Four ways AI can help you keep pace with changing consumer behaviours

Diane Keng is the CEO and co-founder of Breinify, the leading plug and play AI platform for predicting and acting on customers’ highly dynamic interests. Diane was previously at Apple and Symantec. Diane ran three successful businesses before she was 18 and is a noted software innovator who frequently speaks on the intersection of AI, personal data, privacy, and the future of smarter products. She has been featured in The Wall Street Journal, HuffPost, TechCrunch, OZY, and Inc. Magazine.

Consumer behaviour looks entirely different than it did a year ago. Lockdowns and shelter-in-place orders gave people more time to browse online, discover, and fall in love with existing and new brands. More than ever, consumers expect relevancy — and their tolerance for unpurposeful experiences has plummeted.

In other words, spray-and-pray marketing tactics no longer work. Burying consumers in content also won’t work. Loyal customers don’t want every last bit of your content — they want tailored experiences that offer the best products and information. They want meaningful quality rather than irrelevant quantity.

Marketers now face the challenging task of meeting these heightened consumer expectations for digital experiences. They need to leverage fresh data and AI marketing solutions to predict consumer behaviour, so they know precisely when to reach out to consumers and what content to share.

Context is crucial here. Historical data from last year won’t cut it because consumers were out enjoying picnics in the park 12 months ago. This year, they’re staying home and scheduling virtual happy hours via Zoom. Life is different amid a pandemic, and your old data no longer applies.

Stay-at-home orders are temporary, but changing consumer behaviours toward a preference for more relevant and targeted experiences are not. Brands must embrace the fact that consumers’ baseline expectations have changed and begin to pivot their strategies to match. The use of artificial intelligence in marketing is the key to making this happen.

Enlisting the help of AI marketing solutions

Delivering the perfect experience is easier said than done — especially now. Many companies are experiencing a damaging cycle: Lost revenue leads to furloughed marketing employees, which leads to fewer people to run better experiences, which leads to lost customers, which leads to lost revenue. Repeat. You get the idea.

As marketers confront these new challenges and expectations related to predicting consumer behaviour, they must also contend with limited teams and resources. Faced with a tight budget, companies often reduce marketing spend to preserve funds for more essential activities. Due to revenue loss from the coronavirus pandemic, for example, major retailers — including The RealReal, Best Buy, and Kohl’s — have cut their marketing budgets dramatically. But revenue should not be driven by headcount; it should be the result of headcount running the business effectively.

Data science can help simplify the marketing process, but it can also help drive more effective experiences. Despite this potential, data science might feel unattainable for brands struggling to manage existing marketing task forces and everything else going on.

AI can help fill in the gap for marketing teams by helping them understand how consumer behaviour has changed while providing data to create efficient, targeted, and personalised campaigns. AI can monitor millions of users in real time and make effective, personalised decisions in an instant.

Rather than replacing marketers, AI technology saves them from getting bogged down with manual and static segmentation or in curating and activating content for general segmentation. Think of it as data science without the data scientists. AI can serve as the data science extension to the human brain. It generates impactful results and frees marketers up to invest their time and resources more strategically.

Specifically, the use of artificial intelligence in marketing can make it easier to mine rich consumer data and create a personalised customer experience by:

Ensuring relevant content via availability

AI can keep track of customers’ purchase histories and predict when they’ll run out of your products, nudging them at just the right time to restock. Sephora’s Visual Artist app offers a great example of this; it uses predictive analytics to analyse a user’s purchase history, recommends new products, and predicts future needs.

Giving personalised recommendations for individualised experiences

AI can predict consumer behaviour by understanding what products consumers purchase or consider and what content they peruse. As a result, brands can more effectively target shoppers with relevant recommendations. The ROI for individualised experiences is immense. In my company’s tests, personalised landing pages had 20 times the ROI of similar pages in a control group.

Netflix is one of the most well-known companies using AI to improve customer experiences. The streaming giant uses machine learning to analyse customers’ viewing, search, and rating histories to create its hyper-targeted recommendations. In 2014, the brand used more than 75,000 “altgenres” to personalise its customer experience and keep users hooked with recommendations tailored to their unique tastes.

Creating AI-based customer loyalty programs

Predicting consumer behaviour is challenging when a person’s preferences can change based on the time of day, day of the week, or season. AI can help brands tweak loyalty programs to best appeal to consumers in light of these factors.

Instead of treating new customers as complete unknowns, start with “anonymous personalisation” that uses anonymous data such as the device used, referral source, and country to tailor the experience. You can also use AI to create customer personas segmented by age, interest, or location. Then, use those personas to create personalised loyalty programs.

Targeted loyalty programs are well worth the effort: An Accenture Interactive study found that shoppers who are members of a loyalty program can generate nearly 20% more revenue than shoppers who do not participate in the program. The important thing is that the program is customised. A Forrester report found that most loyalty program members value receiving special offers or preferential treatment; this is only possible with insights into customer behaviours and preferences.

Offering an omnichannel experience

Marketers can use AI to improve customer experiences by understanding the right channels to reach customers and the impactful experiences to send their way. AI can fuel omnichannel marketing campaigns by keeping tabs on changing customer preferences and needs to deliver content that fits across all channels. Staying ahead of rapid — and sometimes subtle — changes in the customer journey would be nearly impossible without this technology.

This year has brought a sea change in consumer behaviour. Brands must throw out their old marketing playbooks and use AI to improve customer experiences and deliver personalised content. AI can analyse customer behaviour rapidly to help you meet heightened consumer expectations successfully.

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