Artificial Intelligence (AI) is perhaps the only way marketers today can keep up with customers’ wants and expectations. If you are looking to introduce AI in your marketing activities, we have insights from five MTA experts to get you started.
Artificial intelligence has made giant strides in the marketing functions of organizations in recent years. 2018 saw conversational AI finally gaining mainstream acceptance. In this article, we share five ways, recommended by MTA experts, to introduce AI in your marketing in 2019.
1. Introduce AI in Content Curation
Content curation is an essential area of content marketing. It helps marketers engage users that are in the awareness stage. AI-driven content curation crawls the web and sends personalized emails to users containing news, blog posts and original content.
Lasya Marla (Director of Product, Lucidworks) says, “A sophisticated AI can learn patterns in your content and use those patterns to create more content of the same type. As the ability to create tons of machine generated content becomes more common, a complex and smart system for maintaining high quality in that content will be absolutely necessary. Companies today use AI to create and curate content, discover hidden taxonomies, identify outliers and anomalies and much more.”
Also Read: AI Adoption Trends and Predictions for 2019
2. Run Intent-Driven Ads
Intent-driven personalization analyzes a myriad of data points to understand and predict the customer intent. It helps marketers understand their purchase behavior and the stage of the buyer’s journey they’re in to accordingly decide the future course of action.
AI can help with intent-driven ads by optimizing the creative elements of ads. Daniel Winterstein (Co-founder and CTO, Good-Loop) aptly puts it as, “Intent-driven ads will blur the lines between adverts and advisers.” Daniel further says, “Machines are good at exploring many options: such as trying out different wording, colors, and stock image choices. These choices can be linked to performance metrics, providing feedback to automatically pick the best options – and to train the AI.”
3. Engage Customers Intentionally
Social media gave brands an opportunity to engage with their target audience on a one-on-one basis. Personalization allowed brands to initiate one-way communication through emails and other avenues. Despite making these advancements, brands are still not able to intentionally engage with customers on a mass level. With the help of deep learning, you can now uncover hidden patterns and trends within customer behavior and engage with them on a personal level.
Nicholas Cumins (General Manager, SAP Marketing Cloud) opines, “Modern consumers are often disconnected due to the pervasiveness of mobile devices, significantly impacting a brand’s ability to break through. Now, deep learning allows brands to form stronger connections with customers by understanding specific behavior and an individual’s propensity to take the next best action. Over time, marketers can analyze these patterns, determine what led to successful outcomes for each individual and use similar strategies for each interaction following.”
4. Make Lead Scoring Data-Driven
Lead scoring is a model that helps sales and marketing departments determine which prospects to pursue. Before the advent of AI, this process was performed using human judgment and later adopted a rule-based approach. AI is changing the process by making lead scoring a data-driven process.
Carl Landers (CMO, Conversica) affirms, “In real-world terms, using AI to optimize lead scoring increases the likelihood that they will convert. Where AI really shines is by achieving a fine-grained and nuanced understanding of customers’ responses and interest level in order to feed good information into the system. This delivers an improvement over previous rules- and intuition-based approaches.”
5. Offer Superior Customer Experience
As brands prioritize Customer Experience (CX) in 2019, AI will contribute a huge chunk to CX activities at every step of the buyer’s journey. Marketers can extract information from customer behavior and purchase history, which can help the support team deliver better customer experience.
Mark Floisand (CEO, Coveo) recommends, “Having case-relevant information at hand will enable your agents to deliver personalized assisted-support and ensure the process is as frictionless as possible. If your customers don’t find what they’re looking for on your site or app, it could be an indicator that there’s a content gap, which your team can easily address and make available. Or, perhaps they’re looking for a product or service that doesn’t yet exist, which could be great insight to pass to your product development team.”
When implemented correctly, AI can project your organization’s marketing efforts to the next level. However, when done improperly, it can stall your growth. To ensure you’re on the right path, check whether you are making any of these mistakes.