By Jayakrishnan Sasidharan
Brands invest millions of dollars to get their messages in front of customers. But sometimes less is more. When customers are tired of seeing the same messages over and over, fatigue sets in. That can stop them from engaging with you and lead to a less-than-favorable view of your brand.
The Covid-19 pandemic is only heightening brand fatigue. Last spring, during the peak pandemic lockdown, people watched eight more hours of television per week and went online 50 to 70 percent more than they were prior. They shopped online more, downloaded more apps, and, naturally, received more ads. It’s little wonder they grew tired of company messages — even from brands they liked.
Although Covid-19 may have exacerbated the problem, brand fatigue isn’t new. According to Gartner, before the pandemic, one in four consumers said they were “overwhelmed” with the amount of content thrown their way, and 15 percent said they were “annoyed.”
Using AI to address brand fatigue
Even your most loyal customers can reach a point where they are tired of receiving marketing messages. It can be a fine line between when a customer welcomes your emails or deems them annoying, yet determining what pushes customers over the edge can be difficult to figure out. This is where artificial intelligence (AI) can help: by providing the data-driven insights you need to reduce customer frustration and bypass brand fatigue.
Find out where in the customer journey the fatigue is hitting
For customers who aren’t buying your products, you need to know when and where they’ve stopped paying attention. At what points in the journey are they engaging — and not engaging — with you? If you look at a specific customer segment, is there a consistent pattern for when people start to disengage? Has this pattern changed over time?
Getting this information is critical, but it’s not easy. It requires stitching together customer data from different systems to form a cohesive picture. If you have the right infrastructure to unify those data sources, AI can do the heavy lifting of quickly synthesising the data and spotlighting areas to focus on.
For example, AI can look at how customers are interacting with your brand in multiple channels and analyse clickstream data — as well as customer reviews and social media sentiment — to flag potential problems. Using AI-powered customer journey analysis, marketers can determine the best time, frequency, and channel for reaching out to a certain customer segment. AI can also calculate a “fatigue score” to help you find the right balance — so you can nurture your customers without over communicating.
Deliver content that matches your customers’ current needs
In an era of media saturation, customers only pay attention to messages that are highly relevant to them in a given moment. But that relevancy can change quickly. For example, someone may research new cars for six months but no longer want to see car ads in their social media stream after they’ve made their purchase. Similarly, parents of toddlers will dismiss ads for newborn products.
AI can help marketers understand these changes in customer needs as they happen. For example, AI can look for patterns in how customers are engaging with your email messages. Do those who open the emails quickly follow up or make purchases in any of your channels? Conversely, are there customers who used to open your emails promptly but now do not? Are they interacting with your brand through other channels?
AI can look for data that indicates lifestyle changes. It can also help you craft more effective language for specific segments. These insights will give you a better idea of how, where, and how often to interact with customers in ways that bring them value.
Anticipate — and adapt to — changes in the market
If this year has taught us anything, it’s that predicting the future is tough. The world is a dynamic place and customer preferences are highly fluid. Yet, the best way to prepare for market fluctuations is to gather and make sense of as much relevant data as possible. AI can make this task easier with demand forecasting and predictive analytics.
For example, an automobile company could use AI to predict which cars people are likely to buy based on data about their hobbies. And a financial services firm could use AI to identify unusual credit card usage patterns that indicate potentially fraudulent behavior.
AI gives you the ability to listen to your customers in new ways — by analyzing all the clues they leave behind in their digital lives — so that you can fine-tune your messaging and improve the overall customer experience. When your messages are timely, contextually relevant, and genuinely useful, your customer will always be ready to listen.
The author is vice president, Adobe Customer Solutions – APAC
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