Hayley Strang, Field Marketing Manager, UK & NE at Mapp Digital, explores the relationship between AI and customer satisfaction.
AI and machine learning in marketing is nothing new, but the technology has been expertly developed over the years and is now widely used by marketers to great effect – in email marketing, for example. With the help of AI-supported tools, customer behaviour can now be predicted, and customer satisfaction and sales can be increased in a targeted way.
But with budgets being squeezed and the need for marketers to do more with less, can investment in AI tools be justified right now? Sure, AI tools will help, but are they really the magic bullet they claim to be?
More data, better customer satisfaction
The use of AI and machine learning enables marketers to predict and influence specific customer behaviour. But to do this, companies need to know their customers and understand their needs.
In a recently commissioned study conducted by Forrester Consulting*, 89 per cent of marketers rated a holistic customer experience strategy as important or very important. For many companies, however, there are still issues associated with the implementation of such strategies. The biggest challenge for 54 per cent of companies is a lack of customer insights, as more than half say they are not able to identify customers on their own website.
This is where AI-powered tools come in, creating contact profiles and patterns based on first-party data. Central customer profiles give each individual user a distinctive face and provide marketers with a 360-degree view, bringing together sociographic characteristics, transactional and interaction data that can be used for advanced segmentation and automated outreach. In this way, marketers gain insights into customer behaviour and can use AI to calculate which aspects, for example, generate buying interest in the customer. Through these data-driven insights, marketers are now able to predict customer actions and react to them automatically to significantly increase customer loyalty and satisfaction.
The importance of data
AI makes it possible to enter a regular customer exchange with suitable, personalised offers. For example, individually designed discount offers can be played out at the right time, because AI can determine when that time will be based on certain user characteristics. RFM analyses, which are created based on Recency, Frequency, and Monetary, play a decisive role here, particularly when it comes to determining next basket values, ie the user’s expected next basket value, which goes a long way towards optimising conversions in the short-term.
AI and customer retention in email marketing
Artificial intelligence has a growing role to play when it comes to increasing customer loyalty and satisfaction, providing insights into recipient information and target groups, and analysing the opening, clicking, and buying behaviour of the respective recipient groups to understand optimal sending times for each individual contact. Based on individual usage times, the preferred time for receiving the message can be predicted with the help of AI, resulting in a significant increase in open and interaction rates of up to 15 per cent.
AI-supported systems are already designed to carry out machine-controlled campaigns along the customer journey based on available and interpreted data. Contacting by third-party systems can also be integrated here by creating seamless workflows. The AI system then automatically manages segmentation, message generation, addressing, and multi-level contacting. Areas of application are, for example, the triggering of repeat purchases in the retail and eCommerce sector, demand-oriented offers through targeted and rule-based cross- and upselling offers in the financial sector or the conversion of interested parties and occasional readers into paying customers in the publishing sector.
Algorithms and customer loyalty
Using AI to increase sales in the long-term takes strong customer loyalty. Companies should not focus solely on new customers, but rather turn their attention to users who are willing to churn and strengthen their loyalty to the brand or the company. With AI, marketers can gain in-depth insights into the expected lifetime value of each individual customer and, if necessary, react in real time.
To make customer obsession a reality, marketers must deploy a customer experience platform that allows consistent and regular engagement based on true and actionable insights. With the help of AI and predictive analytics they can forecast the customer lifetime value as well as conversion and churn probabilities. Future sales trends can then be projected, and marketing budgets adjusted accordingly. This technology need not be intrusive, but instead supportive of the customer journey.
The best response to budget-driven needs for marketing efficiency is the use of insights – ones that can be seamlessly used for digital marketing. Such insights enable a holistic understanding of the customer across all channels and help to optimise and further develop one’s own marketing strategy. At the same time, they help to avoid ineffective targeting and ensure good use of marketing budgets.
Investment in data and investment in customers goes hand in hand. This, along with investment in the right tools to provide the best digital experiences are the best things marketers can do.
* The commissioned study “Use Analytics And Insights To Accelerate Your Customer Experience Strategy” was conducted by Forrester Consulting on behalf of Mapp in December 2020.