Five Ways to Leverage AI in Marketing: A Direct-to-Consumer Approach
Implementing AI in marketing plays a major role in optimizing content for these personalized experiences. Virtual assistants, cognitive search, visual search, and other new AI capabilities work together to elevate the entire marketing experience.
People are accustomed to receiving personalized attention when they shop in brick-and-mortar stores. As a growing share of commerce moves online, artificial intelligence (AI) offers a unique opportunity to replicate the most personal aspects of the direct-to-consumer experience, with the added benefit for retailers of capturing every aspect of the interaction. This information helps chatbots improve personalization, provide solutions that best match the customer’s needs and deliver a positive impact to the bottom line.
Automating operations has become an essential aspect of a modern marketing organization and adding AI to the solutions mix takes team performance and customer experience to a new level. From bots to virtual assistants and other innovative new uses, AI in marketing improves a company’s ability to scale and significantly reinforces its marketing strategy and infrastructure. By infusing their marketing programs with AI, companies are able to give customers exactly what they want while addressing key business challenges such as standing out from the competition, improving loyalty, maximizing effectiveness, and improving the company’s ability to respond to new market trends or customer demands.
Getting Closer to the Customer is Not Just a Good Idea – It is Expected
Digitalization has revolutionized the personal experience. Today’s consumers grew up using digital platforms and they now expect every company to provide the same level of personalization that they get from innovative tech enterprises. While personalized online experiences were once reserved for targeted offers in the sales cycle, today’s customers are coming to expect customization in every company interaction, from sales to service. In fact, frequent shoppers have stated that they will only shop with brands that offer a personalized experience and personalized customer-service interactions.
These interactions help build trust, which is critical for customer loyalty.
AI is Required to Build Personal Customer Experiences
While the application of AI in marketing might seem confusing, it is simply applying automated technology to improve the customer experience. If the main goal of advertising is to give customers what they want, the best way to actually achieve this is through personalization. AI monitors and collects required customer interaction data to make personalization possible on a large scale. AI bots can quickly fetch the most relevant information from a variety of datasets, constantly listening and learning to improve experiences. Whether the engagement is service or sales, bots can automate, improve, and scale engagement on any platform. Innovative companies that use AI in direct-to-consumer marketing are already seeing the results.
AI in Direct-to-Consumer Marketing: Five Focus Areas to Modernize the Approach
Leading companies are applying AI in a variety of ways, removing the guesswork from customer interactions and allowing companies to implement the right solutions based on customer needs and interests. Here are five ways marketing teams can deploy productivity-boosting AI in direct-to-consumer marketing to distinguish themselves from the competition, modernize their marketing approach and make significant gains.
AI chatbots or virtual assistants (VAs) are often used for customer support, but adding VAs to social and web platforms can also automate engagement and improve scalability on any platform. Bots listen and learn by capturing data from every interaction to improve the customer experience. If needed, they can even help create conversational advertisements and social media marketing experiences that match real-time customer interest.
Some companies think their customers aren’t ready to interact with AI or VAs. However, today’s VAs rely on innovative technologies like natural language processing (NLP) and generative pre-trained transformer 3 (GPT-3) to respond in human-like language and collect valuable data that gauges sentiment, attitudes, evaluations, and emotions.
Search: Cognitive and Visual
Cognitive Search uses AI to present relevant results from multiple datasets. This new way to search is important as the growing volume of data housed in many different databases renders traditional search ineffective. Cognitive search can parse more data sources while collecting valuable information from every interaction, allowing for further fine-tuning that then provides even better results. But cognitive search is not just for customers. It can be leveraged internally to improve employee productivity, lower operational costs, and improve the employee experience.
Because people are visual by nature, raw data can be boring to customers. The strength of visual images drives the popularity of social media platforms like Instagram and Pinterest. Modern visual search technology uses AI to capture and understand the content and context of images, creating smarter and more accurate search results. A computer vision process interprets images, assigns classifications or labels, and identifies any patterns. This analysis helps companies accurately assign customers to highly relevant segments.
Better segmentation means exposure to more relevant content and more relevant content often translates to increased sales and close rates.
Having a 360-degree view of the customer allows companies to provide highly personalized experiences that are increasingly expected by users.
AI can search multiple datasets (previous visits, purchase history, support tickets, site searches, etc.) to provide this enriched view of the customer. If VA is used, data from every interaction is collected and fed into the “customer 360” profile, enabling even better experiences in the future.
Amid this personalization push, companies are moving away from blanketing the airways with generic sales content and are instead tailoring high-performing content to targeted personas. Implementing AI in marketing plays a major role in optimizing content for these personalized experiences. Virtual assistants, cognitive search, visual search, and other new AI capabilities work together to elevate the entire marketing experience.
Having access to customer data also enables companies to provide a journey that feels more natural one in which online experiences simulate the offline experience. For example, machine learning infused campaigns continuously learn with every interaction. When used in social media interactions, customer sentiment (a key component in customer loyalty) improves significantly. Whether the customer engagement is related to service or sales, bots can automate, improve and scale engagement on any platform.
AI-Optimized Content and SEO
AI can play an active and important role in content optimization. New AI technologies like content AI help marketers create high-quality content based on consumer reviews, keywords and sentiment. Other AI solutions like Wipro’s Boostr can review large datasets from past campaigns to find the components of the highest performing campaigns across all platforms and optimize accordingly. A predictive campaign dashboard then suggests the most impactful content, social channels and other purchase motivators for each target audience before marketers embark on creating a new campaign.
Furthermore, the intelligent use of bots can improve SEO by greeting someone who arrives on a site and offering to help with an inquiry. While the bot interacts with the visitor, the visitor stays on the page, which increases their time on the website and enables the company to collect valuable information that can be used to further improve the site experience. AI can also optimize SEO by analyzing all site content, search results and search relevancy to inform the keyword strategy. Bots can identify associated keywords or keywords that are currently trending in real-time and use those to quickly adjust a campaign for maximum effectiveness.
Think of AI as a customer insights platform that uses every interaction as an opportunity to collect and fine tune a customer’s journey. Consumer transactions, locations, and interests are all connected via the platform to help companies understand the customer’s behavior, offer targeted solutions, build relationships and create authentic experiences.
When used to mine and engage in social and online conversations, bots can improve customer sentiment and provide deeper insight into the customer’s needs and behaviors. That information can then be used to automate more relevant journeys. AI can analyze past campaigns to learn what specific details resonated with the target audiences, then return predictive segmentation to improve future campaigns. Then predictive campaigns are able to use the most-impactful content which leads to better performance.
AI Modernizes Direct-to-Consumer Marketing
Many companies are spending more and more on direct-to-consumer digital campaigns yet struggle to see direct results. In an environment where it’s increasingly more important to have customized connections with the customer, it’s becoming harder and harder to forge these critical bonds. The competitive landscape has undergone a titanic change alongside shifts in consumer shopping and buying habits. Companies must focus on these new trends if they want to succeed in the modern economy. Two critical pieces in this journey are speed and personalization, they are steps that companies can take to best meet the unique needs of each customer by quickly by adopting AI in marketing.
AI in direct-to-consumer marketing can add tremendous value across the entire marketing value chain. It can fuel for creativity, automate campaigns, and collect valuable data that continuously improves the customer experience and journey. In some cases, it can even contribute to search-engine optimization (SEO). In today’s data-driven world, is it any surprise that a majority of marketers believe AI in marketing is the most important tool to achieve their data strategy?