Given the firehose of inputs coming into mid-market to large enterprise companies, it is no wonder that it feels like the marketing function has been reduced to a series of reactions. There is little time to focus on customer needs or end-benefits at an emotional level. More and more pressure on marketing teams means that they must deliver positive metrics on many types of marketing programs, with less visibility or time for planning. In turn, this fuels a steady move away from a customer mindset to one focused primarily on execution. At Surveys & Forecasts, LLC we focus on these important marketing developments with many of our clients.
Emotional Relevance and ROAS
Today’s modern marketers tend not to holistically focus on meeting customer needs because there is no incentive to do so. Given this pressure, marketers focus on understanding the short-term financial impact of their marketing spending. Commonly used metrics, such as return on ad spend (ROAS), help marketers assess the pros and cons of different investments and levels on their shorter-term campaigns. Some organizations have the benefit of extra resources to look at the long-term impact of marketing programs through lifetime value (CLV), which extends the evaluation horizon beyond an individual campaign’s effectiveness.
A brilliant colleague of mine has conducted many studies to prove that marketers can achieve significant increases in ROAS when media dollars are targeted at moderately active buyers within a category (i.e., the “moveable middle”). Yet one wonders about the linkage between heavily targeted (or perhaps over-conditioned) buyers and the impact on their emotional connection to the brand or perceived end-benefits over time.
Do increases in respondent-level share of requirements (i.e., the share of a brand within a person’s overall category consumption) always translate to increases in positive emotional valence towards the brand? Like reach and frequency, does the response curve flatten with additional promotion, or perhaps as new products enter a market? As I buy more corn flakes, might I not also grow weary of them, or am I emotionally protected from erosion effects because I love Kellogg's?
AI to the Rescue
Research is a likely place for AI to flourish on both the positive and negative side. At two recent conferences (QRCA, Quirk’s) we saw disturbing implications of rapid advances of AI on research, especially the specter of more fraudulent research data. Given well-known declines in response rates and issues with response quality, the worry is certainly justified. That being said, AI holds great promise to detect fraudulent behavior, and do a far better job of identifying unengaged or disinterested respondents (well beyond simple measures of speeding and straight-lining). AI holds the promise being able to sweep across entire data sets to look for patterns of similarity or aberrance, to detect suspicious activity, or identify survey responses that may originate from click farms or from bots.
Closing the Emotional Connection Loop
But there is so much more that AI will offer us. Let’s flip things around and look at experiences from the customer’s point of view. Many aspects of a seamless customer experience are thankless company tasks and are invisible to the customer. AI solves for those thankless tasks and frees humans to be human again. AI is already helping businesses streamline operations and improve customer experience by automating tasks, order tracking, inventory management, and scheduling. While much of the current level of sophistication primarily logistical, there is no question that AI is deeply embedded in decision-making for many ecommerce companies. Every time a package arrives at my door from Amazon, I know that AI was on the scene.
But what about my earlier premise regarding the need for closer emotional connections with our customers? This is where I truly believe AI will open up tremendous possibilities. Think about all of the human labor involved in dealing with routine and mundane tasks between companies and their customers!
By leveraging AI to handle routine and mundane tasks, and automate processes, more time and resources are available for marketers to focus on building stronger relationships with customers.
Virtually all integrated feedback systems have already introduced AI- enhanced tools to improve customer experience. AI-powered chatbots increasingly handle routine customer inquiries and support requests. Today AI interaction is basic and can be very frustrating. As AI tools become more sophisticated, human interaction will be elevated to solve the more complex, sophisticated inquiries that virtual assistants and chat bots cannot perform.
The net result free marketers to focus on higher-order tasks, such as developing more powerful customer engagement strategies and analyzing feedback. This can only lead to higher satisfaction, increased loyalty, retention, and ultimately business success (on multiple dimensions).
AI can connect with a customer in several ways to produce a positive emotional response. Here are a few examples:
Personalization
AI can be used to provide personalized recommendations and experiences for customers, which can help them feel understood and valued. By analyzing customer data such as purchase history, browsing behavior, and preferences, AI can recommend products or services that are tailored to the customer's specific interests and needs. This can create a positive emotional response by showing the customer that the business cares about their preferences.
Chatbots
AI-powered chatbots can provide quick and efficient support for routine (not all) customer inquiries, freeing up customer service agents to focus on more complex issues and provide personalized interactions with customers who really need it. Chatbots also use natural language processing (NLP) and sentiment analysis to respond to customer inquiries with empathy and understanding, creating a positive emotional response.
Visual Search
AI-powered visual search technology can help customers find the products they are looking for more easily by allowing them to search using images. This can create a positive emotional response by making the shopping experience faster, more accurate, and generally fun and enjoyable.
Predictive Analytics
AI-powered predictive analytics can help businesses anticipate customer needs and preferences before they even express them. By analyzing customer data and behavior patterns, businesses can make informed decisions about which products or services to offer, when to offer them, and how to market them to specific customer segments. This will create a positive emotional response by showing the customer that the business understands their needs and is proactively working to meet them.
AI will be an enhancement to knowledge workers everywhere, and especially for companies that have many complex interactions with their customers. The current level of AI sophistication in dealing with customers is, at best, mediocre. But as sophistication increases, and as GPT-like models improve their reasoning and knowledge, the opportunity to enhance emotional connections with customers will vastly improve.
Marketers will have the opportunity to pivot back to their core mission: the function in an organization that is best suited to grow and maintain meaningful relationships with customers and, in doing so, grow sales.
Overall, AI can create positive emotional interactions by providing personalized experiences, efficient support, and anticipating customer needs. By leveraging AI in these ways, businesses can build stronger relationships with their customers, drive loyalty, and ultimately, grow their business.
If your research or customer feedback program needs AI help - or is yet to be built - please reach out.. For more information about our customer feedback programs, please visit the Surveys & Forecasts, LLC website or get in touch at info@safllc.com.
