address first, brands should undertake background research with marketers identifying which personalisation processes are currently creating the most conversions online, and which are less successful.

Another important foundation is to ensure that all data sets are integrated and consolidated. In order to offer recommendations in real time, brands must be able to predict consumer needs and use data to meet them at the right moment, on the right platform. AI can be used to accurately forecast where the customer will be in their decision making. Without access to all of the data about any given customer, there will always be a limit to how successful these predictions can be.

Clueless: Without accurate data, it will be impossible to fully predict a customer’s decision

In conclusion, it is key to remember that although AI has great potential to offer tailored experiences for customers in real time, the initial investment does not automatically guarantee quality personalisation and a return on investment. For that, a solid foundation must be put in place by understanding where customer experience can be improved, deciding on a clear strategy for implementation and removing data from silos.

Then, AI has the power to offer personalised experiences which offer true value to customers and meet, or even exceed, their expectations.


Vijayanta Gupta

Vijayanta Gupta

Vijayanta Gupta is VP of Strategy & Industries at CX management firm Sitecore.


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