Top Technologies: The Tools Marketers Need to Turn Consumers into Loyal Customers

Often, the consumer buying cycle for larger purchases, such as travel or luxury goods, is anything but straightforward. A potential customer may research and dream for months before finally committing. Marketers must find potential customers early, determine intent, and then deliver relevant ads to drive conversions. And a marketer’s job isn’t done once the customer converts. They must ensure brands are delivering on consumer expectations by providing the right experience to create not just a customer, but a long-term loyal customer.  

Competition is fierce and consumers are inundated with ads, which means marketers must prove early on that they know just what a consumer is looking for and can meet or exceed expectations–and that’s where technology comes in. By using the right technology at every stage of the funnel, marketers can engage consumers at every stage of their journey and build brand loyalty to increase the customer lifetime value. Here’s a breakdown of how marketers can leverage tools, such as artificial intelligence (AI) and machine learning (ML), to deploy successful campaigns that stand out from the crowd.

Create lookalike audiences to determine intent

When consumers are beginning their search for the right product or service, they’re often gathering information from social media, websites, or other sources of inspiration. But what’s the difference between a potential customer and someone who might just be bored at work or dreaming about a purchase they won’t make for several years? Marketers must get in front of a consumer as they start to research, but they can’t afford to spend their money marketing to people who aren’t serious. 

One of the best ways marketers can begin to separate serious buyers from the crowd is to use ML to create lookalike audiences. For example, semi-supervised learning or  propensity modeling can be used to analyze the behaviors and traits of customers who have already purchased and then determine which prospects are showing those same traits. By using ML to focus marketing spend on audiences of potential customers that are most similar to loyal customers, marketers can create more relevant campaigns that are less expensive and generate better ROI. 

Maximize budget allocation using AI

Once consumers have demonstrated intent, marketers must stay on their radar to continue to push them further down the funnel. When making a big purchase, they might be weighing out multiple options–or simply determining whether to make the purchase at all. Often, marketers deploy retargeting ads across channels to help sway their decisions. However, finding the exact right mix of channels, ads, duration, and timing is a science, and that science can help marketers maximize their budgets.

AI tools can help marketers optimize how they allocate budgets to potential customers on the right channel at the right time. Adtech platforms and partners provide AI-enabled tools that can help marketers better direct their spend, including which marketing tactics they use and which groups of consumers to target. The marketer provides their budgets, campaign goals, and additional information, and an AI agent optimizes the channels, tactics, and budgets that will maximize campaign performance. Using a combination of machine learning and Bayesian statistics, they can forecast conversion rates and available ad spend, helping marketers exceed performance goals. Regardless of which options marketers choose, these solutions can help save a lot of time while stretching their budgets. 

Use first-party data to curate the customer experience

When customers make a big purchase, they also expect a great experience–and that experience starts before they go on their trip or even receive their item. By laying the right groundwork through communication and proactive service, marketers can engage with customers and build long standing relationships. This is where first-party data, or information located in a brand’s customer data platform (CDP) or customer relationship management (CRM) becomes critical. First-party data includes information, such as demographics, geographics, and identifiers collected from the company website and other channels with consent. This data is used to build customer profiles and can be shared with marketing partners and platforms to bolster campaigns. For example, many CDP and CRM solutions integrate email marketing capabilities. and will be imperative for marketers once cookies go away. 

First-party data is also the foundation for machine learning and helps marketers create more personalized and compelling content. Marketers can use their first-party data in conjunction with uplift modeling to identify which messaging to use to truly influence a purchase. This is a great way to create a personalized experience, even while marketers are still learning about their newest customers. Many CDP and CRM solutions have email marketing capabilities integrated in, making it simple to create and send compelling, personalized communication and offers that inspire customers to add-on to their purchase or take advantage of a new opportunity. 

Leverage generative AI and your customer database to generate repeat business–and build brand loyalty

Marketing isn’t just about capturing that upsell opportunity or even an additional purchase; it’s ultimately about building loyal brand advocates who will refer other customers. To continue building those relationships, marketers can use a blend of digital advertising tools, like programmatic and email marketing, along with ML to continue to target these customers for repeat business and deliver personalized offers and communications that make them feel valued.

Beyond communications and offers, customer service is a critically important part of the customer journey. AI-enabled chatbots allow marketers to scale customer service to offer timely, responsive, and informative answers when a customer needs support. These tools use traditional call center technology and generative AI to create a large database of frequently asked questions. This database is then made accessible to customers over the channels they prefer, including text, WhatsApp, Facebook Messenger, or email, so they can communicate with brands to easily get the answers they need.

In addition to answering questions, generative AI-enabled customer experience tools enable conversational commerce, which opens up opportunities to unlock potential revenue. For example, if a customer asks the chatbot a support question, the chatbot can suggest additional products over the course of the conversation. Companies can then use generative AI to analyze this complex structured and unstructured data from multiple channels to create comprehensive reports and run business analytics. 

Beyond upsell opportunities, generative AI opens up new lines of communication to better understand a guest’s experience. This type of real-time feedback not only allows customer service teams to course correct before situations escalate, but also increases the chance of generating positive reviews on social media. Generative AI can even go as far as to create draft responses to consumer reviews on TripAdvisor, Yelp, Google reviews, and more. Using prompt engineering and LLMs like Google’s Gemini LLM, AI can create personalized, human-sounding responses to customer reviews quickly and at scale, saving marketers precious time while still making customers feel heard. 

The customer buying cycle is complex, but with the right technology, marketers can gain the visibility they need to maximize campaign performance and customer satisfaction. In a world where customer experience matters, every interaction–from first look to post-checkout–matters, and the right tools and technologies can make brands stand out from the competition to capture the conversion and cultivate long-term loyalty.