In this Business Mondays Q&A, Julio Lopez, Senior Director of Retail Strategy, Practice Lead at Movable Ink, a leading AI-driven content personalization platform, delves into the positive impact of AI on the retail industry. Lopez discusses how AI is implemented into retail marketing strategies, improving processes for marketers by automating tasks and enhancing customer engagement and retention. While highlighting the benefits, he also emphasizes the importance of addressing biases in AI models through diverse datasets and using multiple AI solutions to ensure objectivity.
In what ways is AI being implemented into retail marketing strategy?
Every digital marketer knows about reinforcement tactics, like sending brand messaging to reinforce core values, setting up automated triggers, or generating personalized emails based on zero- and first-party data, all centred around a customer’s recent transactions. However, reinforcement should be a slice of the broader strategy, not the whole pie. Marketers can use past interactions to gain insights about customers, creating opportunities for follow-up with content that’s even more relevant. For example, if a customer looks at hiking boots, traditional tactics might just keep reminding them of those boots. But with AI-powered decisioning, the possibilities for product suggestions expand greatly, potentially even branching into different categories. Thanks to the AI’s analysis of the customer’s entire interaction history, including previous reinforcement activities, it can introduce a completely new product that the customer is likely to enjoy. Instead of merely repeating what’s been shown before, the AI can introduce something unexpected and delightful.
How has this improved processes for marketers?
Today’s legacy campaign process is broken. AI, however, has transformed the age-old approach, transforming marketing programs to drive revenue, run more efficiently, and build better relationships with customers—and not just for today, but for the future.
At a time when the fight for customer attention and budget and resources is at an all-time high, brands are looking for ways to be more efficient while still optimizing the best possible experience. AI gives marketers the swiss army knife of marketing tools to automate mundane tasks such as sending emails, input real-time information and manage campaigns, giving marketers time to focus on more creative tasks.
For example, Movable Ink Da Vinci’s streamlined workflows decouples content from the campaign, automating the email creation process. From determining the ideal messaging frequency, to selecting the best creative, to personalizing send-times, Da Vinci maximizes customer engagement while removing manual tasks for marketers, allowing them to focus on more strategic work.
Has this increased customer engagement and retention for retailers?
With AI-powered reinforcement and content optimization in marketers’ back pocket, creating a purposeful journey of discovery for your customer becomes a breeze. Using these methods empowers marketers to truly get to know their customers at scale and help them discover more about the brand. Once the brand has learned about the customer through fishing and testing, they understand what products will pique customer interest to explore new categories.
Think of a customer who has historically bought beauty products from a wellness brand. The AI now understands the customer and the brand’s products intimately enough that the program knows the exact product to send that will guide customers into a new category. Through content optimization, the AI can bring that idea to life by sending an enticing email to introduce customers to skincare.
Are there any negatives to implementing AI? What do retailers have to look out for?
Like with every new technology, AI has advantages and, naturally, some challenges. For example, every AI model is trained using data created by humans, who definitely have biases colouring their view. While in some cases this can make a negligible difference, some datasets can cause major repercussions for brand integrity. Marketers should play an active part in ensuring objectivity, including:
- Ensuring diverse datasets. If the inputted data is more balanced, the AI’s output will also be more objective.
- Using more than one type of AI solution. Generative AI is the most well-known form of AI, but be sure to activate various forms of AI instead of relying on a single solution. Multiple sources work to check and balance each other.
- Looking beyond open-source AI. Open-source AI is arguably the most liable to bias, as it’s subject to unreliable inputs. Opt for an AI solution that uses data you know is reliable—like your own sources of customer data.
