We are now in Q4, and the holiday season is here. It’s no surprise that 2023’s surge in AI will fuel many marketers’ holiday efforts this year.

This will be the first year where marketers across the board will use AI to creatively reach and connect with customers. Customers are demanding both speed and personalization. In fact, according to a McKinsey study, 80% of customers are more likely to purchase when brands offer personalized experiences. Luckily, AI helps accomplish both things.

As you start (or continue) plotting your AI strategies this holiday season, consider these customer experience use cases.

AI can help turn the pre-purchase stage into a conversation

Many successful brands will be using AI chatbots to establish conversations with their customers. These aren’t your average chatbots.

Historically, the most common type of chatbot is trained with specific questions and can only provide predetermined answers. They typically outline upfront what they are capable of speaking on, giving customers a select number of options to choose from. More times than not, these chatbots hit a dead end when customers ask them more complex questions leading to frustrated shoppers.

Sound familiar?

Chatbots that are equipped with conversational AI capabilities engage with customers with a human-like approach. Instead of being limited to a pre-existing script, they offer a natural, conversational flow. They understand and analyze what’s being asked and generate tailored answers based on customer input. They take what they’ve learned from previous customer conversations to fuel their future responses.

A big opportunity for brands is at the pre-purchase decision stage. One PwC survey found that 44 percent of respondents were interested in using AI-enhanced, conversational chatbots to help them decide on purchases.

Think of conversational chatbots as a personal virtual shopping assistant. These bots can provide recommendations based on the customer’s price range, suggest products similar to what they’ve been browsing, or ask if they have any questions about the items in a cart. The “assistant” allows customers to find what they need quickly, and good experiences drive repeat customers.

Consider the use cases at the local level, too. For example, if a customer is browsing a national website but wants to see or test the product in the flesh at a local store, they can ask the chatbot for recommendations of stores near their zip code. This drives both foot traffic to the brick-and-mortar locations and opportunities for them to build on-the-ground relationships and repeat visits.

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Enhance post-purchase experiences with AI

The first few months of the new year are a prime window for product returns, service questions, and warranty registrations; one out of 3 consumers are looking to retailers’ chatbots for customer service support. Prepare your first line of customer service defense with AI to support those post-purchase customer service touchpoints and build relationships.

With the proper data and training, AI can improve customer experiences through any challenges, while saving service departments time to focus on the more serious escalations. When it’s time for a human agent to get involved, bots can quickly gather the information at hand to create a support ticket. This not only saves teams time but also alleviates the need for customers to repeat themselves.

You can also tap into AI in the post-purchase to enhance loyalty and repeat purchases. For example, once a customer makes a purchase they may be notified that they can unlock a coupon for their next purchase by leaving a review or as a simple thank you. But make it personal. Your AI tool could determine what sort of incentive would most bring that particular customer back – one might want that discount, but another might want an invitation to an exclusive in-store event

AI tools can analyze chatbots and pull out recurring themes in customer conversations to inform you what is trending. Marketers can interpret this data and apply it to their future campaigns and initiatives. That way when an influx of similar requests arises, the chatbots are armed and ready with solution-fueled responses.

Be transparent about how you use customers’ data.

At the same time that AI and personalization are growing, so is the desire for data privacy. Customers want to have more control over their personal information and businesses agree that transparency is critical in building trust. According to a Cisco survey, 92% of respondents feel their organization needs to reassure customers that their data is used for legitimate purposes when AI is involved.

During the 2022 holiday season, consumers spent $211.7 billion on online shopping alone. Imagine the amount of personal and financial information being shared while they’re at it.

Brands must outline how they are using, storing, and protecting their customer’s data upfront by making their privacy policies accessible. For example, a pop-up may appear when customers enter the website or access the chatbot. They must be given the choice of whether or not they want their information shared. They also should have (easy) control over accessing their information and deleting data if necessary.

Concerns over data privacy may need to dictate how you use AI. For example, earlier this year, OpenAI experienced a security breach that allowed some users to see other users’ private data. That kind of error could kill a brand. Few really understand what happens under the hood, so make sure that you have equipped your team to evaluate the risks of AI and how to mitigate them.

As we enter one of the busiest times of the year, connecting with customers personally, efficiently, and transparently is at the top of every marketer’s wishlist. AI can help them accomplish just that – pre and post-purchase. Keep testing the different tools to learn and iterate what works best for your customers.

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